Molecular tailoring approach for exploring structures, energetics and ...

Indian Academy of Sciences (India)

Administrator

Keywords. Molecular clusters; linear scaling methods; molecular tailoring approach (MTA); Hartree– ..... energy decomposition analysis also performed and which clearly ... through molecular dynamics simulation furnished by. Takeguchi,. 46.

A Bayesian approach to estimating hidden variables as well as missing and wrong molecular interactions in ordinary differential equation-based mathematical models.

Science.gov (United States)

Engelhardt, Benjamin; Kschischo, Maik; Fröhlich, Holger

2017-06-01

Ordinary differential equations (ODEs) are a popular approach to quantitatively model molecular networks based on biological knowledge. However, such knowledge is typically restricted. Wrongly modelled biological mechanisms as well as relevant external influence factors that are not included into the model are likely to manifest in major discrepancies between model predictions and experimental data. Finding the exact reasons for such observed discrepancies can be quite challenging in practice. In order to address this issue, we suggest a Bayesian approach to estimate hidden influences in ODE-based models. The method can distinguish between exogenous and endogenous hidden influences. Thus, we can detect wrongly specified as well as missed molecular interactions in the model. We demonstrate the performance of our Bayesian dynamic elastic-net with several ordinary differential equation models from the literature, such as human JAK-STAT signalling, information processing at the erythropoietin receptor, isomerization of liquid α -Pinene, G protein cycling in yeast and UV-B triggered signalling in plants. Moreover, we investigate a set of commonly known network motifs and a gene-regulatory network. Altogether our method supports the modeller in an algorithmic manner to identify possible sources of errors in ODE-based models on the basis of experimental data. © 2017 The Author(s).

FROM ATOMISTIC TO SYSTEMATIC COARSE-GRAINED MODELS FOR MOLECULAR SYSTEMS

KAUST Repository

Harmandaris, Vagelis

2017-10-03

The development of systematic (rigorous) coarse-grained mesoscopic models for complex molecular systems is an intense research area. Here we first give an overview of methods for obtaining optimal parametrized coarse-grained models, starting from detailed atomistic representation for high dimensional molecular systems. Different methods are described based on (a) structural properties (inverse Boltzmann approaches), (b) forces (force matching), and (c) path-space information (relative entropy). Next, we present a detailed investigation concerning the application of these methods in systems under equilibrium and non-equilibrium conditions. Finally, we present results from the application of these methods to model molecular systems.

Hidden Markov models and other machine learning approaches in computational molecular biology

Energy Technology Data Exchange (ETDEWEB)

Baldi, P. [California Inst. of Tech., Pasadena, CA (United States)

1995-12-31

This tutorial was one of eight tutorials selected to be presented at the Third International Conference on Intelligent Systems for Molecular Biology which was held in the United Kingdom from July 16 to 19, 1995. Computational tools are increasingly needed to process the massive amounts of data, to organize and classify sequences, to detect weak similarities, to separate coding from non-coding regions, and reconstruct the underlying evolutionary history. The fundamental problem in machine learning is the same as in scientific reasoning in general, as well as statistical modeling: to come up with a good model for the data. In this tutorial four classes of models are reviewed. They are: Hidden Markov models; artificial Neural Networks; Belief Networks; and Stochastic Grammars. When dealing with DNA and protein primary sequences, Hidden Markov models are one of the most flexible and powerful alignments and data base searches. In this tutorial, attention is focused on the theory of Hidden Markov Models, and how to apply them to problems in molecular biology.

Molecular modeling of protein materials: case study of elastin

International Nuclear Information System (INIS)

Tarakanova, Anna; Buehler, Markus J

2013-01-01

Molecular modeling of protein materials is a quickly growing area of research that has produced numerous contributions in fields ranging from structural engineering to medicine and biology. We review here the history and methods commonly employed in molecular modeling of protein materials, emphasizing the advantages for using modeling as a complement to experimental work. We then consider a case study of the protein elastin, a critically important ‘mechanical protein’ to exemplify the approach in an area where molecular modeling has made a significant impact. We outline the progression of computational modeling studies that have considerably enhanced our understanding of this important protein which endows elasticity and recoil to the tissues it is found in, including the skin, lungs, arteries and the heart. A vast collection of literature has been directed at studying the structure and function of this protein for over half a century, the first molecular dynamics study of elastin being reported in the 1980s. We review the pivotal computational works that have considerably enhanced our fundamental understanding of elastin's atomistic structure and its extraordinary qualities—focusing on two in particular: elastin's superb elasticity and the inverse temperature transition—the remarkable ability of elastin to take on a more structured conformation at higher temperatures, suggesting its effectiveness as a biomolecular switch. Our hope is to showcase these methods as both complementary and enriching to experimental approaches that have thus far dominated the study of most protein-based materials. (topical review)

Agent-Based Modeling in Molecular Systems Biology.

Science.gov (United States)

Soheilypour, Mohammad; Mofrad, Mohammad R K

2018-06-08

Molecular systems orchestrating the biology of the cell typically involve a complex web of interactions among various components and span a vast range of spatial and temporal scales. Computational methods have advanced our understanding of the behavior of molecular systems by enabling us to test assumptions and hypotheses, explore the effect of different parameters on the outcome, and eventually guide experiments. While several different mathematical and computational methods are developed to study molecular systems at different spatiotemporal scales, there is still a need for methods that bridge the gap between spatially-detailed and computationally-efficient approaches. In this review, we summarize the capabilities of agent-based modeling (ABM) as an emerging molecular systems biology technique that provides researchers with a new tool in exploring the dynamics of molecular systems/pathways in health and disease. © 2018 WILEY Periodicals, Inc.

Evaluation of the molecular level visualisation approach for teaching and learning chemistry in Thailand

Science.gov (United States)

Phenglengdi, Butsari

. Pre-test and post-test scores were compared across the three classes. The results from the multiple choice and calculation tests showed that the Class C - molecular level visualisation approach group demonstrated a deeper understanding of chemistry concepts than students in Classes A and B. However, the results showed that all the students were unable to perform satisfactorily on the calculation tests because the students had insufficient prior knowledge about stoichiometry to connect with the new knowledge. In the drawing tests the students exposed to the molecular level visualisation approach had a better mental model than the other classes, albeit with some remaining misconceptions. The findings highlight the intersecting nature of the teacher, student, and modelling in chemistry teaching. Use of a multi-step molecular level visualisation approach that encourages observation, reflection of prior understanding, and multiple opportunities at viewing (and using various visualisation elements), are key elements leading to a deeper understanding of chemistry. Presentation of the multi-step molecular level visualisation approach must be coupled with careful consideration of student prior knowledge, and with adequate guidance from a teacher who understands the topics at a deep level.

Molecular models and simulations of layered materials

International Nuclear Information System (INIS)

Kalinichev, Andrey G.; Cygan, Randall Timothy; Heinz, Hendrik; Greathouse, Jeffery A.

2008-01-01

The micro- to nano-sized nature of layered materials, particularly characteristic of naturally occurring clay minerals, limits our ability to fully interrogate their atomic dispositions and crystal structures. The low symmetry, multicomponent compositions, defects, and disorder phenomena of clays and related phases necessitate the use of molecular models and modern simulation methods. Computational chemistry tools based on classical force fields and quantum-chemical methods of electronic structure calculations provide a practical approach to evaluate structure and dynamics of the materials on an atomic scale. Combined with classical energy minimization, molecular dynamics, and Monte Carlo techniques, quantum methods provide accurate models of layered materials such as clay minerals, layered double hydroxides, and clay-polymer nanocomposites

Discovery of Novel Inhibitors for Nek6 Protein through Homology Model Assisted Structure Based Virtual Screening and Molecular Docking Approaches

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P. Srinivasan

2014-01-01

Full Text Available Nek6 is a member of the NIMA (never in mitosis, gene A-related serine/threonine kinase family that plays an important role in the initiation of mitotic cell cycle progression. This work is an attempt to emphasize the structural and functional relationship of Nek6 protein based on homology modeling and binding pocket analysis. The three-dimensional structure of Nek6 was constructed by molecular modeling studies and the best model was further assessed by PROCHECK, ProSA, and ERRAT plot in order to analyze the quality and consistency of generated model. The overall quality of computed model showed 87.4% amino acid residues under the favored region. A 3 ns molecular dynamics simulation confirmed that the structure was reliable and stable. Two lead compounds (Binding database ID: 15666, 18602 were retrieved through structure-based virtual screening and induced fit docking approaches as novel Nek6 inhibitors. Hence, we concluded that the potential compounds may act as new leads for Nek6 inhibitors designing.

Understanding valence-shell electron-pair repulsion (VSEPR) theory using origami molecular models

International Nuclear Information System (INIS)

Saraswati, Teguh Endah; Saputro, Sulistyo; Ramli, Murni; Praseptiangga, Danar; Khasanah, Nurul; Marwati, Sri

2017-01-01

Valence-shell electron-pair repulsion (VSEPR) theory is conventionally used to predict molecular geometry. However, it is difficult to explore the full implications of this theory by simply drawing chemical structures. Here, we introduce origami modelling as a more accessible approach for exploration of the VSEPR theory. Our technique is simple, readily accessible and inexpensive compared with other sophisticated methods such as computer simulation or commercial three-dimensional modelling kits. This method can be implemented in chemistry education at both the high school and university levels. We discuss the example of a simple molecular structure prediction for ammonia (NH 3 ). Using the origami model, both molecular shape and the scientific justification can be visualized easily. This ‘hands-on’ approach to building molecules will help promote understanding of VSEPR theory. (paper)

Understanding valence-shell electron-pair repulsion (VSEPR) theory using origami molecular models

Science.gov (United States)

Endah Saraswati, Teguh; Saputro, Sulistyo; Ramli, Murni; Praseptiangga, Danar; Khasanah, Nurul; Marwati, Sri

2017-01-01

Valence-shell electron-pair repulsion (VSEPR) theory is conventionally used to predict molecular geometry. However, it is difficult to explore the full implications of this theory by simply drawing chemical structures. Here, we introduce origami modelling as a more accessible approach for exploration of the VSEPR theory. Our technique is simple, readily accessible and inexpensive compared with other sophisticated methods such as computer simulation or commercial three-dimensional modelling kits. This method can be implemented in chemistry education at both the high school and university levels. We discuss the example of a simple molecular structure prediction for ammonia (NH3). Using the origami model, both molecular shape and the scientific justification can be visualized easily. This ‘hands-on’ approach to building molecules will help promote understanding of VSEPR theory.

Molecular Modeling

Indian Academy of Sciences (India)

Home; Journals; Resonance – Journal of Science Education; Volume 9; Issue 5. Molecular Modeling: A Powerful Tool for Drug Design and Molecular Docking. Rama Rao Nadendla. General Article Volume 9 Issue 5 May 2004 pp 51-60. Fulltext. Click here to view fulltext PDF. Permanent link:

Molecular modeling-driven approach for identification of Janus kinase 1 inhibitors through 3D-QSAR, docking and molecular dynamics simulations.

Science.gov (United States)

Itteboina, Ramesh; Ballu, Srilata; Sivan, Sree Kanth; Manga, Vijjulatha

2017-10-01

Janus kinase 1 (JAK 1) belongs to the JAK family of intracellular nonreceptor tyrosine kinase. JAK-signal transducer and activator of transcription (JAK-STAT) pathway mediate signaling by cytokines, which control survival, proliferation and differentiation of a variety of cells. Three-dimensional quantitative structure activity relationship (3 D-QSAR), molecular docking and molecular dynamics (MD) methods was carried out on a dataset of Janus kinase 1(JAK 1) inhibitors. Ligands were constructed and docked into the active site of protein using GLIDE 5.6. Best docked poses were selected after analysis for further 3 D-QSAR analysis using comparative molecular field analysis (CoMFA) and comparative molecular similarity indices analysis (CoMSIA) methodology. Employing 60 molecules in the training set, 3 D-QSAR models were generate that showed good statistical reliability, which is clearly observed in terms of r 2 ncv and q 2 loo values. The predictive ability of these models was determined using a test set of 25 molecules that gave acceptable predictive correlation (r 2 Pred ) values. The key amino acid residues were identified by means of molecular docking, and the stability and rationality of the derived molecular conformations were also validated by MD simulation. The good consonance between the docking results and CoMFA/CoMSIA contour maps provides helpful clues about the reasonable modification of molecules in order to design more efficient JAK 1 inhibitors. The developed models are expected to provide some directives for further synthesis of highly effective JAK 1 inhibitors.

Molecular structure based property modeling: Development/ improvement of property models through a systematic property-data-model analysis

DEFF Research Database (Denmark)

Hukkerikar, Amol Shivajirao; Sarup, Bent; Sin, Gürkan

2013-01-01

models. To make the property-data-model analysis fast and efficient, an approach based on the “molecular structure similarity criteria” to identify molecules (mono-functional, bi-functional, etc.) containing specified set of structural parameters (that is, groups) is employed. The method has been applied...

An approach towards understanding the structure of complex molecular systems: the case of lower aliphatic alcohols

Energy Technology Data Exchange (ETDEWEB)

Vrhovsek, Aleksander; Gereben, Orsolya; Pothoczki, Szilvia; Pusztai, Laszlo [Research Institute for Solid State Physics and Optics, Hungarian Academy of Sciences, H-1525 Budapest, PO Box 49 (Hungary); Tomsic, Matija; Jamnik, Andrej [Faculty of Chemistry and Chemical Technology, University of Ljubljana, Askerceva 5, SI-1001 Ljubljana (Slovenia); Kohara, Shinji, E-mail: aleksander.vrhovsek@gmail.co [Research and Utilization Division, Japan Synchrotron Radiation Research Institute (JASRI, SPring-8), 1-1-1 Koto, Sayo-cho, Sayo-gun, Hyogo 679-5198 (Japan)

2010-10-13

An extensive study of liquid aliphatic alcohols methanol, ethanol, and propanol, applying reverse Monte Carlo modelling as a method of interpretation of diffraction data, is presented. The emphasis is on the evaluation of several computational strategies in view of their suitability to obtain high quality molecular models via the reverse Monte Carlo procedure. A consistent set of distances of closest approach and fixed neighbour constraints applicable to all three investigated systems was developed. An all-atom description is compared with a united-atom approach. The potentialities of employment of neutron diffraction data of completely deuterated and isotopically substituted samples, x-ray diffraction data, and results of either molecular dynamics or Monte Carlo calculations were investigated. Results show that parallel application of x-ray and neutron diffraction data, the latter being from completely deuterated samples, within an all-atom reverse Monte Carlo procedure is the most successful strategy towards attaining reliable, detailed, and well-structured molecular models, especially if the models are subsequently refined with the results of molecular dynamics simulations.

Prediction of EPR Spectra of Lyotropic Liquid Crystals using a Combination of Molecular Dynamics Simulations and the Model-Free Approach.

Science.gov (United States)

Prior, Christopher; Oganesyan, Vasily S

2017-09-21

We report the first application of fully atomistic molecular dynamics (MD) simulations to the prediction of the motional electron paramagnetic resonance (EPR) spectra of lyotropic liquid crystals in different aggregation states doped with a paramagnetic spin probe. The purpose of this study is twofold. First, given that EPR spectra are highly sensitive to the motions and order of the spin probes doped within lyotropic aggregates, simulation of EPR line shapes from the results of MD modelling provides an ultimate test bed for the force fields currently employed to model such systems. Second, the EPR line shapes are simulated using the motional parameters extracted from MD trajectories using the Model-Free (MF) approach. Thus a combined MD-EPR methodology allowed us to test directly the validity of the application of the MF approach to systems with multi-component molecular motions. All-atom MD simulations using the General AMBER Force Field (GAFF) have been performed on sodium dodecyl sulfate (SDS) and dodecyltrimethylammonium chloride (DTAC) liquid crystals. The resulting MD trajectories were used to predict and interpret the EPR spectra of pre-micellar, micellar, rod and lamellar aggregates. The predicted EPR spectra demonstrate good agreement with most of experimental line shapes thus confirming the validity of both the force fields employed and the MF approach for the studied systems. At the same time simulation results confirm that GAFF tends to overestimate the packing and the order of the carbonyl chains of the surfactant molecules. © 2017 Wiley-VCH Verlag GmbH & Co. KGaA, Weinheim.

Multiscale Modeling of PEEK Using Reactive Molecular Dynamics Modeling and Micromechanics

Science.gov (United States)

Pisani, William A.; Radue, Matthew; Chinkanjanarot, Sorayot; Bednarcyk, Brett A.; Pineda, Evan J.; King, Julia A.; Odegard, Gregory M.

2018-01-01

Polyether ether ketone (PEEK) is a high-performance, semi-crystalline thermoplastic that is used in a wide range of engineering applications, including some structural components of aircraft. The design of new PEEK-based materials requires a precise understanding of the multiscale structure and behavior of semi-crystalline PEEK. Molecular Dynamics (MD) modeling can efficiently predict bulk-level properties of single phase polymers, and micromechanics can be used to homogenize those phases based on the overall polymer microstructure. In this study, MD modeling was used to predict the mechanical properties of the amorphous and crystalline phases of PEEK. The hierarchical microstructure of PEEK, which combines the aforementioned phases, was modeled using a multiscale modeling approach facilitated by NASA's MSGMC. The bulk mechanical properties of semi-crystalline PEEK predicted using MD modeling and MSGMC agree well with vendor data, thus validating the multiscale modeling approach.

Assessment of Molecular Modeling & Simulation

Energy Technology Data Exchange (ETDEWEB)

None

2002-01-03

This report reviews the development and applications of molecular and materials modeling in Europe and Japan in comparison to those in the United States. Topics covered include computational quantum chemistry, molecular simulations by molecular dynamics and Monte Carlo methods, mesoscale modeling of material domains, molecular-structure/macroscale property correlations like QSARs and QSPRs, and related information technologies like informatics and special-purpose molecular-modeling computers. The panel's findings include the following: The United States leads this field in many scientific areas. However, Canada has particular strengths in DFT methods and homogeneous catalysis; Europe in heterogeneous catalysis, mesoscale, and materials modeling; and Japan in materials modeling and special-purpose computing. Major government-industry initiatives are underway in Europe and Japan, notably in multi-scale materials modeling and in development of chemistry-capable ab-initio molecular dynamics codes.

Digital learning material for experimental design and model building in molecular biology

NARCIS (Netherlands)

Aegerter-Wilmsen, T.

2005-01-01

Designing experimental approaches is a major cognitive skill in molecular biology research, and building models, including quantitative ones, is a cognitive skill which is rapidly gaining importance. Since molecular biology education at university level is aimed at educating future researchers, we

The Effect of Molecular Structure and Environment on the Miscibility and Diffusivity in Polythiophene-Methanofullerene Bulk Heterojunctions: Theory and Modeling with the RISM Approach

Directory of Open Access Journals (Sweden)

Alexander E. Kobryn

2016-04-01

Full Text Available Although better means to model the properties of bulk heterojunction molecular blends are much needed in the field of organic optoelectronics, only a small subset of methods based on molecular dynamics- and Monte Carlo-based approaches have been hitherto employed to guide or replace empirical characterization and testing. Here, we present the first use of the integral equation theory of molecular liquids in modelling the structural properties of blends of phenyl-C61-butyric acid methyl ester (PCBM with poly(3-hexylthiophene (P3HT and a carboxylated poly(3-butylthiophene (P3BT, respectively. For this, we use the Reference Interaction Site Model (RISM with the Universal Force Field (UFF to compute the microscopic structure of blends and obtain insight into the miscibility of its components. Input parameters for RISM, such as optimized molecular geometries and charge distribution of interaction sites, are derived by the Density Functional Theory (DFT methods. We also run Molecular Dynamics (MD simulation to compare the diffusivity of the PCBM in binary blends with P3HT and P3BT, respectively. A remarkably good agreement with available experimental data and results of alternative modelling/simulation is observed for PCBM in the P3HT system. We interpret this as a step in the validation of the use of our approach for organic photovoltaics and support of its results for new systems that do not have reference data for comparison or calibration. In particular, for the less-studied P3BT, our results show that expectations about its performance in binary blends with PCBM may be overestimated, as it does not demonstrate the required level of miscibility and short-range structural organization. In addition, the simulated mobility of PCBM in P3BT is somewhat higher than what is expected for polymer blends and falls into a range typical for fluids. The significance of our predictive multi-scale modelling lies in the insights it offers into nanoscale

Molecular modeling

Directory of Open Access Journals (Sweden)

Aarti Sharma

2009-01-01

Full Text Available The use of computational chemistry in the development of novel pharmaceuticals is becoming an increasingly important tool. In the past, drugs were simply screened for effectiveness. The recent advances in computing power and the exponential growth of the knowledge of protein structures have made it possible for organic compounds to be tailored to decrease the harmful side effects and increase the potency. This article provides a detailed description of the techniques employed in molecular modeling. Molecular modeling is a rapidly developing discipline, and has been supported by the dramatic improvements in computer hardware and software in recent years.

A molecular prognostic model predicts esophageal squamous cell carcinoma prognosis.

Directory of Open Access Journals (Sweden)

Hui-Hui Cao

Full Text Available Esophageal squamous cell carcinoma (ESCC has the highest mortality rates in China. The 5-year survival rate of ESCC remains dismal despite improvements in treatments such as surgical resection and adjuvant chemoradiation, and current clinical staging approaches are limited in their ability to effectively stratify patients for treatment options. The aim of the present study, therefore, was to develop an immunohistochemistry-based prognostic model to improve clinical risk assessment for patients with ESCC.We developed a molecular prognostic model based on the combined expression of axis of epidermal growth factor receptor (EGFR, phosphorylated Specificity protein 1 (p-Sp1, and Fascin proteins. The presence of this prognostic model and associated clinical outcomes were analyzed for 130 formalin-fixed, paraffin-embedded esophageal curative resection specimens (generation dataset and validated using an independent cohort of 185 specimens (validation dataset.The expression of these three genes at the protein level was used to build a molecular prognostic model that was highly predictive of ESCC survival in both generation and validation datasets (P = 0.001. Regression analysis showed that this molecular prognostic model was strongly and independently predictive of overall survival (hazard ratio = 2.358 [95% CI, 1.391-3.996], P = 0.001 in generation dataset; hazard ratio = 1.990 [95% CI, 1.256-3.154], P = 0.003 in validation dataset. Furthermore, the predictive ability of these 3 biomarkers in combination was more robust than that of each individual biomarker.This technically simple immunohistochemistry-based molecular model accurately predicts ESCC patient survival and thus could serve as a complement to current clinical risk stratification approaches.

Molecular Modelling

Directory of Open Access Journals (Sweden)

Aarti Sharma

2009-12-01

Full Text Available

New approaches in mathematical biology: Information theory and molecular machines

International Nuclear Information System (INIS)

Schneider, T.

1995-01-01

My research uses classical information theory to study genetic systems. Information theory was founded by Claude Shannon in the 1940's and has had an enormous impact on communications engineering and computer sciences. Shannon found a way to measure information. This measure can be used to precisely characterize the sequence conservation at nucleic-acid binding sites. The resulting methods, by completely replacing the use of ''consensus sequences'', provide better models for molecular biologists. An excess of conservation led us to do experimental work on bacteriophage T7 promoters and the F plasmid IncD repeats. The wonderful fidelity of telephone communications and compact disk (CD) music can be traced directly to Shannon's channel capacity theorem. When rederived for molecular biology, this theorem explains the surprising precision of many molecular events. Through connections with the Second Law of Thermodyanmics and Maxwell's Demon, this approach also has implications for the development of technology at the molecular level. Discussions of these topics are held on the internet news group bionet.info-theo. (author). (Abstract only)

Combined Molecular Dynamics Simulation-Molecular-Thermodynamic Theory Framework for Predicting Surface Tensions.

Science.gov (United States)

Sresht, Vishnu; Lewandowski, Eric P; Blankschtein, Daniel; Jusufi, Arben

2017-08-22

A molecular modeling approach is presented with a focus on quantitative predictions of the surface tension of aqueous surfactant solutions. The approach combines classical Molecular Dynamics (MD) simulations with a molecular-thermodynamic theory (MTT) [ Y. J. Nikas, S. Puvvada, D. Blankschtein, Langmuir 1992 , 8 , 2680 ]. The MD component is used to calculate thermodynamic and molecular parameters that are needed in the MTT model to determine the surface tension isotherm. The MD/MTT approach provides the important link between the surfactant bulk concentration, the experimental control parameter, and the surfactant surface concentration, the MD control parameter. We demonstrate the capability of the MD/MTT modeling approach on nonionic alkyl polyethylene glycol surfactants at the air-water interface and observe reasonable agreement of the predicted surface tensions and the experimental surface tension data over a wide range of surfactant concentrations below the critical micelle concentration. Our modeling approach can be extended to ionic surfactants and their mixtures with both ionic and nonionic surfactants at liquid-liquid interfaces.

Hybrid Quantum Mechanics/Molecular Mechanics/Coarse Grained Modeling: A Triple-Resolution Approach for Biomolecular Systems.

Science.gov (United States)

Sokkar, Pandian; Boulanger, Eliot; Thiel, Walter; Sanchez-Garcia, Elsa

2015-04-14

We present a hybrid quantum mechanics/molecular mechanics/coarse-grained (QM/MM/CG) multiresolution approach for solvated biomolecular systems. The chemically important active-site region is treated at the QM level. The biomolecular environment is described by an atomistic MM force field, and the solvent is modeled with the CG Martini force field using standard or polarizable (pol-CG) water. Interactions within the QM, MM, and CG regions, and between the QM and MM regions, are treated in the usual manner, whereas the CG-MM and CG-QM interactions are evaluated using the virtual sites approach. The accuracy and efficiency of our implementation is tested for two enzymes, chorismate mutase (CM) and p-hydroxybenzoate hydroxylase (PHBH). In CM, the QM/MM/CG potential energy scans along the reaction coordinate yield reaction energies that are too large, both for the standard and polarizable Martini CG water models, which can be attributed to adverse effects of using large CG water beads. The inclusion of an atomistic MM water layer (10 Å for uncharged CG water and 5 Å for polarizable CG water) around the QM region improves the energy profiles compared to the reference QM/MM calculations. In analogous QM/MM/CG calculations on PHBH, the use of the pol-CG description for the outer water does not affect the stabilization of the highly charged FADHOOH-pOHB transition state compared to the fully atomistic QM/MM calculations. Detailed performance analysis in a glycine-water model system indicates that computation times for QM energy and gradient evaluations at the density functional level are typically reduced by 40-70% for QM/MM/CG relative to fully atomistic QM/MM calculations.

Metal cluster fission: jellium model and Molecular dynamics simulations

DEFF Research Database (Denmark)

Lyalin, Andrey G.; Obolensky, Oleg I.; Solov'yov, Ilia

2004-01-01

Fission of doubly charged sodium clusters is studied using the open-shell two-center deformed jellium model approximation and it ab initio molecular dynamic approach accounting for all electrons in the system. Results of calculations of fission reactions Na_10^2+ --> Na_7^+ + Na_3^+ and Na_18...

Gradient models in molecular biophysics: progress, challenges, opportunities

Science.gov (United States)

Bardhan, Jaydeep P.

2013-12-01

In the interest of developing a bridge between researchers modeling materials and those modeling biological molecules, we survey recent progress in developing nonlocal-dielectric continuum models for studying the behavior of proteins and nucleic acids. As in other areas of science, continuum models are essential tools when atomistic simulations (e.g., molecular dynamics) are too expensive. Because biological molecules are essentially all nanoscale systems, the standard continuum model, involving local dielectric response, has basically always been dubious at best. The advanced continuum theories discussed here aim to remedy these shortcomings by adding nonlocal dielectric response. We begin by describing the central role of electrostatic interactions in biology at the molecular scale, and motivate the development of computationally tractable continuum models using applications in science and engineering. For context, we highlight some of the most important challenges that remain, and survey the diverse theoretical formalisms for their treatment, highlighting the rigorous statistical mechanics that support the use and improvement of continuum models. We then address the development and implementation of nonlocal dielectric models, an approach pioneered by Dogonadze, Kornyshev, and their collaborators almost 40 years ago. The simplest of these models is just a scalar form of gradient elasticity, and here we use ideas from gradient-based modeling to extend the electrostatic model to include additional length scales. The review concludes with a discussion of open questions for model development, highlighting the many opportunities for the materials community to leverage its physical, mathematical, and computational expertise to help solve one of the most challenging questions in molecular biology and biophysics.

Magnetohydrodynamic Models of Molecular Tornadoes

Science.gov (United States)

Au, Kelvin; Fiege, Jason D.

2017-07-01

Recent observations near the Galactic Center (GC) have found several molecular filaments displaying striking helically wound morphology that are collectively known as molecular tornadoes. We investigate the equilibrium structure of these molecular tornadoes by formulating a magnetohydrodynamic model of a rotating, helically magnetized filament. A special analytical solution is derived where centrifugal forces balance exactly with toroidal magnetic stress. From the physics of torsional Alfvén waves we derive a constraint that links the toroidal flux-to-mass ratio and the pitch angle of the helical field to the rotation laws, which we find to be an important component in describing the molecular tornado structure. The models are compared to the Ostriker solution for isothermal, nonmagnetic, nonrotating filaments. We find that neither the analytic model nor the Alfvén wave model suffer from the unphysical density inversions noted by other authors. A Monte Carlo exploration of our parameter space is constrained by observational measurements of the Pigtail Molecular Cloud, the Double Helix Nebula, and the GC Molecular Tornado. Observable properties such as the velocity dispersion, filament radius, linear mass, and surface pressure can be used to derive three dimensionless constraints for our dimensionless models of these three objects. A virial analysis of these constrained models is studied for these three molecular tornadoes. We find that self-gravity is relatively unimportant, whereas magnetic fields and external pressure play a dominant role in the confinement and equilibrium radial structure of these objects.

Magnetohydrodynamic Models of Molecular Tornadoes

Energy Technology Data Exchange (ETDEWEB)

Au, Kelvin; Fiege, Jason D., E-mail: fiege@physics.umanitoba.ca [Department of Physics and Astronomy, University of Manitoba Winnipeg, MB R3T 2N2 (Canada)

2017-07-10

Recent observations near the Galactic Center (GC) have found several molecular filaments displaying striking helically wound morphology that are collectively known as molecular tornadoes. We investigate the equilibrium structure of these molecular tornadoes by formulating a magnetohydrodynamic model of a rotating, helically magnetized filament. A special analytical solution is derived where centrifugal forces balance exactly with toroidal magnetic stress. From the physics of torsional Alfvén waves we derive a constraint that links the toroidal flux-to-mass ratio and the pitch angle of the helical field to the rotation laws, which we find to be an important component in describing the molecular tornado structure. The models are compared to the Ostriker solution for isothermal, nonmagnetic, nonrotating filaments. We find that neither the analytic model nor the Alfvén wave model suffer from the unphysical density inversions noted by other authors. A Monte Carlo exploration of our parameter space is constrained by observational measurements of the Pigtail Molecular Cloud, the Double Helix Nebula, and the GC Molecular Tornado. Observable properties such as the velocity dispersion, filament radius, linear mass, and surface pressure can be used to derive three dimensionless constraints for our dimensionless models of these three objects. A virial analysis of these constrained models is studied for these three molecular tornadoes. We find that self-gravity is relatively unimportant, whereas magnetic fields and external pressure play a dominant role in the confinement and equilibrium radial structure of these objects.

Computing the blood brain barrier (BBB) diffusion coefficient: A molecular dynamics approach

Energy Technology Data Exchange (ETDEWEB)

Shamloo, Amir, E-mail: shamloo@sharif.edu; Pedram, Maysam Z.; Heidari, Hossein; Alasty, Aria, E-mail: aalasti@sharif.edu

2016-07-15

Various physical and biological aspects of the Blood Brain Barrier (BBB) structure still remain unfolded. Therefore, among the several mechanisms of drug delivery, only a few have succeeded in breaching this barrier, one of which is the use of Magnetic Nanoparticles (MNPs). However, a quantitative characterization of the BBB permeability is desirable to find an optimal magnetic force-field. In the present study, a molecular model of the BBB is introduced that precisely represents the interactions between MNPs and the membranes of Endothelial Cells (ECs) that form the BBB. Steered Molecular Dynamics (SMD) simulations of the BBB crossing phenomenon have been carried out. Mathematical modeling of the BBB as an input-output system has been considered from a system dynamics modeling viewpoint, enabling us to analyze the BBB behavior based on a robust model. From this model, the force profile required to overcome the barrier has been extracted for a single NP from the SMD simulations at a range of velocities. Using this data a transfer function model has been obtained and the diffusion coefficient is evaluated. This study is a novel approach to bridge the gap between nanoscale models and microscale models of the BBB. The characteristic diffusion coefficient has the nano-scale molecular effects inherent, furthermore reducing the computational costs of a nano-scale simulation model and enabling much more complex studies to be conducted. - Highlights: • Molecular dynamics simulation of crossing nano-particles through the BBB membrane at different velocities. • Recording the position of nano-particle and the membrane-NP interaction force profile. • Identification of a frequency domain model for the membrane. • Calculating the diffusion coefficient based on MD simulation and identified model. • Obtaining a relation between continuum medium and discrete medium.

Automated chemical kinetic modeling via hybrid reactive molecular dynamics and quantum chemistry simulations.

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Döntgen, Malte; Schmalz, Felix; Kopp, Wassja A; Kröger, Leif C; Leonhard, Kai

2018-06-13

An automated scheme for obtaining chemical kinetic models from scratch using reactive molecular dynamics and quantum chemistry simulations is presented. This methodology combines the phase space sampling of reactive molecular dynamics with the thermochemistry and kinetics prediction capabilities of quantum mechanics. This scheme provides the NASA polynomial and modified Arrhenius equation parameters for all species and reactions that are observed during the simulation and supplies them in the ChemKin format. The ab initio level of theory for predictions is easily exchangeable and the presently used G3MP2 level of theory is found to reliably reproduce hydrogen and methane oxidation thermochemistry and kinetics data. Chemical kinetic models obtained with this approach are ready-to-use for, e.g., ignition delay time simulations, as shown for hydrogen combustion. The presented extension of the ChemTraYzer approach can be used as a basis for methodologically advancing chemical kinetic modeling schemes and as a black-box approach to generate chemical kinetic models.

Molecular Approaches to Studying Denitrification

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Voytek, M. A.

2001-05-01

Denitrification is carried out by a diverse array of microbes, mainly as an alternative mode of respiration that allows the organisms to respire using oxidized N compounds instead of oxygen. A common approach in biogeochemistry to the study of the regulation of denitrification is to assess activity by mass balance of substrates and products or direct rate measurements and has intrinsically assumed resource regulation of denitrification. Reported rates can vary significantly even among ecosystems characterized by similar environmental conditions, thus indicating that direct control by abiotic factors often is not sufficient to predict denitrification rates accurately in natural environments. Alternatively, a microbiological approach would proceed with the identification of the organisms responsible and an evaluation of the effect of environmental factors on the biochemical pathways involved. Traditional studies have relied on culturing techniques, such as most probable number enrichments, and have failed to assess the role of the predominately uncultivable members of the microbial community. A combination of biogeochemical measurements and the assessment of the microbial community is necessary and becoming increasingly possible with the development and application of molecular techniques. In order to understand how the composition and physiological behavior of the microbial community affects denitrification rates, we use a suite of molecular techniques developed for phylogenetic and metabolic characterization of denitrifying communities. Molecular tools available for quantifying denitrifying bacteria and assessing their diversity and activity are summarized. Their application is illustrated with examples from marine and freshwater environments. Emerging techniques and their application to ground water studies will be discussed.

Molecular level in silico studies for oncology. Direct models review

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Psakhie, S. G.; Tsukanov, A. A.

2017-09-01

The combination of therapy and diagnostics in one process "theranostics" is a trend in a modern medicine, especially in oncology. Such an approach requires development and usage of multifunctional hybrid nanoparticles with a hierarchical structure. Numerical methods and mathematical models play a significant role in the design of the hierarchical nanoparticles and allow looking inside the nanoscale mechanisms of agent-cell interactions. The current position of in silico approach in biomedicine and oncology is discussed. The review of the molecular level in silico studies in oncology, which are using the direct models, is presented.

Dissecting the critical factors for thermodynamic stability of modular proteins using molecular modeling approach.

Directory of Open Access Journals (Sweden)

Yuno Lee

Full Text Available Repeat proteins have recently attracted much attention as alternative scaffolds to immunoglobulin antibodies due to their unique structural and biophysical features. In particular, repeat proteins show high stability against temperature and chaotic agents. Despite many studies, structural features for the stability of repeat proteins remain poorly understood. Here we present an interesting result from in silico analyses pursuing the factors which affect the stability of repeat proteins. Previously developed repebody structure based on variable lymphocytes receptors (VLRs which consists of leucine-rich repeat (LRR modules was used as initial structure for the present study. We constructed extra six repebody structures with varying numbers of repeat modules and those structures were used for molecular dynamics simulations. For the structures, the intramolecular interactions including backbone H-bonds, van der Waals energy, and hydrophobicity were investigated and then the radius of gyration, solvent-accessible surface area, ratio of secondary structure, and hydration free energy were also calculated to find out the relationship between the number of LRR modules and stability of the protein. Our results show that the intramolecular interactions lead to more compact structure and smaller surface area of the repebodies, which are critical for the stability of repeat proteins. The other features were also well compatible with the experimental results. Based on our observations, the repebody-5 was proposed as the best structure from the all repebodies in structure optimization process. The present study successfully demonstrated that our computer-based molecular modeling approach can significantly contribute to the experiment-based protein engineering challenge.

Gradient Models in Molecular Biophysics: Progress, Challenges, Opportunities.

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Bardhan, Jaydeep P

2013-12-01

In the interest of developing a bridge between researchers modeling materials and those modeling biological molecules, we survey recent progress in developing nonlocal-dielectric continuum models for studying the behavior of proteins and nucleic acids. As in other areas of science, continuum models are essential tools when atomistic simulations (e.g. molecular dynamics) are too expensive. Because biological molecules are essentially all nanoscale systems, the standard continuum model, involving local dielectric response, has basically always been dubious at best. The advanced continuum theories discussed here aim to remedy these shortcomings by adding features such as nonlocal dielectric response, and nonlinearities resulting from dielectric saturation. We begin by describing the central role of electrostatic interactions in biology at the molecular scale, and motivate the development of computationally tractable continuum models using applications in science and engineering. For context, we highlight some of the most important challenges that remain and survey the diverse theoretical formalisms for their treatment, highlighting the rigorous statistical mechanics that support the use and improvement of continuum models. We then address the development and implementation of nonlocal dielectric models, an approach pioneered by Dogonadze, Kornyshev, and their collaborators almost forty years ago. The simplest of these models is just a scalar form of gradient elasticity, and here we use ideas from gradient-based modeling to extend the electrostatic model to include additional length scales. The paper concludes with a discussion of open questions for model development, highlighting the many opportunities for the materials community to leverage its physical, mathematical, and computational expertise to help solve one of the most challenging questions in molecular biology and biophysics.

Gradient Models in Molecular Biophysics: Progress, Challenges, Opportunities

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Bardhan, Jaydeep P.

2014-01-01

In the interest of developing a bridge between researchers modeling materials and those modeling biological molecules, we survey recent progress in developing nonlocal-dielectric continuum models for studying the behavior of proteins and nucleic acids. As in other areas of science, continuum models are essential tools when atomistic simulations (e.g. molecular dynamics) are too expensive. Because biological molecules are essentially all nanoscale systems, the standard continuum model, involving local dielectric response, has basically always been dubious at best. The advanced continuum theories discussed here aim to remedy these shortcomings by adding features such as nonlocal dielectric response, and nonlinearities resulting from dielectric saturation. We begin by describing the central role of electrostatic interactions in biology at the molecular scale, and motivate the development of computationally tractable continuum models using applications in science and engineering. For context, we highlight some of the most important challenges that remain and survey the diverse theoretical formalisms for their treatment, highlighting the rigorous statistical mechanics that support the use and improvement of continuum models. We then address the development and implementation of nonlocal dielectric models, an approach pioneered by Dogonadze, Kornyshev, and their collaborators almost forty years ago. The simplest of these models is just a scalar form of gradient elasticity, and here we use ideas from gradient-based modeling to extend the electrostatic model to include additional length scales. The paper concludes with a discussion of open questions for model development, highlighting the many opportunities for the materials community to leverage its physical, mathematical, and computational expertise to help solve one of the most challenging questions in molecular biology and biophysics. PMID:25505358

A classical Master equation approach to modeling an artificial protein motor

International Nuclear Information System (INIS)

Kuwada, Nathan J.; Blab, Gerhard A.; Linke, Heiner

2010-01-01

Inspired by biomolecular motors, as well as by theoretical concepts for chemically driven nanomotors, there is significant interest in constructing artificial molecular motors. One driving force is the opportunity to create well-controlled model systems that are simple enough to be modeled in detail. A remaining challenge is the fact that such models need to take into account processes on many different time scales. Here we describe use of a classical Master equation approach, integrated with input from Langevin and molecular dynamics modeling, to stochastically model an existing artificial molecular motor concept, the Tumbleweed, across many time scales. This enables us to study how interdependencies between motor processes, such as center-of-mass diffusion and track binding/unbinding, affect motor performance. Results from our model help guide the experimental realization of the proposed motor, and potentially lead to insights that apply to a wider class of molecular motors.

Modeling of nanotoxicity molecular interactions of nanomaterials with bionanomachines

CERN Document Server

Zhou, Ruhong

2015-01-01

This book provides a comprehensive overview of the fundamentals of nanotoxicity modeling and its implications for the development of novel nanomedicines. It lays out the fundamentals of nanotoxicity modeling for an array of nanomaterial systems, ranging from carbon-based nanoparticles to noble metals, metal oxides, and quantum dots. The author illustrates how molecular (classical mechanics) and atomic (quantum mechanics) modeling approaches can be applied to bolster our understanding of many important aspects of this critical nanotoxicity issue. Each chapter is organized by types of nanomaterials for practicality, making this an ideal book for senior undergraduate students, graduate students, and researchers in nanotechnology, chemistry, physics, molecular biology, and computer science. It is also of interest to academic and industry professionals who work on nanodrug delivery and related biomedical applications, and aids readers in their biocompatibility assessment efforts in the coming age of nanotechnology...

Chemical Topic Modeling: Exploring Molecular Data Sets Using a Common Text-Mining Approach.

Science.gov (United States)

Schneider, Nadine; Fechner, Nikolas; Landrum, Gregory A; Stiefl, Nikolaus

2017-08-28

Big data is one of the key transformative factors which increasingly influences all aspects of modern life. Although this transformation brings vast opportunities it also generates novel challenges, not the least of which is organizing and searching this data deluge. The field of medicinal chemistry is not different: more and more data are being generated, for instance, by technologies such as DNA encoded libraries, peptide libraries, text mining of large literature corpora, and new in silico enumeration methods. Handling those huge sets of molecules effectively is quite challenging and requires compromises that often come at the expense of the interpretability of the results. In order to find an intuitive and meaningful approach to organizing large molecular data sets, we adopted a probabilistic framework called "topic modeling" from the text-mining field. Here we present the first chemistry-related implementation of this method, which allows large molecule sets to be assigned to "chemical topics" and investigating the relationships between those. In this first study, we thoroughly evaluate this novel method in different experiments and discuss both its disadvantages and advantages. We show very promising results in reproducing human-assigned concepts using the approach to identify and retrieve chemical series from sets of molecules. We have also created an intuitive visualization of the chemical topics output by the algorithm. This is a huge benefit compared to other unsupervised machine-learning methods, like clustering, which are commonly used to group sets of molecules. Finally, we applied the new method to the 1.6 million molecules of the ChEMBL22 data set to test its robustness and efficiency. In about 1 h we built a 100-topic model of this large data set in which we could identify interesting topics like "proteins", "DNA", or "steroids". Along with this publication we provide our data sets and an open-source implementation of the new method (CheTo) which

Direct calculation of ice homogeneous nucleation rate for a molecular model of water

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Haji-Akbari, Amir; Debenedetti, Pablo G.

2015-01-01

Ice formation is ubiquitous in nature, with important consequences in a variety of environments, including biological cells, soil, aircraft, transportation infrastructure, and atmospheric clouds. However, its intrinsic kinetics and microscopic mechanism are difficult to discern with current experiments. Molecular simulations of ice nucleation are also challenging, and direct rate calculations have only been performed for coarse-grained models of water. For molecular models, only indirect estimates have been obtained, e.g., by assuming the validity of classical nucleation theory. We use a path sampling approach to perform, to our knowledge, the first direct rate calculation of homogeneous nucleation of ice in a molecular model of water. We use TIP4P/Ice, the most accurate among existing molecular models for studying ice polymorphs. By using a novel topological approach to distinguish different polymorphs, we are able to identify a freezing mechanism that involves a competition between cubic and hexagonal ice in the early stages of nucleation. In this competition, the cubic polymorph takes over because the addition of new topological structural motifs consistent with cubic ice leads to the formation of more compact crystallites. This is not true for topological hexagonal motifs, which give rise to elongated crystallites that are not able to grow. This leads to transition states that are rich in cubic ice, and not the thermodynamically stable hexagonal polymorph. This mechanism provides a molecular explanation for the earlier experimental and computational observations of the preference for cubic ice in the literature. PMID:26240318

Modeling molecular acidity with electronic properties and Hammett constants for substituted benzoic acids.

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Huang, Ying; Liu, Lianghong; Liu, Wanhui; Liu, Shaogang; Liu, Shubin

2011-12-29

Molecular acidity is an important physiochemical property essential in many fields of molecular studies, but an efficient and reliable computational approach to make accurate predictions is still missing. In this work, based on our previous studies to use gas phase electronic properties such as molecular electrostatic potential and valence natural atomic orbitals of the acidic atom and leaving proton, we demonstrate here that different approaches can be employed to tackle this problem. To that end, we employ 196 singly, doubly, and triply substituted benzoic acids for the study. We show that two different approaches are possible, one focusing on the carboxyl group through its localized electronic properties and the other on the substituting groups via Hammett constants and their additivity rule. Our present results clearly exhibit that with the linear models built from the singly substituted species, one can accurately predict the pK(a) values for the doubly and triply substituted species with both of these two approaches. The predictions from these approaches are consistent with each other and agree well with the experimental data. These intrinsically different approaches are the two manifestations of the same molecular acidity property, both valid and complementary to each other. © 2011 American Chemical Society

Tunneling of electrons via rotor–stator molecular interfaces: Combined ab initio and model study

Energy Technology Data Exchange (ETDEWEB)

Petreska, Irina, E-mail: irina.petreska@pmf.ukim.mk [Institute of Physics, Faculty of Natural Sciences and Mathematics, Ss. Cyril and Methodius University, PO Box 162, 1000 Skopje, Former Yugolav Republic of Macedonia, The (Macedonia, The Former Yugoslav Republic of); Ohanesjan, Vladimir [Institute of Physics, Faculty of Natural Sciences and Mathematics, Ss. Cyril and Methodius University, PO Box 162, 1000 Skopje, Former Yugolav Republic of Macedonia, The (Macedonia, The Former Yugoslav Republic of); Pejov, Ljupčo [Institute of Chemistry, Department of Physical Chemistry, Ss. Cyril and Methodius University, Arhimedova 5, P.O. Box 162, 1000 Skopje, Former Yugolav Republic of Macedonia, The (Macedonia, The Former Yugoslav Republic of); Kocarev, Ljupčo [Macedonian Academy of Sciences and Arts, Krste Misirkov 2, PO Box 428, 1000 Skopje, Former Yugolav Republic of Macedonia, The (Macedonia, The Former Yugoslav Republic of); Faculty of Computer Science and Engineering, Ss. Cyril and Methodius University, Skopje, Former Yugolav Republic of Macedonia, The (Macedonia, The Former Yugoslav Republic of)

2016-07-01

Tunneling of electrons through rotor–stator anthracene aldehyde molecular interfaces is studied with a combined ab initio and model approach. Molecular electronic structure calculated from first principles is utilized to model different shapes of tunneling barriers. Together with a rectangular barrier, we also consider a sinusoidal shape that captures the effects of the molecular internal structure more realistically. Quasiclassical approach with the Simmons’ formula for current density is implemented. Special attention is paid on conformational dependence of the tunneling current. Our results confirm that the presence of the side aldehyde group enhances the interesting electronic properties of the pure anthracene molecule, making it a bistable system with geometry dependent transport properties. We also investigate the transition voltage and we show that conformation-dependent field emission could be observed in these molecular interfaces at realistically low voltages. The present study accompanies our previous work where we investigated the coherent transport via strongly coupled delocalized orbital by application of Non-equilibrium Green’s Function Formalism.

Open source molecular modeling.

Science.gov (United States)

Pirhadi, Somayeh; Sunseri, Jocelyn; Koes, David Ryan

2016-09-01

The success of molecular modeling and computational chemistry efforts are, by definition, dependent on quality software applications. Open source software development provides many advantages to users of modeling applications, not the least of which is that the software is free and completely extendable. In this review we categorize, enumerate, and describe available open source software packages for molecular modeling and computational chemistry. An updated online version of this catalog can be found at https://opensourcemolecularmodeling.github.io. Copyright © 2016 The Author(s). Published by Elsevier Inc. All rights reserved.

PRO_LIGAND: an approach to de novo molecular design. 2. Design of novel molecules from molecular field analysis (MFA) models and pharmacophores.

Science.gov (United States)

Waszkowycz, B; Clark, D E; Frenkel, D; Li, J; Murray, C W; Robson, B; Westhead, D R

1994-11-11

A computational approach for molecular design, PRO_LIGAND, has been developed within the PROMETHEUS molecular design and simulation system in order to provide a unified framework for the de novo generation of diverse molecules which are either similar or complementary to a specified target. In this instance, the target is a pharmacophore derived from a series of active structures either by a novel interpretation of molecular field analysis data or by a pharmacophore-mapping procedure based on clique detection. After a brief introduction to PRO_LIGAND, a detailed description is given of the two pharmacophore generation procedures and their abilities are demonstrated by the elucidation of pharmacophores for steroid binding and ACE inhibition, respectively. As a further indication of its efficacy in aiding the rational drug design process, PRO_LIGAND is then employed to build novel organic molecules to satisfy the physicochemical constraints implied by the pharmacophores.

A Systems Biology Approach to Understanding Alcoholic Liver Disease Molecular Mechanism: The Development of Static and Dynamic Models.

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Shafaghati, Leila; Razaghi-Moghadam, Zahra; Mohammadnejad, Javad

2017-11-01

Alcoholic liver disease (ALD) is a complex disease characterized by damages to the liver and is the consequence of excessive alcohol consumption over years. Since this disease is associated with several pathway failures, pathway reconstruction and network analysis are likely to explicit the molecular basis of the disease. To this aim, in this paper, a network medicine approach was employed to integrate interactome (protein-protein interaction and signaling pathways) and transcriptome data to reconstruct both a static network of ALD and a dynamic model for it. Several data sources were exploited to assemble a set of ALD-associated genes which further was used for network reconstruction. Moreover, a comprehensive literature mining reveals that there are four signaling pathways with crosstalk (TLR4, NF- [Formula: see text]B, MAPK and Apoptosis) which play a major role in ALD. These four pathways were exploited to reconstruct a dynamic model of ALD. The results assure that these two models are consistent with a number of experimental observations. The static network of ALD and its dynamic model are the first models provided for ALD which offer potentially valuable information for researchers in this field.

Bayesian semiparametric regression models to characterize molecular evolution

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Datta Saheli

2012-10-01

Full Text Available Abstract Background Statistical models and methods that associate changes in the physicochemical properties of amino acids with natural selection at the molecular level typically do not take into account the correlations between such properties. We propose a Bayesian hierarchical regression model with a generalization of the Dirichlet process prior on the distribution of the regression coefficients that describes the relationship between the changes in amino acid distances and natural selection in protein-coding DNA sequence alignments. Results The Bayesian semiparametric approach is illustrated with simulated data and the abalone lysin sperm data. Our method identifies groups of properties which, for this particular dataset, have a similar effect on evolution. The model also provides nonparametric site-specific estimates for the strength of conservation of these properties. Conclusions The model described here is distinguished by its ability to handle a large number of amino acid properties simultaneously, while taking into account that such data can be correlated. The multi-level clustering ability of the model allows for appealing interpretations of the results in terms of properties that are roughly equivalent from the standpoint of molecular evolution.

Computer modeling of properties of complex molecular systems

Energy Technology Data Exchange (ETDEWEB)

Kulkova, E.Yu. [Moscow State University of Technology “STANKIN”, Vadkovsky per., 1, Moscow 101472 (Russian Federation); Khrenova, M.G.; Polyakov, I.V. [Lomonosov Moscow State University, Chemistry Department, Leninskie Gory 1/3, Moscow 119991 (Russian Federation); Nemukhin, A.V. [Lomonosov Moscow State University, Chemistry Department, Leninskie Gory 1/3, Moscow 119991 (Russian Federation); N.M. Emanuel Institute of Biochemical Physics, Russian Academy of Sciences, Kosygina 4, Moscow 119334 (Russian Federation)

2015-03-10

Large molecular aggregates present important examples of strongly nonhomogeneous systems. We apply combined quantum mechanics / molecular mechanics approaches that assume treatment of a part of the system by quantum-based methods and the rest of the system with conventional force fields. Herein we illustrate these computational approaches by two different examples: (1) large-scale molecular systems mimicking natural photosynthetic centers, and (2) components of prospective solar cells containing titan dioxide and organic dye molecules. We demonstrate that modern computational tools are capable to predict structures and spectra of such complex molecular aggregates.

The Secondary Organic Aerosol Processor (SOAP v1.0) model: a unified model with different ranges of complexity based on the molecular surrogate approach

Science.gov (United States)

Couvidat, F.; Sartelet, K.

2015-04-01

In this paper the Secondary Organic Aerosol Processor (SOAP v1.0) model is presented. This model determines the partitioning of organic compounds between the gas and particle phases. It is designed to be modular with different user options depending on the computation time and the complexity required by the user. This model is based on the molecular surrogate approach, in which each surrogate compound is associated with a molecular structure to estimate some properties and parameters (hygroscopicity, absorption into the aqueous phase of particles, activity coefficients and phase separation). Each surrogate can be hydrophilic (condenses only into the aqueous phase of particles), hydrophobic (condenses only into the organic phases of particles) or both (condenses into both the aqueous and the organic phases of particles). Activity coefficients are computed with the UNIFAC (UNIversal Functional group Activity Coefficient; Fredenslund et al., 1975) thermodynamic model for short-range interactions and with the Aerosol Inorganic-Organic Mixtures Functional groups Activity Coefficients (AIOMFAC) parameterization for medium- and long-range interactions between electrolytes and organic compounds. Phase separation is determined by Gibbs energy minimization. The user can choose between an equilibrium representation and a dynamic representation of organic aerosols (OAs). In the equilibrium representation, compounds in the particle phase are assumed to be at equilibrium with the gas phase. However, recent studies show that the organic aerosol is not at equilibrium with the gas phase because the organic phases could be semi-solid (very viscous liquid phase). The condensation-evaporation of organic compounds could then be limited by the diffusion in the organic phases due to the high viscosity. An implicit dynamic representation of secondary organic aerosols (SOAs) is available in SOAP with OAs divided into layers, the first layer being at the center of the particle (slowly

Integrating survey and molecular approaches to better understand wildlife disease ecology.

Directory of Open Access Journals (Sweden)

Brendan D Cowled

Full Text Available Infectious wildlife diseases have enormous global impacts, leading to human pandemics, global biodiversity declines and socio-economic hardship. Understanding how infection persists and is transmitted in wildlife is critical for managing diseases, but our understanding is limited. Our study aim was to better understand how infectious disease persists in wildlife populations by integrating genetics, ecology and epidemiology approaches. Specifically, we aimed to determine whether environmental or host factors were stronger drivers of Salmonella persistence or transmission within a remote and isolated wild pig (Sus scrofa population. We determined the Salmonella infection status of wild pigs. Salmonella isolates were genotyped and a range of data was collected on putative risk factors for Salmonella transmission. We a priori identified several plausible biological hypotheses for Salmonella prevalence (cross sectional study design versus transmission (molecular case series study design and fit the data to these models. There were 543 wild pig Salmonella observations, sampled at 93 unique locations. Salmonella prevalence was 41% (95% confidence interval [CI]: 37-45%. The median Salmonella DICE coefficient (or Salmonella genetic similarity was 52% (interquartile range [IQR]: 42-62%. Using the traditional cross sectional prevalence study design, the only supported model was based on the hypothesis that abundance of available ecological resources determines Salmonella prevalence in wild pigs. In the molecular study design, spatial proximity and herd membership as well as some individual risk factors (sex, condition score and relative density determined transmission between pigs. Traditional cross sectional surveys and molecular epidemiological approaches are complementary and together can enhance understanding of disease ecology: abundance of ecological resources critical for wildlife influences Salmonella prevalence, whereas Salmonella transmission is

Integrating Survey and Molecular Approaches to Better Understand Wildlife Disease Ecology

Science.gov (United States)

Cowled, Brendan D.; Ward, Michael P.; Laffan, Shawn W.; Galea, Francesca; Garner, M. Graeme; MacDonald, Anna J.; Marsh, Ian; Muellner, Petra; Negus, Katherine; Quasim, Sumaiya; Woolnough, Andrew P.; Sarre, Stephen D.

2012-01-01

Infectious wildlife diseases have enormous global impacts, leading to human pandemics, global biodiversity declines and socio-economic hardship. Understanding how infection persists and is transmitted in wildlife is critical for managing diseases, but our understanding is limited. Our study aim was to better understand how infectious disease persists in wildlife populations by integrating genetics, ecology and epidemiology approaches. Specifically, we aimed to determine whether environmental or host factors were stronger drivers of Salmonella persistence or transmission within a remote and isolated wild pig (Sus scrofa) population. We determined the Salmonella infection status of wild pigs. Salmonella isolates were genotyped and a range of data was collected on putative risk factors for Salmonella transmission. We a priori identified several plausible biological hypotheses for Salmonella prevalence (cross sectional study design) versus transmission (molecular case series study design) and fit the data to these models. There were 543 wild pig Salmonella observations, sampled at 93 unique locations. Salmonella prevalence was 41% (95% confidence interval [CI]: 37–45%). The median Salmonella DICE coefficient (or Salmonella genetic similarity) was 52% (interquartile range [IQR]: 42–62%). Using the traditional cross sectional prevalence study design, the only supported model was based on the hypothesis that abundance of available ecological resources determines Salmonella prevalence in wild pigs. In the molecular study design, spatial proximity and herd membership as well as some individual risk factors (sex, condition score and relative density) determined transmission between pigs. Traditional cross sectional surveys and molecular epidemiological approaches are complementary and together can enhance understanding of disease ecology: abundance of ecological resources critical for wildlife influences Salmonella prevalence, whereas Salmonella transmission is driven by

A classical approach in simple nuclear fusion reaction 1H2+1H3 using two-dimension granular molecular dynamics model

International Nuclear Information System (INIS)

Viridi, S.; Kurniadi, R.; Waris, A.; Perkasa, Y. S.

2012-01-01

Molecular dynamics in 2-D accompanied by granular model provides an opportunity to investigate binding between nuclei particles and its properties that arises during collision in a fusion reaction. A fully classical approach is used to observe the influence of initial angle of nucleus orientation to the product yielded by the reaction. As an example, a simplest fusion reaction between 1 H 2 and 1 H 3 is observed. Several products of the fusion reaction have been obtained, even the unreported ones, including temporary 2 He 4 nucleus.

Theoretical study of molecular vibrations in electron momentum spectroscopy experiments on furan: An analytical versus a molecular dynamical approach

International Nuclear Information System (INIS)

Morini, Filippo; Deleuze, Michael S.; Watanabe, Noboru; Takahashi, Masahiko

2015-01-01

The influence of thermally induced nuclear dynamics (molecular vibrations) in the initial electronic ground state on the valence orbital momentum profiles of furan has been theoretically investigated using two different approaches. The first of these approaches employs the principles of Born-Oppenheimer molecular dynamics, whereas the so-called harmonic analytical quantum mechanical approach resorts to an analytical decomposition of contributions arising from quantized harmonic vibrational eigenstates. In spite of their intrinsic differences, the two approaches enable consistent insights into the electron momentum distributions inferred from new measurements employing electron momentum spectroscopy and an electron impact energy of 1.2 keV. Both approaches point out in particular an appreciable influence of a few specific molecular vibrations of A 1 symmetry on the 9a 1 momentum profile, which can be unravelled from considerations on the symmetry characteristics of orbitals and their energy spacing

Description of ionization in the molecular approach to atomic collisions. II

International Nuclear Information System (INIS)

Errea, L.F.; Mendez, L.; Riera, A.; Sevila, I.; Harel, C.; Jouin, H.; Pons, B.

2002-01-01

We complement a previous article [Harel et al., Phys. Rev. A 55, 287 (1997)] that studied the characteristics of the description of ionization by the molecular approach to atomic collisions, by comparing the wave functions with accurate counterparts. We show how the failure of the basis to describe the phase of the ionizing wave function results in a trapping of the corresponding population in some molecular channels. The time evolution of the molecular wave function then departs from the exact one and the ionization and capture mechanisms appear as interlocked. We thus elucidate the question of the 'natural' boundary of the molecular approach and draw further consequences as to the choice of pseudostates and the use of translation factors

An analytic approach to 2D electronic PE spectra of molecular systems

International Nuclear Information System (INIS)

Szoecs, V.

2011-01-01

Graphical abstract: The three-pulse photon echo (3P-PE) spectra of finite molecular systems using direct calculation from electronic Hamiltonians allows peak classification from 3P-PE spectra dynamics. Display Omitted Highlights: → RWA approach to electronic photon echo. → A straightforward calculation of 2D electronic spectrograms in finite molecular systems. → Importance of population time dynamics in relation to inter-site coherent coupling. - Abstract: The three-pulse photon echo (3P-PE) spectra of finite molecular systems and simplified line broadening models is presented. The Fourier picture of a heterodyne detected three-pulse rephasing PE signal in the δ-pulse limit of the external field is derived in analytic form. The method includes contributions of one and two-excitonic states and allows direct calculation of Fourier PE spectrogram from corresponding Hamiltonian. As an illustration, the proposed treatment is applied to simple systems, e.g. 2-site two-level system (TLS) and n-site TLS model of photosynthetic unit. The importance of relation between Fourier picture of 3P-PE dynamics (corresponding to nonzero population time, T) and coherent inter-state coupling is emphasized.

Molecular biology approaches in bioadhesion research

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Marcelo Rodrigues

2014-07-01

Full Text Available The use of molecular biology tools in the field of bioadhesion is still in its infancy. For new research groups who are considering taking a molecular approach, the techniques presented here are essential to unravelling the sequence of a gene, its expression and its biological function. Here we provide an outline for addressing adhesion-related genes in diverse organisms. We show how to gradually narrow down the number of candidate transcripts that are involved in adhesion by (1 generating a transcriptome and a differentially expressed cDNA list enriched for adhesion-related transcripts, (2 setting up a BLAST search facility, (3 perform an in situ hybridization screen, and (4 functional analyses of selected genes by using RNA interference knock-down. Furthermore, latest developments in genome-editing are presented as new tools to study gene function. By using this iterative multi-technologies approach, the identification, isolation, expression and function of adhesion-related genes can be studied in most organisms. These tools will improve our understanding of the diversity of molecules used for adhesion in different organisms and these findings will help to develop innovative bio-inspired adhesives.

Molecular approaches for bacterial azoreductases

Directory of Open Access Journals (Sweden)

Montira Leelakriangsak

2013-12-01

Full Text Available Azo dyes are the dominant types of synthetic dyes, widely used in textiles, foods, leather, printing, tattooing, cosmetics, and pharmaceutical industries. Many microorganisms are able to decolorize azo dyes, and there is increasing interest in biological waste treatment methods. Bacterial azoreductases can cleave azo linkages (-N=N- in azo dyes, forming aromatic amines. This review mainly focuses on employing molecular approaches, including gene manipulation and recombinant strains, to study bacterial azoreductases. The construction of the recombinant protein by cloning and the overexpression of azoreductase is described. The mechanisms and function of bacterial azoreductases can be studied by other molecular techniques discussed in this review, such as RT-PCR, southern blot analysis, western blot analysis, zymography, and muta-genesis in order to understand bacterial azoreductase properties, function and application. In addition, understanding the regulation of azoreductase gene expression will lead to the systematic use of gene manipulation in bacterial strains for new strategies in future waste remediation technologies.

Usher syndrome (sensorineural deafness and retinitis pigmentosa): pathogenesis, molecular diagnosis and therapeutic approaches.

Science.gov (United States)

Bonnet, Crystel; El-Amraoui, Aziz

2012-02-01

Usher syndrome (USH) is the most prevalent cause of hereditary deafness-blindness in humans. In this review, we pinpoint new insights regarding the molecular mechanisms defective in this syndrome, its molecular diagnosis and prospective therapies. Animal models wherein USH proteins were targeted at different maturation stages of the auditory hair cells have been engineered, shedding new light on the development and functioning of the hair bundle, the sound receptive structure. Improved protocols and guidelines for early molecular diagnosis of USH (USH genotyping microarrays, otochips and complete Sanger sequencing of the 366 coding exons of identified USH genes) have been developed. Approaches to alleviate or cure hearing and visual impairments have been initiated, leading to various degrees of functional rescuing. Whereas the mechanisms underlying hearing impairment in USH patients are being unraveled, showing in particular that USH1 proteins are involved in the shaping of the hair bundle and the functioning of the mechanoelectrical transduction machinery, the mechanisms underlying the retinal defects are still unclear. Efforts to improve clinical diagnosis have been successful. Yet, despite some encouraging results, further development of therapeutic approaches is necessary to ultimately treat this dual sensory defect.

Thumbs down: a molecular-morphogenetic approach to avian digit homology.

Science.gov (United States)

Capek, Daniel; Metscher, Brian D; Müller, Gerd B

2014-01-01

Avian forelimb digit homology remains one of the standard themes in comparative biology and EvoDevo research. In order to resolve the apparent contradictions between embryological and paleontological evidence a variety of hypotheses have been presented in recent years. The proposals range from excluding birds from the dinosaur clade, to assignments of homology by different criteria, or even assuming a hexadactyl tetrapod limb ground state. At present two approaches prevail: the frame shift hypothesis and the pyramid reduction hypothesis. While the former postulates a homeotic shift of digit identities, the latter argues for a gradual bilateral reduction of phalanges and digits. Here we present a new model that integrates elements from both hypotheses with the existing experimental and fossil evidence. We start from the main feature common to both earlier concepts, the initiating ontogenetic event: reduction and loss of the anterior-most digit. It is proposed that a concerted mechanism of molecular regulation and developmental mechanics is capable of shifting the boundaries of hoxD expression in embryonic forelimb buds as well as changing the digit phenotypes. Based on a distinction between positional (topological) and compositional (phenotypic) homology criteria, we argue that the identity of the avian digits is II, III, IV, despite a partially altered phenotype. Finally, we introduce an alternative digit reduction scheme that reconciles the current fossil evidence with the presented molecular-morphogenetic model. Our approach identifies specific experiments that allow to test whether gene expression can be shifted and digit phenotypes can be altered by induced digit loss or digit gain. © 2013 Wiley Periodicals, Inc.

Combinatorial chemistry approach to development of molecular plastic solar cells

NARCIS (Netherlands)

Godovsky, Dmitri; Inganäs, Olle; Brabec, Christoph J.; Sariciftci, N. Serdar; Hummelen, Jan C.; Janssen, Rene A.J.; Prato, M.; Maggini, M.; Segura, Jose; Martin, Nazario

1999-01-01

We used a combinatorial chemistry approach to develop the molecular plastic solar cells based on soluble fullerene derivatives or solubilized TCNQ molecules in combination with conjugated polymers. Profiles, formed by the diffusion of low molecular weight component in the spin-cast polymer host were

Individual Biomarkers Using Molecular Personalized Medicine Approaches.

Science.gov (United States)

Zenner, Hans P

2017-01-01

Molecular personalized medicine tries to generate individual predictive biomarkers to assist doctors in their decision making. These are thought to improve the efficacy and lower the toxicity of a treatment. The molecular basis of the desired high-precision prediction is modern "omex" technologies providing high-throughput bioanalytical methods. These include genomics and epigenomics, transcriptomics, proteomics, metabolomics, microbiomics, imaging, and functional analyses. In most cases, producing big data also requires a complex biomathematical analysis. Using molecular personalized medicine, the conventional physician's check of biomarker results may no longer be sufficient. By contrast, the physician may need to cooperate with the biomathematician to achieve the desired prediction on the basis of the analysis of individual big data typically produced by omex technologies. Identification of individual biomarkers using molecular personalized medicine approaches is thought to allow a decision-making for the precise use of a targeted therapy, selecting the successful therapeutic tool from a panel of preexisting drugs or medical products. This should avoid the treatment of nonresponders and responders that produces intolerable unwanted effects. © 2017 S. Karger AG, Basel.

Multiscale Molecular Dynamics Model for Heterogeneous Charged Systems

Science.gov (United States)

Stanton, L. G.; Glosli, J. N.; Murillo, M. S.

2018-04-01

Modeling matter across large length scales and timescales using molecular dynamics simulations poses significant challenges. These challenges are typically addressed through the use of precomputed pair potentials that depend on thermodynamic properties like temperature and density; however, many scenarios of interest involve spatiotemporal variations in these properties, and such variations can violate assumptions made in constructing these potentials, thus precluding their use. In particular, when a system is strongly heterogeneous, most of the usual simplifying assumptions (e.g., spherical potentials) do not apply. Here, we present a multiscale approach to orbital-free density functional theory molecular dynamics (OFDFT-MD) simulations that bridges atomic, interionic, and continuum length scales to allow for variations in hydrodynamic quantities in a consistent way. Our multiscale approach enables simulations on the order of micron length scales and 10's of picosecond timescales, which exceeds current OFDFT-MD simulations by many orders of magnitude. This new capability is then used to study the heterogeneous, nonequilibrium dynamics of a heated interface characteristic of an inertial-confinement-fusion capsule containing a plastic ablator near a fuel layer composed of deuterium-tritium ice. At these scales, fundamental assumptions of continuum models are explored; features such as the separation of the momentum fields among the species and strong hydrogen jetting from the plastic into the fuel region are observed, which had previously not been seen in hydrodynamic simulations.

A Statistical Approach to Exoplanetary Molecular Spectroscopy Using Spitzer Eclipses

Science.gov (United States)

Deming, Drake; Garhart, Emily; Burrows, Adam; Fortney, Jonathan; Knutson, Heather; Todorov, Kamen

2018-01-01

Secondary eclipses of exoplanets observed using the Spitzer Space Telescope measure the total emission emergent from exoplanetary atmospheres integrated over broad photometric bands. Spitzer photometry is excellent for measuring day side temperatures, but is less well suited to the detection of molecular absorption or emission features. Even for very hot exoplanets, it can be difficult to attain the accuracy on eclipse depth that is needed to unambiguously interpret the Spitzer results in terms of molecular absorption or emission. However, a statistical approach, wherein we seek deviations from a simple blackbody planet as a function of the planet's equilibrium temperature, shows promise for defining the nature and strength of molecular absorption in ensembles of planets. In this paper, we explore such an approach using secondary eclipses observed for tens of hot exoplanets during Spitzer's Cycles 10, 12, and 13. We focus on the possibility that the hottest planets exhibit molecular features in emission, due to temperature inversions.

3D Printing of Molecular Models

Science.gov (United States)

Gardner, Adam; Olson, Arthur

2016-01-01

Physical molecular models have played a valuable role in our understanding of the invisible nano-scale world. We discuss 3D printing and its use in producing models of the molecules of life. Complex biomolecular models, produced from 3D printed parts, can demonstrate characteristics of molecular structure and function, such as viral self-assembly,…

Learning reduced kinetic Monte Carlo models of complex chemistry from molecular dynamics.

Science.gov (United States)

Yang, Qian; Sing-Long, Carlos A; Reed, Evan J

2017-08-01

We propose a novel statistical learning framework for automatically and efficiently building reduced kinetic Monte Carlo (KMC) models of large-scale elementary reaction networks from data generated by a single or few molecular dynamics simulations (MD). Existing approaches for identifying species and reactions from molecular dynamics typically use bond length and duration criteria, where bond duration is a fixed parameter motivated by an understanding of bond vibrational frequencies. In contrast, we show that for highly reactive systems, bond duration should be a model parameter that is chosen to maximize the predictive power of the resulting statistical model. We demonstrate our method on a high temperature, high pressure system of reacting liquid methane, and show that the learned KMC model is able to extrapolate more than an order of magnitude in time for key molecules. Additionally, our KMC model of elementary reactions enables us to isolate the most important set of reactions governing the behavior of key molecules found in the MD simulation. We develop a new data-driven algorithm to reduce the chemical reaction network which can be solved either as an integer program or efficiently using L1 regularization, and compare our results with simple count-based reduction. For our liquid methane system, we discover that rare reactions do not play a significant role in the system, and find that less than 7% of the approximately 2000 reactions observed from molecular dynamics are necessary to reproduce the molecular concentration over time of methane. The framework described in this work paves the way towards a genomic approach to studying complex chemical systems, where expensive MD simulation data can be reused to contribute to an increasingly large and accurate genome of elementary reactions and rates.

Quantifying and Visualizing Uncertainties in Molecular Models

OpenAIRE

Rasheed, Muhibur; Clement, Nathan; Bhowmick, Abhishek; Bajaj, Chandrajit

2015-01-01

Computational molecular modeling and visualization has seen significant progress in recent years with sev- eral molecular modeling and visualization software systems in use today. Nevertheless the molecular biology community lacks techniques and tools for the rigorous analysis, quantification and visualization of the associated errors in molecular structure and its associated properties. This paper attempts at filling this vacuum with the introduction of a systematic statistical framework whe...

Novel approach to improve molecular imaging research: Correlation between macroscopic and molecular pathological findings in patients

Energy Technology Data Exchange (ETDEWEB)

Boehm, Ingrid, E-mail: i.boehm@uni-bonn.de [Department of Diagnostic Radiology, ZARF Project, Center for Molecular Imaging Research MBMB, Philipps University of Marburg, Baldingerstrasse, 35039 Marburg (Germany)

2011-09-15

Purpose: Currently, clinical research approaches are sparse in molecular imaging studies. Moreover, possible links between imaging features and pathological laboratory parameters are unknown, so far. Therefore, the goal was to find a possible relationship between imaging features and peripheral blood cell apoptosis, and thereby to present a novel way to complement molecular imaging research. Materials and methods: The investigation has been done in systemic lupus erythematosus (SLE), a prototype of an autoimmune disease characterized by multiorgan involvement, autoantibody production, and disturbed apoptosis. Retrospectively, radiological findings have been compared to both autoantibody findings and percentage apoptotic blood cells. Results: Two SLE groups could be identified: patients with normal (annexin V binding < 20%), and with increased apoptosis (annexin V binding > 20%) of peripheral blood cells. The frequency of radiological examinations in SLE patients significantly correlated with an increased percentage of apoptotic cells (p < 0.005). In patients with characteristic imaging findings (e.g. lymph node swelling, pleural effusion) an elevated percentage of apoptotic cells was present. In contrast SLE-patients with normal imaging findings or uncharacteristic results of minimal severity had normal percentages of apoptotic blood cells. Conclusion: This correlation between radiographic findings and percentage of apoptotic blood cells provides (1) further insight into pathological mechanisms of SLE, (2) will offer the possibility to introduce apoptotic biomarkers as molecular probes for clinical molecular imaging approaches in future to early diagnose organ complaints in patients with SLE, and (3) is a plea to complement molecular imaging research by this clinical approach.

Atomic and Molecular Data Needs for Radiation Damage Modeling: Multiscale Approach

International Nuclear Information System (INIS)

Yakubovich, Alexander V.; Solov'yov, Andrey V.; Surdutovich, Eugene

2011-01-01

We present a brief overview of the multiscale approach towards understanding of the processes responsible for the radiation damage caused by energetic ions. This knowledge is very important, because it can be utilized in the ion-beam cancer therapy, which is one of the most advanced modern techniques to cure certain type of cancer. The central element of the multiscale approach is the theoretical evaluation and quantification of the DNA damage within cell environment. To achieve this goal one needs a significant amount of data on various atomic and molecular processes involved into the cascade of events starting with the ion entering and propagation in the biological medium and resulting in the DNA damage. The discussion of the follow up biological processes are beyond the scope of this brief overview. We consider different paths of the DNA damage and focus on the the illustration of the thermo-mechanical effects caused by the propagation of ions through the biological environment and in particular on the possibility of the creation of the shock waves in the vicinity of the ion tracks. We demonstrate that at the initial stages after ion's passage the shock wave is so strong that it can contribute to the DNA damage due to large pressure gradients developed at the distances of a few nanometers from the ionic tracks. This novel mechanism of the DNA damage provides an important contribution to the cumulative biodamage caused by low-energy secondary electrons, holes and free radicals.

Molecular Mechanism of Gastric Carcinogenesis in Helicobacter pylori-Infected Rodent Models

Directory of Open Access Journals (Sweden)

Takeshi Toyoda

2014-06-01

Full Text Available Since the discovery of Helicobacter pylori (H. pylori, many efforts have been made to establish animal models for the investigation of the pathological features and molecular mechanisms of gastric carcinogenesis. Among the animal models, Mongolian gerbils and mice are particularly useful for the analysis of H. pylori-associated inflammatory reactions and gastric cancer development. Inhibitors of oxidative stress, cyclooxygenase-2 (COX-2 and nuclear factor-κB, exert preventive effects on chronic gastritis and the development of adenocarcinomas in H. pylori-infected gerbils. Genetically-modified mouse models, including transgenic and knockout mice, have also revealed the importance of p53, COX-2/prostaglandin, Wnt/β-catenin, proinflammatory cytokines, gastrin and type III mucin in the molecular mechanisms of gastric carcinogenesis. Microarray technology is available for comprehensive gene analysis in the gastric mucosa of mouse models, and epigenetics, such as DNA methylation, could be an alternative approach to correlate the observations in animal models with the etiology in humans.

Modeling ion sensing in molecular electronics

International Nuclear Information System (INIS)

Chen, Caroline J.; Smeu, Manuel; Ratner, Mark A.

2014-01-01

We examine the ability of molecules to sense ions by measuring the change in molecular conductance in the presence of such charged species. The detection of protons (H + ), alkali metal cations (M + ), calcium ions (Ca 2+ ), and hydronium ions (H 3 O + ) is considered. Density functional theory (DFT) is used within the Keldysh non-equilibrium Green's function framework (NEGF) to model electron transport properties of quinolinedithiol (QDT, C 9 H 7 NS 2 ), bridging Al electrodes. The geometry of the transport region is relaxed with DFT. The transport properties of the device are modeled with NEGF-DFT to determine if this device can distinguish among the M + + QDT species containing monovalent cations, where M + = H + , Li + , Na + , or K + . Because of the asymmetry of QDT in between the two electrodes, both positive and negative biases are considered. The electron transmission function and conductance properties are simulated for electrode biases in the range from −0.5 V to 0.5 V at increments of 0.1 V. Scattering state analysis is used to determine the molecular orbitals that are the main contributors to the peaks in the transmission function near the Fermi level of the electrodes, and current-voltage relationships are obtained. The results show that QDT can be used as a proton detector by measuring transport through it and can conceivably act as a pH sensor in solutions. In addition, QDT may be able to distinguish among different monovalent species. This work suggests an approach to design modern molecular electronic conductance sensors with high sensitivity and specificity using well-established quantum chemistry

Deep Generative Models for Molecular Science

DEFF Research Database (Denmark)

Jørgensen, Peter Bjørn; Schmidt, Mikkel Nørgaard; Winther, Ole

2018-01-01

Generative deep machine learning models now rival traditional quantum-mechanical computations in predicting properties of new structures, and they come with a significantly lower computational cost, opening new avenues in computational molecular science. In the last few years, a variety of deep...... generative models have been proposed for modeling molecules, which differ in both their model structure and choice of input features. We review these recent advances within deep generative models for predicting molecular properties, with particular focus on models based on the probabilistic autoencoder (or...

Molecular approach of uranyl/mineral surfaces: theoretical approach

International Nuclear Information System (INIS)

Roques, J.

2009-01-01

As migration of radio-toxic elements through the geosphere is one of the processes which may affect the safety of a radioactive waste storage site, the author shows that numerical modelling is a support to experimental result exploitation, and allows the development of new interpretation and prediction codes. He shows that molecular modelling can be used to study processes of interaction between an actinide ion (notably a uranyl ion) and a mineral surface (a TiO 2 substrate). He also reports the predictive theoretical study of the interaction between an uranyl ion and a gibbsite substrate

In silico simulations of tunneling barrier measurements for molecular orbital-mediated junctions: A molecular orbital theory approach to scanning tunneling microscopy

Energy Technology Data Exchange (ETDEWEB)

Terryn, Raymond J.; Sriraman, Krishnan; Olson, Joel A., E-mail: jolson@fit.edu; Baum, J. Clayton, E-mail: cbaum@fit.edu [Department of Chemistry, Florida Institute of Technology, 150 West University Boulevard, Melbourne, Florida 32901 (United States); Novak, Mark J. [Department of Chemistry and Applied Biological Sciences, South Dakota School of Mines and Technology, 501 E. Saint Joseph Street, Rapid City, South Dakota 57701 (United States)

2016-09-15

A new simulator for scanning tunneling microscopy (STM) is presented based on the linear combination of atomic orbitals molecular orbital (LCAO-MO) approximation for the effective tunneling Hamiltonian, which leads to the convolution integral when applied to the tip interaction with the sample. This approach intrinsically includes the structure of the STM tip. Through this mechanical emulation and the tip-inclusive convolution model, dI/dz images for molecular orbitals (which are closely associated with apparent barrier height, ϕ{sub ap}) are reported for the first time. For molecular adsorbates whose experimental topographic images correspond well to isolated-molecule quantum chemistry calculations, the simulator makes accurate predictions, as illustrated by various cases. Distortions in these images due to the tip are shown to be in accord with those observed experimentally and predicted by other ab initio considerations of tip structure. Simulations of the tunneling current dI/dz images are in strong agreement with experiment. The theoretical framework provides a solid foundation which may be applied to LCAO cluster models of adsorbate–substrate systems, and is extendable to emulate several aspects of functional STM operation.

In silico simulations of tunneling barrier measurements for molecular orbital-mediated junctions: A molecular orbital theory approach to scanning tunneling microscopy

International Nuclear Information System (INIS)

Terryn, Raymond J.; Sriraman, Krishnan; Olson, Joel A.; Baum, J. Clayton; Novak, Mark J.

2016-01-01

A new simulator for scanning tunneling microscopy (STM) is presented based on the linear combination of atomic orbitals molecular orbital (LCAO-MO) approximation for the effective tunneling Hamiltonian, which leads to the convolution integral when applied to the tip interaction with the sample. This approach intrinsically includes the structure of the STM tip. Through this mechanical emulation and the tip-inclusive convolution model, dI/dz images for molecular orbitals (which are closely associated with apparent barrier height, ϕ_a_p) are reported for the first time. For molecular adsorbates whose experimental topographic images correspond well to isolated-molecule quantum chemistry calculations, the simulator makes accurate predictions, as illustrated by various cases. Distortions in these images due to the tip are shown to be in accord with those observed experimentally and predicted by other ab initio considerations of tip structure. Simulations of the tunneling current dI/dz images are in strong agreement with experiment. The theoretical framework provides a solid foundation which may be applied to LCAO cluster models of adsorbate–substrate systems, and is extendable to emulate several aspects of functional STM operation.

Chemical insight from density functional modeling of molecular adsorption: Tracking the bonding and diffusion of anthracene derivatives on Cu(111) with molecular orbitals

Science.gov (United States)

Wyrick, Jonathan; Einstein, T. L.; Bartels, Ludwig

2015-03-01

We present a method of analyzing the results of density functional modeling of molecular adsorption in terms of an analogue of molecular orbitals. This approach permits intuitive chemical insight into the adsorption process. Applied to a set of anthracene derivates (anthracene, 9,10-anthraquinone, 9,10-dithioanthracene, and 9,10-diselenonanthracene), we follow the electronic states of the molecules that are involved in the bonding process and correlate them to both the molecular adsorption geometry and the species' diffusive behavior. We additionally provide computational code to easily repeat this analysis on any system.

Adult soft tissue sarcomas: conventional therapies and molecularly targeted approaches.

Science.gov (United States)

Mocellin, Simone; Rossi, Carlo R; Brandes, Alba; Nitti, Donato

2006-02-01

The therapeutic approach to soft tissue sarcomas (STS) has evolved over the past two decades based on the results from randomized controlled trials, which are guiding physicians in the treatment decision-making process. Despite significant improvements in the control of local disease, a significant number of patients ultimately die of recurrent/metastatic disease following radical surgery due to a lack of effective adjuvant treatments. In addition, the characteristic chemoresistance of STS has compromised the therapeutic value of conventional antineoplastic agents in cases of unresectable advanced/metastatic disease. Therefore, novel therapeutic strategies are urgently needed to improve the prognosis of patients with STS. Recent advances in STS biology are paving the way to the development of molecularly targeted therapeutic strategies, the efficacy of which relies not only on the knowledge of the molecular mechanisms underlying cancer development/progression but also on the personalization of the therapeutic regimen according to the molecular features of individual tumours. In this work, we review the state-of-the-art of conventional treatments for STS and summarize the most promising findings in the development of molecularly targeted therapeutic approaches.

Free Energy Calculations using a Swarm-Enhanced Sampling Molecular Dynamics Approach.

Science.gov (United States)

Burusco, Kepa K; Bruce, Neil J; Alibay, Irfan; Bryce, Richard A

2015-10-26

Free energy simulations are an established computational tool in modelling chemical change in the condensed phase. However, sampling of kinetically distinct substates remains a challenge to these approaches. As a route to addressing this, we link the methods of thermodynamic integration (TI) and swarm-enhanced sampling molecular dynamics (sesMD), where simulation replicas interact cooperatively to aid transitions over energy barriers. We illustrate the approach by using alchemical alkane transformations in solution, comparing them with the multiple independent trajectory TI (IT-TI) method. Free energy changes for transitions computed by using IT-TI grew increasingly inaccurate as the intramolecular barrier was heightened. By contrast, swarm-enhanced sampling TI (sesTI) calculations showed clear improvements in sampling efficiency, leading to more accurate computed free energy differences, even in the case of the highest barrier height. The sesTI approach, therefore, has potential in addressing chemical change in systems where conformations exist in slow exchange. © 2015 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Recent molecular approaches to understanding astrocyte function in vivo

Directory of Open Access Journals (Sweden)

David eDavila

2013-12-01

Full Text Available Astrocytes are a predominant glial cell type in the nervous systems, and are becoming recognized as important mediators of normal brain function as well as neurodevelopmental, neurological, and neurodegenerative brain diseases. Although numerous potential mechanisms have been proposed to explain the role of astrocytes in the normal and diseased brain, research into the physiological relevance of these mechanisms in vivo is just beginning. In this review, we will summarize recent developments in innovative and powerful molecular approaches, including knockout mouse models, transgenic mouse models, and astrocyte-targeted gene transfer/expression, which have led to advances in understanding astrocyte biology in vivo that were heretofore inaccessible to experimentation. We will examine the recently improved understanding of the roles of astrocytes - with an emphasis on astrocyte signaling - in the context of both the healthy and diseased brain, discuss areas where the role of astrocytes remains debated, and suggest new research directions.

Exploring the site-selective binding of jatrorrhizine to human serum albumin: spectroscopic and molecular modeling approaches.

Science.gov (United States)

Mi, Ran; Hu, Yan-Jun; Fan, Xiao-Yang; Ouyang, Yu; Bai, Ai-Min

2014-01-03

This paper exploring the site-selective binding of jatrorrhizine to human serum albumin (HSA) under physiological conditions (pH=7.4). The investigation was carried out using fluorescence spectroscopy, UV-vis spectroscopy, and molecular modeling. The results of fluorescence quenching and UV-vis absorption spectra experiments indicated the formation of the complex of HSA-jatrorrhizine. Binding parameters calculating from Stern-Volmer method and Scatchard method were calculated at 298, 304 and 310 K, with the corresponding thermodynamic parameters ΔG, ΔH and ΔS as well. Binding parameters calculating from Stern-Volmer method and Scatchard method showed that jatrorrhizine bind to HSA with the binding affinities of the order 10(4) L mol(-1). The thermodynamic parameters studies revealed that the binding was characterized by negative enthalpy and positive entropy changes and the electrostatic interactions play a major role for jatrorrhizine-HSA association. Site marker competitive displacement experiments and molecular modeling calculation demonstrating that jatrorrhizine is mainly located within the hydrophobic pocket of the subdomain IIIA of HSA. Furthermore, the synchronous fluorescence spectra suggested that the association between jatrorrhizine and HSA changed molecular conformation of HSA. Copyright © 2013. Published by Elsevier B.V.

Water models based on a single potential energy surface and different molecular degrees of freedom

Science.gov (United States)

Saint-Martin, Humberto; Hernández-Cobos, Jorge; Ortega-Blake, Iván

2005-06-01

Up to now it has not been possible to neatly assess whether a deficient performance of a model is due to poor parametrization of the force field or the lack of inclusion of enough molecular properties. This work compares several molecular models in the framework of the same force field, which was designed to include many-body nonadditive effects: (a) a polarizable and flexible molecule with constraints that account for the quantal nature of the vibration [B. Hess, H. Saint-Martin, and H. J. C. Berendsen, J. Chem. Phys. 116, 9602 (2002), H. Saint-Martin, B. Hess, and H. J. C. Berendsen, J. Chem. Phys. 120, 11133 (2004)], (b) a polarizable and classically flexible molecule [H. Saint-Martin, J. Hernández-Cobos, M. I. Bernal-Uruchurtu, I. Ortega-Blake, and H. J. C. Berendsen, J. Chem. Phys. 113, 10899 (2000)], (c) a polarizable and rigid molecule, and finally (d) a nonpolarizable and rigid molecule. The goal is to determine how significant the different molecular properties are. The results indicate that all factors—nonadditivity, polarizability, and intramolecular flexibility—are important. Still, approximations can be made in order to diminish the computational cost of the simulations with a small decrease in the accuracy of the predictions, provided that those approximations are counterbalanced by the proper inclusion of an effective molecular property, that is, an average molecular geometry or an average dipole. Hence instead of building an effective force field by parametrizing it in order to reproduce the properties of a specific phase, a building approach is proposed that is based on adequately restricting the molecular flexibility and/or polarizability of a model potential fitted to unimolecular properties, pair interactions, and many-body nonadditive contributions. In this manner, the same parental model can be used to simulate the same substance under a wide range of thermodynamic conditions. An additional advantage of this approach is that, as the force

Synthetic model for Doppler broadening of neutron absorption resonances in molecular fluids

Energy Technology Data Exchange (ETDEWEB)

Villanueva, Alejandro J., E-mail: villanueva@cab.cnea.gov.a [Comision Nacional de Energia Atomica, Centro Atomico Bariloche and Instituto Balseiro, 8400 S.C. de Bariloche (RN) (Argentina); Consejo Nacional de Investigaciones Cientificas y Tecnicas (Argentina); Granada, J.R. [Comision Nacional de Energia Atomica, Centro Atomico Bariloche and Instituto Balseiro, 8400 S.C. de Bariloche (RN) (Argentina); Consejo Nacional de Investigaciones Cientificas y Tecnicas (Argentina)

2010-08-15

A general and systematic approach expressed in modern language, accounting for molecular motion effects on Doppler Broadening of Neutron Absorption Resonances (DBNAR) is given the form of a new model. It relies on well validated hypothesis: The separability of atomic from nuclear degrees of freedom, the use of the Van Hove scattering formalism and the fact that a conceptually identical approach produced experimentally proved predictions when applied to DBNAR in solid systems. We treat the molecular internal degrees of freedom approximately as harmonic oscillators. As a second contribution of this work, a synthetic model is presented in order to make the more complete model mentioned above suitable for neutron calculation codes. This second synthetic model reduces to the exact expressions of the complete model in the low and high neutron energy regimes and provides a plausible transition in between. Numerical results are presented for a general hypothetical case to show its strengths and limitations. Also, both models are applied to a real case of the {sup 238}U 6.674 eV resonant effective broadened absorption cross-section in UF6 (uranium hexafluoride). A direct experimental validation of our models is still necessary for which a special high resolution neutron transmission experiment ought to be devised at low temperatures and pressures on a gaseous system. It is showed how the synthetic model can be used to make thermometric predictions in an improved fashion in comparison to the effective temperature gas model at low temperatures.

Elucidating Mechanisms of Molecular Recognition Between Human Argonaute and miRNA Using Computational Approaches

KAUST Repository

Jiang, Hanlun

2016-12-06

MicroRNA (miRNA) and Argonaute (AGO) protein together form the RNA-induced silencing complex (RISC) that plays an essential role in the regulation of gene expression. Elucidating the underlying mechanism of AGO-miRNA recognition is thus of great importance not only for the in-depth understanding of miRNA function but also for inspiring new drugs targeting miRNAs. In this chapter we introduce a combined computational approach of molecular dynamics (MD) simulations, Markov state models (MSMs), and protein-RNA docking to investigate AGO-miRNA recognition. Constructed from MD simulations, MSMs can elucidate the conformational dynamics of AGO at biologically relevant timescales. Protein-RNA docking can then efficiently identify the AGO conformations that are geometrically accessible to miRNA. Using our recent work on human AGO2 as an example, we explain the rationale and the workflow of our method in details. This combined approach holds great promise to complement experiments in unraveling the mechanisms of molecular recognition between large, flexible, and complex biomolecules.

Elucidating Mechanisms of Molecular Recognition Between Human Argonaute and miRNA Using Computational Approaches.

Science.gov (United States)

Jiang, Hanlun; Zhu, Lizhe; Héliou, Amélie; Gao, Xin; Bernauer, Julie; Huang, Xuhui

2017-01-01

MicroRNA (miRNA) and Argonaute (AGO) protein together form the RNA-induced silencing complex (RISC) that plays an essential role in the regulation of gene expression. Elucidating the underlying mechanism of AGO-miRNA recognition is thus of great importance not only for the in-depth understanding of miRNA function but also for inspiring new drugs targeting miRNAs. In this chapter we introduce a combined computational approach of molecular dynamics (MD) simulations, Markov state models (MSMs), and protein-RNA docking to investigate AGO-miRNA recognition. Constructed from MD simulations, MSMs can elucidate the conformational dynamics of AGO at biologically relevant timescales. Protein-RNA docking can then efficiently identify the AGO conformations that are geometrically accessible to miRNA. Using our recent work on human AGO2 as an example, we explain the rationale and the workflow of our method in details. This combined approach holds great promise to complement experiments in unraveling the mechanisms of molecular recognition between large, flexible, and complex biomolecules.

Generalized kinetic model of reduction of molecular oxidant by metal containing redox

International Nuclear Information System (INIS)

Kravchenko, T.A.

1986-01-01

Present work is devoted to kinetics of reduction of molecular oxidant by metal containing redox. Constructed generalized kinetic model of redox process in the system solid redox - reagent solution allows to perform the general theoretical approach to research and to obtain new results on kinetics and mechanism of interaction of redox with oxidants.

Molecular modelling and radiopharmaceutical design

International Nuclear Information System (INIS)

Neves, M.; Gano, L.; Costa, M.C.; Raminhos, H.; Rosado, M.; Fausto, R.

2002-01-01

Aim: Among several headings for radiopharmaceuticals (RPs) design, molecular modelling (MM) could be used for the prediction of ligands and metal-complexes structures. Using MM it is also possible to simulate molecular interactions between predicted structures and specific biomolecules. Bisphosphonates (BPs) are ligands that are able to coordinate radioactive metals, such as 153 Sm, 166 Ho, 186 Re, etc., but they are all polymeric complexes difficult to characterize. It is reported that the bone uptake does not depend on the nature of metal center, but is primarily driven by the nature of the ligand, as in the case of HEDP-M (M= 99m Tc, 186 Re, 113 Sn). So, it would be interesting to estimate the relevant molecular properties of BPs by MM, simulate their interaction with hydroxyapatite (HAP) the main bone component, and then correlate the predicted molecular parameters with experimental data obtained from HAP binding and biodistribution studies of BPs carrying radioactive metals. Materials and Methods: The molecular structures and preferred conformations of BPs differing in the length of the aliphatic chain attached to their substituted amine groups (pami-dronate, olpadronate and ibandronate) were obtained using the second-generation CVFF 950 (version 1.01) force field of Hwang et al. Simulation of the interactions between the studied BPs and HAP were performed using a Cerius-2 system of programs running on a Silicon Graphics O2 workstation. BPs- 153 Sm complexes were synthesized and characterized by ITLC. Their binding to HAP and in vivo biodistribution studies were carried out as usual described in literature. Results: A direct correlation could be established between in vitro BPs affinity towards HAP and their corresponding energies from the Coulomb interactions involving the N and P atoms of the studied BPs bound to the HAP (0,0,1) surface and the nearest Ca atoms of HAP. The BPs- 153 Sm showing the highest binding to HAP and skeletal uptake are those which

Molecular Modeling and Simulation Tools in the Development of Peptide-Based Biosensors for Mycotoxin Detection: Example of Ochratoxin

Directory of Open Access Journals (Sweden)

Aby A. Thyparambil

2017-12-01

Full Text Available Mycotoxin contamination of food and feed is now ubiquitous. Exposures to mycotoxin via contact or ingestion can potentially induce adverse health outcomes. Affordable mycotoxin-monitoring systems are highly desired but are limited by (a the reliance on technically challenging and costly molecular recognition by immuno-capture technologies; and (b the lack of predictive tools for directing the optimization of alternative molecular recognition modalities. Our group has been exploring the development of ochratoxin detection and monitoring systems using the peptide NFO4 as the molecular recognition receptor in fluorescence, electrochemical and multimodal biosensors. Using ochratoxin as the model mycotoxin, we share our perspective on addressing the technical challenges involved in biosensor fabrication, namely: (a peptide receptor design; and (b performance evaluation. Subsequently, the scope and utility of molecular modeling and simulation (MMS approaches to address the above challenges are described. Informed and enabled by phage display, the subsequent application of MMS approaches can rationally guide subsequent biomolecular engineering of peptide receptors, including bioconjugation and bioimmobilization approaches to be used in the fabrication of peptide biosensors. MMS approaches thus have the potential to reduce biosensor development cost, extend product life cycle, and facilitate multi-analyte detection of mycotoxins, each of which positively contributes to the overall affordability of mycotoxin biosensor monitoring systems.

The cognitive life of mechanical molecular models.

Science.gov (United States)

Charbonneau, Mathieu

2013-12-01

The use of physical models of molecular structures as research tools has been central to the development of biochemistry and molecular biology. Intriguingly, it has received little attention from scholars of science. In this paper, I argue that these physical models are not mere three-dimensional representations but that they are in fact very special research tools: they are cognitive augmentations. Despite the fact that they are external props, these models serve as cognitive tools that augment and extend the modeler's cognitive capacities and performance in molecular modeling tasks. This cognitive enhancement is obtained because of the way the modeler interacts with these models, the models' materiality contributing to the solving of the molecule's structure. Furthermore, I argue that these material models and their component parts were designed, built and used specifically to serve as cognitive facilitators and cognitive augmentations. Copyright © 2013 Elsevier Ltd. All rights reserved.

Theoretical modeling of large molecular systems. Advances in the local self consistent field method for mixed quantum mechanics/molecular mechanics calculations.

Science.gov (United States)

Monari, Antonio; Rivail, Jean-Louis; Assfeld, Xavier

2013-02-19

Molecular mechanics methods can efficiently compute the macroscopic properties of a large molecular system but cannot represent the electronic changes that occur during a chemical reaction or an electronic transition. Quantum mechanical methods can accurately simulate these processes, but they require considerably greater computational resources. Because electronic changes typically occur in a limited part of the system, such as the solute in a molecular solution or the substrate within the active site of enzymatic reactions, researchers can limit the quantum computation to this part of the system. Researchers take into account the influence of the surroundings by embedding this quantum computation into a calculation of the whole system described at the molecular mechanical level, a strategy known as the mixed quantum mechanics/molecular mechanics (QM/MM) approach. The accuracy of this embedding varies according to the types of interactions included, whether they are purely mechanical or classically electrostatic. This embedding can also introduce the induced polarization of the surroundings. The difficulty in QM/MM calculations comes from the splitting of the system into two parts, which requires severing the chemical bonds that link the quantum mechanical subsystem to the classical subsystem. Typically, researchers replace the quantoclassical atoms, those at the boundary between the subsystems, with a monovalent link atom. For example, researchers might add a hydrogen atom when a C-C bond is cut. This Account describes another approach, the Local Self Consistent Field (LSCF), which was developed in our laboratory. LSCF links the quantum mechanical portion of the molecule to the classical portion using a strictly localized bond orbital extracted from a small model molecule for each bond. In this scenario, the quantoclassical atom has an apparent nuclear charge of +1. To achieve correct bond lengths and force constants, we must take into account the inner shell of

Medulloblastoma: Molecular Genetics and Animal Models

Directory of Open Access Journals (Sweden)

Corey Raffel

2004-07-01

Full Text Available Medulloblastoma is a primary brain tumor found in the cerebellum of children. The tumor occurs in association with two inherited cancer syndromes: Turcot syndrome and Gorlin syndrome. Insights into the molecular biology of the tumor have come from looking at alterations in the genes altered in these syndromes, PTC and APC, respectively. Murine models of medulloblastoma have been constructed based on these alterations. Additional murine models that, while mimicking the appearance of the human tumor, seem unrelated to the human tumor's molecular alterations have been made. In this review, the clinical picture, origin, molecular biology, murine models of medulloblastoma are discussed. Although a great deal has been discovered about this tumor, the genetic alterations responsible for tumor development in a majority of patients have yet to be described.

A n-vector model for charge transport in molecular semiconductors.

Science.gov (United States)

Jackson, Nicholas E; Kohlstedt, Kevin L; Chen, Lin X; Ratner, Mark A

2016-11-28

We develop a lattice model utilizing coarse-grained molecular sites to study charge transport in molecular semiconducting materials. The model bridges atomistic descriptions and structureless lattice models by mapping molecular structure onto sets of spatial vectors isomorphic with spin vectors in a classical n-vector Heisenberg model. Specifically, this model incorporates molecular topology-dependent orientational and intermolecular coupling preferences, including the direct inclusion of spatially correlated transfer integrals and site energy disorder. This model contains the essential physics required to explicitly simulate the interplay of molecular topology and correlated structural disorder, and their effect on charge transport. As a demonstration of its utility, we apply this model to analyze the effects of long-range orientational correlations, molecular topology, and intermolecular interaction strength on charge motion in bulk molecular semiconductors.

Stability of nanofluids: Molecular dynamic approach and experimental study

International Nuclear Information System (INIS)

Farzaneh, H.; Behzadmehr, A.; Yaghoubi, M.; Samimi, A.; Sarvari, S.M.H.

2016-01-01

Highlights: • Nanofluid stability is investigated and discussed. • A molecular dynamic approach, considering different forces on the nanoparticles, is adopted. • Stability diagrams are presented for different thermo-fluid conditions. • An experimental investigation is carried out to confirm the theoretical approach. - Abstract: Nanofluids as volumetric absorbent in solar energy conversion devices or as working fluid in different heat exchangers have been proposed by various researchers. However, dispersion stability of nanofluids is an important issue that must be well addressed before any industrial applications. Conditions such as severe temperature gradient, high temperature of heat transfer fluid, nanoparticle mean diameters and types of nanoparticles and base fluid are among the most effective parameters on the stability of nanofluid. A molecular dynamic approach, considering kinetic energy of nanoparticles and DLVO potential energy between nanoparticles, is adopted to study the nanofluid stability for different nanofluids at different working conditions. Different forces such as Brownian, thermophoresis, drag and DLVO are considered to introduce the stability diagrams. The latter presents the conditions for which a nanofluid can be stable. In addition an experimental investigation is carried out to find a stable nanofluid and to show the validity of the theoretical approach. There is a good agreement between the experimental and theoretical results that confirms the validity of our theoretical approach.

DP 71 AND BETA DYSTROGLYCAN INTERACTION: A MOLECULAR MODELING APPROACH TO UNDERSTAND DUCHENNE MUSCULAR DYSTROPHY

Directory of Open Access Journals (Sweden)

Simanti Bhattacharya,

2013-12-01

Full Text Available Dp 71 is the most prevalent and widely expressed non muscle isoform of dystrophin (Dp and its mutations are associated with Duchenne muscular dystrophy, a severe form of muscular disorder. Dp 71 deviates from the canonical Dp by means of its truncated N terminal which also has abolished certain amino acids that comprise WW domain in the canonical form. This WW domain is very crucial for Dp’s interaction with partner proteins to establish a bridge between extra cellular matrices and cellular cytoskeleton. In our current study we have employed molecular modeling technique to understand the structural architecture of the N terminal region of Dp 71 and its deviation from the canonical form. We have further extended our studies to analyze the interaction probabilities between Dp 71 and β-DG applying molecular docking. Our studies for the first time have revealed that in spite of the underlying differences in terms of amino acids and structural organization, Dp 71 can interact with β-DG with its N terminal region which shares the similar molecular surface with the canonical form of Dp. These findings have opened up a platform to investigate the molecular interactions, spatio temporal orientations of the amino acids of Dp 71 and β-DG to understand the onset of DMD in much more greater detail

Ionization Energies, Electron Affinities, and Polarization Energies of Organic Molecular Crystals: Quantitative Estimations from a Polarizable Continuum Model (PCM)–Tuned Range-Separated Density Functional Approach

KAUST Repository

Sun, Haitao

2016-05-16

We propose a new methodology for the first-principles description of the electronic properties relevant for charge transport in organic molecular crystals. This methodology, which is based on the combination of a non-empirical, optimally tuned range-separated hybrid functional with the polarizable continuum model, is applied to a series of eight representative molecular semiconductor crystals. We show that it provides ionization energies, electron affinities, and transport gaps in very good agreement with experimental values as well as with the results of many-body perturbation theory within the GW approximation at a fraction of the computational costs. Hence, this approach represents an easily applicable and computationally efficient tool to estimate the gas-to-crystal-phase shifts of the frontier-orbital quasiparticle energies in organic electronic materials.

Stability of nuclei in peripheral collisions in the JAERI quantum molecular dynamics model

International Nuclear Information System (INIS)

Mancusi, Davide; Niita, Koji; Maruyama, Tomoyuki; Sihver, Lembit

2009-01-01

The JAERI quantum molecular dynamics (JQMD) model has been successfully used for a long time now to describe many different aspects of nuclear reactions in a unified way. In some cases, however, the JQMD model cannot produce consistent results: First, it lacks a fully relativistically covariant approach to the problem of molecular dynamics; second, the quantum-mechanical ground state of nuclei cannot be faithfully reproduced in a semiclassical framework. Therefore, we introduce R-JQMD, an improved version of JQMD that also features a new ground-state initialization algorithm for nuclei. We compare the structure of the two codes and discuss whether R-JQMD can be adjusted to improve JQMD's agreement with measured heavy-ion fragmentation cross sections

The application of molecular modelling in the safety assessment of chemicals: A case study on ligand-dependent PPARγ dysregulation.

Science.gov (United States)

Al Sharif, Merilin; Tsakovska, Ivanka; Pajeva, Ilza; Alov, Petko; Fioravanzo, Elena; Bassan, Arianna; Kovarich, Simona; Yang, Chihae; Mostrag-Szlichtyng, Aleksandra; Vitcheva, Vessela; Worth, Andrew P; Richarz, Andrea-N; Cronin, Mark T D

2017-12-01

The aim of this paper was to provide a proof of concept demonstrating that molecular modelling methodologies can be employed as a part of an integrated strategy to support toxicity prediction consistent with the mode of action/adverse outcome pathway (MoA/AOP) framework. To illustrate the role of molecular modelling in predictive toxicology, a case study was undertaken in which molecular modelling methodologies were employed to predict the activation of the peroxisome proliferator-activated nuclear receptor γ (PPARγ) as a potential molecular initiating event (MIE) for liver steatosis. A stepwise procedure combining different in silico approaches (virtual screening based on docking and pharmacophore filtering, and molecular field analysis) was developed to screen for PPARγ full agonists and to predict their transactivation activity (EC 50 ). The performance metrics of the classification model to predict PPARγ full agonists were balanced accuracy=81%, sensitivity=85% and specificity=76%. The 3D QSAR model developed to predict EC 50 of PPARγ full agonists had the following statistical parameters: q 2 cv =0.610, N opt =7, SEP cv =0.505, r 2 pr =0.552. To support the linkage of PPARγ agonism predictions to prosteatotic potential, molecular modelling was combined with independently performed mechanistic mining of available in vivo toxicity data followed by ToxPrint chemotypes analysis. The approaches investigated demonstrated a potential to predict the MIE, to facilitate the process of MoA/AOP elaboration, to increase the scientific confidence in AOP, and to become a basis for 3D chemotype development. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.

Novel thrombopoietin mimetic peptides bind c-Mpl receptor: Synthesis, biological evaluation and molecular modeling.

Science.gov (United States)

Liu, Yaquan; Tian, Fang; Zhi, Dejuan; Wang, Haiqing; Zhao, Chunyan; Li, Hongyu

2017-02-01

Thrombopoietin (TPO) acts in promoting the proliferation of hematopoietic stem cells and by initiating specific maturation events in megakaryocytes. Now, TPO-mimetic peptides with amino acid sequences unrelated to TPO are of considerable pharmaceutical interest. In the present paper, four new TPO mimetic peptides that bind and activate c-Mpl receptor have been identified, synthesized and tested by Dual-Luciferase reporter gene assay for biological activities. The molecular modeling research was also approached to understand key molecular mechanisms and structural features responsible for peptide binding with c-Mpl receptor. The results presented that three of four mimetic peptides showed significant activities. In addition, the molecular modeling approaches proved hydrophobic interactions were the driven positive forces for binding behavior between peptides and c-Mpl receptor. TPO peptide residues in P7, P13 and P7' positions were identified by the analysis of hydrogen bonds and energy decompositions as the key ones for benefiting better biological activities. Our data suggested the synthesized peptides have considerable potential for the future development of stable and highly active TPO mimetic peptides. Copyright © 2016 Elsevier Ltd. All rights reserved.

Molecular targets in cancer therapy: the Ron approach

Directory of Open Access Journals (Sweden)

Serena Germano

2011-12-01

Full Text Available The receptor tyrosine kinase Ron and its ligand, Macrophage Stimulating Protein (MSP, mediate multiple processes involved in the control of cell proliferation, migration and protection from apoptosis. Dysregulated signaling of Ron, due to hyperactivation or loss of negative regulation, is involved in tumor progression and metastasis. Growing evidence indicates that Ron is abnormally expressed and activated in certain types of primary epithelial cancers (i.e. breast, colon, lung, pancreas, bladder and thyroid, where it critically contributes to the maintenance of tumorigenic and invasive phenotype. Furthermore, a positive association between aberrant Ron expression and aggressive biological indicators as well as a worse clinical outcome have been reported in breast, bladder and thyroid carcinomas. Different approaches have proved effective in targeting receptor activation/expression both in vitro and in animal models, leading to reversion of the tumorigenic phenotype. Altogether these results show that Ron is an attractive molecular target for clinical intervention.

New models and molecular markers in evaluation of developmental toxicity

International Nuclear Information System (INIS)

Huuskonen, Hannele

2005-01-01

Mammalian and non-mammalian embryos and embryonic stem cells may be used as models in mechanistic studies and in testing embryotoxicity of compounds. In addition to conventional culture methods, genetic modifications and use of molecular markers offer significant advantages in mechanistic studies as well as in developing new test methods for embryotoxicity. Zebrafish model has been used for a long time and at present several applications are available. It is an easy vertebral non-mammalian model, whose genome is largely known and several genetic modifications are easily constructed to study gene expression or knocked down genes. Fluorescent marker proteins can be used also in zebrafish to indicate gene activation in transgenic models. Chemical genetics approach has been developed using zebrafish model. This is a new approach to screen small molecules that regulate signaling pathways. Embryonic stem cells have been used in mechanistic studies and mouse embryonic stem cell test has been validated to study embryotoxicity in vitro. This method has been improved using quantitative measurements of molecular endpoints by real-time RT-PCR or fluorescent activated cell sorting methods (FACS). Methods facilitating differentiation to several different cell types are available. We have studied preimplantation mouse embryos as a possible model for in vitro testing. In this method, superovulated and in vivo fertilized preimplantation embryos were collected at morula stage and cultured up to blastocysts. The mouse preimplantation culture test was improved by quantitative gene expression measurement using two-step real-time RT-PCR methods. New endpoints improve the tests of in vitro embryotoxicity because subjective assessments are replaced by objective measurements. In addition, automation is possible and less time is needed for analysis. Thus, high throughput screening will come possible to test large numbers of compounds

Modeling Complex Workflow in Molecular Diagnostics

Science.gov (United States)

Gomah, Mohamed E.; Turley, James P.; Lu, Huimin; Jones, Dan

2010-01-01

One of the hurdles to achieving personalized medicine has been implementing the laboratory processes for performing and reporting complex molecular tests. The rapidly changing test rosters and complex analysis platforms in molecular diagnostics have meant that many clinical laboratories still use labor-intensive manual processing and testing without the level of automation seen in high-volume chemistry and hematology testing. We provide here a discussion of design requirements and the results of implementation of a suite of lab management tools that incorporate the many elements required for use of molecular diagnostics in personalized medicine, particularly in cancer. These applications provide the functionality required for sample accessioning and tracking, material generation, and testing that are particular to the evolving needs of individualized molecular diagnostics. On implementation, the applications described here resulted in improvements in the turn-around time for reporting of more complex molecular test sets, and significant changes in the workflow. Therefore, careful mapping of workflow can permit design of software applications that simplify even the complex demands of specialized molecular testing. By incorporating design features for order review, software tools can permit a more personalized approach to sample handling and test selection without compromising efficiency. PMID:20007844

Bounding the electrostatic free energies associated with linear continuum models of molecular solvation.

Science.gov (United States)

Bardhan, Jaydeep P; Knepley, Matthew G; Anitescu, Mihai

2009-03-14

The importance of electrostatic interactions in molecular biology has driven extensive research toward the development of accurate and efficient theoretical and computational models. Linear continuum electrostatic theory has been surprisingly successful, but the computational costs associated with solving the associated partial differential equations (PDEs) preclude the theory's use in most dynamical simulations. Modern generalized-Born models for electrostatics can reproduce PDE-based calculations to within a few percent and are extremely computationally efficient but do not always faithfully reproduce interactions between chemical groups. Recent work has shown that a boundary-integral-equation formulation of the PDE problem leads naturally to a new approach called boundary-integral-based electrostatics estimation (BIBEE) to approximate electrostatic interactions. In the present paper, we prove that the BIBEE method can be used to rigorously bound the actual continuum-theory electrostatic free energy. The bounds are validated using a set of more than 600 proteins. Detailed numerical results are presented for structures of the peptide met-enkephalin taken from a molecular-dynamics simulation. These bounds, in combination with our demonstration that the BIBEE methods accurately reproduce pairwise interactions, suggest a new approach toward building a highly accurate yet computationally tractable electrostatic model.

Bounding the electrostatic free energies associated with linear continuum models of molecular solvation.

Energy Technology Data Exchange (ETDEWEB)

Bardhan, J. P.; Knepley, M. G.; Anitescu, M. (Biosciences Division); ( MCS); (Rush Univ.)

2009-03-01

The importance of electrostatic interactions in molecular biology has driven extensive research toward the development of accurate and efficient theoretical and computational models. Linear continuum electrostatic theory has been surprisingly successful, but the computational costs associated with solving the associated partial differential equations (PDEs) preclude the theory's use in most dynamical simulations. Modern generalized-Born models for electrostatics can reproduce PDE-based calculations to within a few percent and are extremely computationally efficient but do not always faithfully reproduce interactions between chemical groups. Recent work has shown that a boundary-integral-equation formulation of the PDE problem leads naturally to a new approach called boundary-integral-based electrostatics estimation (BIBEE) to approximate electrostatic interactions. In the present paper, we prove that the BIBEE method can be used to rigorously bound the actual continuum-theory electrostatic free energy. The bounds are validated using a set of more than 600 proteins. Detailed numerical results are presented for structures of the peptide met-enkephalin taken from a molecular-dynamics simulation. These bounds, in combination with our demonstration that the BIBEE methods accurately reproduce pairwise interactions, suggest a new approach toward building a highly accurate yet computationally tractable electrostatic model.

Molecular modeling and multiscaling issues for electronic material applications

CERN Document Server

Iwamoto, Nancy; Yuen, Matthew; Fan, Haibo

Volume 1 : Molecular Modeling and Multiscaling Issues for Electronic Material Applications provides a snapshot on the progression of molecular modeling in the electronics industry and how molecular modeling is currently being used to understand material performance to solve relevant issues in this field. This book is intended to introduce the reader to the evolving role of molecular modeling, especially seen through the eyes of the IEEE community involved in material modeling for electronic applications.  Part I presents  the role that quantum mechanics can play in performance prediction, such as properties dependent upon electronic structure, but also shows examples how molecular models may be used in performance diagnostics, especially when chemistry is part of the performance issue.  Part II gives examples of large-scale atomistic methods in material failure and shows several examples of transitioning between grain boundary simulations (on the atomistic level)and large-scale models including an example ...

An Electronic Structure Approach to Charge Transfer and Transport in Molecular Building Blocks for Organic Optoelectronics

Science.gov (United States)

Hendrickson, Heidi Phillips

A fundamental understanding of charge separation in organic materials is necessary for the rational design of optoelectronic devices suited for renewable energy applications and requires a combination of theoretical, computational, and experimental methods. Density functional theory (DFT) and time-dependent (TD)DFT are cost effective ab-initio approaches for calculating fundamental properties of large molecular systems, however conventional DFT methods have been known to fail in accurately characterizing frontier orbital gaps and charge transfer states in molecular systems. In this dissertation, these shortcomings are addressed by implementing an optimally-tuned range-separated hybrid (OT-RSH) functional approach within DFT and TDDFT. The first part of this thesis presents the way in which RSH-DFT addresses the shortcomings in conventional DFT. Environmentally-corrected RSH-DFT frontier orbital energies are shown to correspond to thin film measurements for a set of organic semiconducting molecules. Likewise, the improved RSH-TDDFT description of charge transfer excitations is benchmarked using a model ethene dimer and silsesquioxane molecules. In the second part of this thesis, RSH-DFT is applied to chromophore-functionalized silsesquioxanes, which are currently investigated as candidates for building blocks in optoelectronic applications. RSH-DFT provides insight into the nature of absorptive and emissive states in silsesquioxanes. While absorption primarily involves transitions localized on one chromophore, charge transfer between chromophores and between chromophore and silsesquioxane cage have been identified. The RSH-DFT approach, including a protocol accounting for complex environmental effects on charge transfer energies, was tested and validated against experimental measurements. The third part of this thesis addresses quantum transport through nano-scale junctions. The ability to quantify a molecular junction via spectroscopic methods is crucial to their

Molecular genetic approaches to the study of cellular senescence.

Science.gov (United States)

Goletz, T J; Smith, J R; Pereira-Smith, O M

1994-01-01

Cellular senescence is an inability of cells to synthesize DNA and divide, which results in a terminal loss of proliferation despite the maintenance of basic metabolic processes. Senescence has been proposed as a model for the study of aging at the cellular level, and the basis for this model system and its features have been summarized. Although strong experimental evidence exists to support the hypothesis that cellular senescence is a dominant active process, the mechanisms responsible for this phenomenon remain a mystery. Investigators have taken several approaches to gain a better understanding of senescence. Several groups have documented the differences between young and senescent cells, and others have identified changes that occur during the course of a cell's in vitro life span. Using molecular and biochemical approaches, important changes in gene expression and function of cell-cycle-associated products have been identified. The active production of an inhibitor of DNA synthesis has been demonstrated. This may represent the final step in a cascade of events governing senescence. The study of immortal cells which have escaped senescence has also provided useful information, particularly with regard to the genes governing the senescence program. These studies have identified four complementation groups for indefinite division, which suggests that there are at least four genes or gene pathways in the senescence program. Through the use of microcell-mediated chromosome transfer, chromosomes encoding senescence genes have been identified; efforts to clone these genes are ongoing.(ABSTRACT TRUNCATED AT 250 WORDS)

Fusarium diversity in soil using a specific molecular approach and a cultural approach.

Science.gov (United States)

Edel-Hermann, Véronique; Gautheron, Nadine; Mounier, Arnaud; Steinberg, Christian

2015-04-01

Fusarium species are ubiquitous in soil. They cause plant and human diseases and can produce mycotoxins. Surveys of Fusarium species diversity in environmental samples usually rely on laborious culture-based methods. In the present study, we have developed a molecular method to analyze Fusarium diversity directly from soil DNA. We designed primers targeting the translation elongation factor 1-alpha (EF-1α) gene and demonstrated their specificity toward Fusarium using a large collection of fungi. We used the specific primers to construct a clone library from three contrasting soils. Sequence analysis confirmed the specificity of the assay, with 750 clones identified as Fusarium and distributed among eight species or species complexes. The Fusarium oxysporum species complex (FOSC) was the most abundant one in the three soils, followed by the Fusarium solani species complex (FSSC). We then compared our molecular approach results with those obtained by isolating Fusarium colonies on two culture media and identifying species by sequencing part of the EF-1α gene. The 750 isolates were distributed into eight species or species complexes, with the same dominant species as with the cloning method. Sequence diversity was much higher in the clone library than in the isolate collection. The molecular approach proved to be a valuable tool to assess Fusarium diversity in environmental samples. Combined with high throughput sequencing, it will allow for in-depth analysis of large numbers of samples. Published by Elsevier B.V.

Molecular approaches to detect and study the organisms causing ...

African Journals Online (AJOL)

This review will summarise the molecular approaches used to detect and analyse the genomes of Babesia bovis, B. bigemina and Anaplasma marginale which cause bovine babesiosis and anaplasmosis. These tick borne diseases are widely distributed in Africa, Asia, Australia, and Central and South America and for ...

Evaluation of molecular brain changes associated with environmental stress in rodent models compared to human major depressive disorder: A proteomic systems approach.

Science.gov (United States)

Cox, David Alan; Gottschalk, Michael Gerd; Stelzhammer, Viktoria; Wesseling, Hendrik; Cooper, Jason David; Bahn, Sabine

2016-11-25

Rodent models of major depressive disorder (MDD) are indispensable when screening for novel treatments, but assessing their translational relevance with human brain pathology has proved difficult. Using a novel systems approach, proteomics data obtained from post-mortem MDD anterior prefrontal cortex tissue (n = 12) and matched controls (n = 23) were compared with equivalent data from three commonly used preclinical models exposed to environmental stressors (chronic mild stress, prenatal stress and social defeat). Functional pathophysiological features associated with depression-like behaviour were identified in these models through enrichment of protein-protein interaction networks. A cross-species comparison evaluated which model(s) represent human MDD pathology most closely. Seven functional domains associated with MDD and represented across at least two models such as "carbohydrate metabolism and cellular respiration" were identified. Through statistical evaluation using kernel-based machine learning techniques, the social defeat model was found to represent MDD brain changes most closely for four of the seven domains. This is the first study to apply a method for directly evaluating the relevance of the molecular pathology of multiple animal models to human MDD on the functional level. The methodology and findings outlined here could help to overcome translational obstacles of preclinical psychiatric research.

Integrated multiscale modeling of molecular computing devices

International Nuclear Information System (INIS)

Cummings, Peter T; Leng Yongsheng

2005-01-01

Molecular electronics, in which single organic molecules are designed to perform the functions of transistors, diodes, switches and other circuit elements used in current siliconbased microelecronics, is drawing wide interest as a potential replacement technology for conventional silicon-based lithographically etched microelectronic devices. In addition to their nanoscopic scale, the additional advantage of molecular electronics devices compared to silicon-based lithographically etched devices is the promise of being able to produce them cheaply on an industrial scale using wet chemistry methods (i.e., self-assembly from solution). The design of molecular electronics devices, and the processes to make them on an industrial scale, will require a thorough theoretical understanding of the molecular and higher level processes involved. Hence, the development of modeling techniques for molecular electronics devices is a high priority from both a basic science point of view (to understand the experimental studies in this field) and from an applied nanotechnology (manufacturing) point of view. Modeling molecular electronics devices requires computational methods at all length scales - electronic structure methods for calculating electron transport through organic molecules bonded to inorganic surfaces, molecular simulation methods for determining the structure of self-assembled films of organic molecules on inorganic surfaces, mesoscale methods to understand and predict the formation of mesoscale patterns on surfaces (including interconnect architecture), and macroscopic scale methods (including finite element methods) for simulating the behavior of molecular electronic circuit elements in a larger integrated device. Here we describe a large Department of Energy project involving six universities and one national laboratory aimed at developing integrated multiscale methods for modeling molecular electronics devices. The project is funded equally by the Office of Basic

On interfacial properties of tetrahydrofuran: Atomistic and coarse-grained models from molecular dynamics simulation

Energy Technology Data Exchange (ETDEWEB)

Garrido, J. M. [Departamento de Ingeniería Química, Universidad de Concepción, POB 160-C Concepción (Chile); Algaba, J.; Blas, F. J., E-mail: felipe@uhu.es [Laboratorio de Simulación Molecular y Química Computacional, CIQSO-Centro de Investigación en Química Sostenible and Departamento de Física Aplicada, Universidad de Huelva, 21007 Huelva (Spain); Míguez, J. M. [Laboratoire des Fluides Complexes et Leurs Reservoirs, Université de Pau et des Pays de l’Adour, CNRS, TOTAL–UMR 5150, Avenue de l’Université, B.P. 1155, Pau F-64013 (France); Departamento de Física Aplicada, Universidade de Vigo, E36310 Vigo (Spain); Mendiboure, B. [Laboratoire des Fluides Complexes et Leurs Reservoirs, Université de Pau et des Pays de l’Adour, CNRS, TOTAL–UMR 5150, Avenue de l’Université, B.P. 1155, Pau F-64013 (France); Moreno-Ventas Bravo, A. I. [Laboratorio de Simulación Molecular y Química Computacional, CIQSO-Centro de Investigación en Química Sostenible and Departamento de Geología, Universidad de Huelva, 21007 Huelva (Spain); Piñeiro, M. M. [Departamento de Física Aplicada, Universidade de Vigo, E36310 Vigo (Spain)

2016-04-14

We have determined the interfacial properties of tetrahydrofuran (THF) from direct simulation of the vapor-liquid interface. The molecules are modeled using six different molecular models, three of them based on the united-atom approach and the other three based on a coarse-grained (CG) approach. In the first case, THF is modeled using the transferable parameters potential functions approach proposed by Chandrasekhar and Jorgensen [J. Chem. Phys. 77, 5073 (1982)] and a new parametrization of the TraPPE force fields for cyclic alkanes and ethers [S. J. Keasler et al., J. Phys. Chem. B 115, 11234 (2012)]. In both cases, dispersive and coulombic intermolecular interactions are explicitly taken into account. In the second case, THF is modeled as a single sphere, a diatomic molecule, and a ring formed from three Mie monomers according to the SAFT-γ Mie top-down approach [V. Papaioannou et al., J. Chem. Phys. 140, 054107 (2014)]. Simulations were performed in the molecular dynamics canonical ensemble and the vapor-liquid surface tension is evaluated from the normal and tangential components of the pressure tensor along the simulation box. In addition to the surface tension, we have also obtained density profiles, coexistence densities, critical temperature, density, and pressure, and interfacial thickness as functions of temperature, paying special attention to the comparison between the estimations obtained from different models and literature experimental data. The simulation results obtained from the three CG models as described by the SAFT-γ Mie approach are able to predict accurately the vapor-liquid phase envelope of THF, in excellent agreement with estimations obtained from TraPPE model and experimental data in the whole range of coexistence. However, Chandrasekhar and Jorgensen model presents significant deviations from experimental results. We also compare the predictions for surface tension as obtained from simulation results for all the models with

On interfacial properties of tetrahydrofuran: Atomistic and coarse-grained models from molecular dynamics simulation

International Nuclear Information System (INIS)

Garrido, J. M.; Algaba, J.; Blas, F. J.; Míguez, J. M.; Mendiboure, B.; Moreno-Ventas Bravo, A. I.; Piñeiro, M. M.

2016-01-01

We have determined the interfacial properties of tetrahydrofuran (THF) from direct simulation of the vapor-liquid interface. The molecules are modeled using six different molecular models, three of them based on the united-atom approach and the other three based on a coarse-grained (CG) approach. In the first case, THF is modeled using the transferable parameters potential functions approach proposed by Chandrasekhar and Jorgensen [J. Chem. Phys. 77, 5073 (1982)] and a new parametrization of the TraPPE force fields for cyclic alkanes and ethers [S. J. Keasler et al., J. Phys. Chem. B 115, 11234 (2012)]. In both cases, dispersive and coulombic intermolecular interactions are explicitly taken into account. In the second case, THF is modeled as a single sphere, a diatomic molecule, and a ring formed from three Mie monomers according to the SAFT-γ Mie top-down approach [V. Papaioannou et al., J. Chem. Phys. 140, 054107 (2014)]. Simulations were performed in the molecular dynamics canonical ensemble and the vapor-liquid surface tension is evaluated from the normal and tangential components of the pressure tensor along the simulation box. In addition to the surface tension, we have also obtained density profiles, coexistence densities, critical temperature, density, and pressure, and interfacial thickness as functions of temperature, paying special attention to the comparison between the estimations obtained from different models and literature experimental data. The simulation results obtained from the three CG models as described by the SAFT-γ Mie approach are able to predict accurately the vapor-liquid phase envelope of THF, in excellent agreement with estimations obtained from TraPPE model and experimental data in the whole range of coexistence. However, Chandrasekhar and Jorgensen model presents significant deviations from experimental results. We also compare the predictions for surface tension as obtained from simulation results for all the models with

A multiscale modeling approach for biomolecular systems

Energy Technology Data Exchange (ETDEWEB)

Bowling, Alan, E-mail: bowling@uta.edu; Haghshenas-Jaryani, Mahdi, E-mail: mahdi.haghshenasjaryani@mavs.uta.edu [The University of Texas at Arlington, Department of Mechanical and Aerospace Engineering (United States)

2015-04-15

This paper presents a new multiscale molecular dynamic model for investigating the effects of external interactions, such as contact and impact, during stepping and docking of motor proteins and other biomolecular systems. The model retains the mass properties ensuring that the result satisfies Newton’s second law. This idea is presented using a simple particle model to facilitate discussion of the rigid body model; however, the particle model does provide insights into particle dynamics at the nanoscale. The resulting three-dimensional model predicts a significant decrease in the effect of the random forces associated with Brownian motion. This conclusion runs contrary to the widely accepted notion that the motor protein’s movements are primarily the result of thermal effects. This work focuses on the mechanical aspects of protein locomotion; the effect ATP hydrolysis is estimated as internal forces acting on the mechanical model. In addition, the proposed model can be numerically integrated in a reasonable amount of time. Herein, the differences between the motion predicted by the old and new modeling approaches are compared using a simplified model of myosin V.

SketchBio: a scientist's 3D interface for molecular modeling and animation.

Science.gov (United States)

Waldon, Shawn M; Thompson, Peter M; Hahn, Patrick J; Taylor, Russell M

2014-10-30

Because of the difficulties involved in learning and using 3D modeling and rendering software, many scientists hire programmers or animators to create models and animations. This both slows the discovery process and provides opportunities for miscommunication. Working with multiple collaborators, a tool was developed (based on a set of design goals) to enable them to directly construct models and animations. SketchBio is presented, a tool that incorporates state-of-the-art bimanual interaction and drop shadows to enable rapid construction of molecular structures and animations. It includes three novel features: crystal-by-example, pose-mode physics, and spring-based layout that accelerate operations common in the formation of molecular models. Design decisions and their consequences are presented, including cases where iterative design was required to produce effective approaches. The design decisions, novel features, and inclusion of state-of-the-art techniques enabled SketchBio to meet all of its design goals. These features and decisions can be incorporated into existing and new tools to improve their effectiveness.

Molecular Characterization of Transgenic Events Using Next Generation Sequencing Approach.

Science.gov (United States)

Guttikonda, Satish K; Marri, Pradeep; Mammadov, Jafar; Ye, Liang; Soe, Khaing; Richey, Kimberly; Cruse, James; Zhuang, Meibao; Gao, Zhifang; Evans, Clive; Rounsley, Steve; Kumpatla, Siva P

2016-01-01

Demand for the commercial use of genetically modified (GM) crops has been increasing in light of the projected growth of world population to nine billion by 2050. A prerequisite of paramount importance for regulatory submissions is the rigorous safety assessment of GM crops. One of the components of safety assessment is molecular characterization at DNA level which helps to determine the copy number, integrity and stability of a transgene; characterize the integration site within a host genome; and confirm the absence of vector DNA. Historically, molecular characterization has been carried out using Southern blot analysis coupled with Sanger sequencing. While this is a robust approach to characterize the transgenic crops, it is both time- and resource-consuming. The emergence of next-generation sequencing (NGS) technologies has provided highly sensitive and cost- and labor-effective alternative for molecular characterization compared to traditional Southern blot analysis. Herein, we have demonstrated the successful application of both whole genome sequencing and target capture sequencing approaches for the characterization of single and stacked transgenic events and compared the results and inferences with traditional method with respect to key criteria required for regulatory submissions.

Molecular Characterization of Transgenic Events Using Next Generation Sequencing Approach.

Directory of Open Access Journals (Sweden)

Satish K Guttikonda

Full Text Available Demand for the commercial use of genetically modified (GM crops has been increasing in light of the projected growth of world population to nine billion by 2050. A prerequisite of paramount importance for regulatory submissions is the rigorous safety assessment of GM crops. One of the components of safety assessment is molecular characterization at DNA level which helps to determine the copy number, integrity and stability of a transgene; characterize the integration site within a host genome; and confirm the absence of vector DNA. Historically, molecular characterization has been carried out using Southern blot analysis coupled with Sanger sequencing. While this is a robust approach to characterize the transgenic crops, it is both time- and resource-consuming. The emergence of next-generation sequencing (NGS technologies has provided highly sensitive and cost- and labor-effective alternative for molecular characterization compared to traditional Southern blot analysis. Herein, we have demonstrated the successful application of both whole genome sequencing and target capture sequencing approaches for the characterization of single and stacked transgenic events and compared the results and inferences with traditional method with respect to key criteria required for regulatory submissions.

Combining experimental and simulation data of molecular processes via augmented Markov models.

Science.gov (United States)

Olsson, Simon; Wu, Hao; Paul, Fabian; Clementi, Cecilia; Noé, Frank

2017-08-01

Accurate mechanistic description of structural changes in biomolecules is an increasingly important topic in structural and chemical biology. Markov models have emerged as a powerful way to approximate the molecular kinetics of large biomolecules while keeping full structural resolution in a divide-and-conquer fashion. However, the accuracy of these models is limited by that of the force fields used to generate the underlying molecular dynamics (MD) simulation data. Whereas the quality of classical MD force fields has improved significantly in recent years, remaining errors in the Boltzmann weights are still on the order of a few [Formula: see text], which may lead to significant discrepancies when comparing to experimentally measured rates or state populations. Here we take the view that simulations using a sufficiently good force-field sample conformations that are valid but have inaccurate weights, yet these weights may be made accurate by incorporating experimental data a posteriori. To do so, we propose augmented Markov models (AMMs), an approach that combines concepts from probability theory and information theory to consistently treat systematic force-field error and statistical errors in simulation and experiment. Our results demonstrate that AMMs can reconcile conflicting results for protein mechanisms obtained by different force fields and correct for a wide range of stationary and dynamical observables even when only equilibrium measurements are incorporated into the estimation process. This approach constitutes a unique avenue to combine experiment and computation into integrative models of biomolecular structure and dynamics.

Limiting assumptions in molecular modeling: electrostatics.

Science.gov (United States)

Marshall, Garland R

2013-02-01

Molecular mechanics attempts to represent intermolecular interactions in terms of classical physics. Initial efforts assumed a point charge located at the atom center and coulombic interactions. It is been recognized over multiple decades that simply representing electrostatics with a charge on each atom failed to reproduce the electrostatic potential surrounding a molecule as estimated by quantum mechanics. Molecular orbitals are not spherically symmetrical, an implicit assumption of monopole electrostatics. This perspective reviews recent evidence that requires use of multipole electrostatics and polarizability in molecular modeling.

Offsetting the difficulties of the molecular model of atomic collisions in the intermediate velocity range

International Nuclear Information System (INIS)

Errea, L.F.; Mendez, L.; Riera, A.

1991-01-01

To offset the defective behavior of the molecular method of atomic collisions at intermediate energies, we propose a method to approximate the probability flux towards continuum and discrete states not included in the molecular basis. We check the degree of accuracy and limitations of the method for a model case where transition probabilities can be calculated exactly. An application to the benchmark case of He + +H + collisions is also presented, and yields complementary information on the properties of this approach

Developmental psychopathology in an era of molecular genetics and neuroimaging: A developmental neurogenetics approach.

Science.gov (United States)

Hyde, Luke W

2015-05-01

The emerging field of neurogenetics seeks to model the complex pathways from gene to brain to behavior. This field has focused on imaging genetics techniques that examine how variability in common genetic polymorphisms predict differences in brain structure and function. These studies are informed by other complimentary techniques (e.g., animal models and multimodal imaging) and have recently begun to incorporate the environment through examination of Imaging Gene × Environment interactions. Though neurogenetics has the potential to inform our understanding of the development of psychopathology, there has been little integration between principles of neurogenetics and developmental psychopathology. The paper describes a neurogenetics and Imaging Gene × Environment approach and how these approaches have been usefully applied to the study of psychopathology. Six tenets of developmental psychopathology (the structure of phenotypes, the importance of exploring mechanisms, the conditional nature of risk, the complexity of multilevel pathways, the role of development, and the importance of who is studied) are identified, and how these principles can further neurogenetics applications to understanding the development of psychopathology is discussed. A major issue of this piece is how neurogenetics and current imaging and molecular genetics approaches can be incorporated into developmental psychopathology perspectives with a goal of providing models for better understanding pathways from among genes, environments, the brain, and behavior.

Screening of photosynthetic pigments for herbicidal activity with a new computational molecular approach.

Science.gov (United States)

Krishnaraj, R Navanietha; Chandran, Saravanan; Pal, Parimal; Berchmans, Sheela

2013-12-01

There is an immense interest among the researchers to identify new herbicides which are effective against the herbs without affecting the environment. In this work, photosynthetic pigments are used as the ligands to predict their herbicidal activity. The enzyme 5-enolpyruvylshikimate-3-phosphate (EPSP) synthase is a good target for the herbicides. Homology modeling of the target enzyme is done using Modeler 9.11 and the model is validated. Docking studies were performed with AutoDock Vina algorithm to predict the binding of the natural pigments such as β-carotene, chlorophyll a, chlorophyll b, phycoerythrin and phycocyanin to the target. β-carotene, phycoerythrin and phycocyanin have higher binding energies indicating the herbicidal activity of the pigments. This work reports a procedure to screen herbicides with computational molecular approach. These pigments will serve as potential bioherbicides in the future.

Exploring RNA structure by integrative molecular modelling

DEFF Research Database (Denmark)

Masquida, Benoît; Beckert, Bertrand; Jossinet, Fabrice

2010-01-01

RNA molecular modelling is adequate to rapidly tackle the structure of RNA molecules. With new structured RNAs constituting a central class of cellular regulators discovered every year, the need for swift and reliable modelling methods is more crucial than ever. The pragmatic method based...... on interactive all-atom molecular modelling relies on the observation that specific structural motifs are recurrently found in RNA sequences. Once identified by a combination of comparative sequence analysis and biochemical data, the motifs composing the secondary structure of a given RNA can be extruded...

Proteomic-Biostatistic Integrated Approach for Finding the Underlying Molecular Determinants of Hypertension in Human Plasma.

Science.gov (United States)

Gajjala, Prathibha R; Jankowski, Vera; Heinze, Georg; Bilo, Grzegorz; Zanchetti, Alberto; Noels, Heidi; Liehn, Elisa; Perco, Paul; Schulz, Anna; Delles, Christian; Kork, Felix; Biessen, Erik; Narkiewicz, Krzysztof; Kawecka-Jaszcz, Kalina; Floege, Juergen; Soranna, Davide; Zidek, Walter; Jankowski, Joachim

2017-08-01

Despite advancements in lowering blood pressure, the best approach to lower it remains controversial because of the lack of information on the molecular basis of hypertension. We, therefore, performed plasma proteomics of plasma from patients with hypertension to identify molecular determinants detectable in these subjects but not in controls and vice versa. Plasma samples from hypertensive subjects (cases; n=118) and controls (n=85) from the InGenious HyperCare cohort were used for this study and performed mass spectrometric analysis. Using biostatistical methods, plasma peptides specific for hypertension were identified, and a model was developed using least absolute shrinkage and selection operator logistic regression. The underlying peptides were identified and sequenced off-line using matrix-assisted laser desorption ionization orbitrap mass spectrometry. By comparison of the molecular composition of the plasma samples, 27 molecular determinants were identified differently expressed in cases from controls. Seventy percent of the molecular determinants selected were found to occur less likely in hypertensive patients. In cross-validation, the overall R 2 was 0.434, and the area under the curve was 0.891 with 95% confidence interval 0.8482 to 0.9349, P hypertensive patients were found to be -2.007±0.3568 and 3.383±0.2643, respectively, P hypertensives and normotensives. The identified molecular determinants may be the starting point for further studies to clarify the molecular causes of hypertension. © 2017 American Heart Association, Inc.

Mass Spectrometry-based Approaches to Understand the Molecular Basis of Memory

Directory of Open Access Journals (Sweden)

Arthur Henriques Pontes

2016-10-01

Full Text Available The central nervous system is responsible for an array of cognitive functions such as memory, learning, language and attention. These processes tend to take place in distinct brain regions; yet, they need to be integrated to give rise to adaptive or meaningful behavior. Since cognitive processes result from underlying cellular and molecular changes, genomics and transcriptomics assays have been applied to human and animal models to understand such events. Nevertheless, genes and RNAs are not the end products of most biological functions. In order to gain further insights toward the understanding of brain processes, the field of proteomics has been of increasing importance in the past years. Advancements in liquid chromatography-tandem mass spectrometry (LC-MS/MS have enable the identification and quantification of thousand of proteins with high accuracy and sensitivity, fostering a revolution in the neurosciences. Herein, we review the molecular bases of explicit memory in the hippocampus. We outline the principles of mass spectrometry (MS-based proteomics, highlighting the use of this analytical tool to study memory formation. In addition, we discuss MS-based targeted approaches as the future of protein analysis.

Estimation of flow stress of radiation induced F/M steels using molecular dynamics and discrete dislocation dynamics approach

International Nuclear Information System (INIS)

More, Ameya; Dutta, B.K.; Durgaprasad, P.V.; Arya, A.K.

2012-01-01

Fe-Cr based Ferritic/Martensitic (F/M) steels are the candidate structural materials for future fusion reactors. In this work, a multi-scale approach comprising atomistic Molecular Dynamics (MD) simulations and Discrete Dislocation Dynamics (DDD) simulations are used to model the effect of irradiation dose on the flow stress of F/M steels. At the atomic scale, molecular dynamics simulations are used to study the dislocation interaction with irradiation induced defects, i.e. voids and He bubbles. Whereas, the DDD simulations are used to estimate the change in flow stress of the material as a result of irradiation hardening. (author)

Precision medicine and molecular imaging: new targeted approaches toward cancer therapeutic and diagnosis

Science.gov (United States)

Ghasemi, Mojtaba; Nabipour, Iraj; Omrani, Abdolmajid; Alipour, Zeinab; Assadi, Majid

2016-01-01

This paper presents a review of the importance and role of precision medicine and molecular imaging technologies in cancer diagnosis with therapeutics and diagnostics purposes. Precision medicine is progressively becoming a hot topic in all disciplines related to biomedical investigation and has the capacity to become the paradigm for clinical practice. The future of medicine lies in early diagnosis and individually appropriate treatments, a concept that has been named precision medicine, i.e. delivering the right treatment to the right patient at the right time. Molecular imaging is quickly being recognized as a tool with the potential to ameliorate every aspect of cancer treatment. On the other hand, emerging high-throughput technologies such as omics techniques and systems approaches have generated a paradigm shift for biological systems in advanced life science research. In this review, we describe the precision medicine, difference between precision medicine and personalized medicine, precision medicine initiative, systems biology/medicine approaches (such as genomics, radiogenomics, transcriptomics, proteomics, and metabolomics), P4 medicine, relationship between systems biology/medicine approaches and precision medicine, and molecular imaging modalities and their utility in cancer treatment and diagnosis. Accordingly, the precision medicine and molecular imaging will enable us to accelerate and improve cancer management in future medicine. PMID:28078184

Precision medicine and molecular imaging: new targeted approaches toward cancer therapeutic and diagnosis.

Science.gov (United States)

Ghasemi, Mojtaba; Nabipour, Iraj; Omrani, Abdolmajid; Alipour, Zeinab; Assadi, Majid

2016-01-01

This paper presents a review of the importance and role of precision medicine and molecular imaging technologies in cancer diagnosis with therapeutics and diagnostics purposes. Precision medicine is progressively becoming a hot topic in all disciplines related to biomedical investigation and has the capacity to become the paradigm for clinical practice. The future of medicine lies in early diagnosis and individually appropriate treatments, a concept that has been named precision medicine, i.e. delivering the right treatment to the right patient at the right time. Molecular imaging is quickly being recognized as a tool with the potential to ameliorate every aspect of cancer treatment. On the other hand, emerging high-throughput technologies such as omics techniques and systems approaches have generated a paradigm shift for biological systems in advanced life science research. In this review, we describe the precision medicine, difference between precision medicine and personalized medicine, precision medicine initiative, systems biology/medicine approaches (such as genomics, radiogenomics, transcriptomics, proteomics, and metabolomics), P4 medicine, relationship between systems biology/medicine approaches and precision medicine, and molecular imaging modalities and their utility in cancer treatment and diagnosis. Accordingly, the precision medicine and molecular imaging will enable us to accelerate and improve cancer management in future medicine.

Modeling of molecular weight and molecular weight distribution in slurry polymerization of propylene by Ziegler-Natta catalysts

International Nuclear Information System (INIS)

Khorasani, R.; Pourmahdian, S.

2007-01-01

The Precise prediction of polypropylene synthesized by heterogeneous Ziegler-Natta catalysts needs good knowledge of parameters affecting on polymerization. molecular weight and molecular weight distribution are among important characteristics of a polymer determining physical-mechanical properties. broadening of molecular weight distribution is an important and well known characteristic of polypropylene synthesized by heterogeneous Ziegler-Natta catalysts, So it is important to understand the origin of broad molecular weight. Two main factors in broadening molecular weight, namely mass transfer resistances and multiplicity of active sites, are discussed in this paper and a model including these factors is presented. Then we calculate molecular weight and molecular weight distribution by the model and compare our results with

A consistent transported PDF model for treating differential molecular diffusion

Science.gov (United States)

Wang, Haifeng; Zhang, Pei

2016-11-01

Differential molecular diffusion is a fundamentally significant phenomenon in all multi-component turbulent reacting or non-reacting flows caused by the different rates of molecular diffusion of energy and species concentrations. In the transported probability density function (PDF) method, the differential molecular diffusion can be treated by using a mean drift model developed by McDermott and Pope. This model correctly accounts for the differential molecular diffusion in the scalar mean transport and yields a correct DNS limit of the scalar variance production. The model, however, misses the molecular diffusion term in the scalar variance transport equation, which yields an inconsistent prediction of the scalar variance in the transported PDF method. In this work, a new model is introduced to remedy this problem that can yield a consistent scalar variance prediction. The model formulation along with its numerical implementation is discussed, and the model validation is conducted in a turbulent mixing layer problem.

Development and validation of risk models and molecular diagnostics to permit personalized management of cancer.

Science.gov (United States)

Pu, Xia; Ye, Yuanqing; Wu, Xifeng

2014-01-01

Despite the advances made in cancer management over the past few decades, improvements in cancer diagnosis and prognosis are still poor, highlighting the need for individualized strategies. Toward this goal, risk prediction models and molecular diagnostic tools have been developed, tailoring each step of risk assessment from diagnosis to treatment and clinical outcomes based on the individual's clinical, epidemiological, and molecular profiles. These approaches hold increasing promise for delivering a new paradigm to maximize the efficiency of cancer surveillance and efficacy of treatment. However, they require stringent study design, methodology development, comprehensive assessment of biomarkers and risk factors, and extensive validation to ensure their overall usefulness for clinical translation. In the current study, the authors conducted a systematic review using breast cancer as an example and provide general guidelines for risk prediction models and molecular diagnostic tools, including development, assessment, and validation. © 2013 American Cancer Society.

Advances in molecular modeling of human cytochrome P450 polymorphism.

Science.gov (United States)

Martiny, Virginie Y; Miteva, Maria A

2013-11-01

Cytochrome P450 (CYP) is a supergene family of metabolizing enzymes involved in the phase I metabolism of drugs and endogenous compounds. CYP oxidation often leads to inactive drug metabolites or to highly toxic or carcinogenic metabolites involved in adverse drug reactions (ADR). During the last decade, the impact of CYP polymorphism in various drug responses and ADR has been demonstrated. Of the drugs involved in ADR, 56% are metabolized by polymorphic phase I metabolizing enzymes, 86% among them being CYP. Here, we review the major CYP polymorphic forms, their impact for drug response and current advances in molecular modeling of CYP polymorphism. We focus on recent studies exploring CYP polymorphism performed by the use of sequence-based and/or protein-structure-based computational approaches. The importance of understanding the molecular mechanisms related to CYP polymorphism and drug response at the atomic level is outlined. © 2013.

Discovery of novel inhibitors of Mycobacterium tuberculosis MurG: homology modelling, structure based pharmacophore, molecular docking, and molecular dynamics simulations.

Science.gov (United States)

Saxena, Shalini; Abdullah, Maaged; Sriram, Dharmarajan; Guruprasad, Lalitha

2017-10-17

MurG (Rv2153c) is a key player in the biosynthesis of the peptidoglycan layer in Mycobacterium tuberculosis (Mtb). This work is an attempt to highlight the structural and functional relationship of Mtb MurG, the three-dimensional (3D) structure of protein was constructed by homology modelling using Discovery Studio 3.5 software. The quality and consistency of generated model was assessed by PROCHECK, ProSA and ERRAT. Later, the model was optimized by molecular dynamics (MD) simulations and the optimized model complex with substrate Uridine-diphosphate-N-acetylglucosamine (UD1) facilitated us to employ structure-based virtual screening approach to obtain new hits from Asinex database using energy-optimized pharmacophore modelling (e-pharmacophore). The pharmacophore model was validated using enrichment calculations, and finally, validated model was employed for high-throughput virtual screening and molecular docking to identify novel Mtb MurG inhibitors. This study led to the identification of 10 potential compounds with good fitness, docking score, which make important interactions with the protein active site. The 25 ns MD simulations of three potential lead compounds with protein confirmed that the structure was stable and make several non-bonding interactions with amino acids, such as Leu290, Met310 and Asn167. Hence, we concluded that the identified compounds may act as new leads for the design of Mtb MurG inhibitors.

Molecular recognition of the environment and mechanisms of the origin of species in quantum-like modeling of evolution.

Science.gov (United States)

Melkikh, Alexey V; Khrennikov, Andrei

2017-11-01

A review of the mechanisms of speciation is performed. The mechanisms of the evolution of species, taking into account the feedback of the state of the environment and mechanisms of the emergence of complexity, are considered. It is shown that these mechanisms, at the molecular level, cannot work steadily in terms of classical mechanics. Quantum mechanisms of changes in the genome, based on the long-range interaction potential between biologically important molecules, are proposed as one of possible explanation. Different variants of interactions of the organism and environment based on molecular recognition and leading to new species origins are considered. Experiments to verify the model are proposed. This bio-physical study is completed by the general operational model of based on quantum information theory. The latter is applied to model of epigenetic evolution. We briefly present the basics of the quantum-like approach to modeling of bio-informational processes. This approach is illustrated by the quantum-like model of epigenetic evolution. Copyright © 2017 Elsevier Ltd. All rights reserved.

Constructing Molecular Models with Low-Cost Toy Beads

Science.gov (United States)

Ng, Pun-hon; Wong, Siu-ling; Mak, Se-yuen

2012-01-01

In teaching the science of the nano world, ball-and-stick molecular models are frequently used as 3D representations of molecules. Unlike a chemical formula, a molecular model allows us to visualise the 3D shape of the molecule and the relative positions of its atoms, the bonds between atoms and why a pair of mirror isomers with the same atoms,…

Molecular Simulation towards Efficient and Representative Subsurface Reservoirs Modeling

KAUST Repository

Kadoura, Ahmad Salim

2016-01-01

This dissertation focuses on the application of Monte Carlo (MC) molecular simulation and Molecular Dynamics (MD) in modeling thermodynamics and flow of subsurface reservoir fluids. At first, MC molecular simulation is proposed as a promising method

Molecular Therapeutic Approaches for Pediatric Acute Myeloid Leukemia

Directory of Open Access Journals (Sweden)

Sarah K Tasian

2014-03-01

Full Text Available Approximately two thirds of children with acute myeloid leukemia (AML are cured with intensive multi-agent chemotherapy. However, primary chemorefractory and relapsed AML remains a significant source of childhood cancer mortality, highlighting the need for new therapies. Further therapy intensification with traditional cytotoxic agents is not feasible given the potential for significant toxicity to normal tissues with conventional chemotherapy and the risk for long-term end-organ dysfunction. Significant emphasis has been placed upon the development of molecularly targeted therapeutic approaches for adults and children with high-risk subtypes of AML with the goal of improving remission induction and minimizing relapse. Several promising agents are currently in clinical testing or late preclinical development for AML, including monoclonal antibodies against leukemia cell surface proteins, kinase inhibitors, proteasome inhibitors, epigenetic agents, and chimeric antigen receptor engineered T cell immunotherapies. Many of these therapies have been specifically tested in children with relapsed/refractory AML via phase 1 and 2 trials with a smaller number of new agents under phase 3 evaluation for children with de novo AML. Although successful identification and implementation of new drugs for children with AML remains a formidable challenge, enthusiasm for novel molecular therapeutic approaches is great given the potential for significant clinical benefit for children who will otherwise fail standard therapy.

Companion diagnostics and molecular imaging-enhanced approaches for oncology clinical trials.

Science.gov (United States)

Van Heertum, Ronald L; Scarimbolo, Robert; Ford, Robert; Berdougo, Eli; O'Neal, Michael

2015-01-01

In the era of personalized medicine, diagnostic approaches are helping pharmaceutical and biotechnology sponsors streamline the clinical trial process. Molecular assays and diagnostic imaging are routinely being used to stratify patients for treatment, monitor disease, and provide reliable early clinical phase assessments. The importance of diagnostic approaches in drug development is highlighted by the rapidly expanding global cancer diagnostics market and the emergent attention of regulatory agencies worldwide, who are beginning to offer more structured platforms and guidance for this area. In this paper, we highlight the key benefits of using companion diagnostics and diagnostic imaging with a focus on oncology clinical trials. Nuclear imaging using widely available radiopharmaceuticals in conjunction with molecular imaging of oncology targets has opened the door to more accurate disease assessment and the modernization of standard criteria for the evaluation, staging, and treatment responses of cancer patients. Furthermore, the introduction and validation of quantitative molecular imaging continues to drive and optimize the field of oncology diagnostics. Given their pivotal role in disease assessment and treatment, the validation and commercialization of diagnostic tools will continue to advance oncology clinical trials, support new oncology drugs, and promote better patient outcomes.

Molecular dynamics modeling of polymer flammability

International Nuclear Information System (INIS)

Nyden, M.R.; Brown, J.E.; Lomakin, S.M.

1992-01-01

Molecular dynamic simulations were used to identify factors which promote char formation during the thermal degradation of polymers. Computer movies based on these simulations, indicate that cross-linked model polymers tend to undergo further cross-linking when burned, eventually forming a high molecular weight, thermally stable char. This paper reports that the prediction was confirmed by char yield measurements made on γ and e - -irradiated polyethylene and chemically cross-linked poly(methyl methacrylate)

Vibronic coupling in molecular crystals: A Franck-Condon Herzberg-Teller model of H-aggregate fluorescence based on quantum chemical cluster calculations

Energy Technology Data Exchange (ETDEWEB)

Wykes, M., E-mail: mikewykes@gmail.com; Parambil, R.; Gierschner, J. [Madrid Institute for Advanced Studies, IMDEA Nanoscience, Calle Faraday 9, Campus Cantoblanco, 28049 Madrid (Spain); Beljonne, D. [Laboratory for Chemistry of Novel Materials, University of Mons, Place du Parc 20, 7000 Mons (Belgium)

2015-09-21

Here, we present a general approach to treating vibronic coupling in molecular crystals based on atomistic simulations of large clusters. Such clusters comprise model aggregates treated at the quantum chemical level embedded within a realistic environment treated at the molecular mechanics level. As we calculate ground and excited state equilibrium geometries and vibrational modes of model aggregates, our approach is able to capture effects arising from coupling to intermolecular degrees of freedom, absent from existing models relying on geometries and normal modes of single molecules. Using the geometries and vibrational modes of clusters, we are able to simulate the fluorescence spectra of aggregates for which the lowest excited state bears negligible oscillator strength (as is the case, e.g., ideal H-aggregates) by including both Franck-Condon (FC) and Herzberg-Teller (HT) vibronic transitions. The latter terms allow the adiabatic excited state of the cluster to couple with vibrations in a perturbative fashion via derivatives of the transition dipole moment along nuclear coordinates. While vibronic coupling simulations employing FC and HT terms are well established for single-molecules, to our knowledge this is the first time they are applied to molecular aggregates. Here, we apply this approach to the simulation of the low-temperature fluorescence spectrum of para-distyrylbenzene single-crystal H-aggregates and draw comparisons with coarse-grained Frenkel-Holstein approaches previously extensively applied to such systems.

Kinetics approach to modeling of polymer additive degradation in lubricants

Institute of Scientific and Technical Information of China (English)

llyaI.KUDISH; RubenG.AIRAPETYAN; Michael; J.; COVITCH

2001-01-01

A kinetics problem for a degrading polymer additive dissolved in a base stock is studied.The polymer degradation may be caused by the combination of such lubricant flow parameters aspressure, elongational strain rate, and temperature as well as lubricant viscosity and the polymercharacteristics (dissociation energy, bead radius, bond length, etc.). A fundamental approach tothe problem of modeling mechanically induced polymer degradation is proposed. The polymerdegradation is modeled on the basis of a kinetic equation for the density of the statistical distribu-tion of polymer molecules as a function of their molecular weight. The integrodifferential kineticequation for polymer degradation is solved numerically. The effects of pressure, elongational strainrate, temperature, and lubricant viscosity on the process of lubricant degradation are considered.The increase of pressure promotes fast degradation while the increase of temperature delaysdegradation. A comparison of a numerically calculated molecular weight distribution with an ex-perimental one obtained in bench tests showed that they are in excellent agreement with eachother.

IMPACT (Imaging and Molecular Markers for Patients with Lung Cancer: Approaches with Molecular Targets and Complementary, Innovative and Therapeutic Modalities)

National Research Council Canada - National Science Library

Hong, Waun Ki; Herbst, Roy

2006-01-01

.... These projects combine targeted approaches using molecular and imaging techniques to validate activity against a target and monitor response using imaging modalities specific to the receptor using...

IMPACT (Imaging and Molecular Markers for Patients with Lung Cancer: Approaches with Molecular Targets and Complementary, Innovative and Therapeutic Modalities)

National Research Council Canada - National Science Library

Hong, Waun K; Herbst, Roy

2008-01-01

.... These projects combine targeted approaches using molecular and imaging techniques to validate activity against a target and monitor response using imaging modalities specific to the receptor using...

IMPACT (Imaging and Molecular Markers for Patients with Lung Cancer: Approaches with Molecular Targets and Complementary, Innovative and Therapeutic Modalities)

National Research Council Canada - National Science Library

Hong, Waun K; Herbst, Roy

2007-01-01

.... These projects combine targeted approaches using molecular and imaging techniques to validate activity against a target and monitor response using imaging modalities specific to the receptor using...

Quantum chemical approaches: semiempirical molecular orbital and hybrid quantum mechanical/molecular mechanical techniques.

Science.gov (United States)

Bryce, Richard A; Hillier, Ian H

2014-01-01

The use of computational quantum chemical methods to aid drug discovery is surveyed. An overview of the various computational models spanning ab initio, density function theory, semiempirical molecular orbital (MO), and hybrid quantum mechanical (QM)/molecular mechanical (MM) methods is given and their strengths and weaknesses are highlighted, focussing on the challenge of obtaining the accuracy essential for them to make a meaningful contribution to drug discovery. Particular attention is given to hybrid QM/MM and semiempirical MO methods which have the potential to yield the necessary accurate predictions of macromolecular structure and reactivity. These methods are shown to have advanced the study of many aspects of substrate-ligand interactions relevant to drug discovery. Thus, the successful parametrization of semiempirical MO methods and QM/MM methods can be used to model noncovalent substrate-protein interactions, and to lead to improved scoring functions. QM/MM methods can be used in crystal structure refinement and are particularly valuable for modelling covalent protein-ligand interactions and can thus aid the design of transition state analogues. An extensive collection of examples from the areas of metalloenzyme structure, enzyme inhibition, and ligand binding affinities and scoring functions are used to illustrate the power of these techniques.

Effects of Organics on the Adsorption and Mobility of Metal Cations in Clay Systems: Computational Molecular Modeling Approach

International Nuclear Information System (INIS)

Kalinichev, Andrey G.; Ngouana Wakou, Brice F.; Loganathan, Narasimhan

2013-01-01

Understanding and prediction of many natural and anthropogenic environmental processes ultimately depend on a fundamental understanding of the chemistry occurring at the mineral-fluid inter-faces. Clay-related minerals and natural organic matter (NOM) are ubiquitous in the environment, and metal-NOM complexation induces strong correlations between the NOM concentration in water and the capacity of clay particles to bind metals, thus affecting their speciation, solubility and toxicity in the environment. Despite significant geochemical, environmental and technological interest, the molecular-level mechanisms and dynamics of the physical and chemical processes involving NOM are not yet well understood. In this presentation we compare three different molecular dynamics (MD) computer simulations of metal-NOM complexation in aqueous solutions. The simulation results indicate that despite some obvious quantitative variations in the computed values depending on the size of the simulated system and on the parameters of the force field models used, all three simulations are quite robust and consistent. In particular, approximately 35-50% of Ca 2+ ions in all simulations are associated with the carboxylic groups of NOM at near-neutral pH. The stability of bidentate-coordinated contact ion pair complexes is also always strongly preferred. Easy association of metal cations with negatively charged NOM functional groups and negatively charged clay surfaces allows us to predict that cationic bridging could be the most probable mechanism of NOM association with clays in natural environments. New MD simulations are currently in progress to quantitatively assess these predictions on a molecular scale for nuclear waste disposal applications. New larger-scale clay models incorporate a more realistic representation of the structural and compositional disorder of natural illites and smectites and employ CLAYFF - a fully flexible general force field suitable for the molecular simulations

Molecular modeling of inorganic compounds

National Research Council Canada - National Science Library

Comba, Peter; Hambley, Trevor W; Martin, Bodo

2009-01-01

... mechanics to inorganic and coordination compounds. Initially, simple metal complexes were modeled, but recently the field has been extended to include organometallic compounds, catalysis and the interaction of metal ions with biological macromolecules. The application of molecular mechanics to coordination compounds is complicated by the numbe...

Predicting the performance of molecularly imprinted polymers: Selective extraction of caffeine by molecularly imprinted solid phase extraction

Energy Technology Data Exchange (ETDEWEB)

Farrington, Keith [School of Chemical Sciences, Dublin City University, Glasnevin, Dublin 9 (Ireland); Magner, Edmond [Materials and Surface Science Institute, Chemical and Environmental Sciences Department, University of Limerick, Limerick (Ireland); Regan, Fiona [School of Chemical Sciences, Dublin City University, Glasnevin, Dublin 9 (Ireland)]. E-mail: fiona.regan@dcu.ie

2006-04-27

A rational design approach was taken to the planning and synthesis of a molecularly imprinted polymer capable of extracting caffeine (the template molecule) from a standard solution of caffeine and further from a food sample containing caffeine. Data from NMR titration experiments in conjunction with a molecular modelling approach was used in predicting the relative ratios of template to functional monomer and furthermore determined both the choice of solvent (porogen) and the amount used for the study. In addition the molecular modelling program yielded information regarding the thermodynamic stability of the pre-polymerisation complex. Post-polymerisation analysis of the polymer itself by analysis of the pore size distribution by BET yielded significant information regarding the nature of the size and distribution of the pores within the polymer matrix. Here is proposed a stepwise procedure for the development and testing of a molecularly imprinted polymer using a well-studied compound-caffeine as a model system. It is shown that both the physical characteristics of a molecularly imprinted polymer (MIP) and the analysis of the pre-polymerisation complex can yield vital information, which can predict how well a given MIP will perform.

Predicting the performance of molecularly imprinted polymers: Selective extraction of caffeine by molecularly imprinted solid phase extraction

International Nuclear Information System (INIS)

Farrington, Keith; Magner, Edmond; Regan, Fiona

2006-01-01

A rational design approach was taken to the planning and synthesis of a molecularly imprinted polymer capable of extracting caffeine (the template molecule) from a standard solution of caffeine and further from a food sample containing caffeine. Data from NMR titration experiments in conjunction with a molecular modelling approach was used in predicting the relative ratios of template to functional monomer and furthermore determined both the choice of solvent (porogen) and the amount used for the study. In addition the molecular modelling program yielded information regarding the thermodynamic stability of the pre-polymerisation complex. Post-polymerisation analysis of the polymer itself by analysis of the pore size distribution by BET yielded significant information regarding the nature of the size and distribution of the pores within the polymer matrix. Here is proposed a stepwise procedure for the development and testing of a molecularly imprinted polymer using a well-studied compound-caffeine as a model system. It is shown that both the physical characteristics of a molecularly imprinted polymer (MIP) and the analysis of the pre-polymerisation complex can yield vital information, which can predict how well a given MIP will perform

Uncovering molecular processes in crystal nucleation and growth by using molecular simulation.

Science.gov (United States)

Anwar, Jamshed; Zahn, Dirk

2011-02-25

Exploring nucleation processes by molecular simulation provides a mechanistic understanding at the atomic level and also enables kinetic and thermodynamic quantities to be estimated. However, whilst the potential for modeling crystal nucleation and growth processes is immense, there are specific technical challenges to modeling. In general, rare events, such as nucleation cannot be simulated using a direct "brute force" molecular dynamics approach. The limited time and length scales that are accessible by conventional molecular dynamics simulations have inspired a number of advances to tackle problems that were considered outside the scope of molecular simulation. While general insights and features could be explored from efficient generic models, new methods paved the way to realistic crystal nucleation scenarios. The association of single ions in solvent environments, the mechanisms of motif formation, ripening reactions, and the self-organization of nanocrystals can now be investigated at the molecular level. The analysis of interactions with growth-controlling additives gives a new understanding of functionalized nanocrystals and the precipitation of composite materials. Copyright © 2011 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Exact ground-state correlation functions of an atomic-molecular Bose–Einstein condensate model

Science.gov (United States)

Links, Jon; Shen, Yibing

2018-05-01

We study the ground-state properties of an atomic-molecular Bose–Einstein condensate model through an exact Bethe Ansatz solution. For a certain range of parameter choices, we prove that the ground-state Bethe roots lie on the positive real-axis. We then use a continuum limit approach to obtain a singular integral equation characterising the distribution of these Bethe roots. Solving this equation leads to an analytic expression for the ground-state energy. The form of the expression is consistent with the existence of a line of quantum phase transitions, which has been identified in earlier studies. This line demarcates a molecular phase from a mixed phase. Certain correlation functions, which characterise these phases, are then obtained through the Hellmann–Feynman theorem.

Realistic molecular model of kerogen's nanostructure.

Science.gov (United States)

Bousige, Colin; Ghimbeu, Camélia Matei; Vix-Guterl, Cathie; Pomerantz, Andrew E; Suleimenova, Assiya; Vaughan, Gavin; Garbarino, Gaston; Feygenson, Mikhail; Wildgruber, Christoph; Ulm, Franz-Josef; Pellenq, Roland J-M; Coasne, Benoit

2016-05-01

Despite kerogen's importance as the organic backbone for hydrocarbon production from source rocks such as gas shale, the interplay between kerogen's chemistry, morphology and mechanics remains unexplored. As the environmental impact of shale gas rises, identifying functional relations between its geochemical, transport, elastic and fracture properties from realistic molecular models of kerogens becomes all the more important. Here, by using a hybrid experimental-simulation method, we propose a panel of realistic molecular models of mature and immature kerogens that provide a detailed picture of kerogen's nanostructure without considering the presence of clays and other minerals in shales. We probe the models' strengths and limitations, and show that they predict essential features amenable to experimental validation, including pore distribution, vibrational density of states and stiffness. We also show that kerogen's maturation, which manifests itself as an increase in the sp(2)/sp(3) hybridization ratio, entails a crossover from plastic-to-brittle rupture mechanisms.

Inhibition of Mycobacterium-RmlA by Molecular Modeling, Dynamics Simulation, and Docking

Directory of Open Access Journals (Sweden)

N. Harathi

2016-01-01

Full Text Available The increasing resistance to anti-tb drugs has enforced strategies for finding new drug targets against Mycobacterium tuberculosis (Mtb. In recent years enzymes associated with the rhamnose pathway in Mtb have attracted attention as drug targets. The present work is on α-D-glucose-1-phosphate thymidylyltransferase (RmlA, the first enzyme involved in the biosynthesis of L-rhamnose, of Mtb cell wall. This study aims to derive a 3D structure of RmlA by using a comparative modeling approach. Structural refinement and energy minimization of the built model have been done with molecular dynamics. The reliability assessment of the built model was carried out with various protein checking tools such as Procheck, Whatif, ProsA, Errat, and Verify 3D. The obtained model investigates the relation between the structure and function. Molecular docking interactions of Mtb-RmlA with modified EMB (ethambutol ligands and natural substrate have revealed specific key residues Arg13, Lys23, Asn109, and Thr223 which play an important role in ligand binding and selection. Compared to all EMB ligands, EMB-1 has shown better interaction with Mtb-RmlA model. The information thus discussed above will be useful for the rational design of safe and effective inhibitors specific to RmlA enzyme pertaining to the treatment of tuberculosis.

A New Optimization Model for Computer-Aided Molecular Design Problems

DEFF Research Database (Denmark)

Zhang, Lei; Cignitti, Stefano; Gani, Rafiqul

Computer-Aided Molecular Design (CAMD) is a method to design molecules with desired properties. That is, through CAMD, it is possible to generate molecules that match a specified set of target properties. CAMD has attracted much attention in recent years due to its ability to design novel as well...... with structure information considered due to the increased size of the mathematical problem and number of alternatives. Thus, decomposition-based approach is proposed to solve the problem. In this approach, only first-order groups are considered in the first step to obtain the building block of the designed...... molecule, then the property model is refined with second-order groups based on the results of the first step. However, this may result in the possibility of an optimal solution being excluded. Samudra and Sahinidis [4] used property relaxation method in the first step to avoid this situation...

A model of early formation of uranium molecular oxides in laser-ablated plasmas

Science.gov (United States)

Finko, Mikhail; Curreli, Davide; Azer, Magdi; Weisz, David; Crowhurst, Jonathan; Rose, Timothy; Koroglu, Batikan; Radousky, Harry; Zaug, Joseph; Armstrong, Mike

2017-10-01

An important problem within the field of nuclear forensics is fractionation: the formation of post-detonation nuclear debris whose composition does not reflect that of the source weapon. We are investigating uranium fractionation in rapidly cooling plasma using a combined experimental and modeling approach. In particular, we use laser ablation of uranium metal samples to produce a low-temperature plasma with physical conditions similar to a condensing nuclear fireball. Here we present a first plasma-chemistry model of uranium molecular species formation during the early stage of laser ablated plasma evolution in atmospheric oxygen. The system is simulated using a global kinetic model with rate coefficients calculated according to literature data and the application of reaction rate theory. The model allows for a detailed analysis of the evolution of key uranium molecular species and represents the first step in producing a uranium fireball model that is kinetically validated against spatially and temporally resolved spectroscopy measurements. This project was sponsored by the DoD, Defense Threat Reduction Agency, Grant HDTRA1-16- 1-0020. This work was performed in part under the auspices of the U.S. DoE by Lawrence Livermore National Laboratory under Contract DE-AC52- 07NA27344.

Towards high-throughput molecular detection of Plasmodium: new approaches and molecular markers

Directory of Open Access Journals (Sweden)

Rogier Christophe

2009-04-01

Full Text Available Abstract Background Several strategies are currently deployed in many countries in the tropics to strengthen malaria control toward malaria elimination. To measure the impact of any intervention, there is a need to detect malaria properly. Mostly, decisions still rely on microscopy diagnosis. But sensitive diagnosis tools enabling to deal with a large number of samples are needed. The molecular detection approach offers a much higher sensitivity, and the flexibility to be automated and upgraded. Methods Two new molecular methods were developed: dot18S, a Plasmodium-specific nested PCR based on the 18S rRNA gene followed by dot-blot detection of species by using species-specific probes and CYTB, a Plasmodium-specific nested PCR based on cytochrome b gene followed by species detection using SNP analysis. The results were compared to those obtained with microscopic examination and the "standard" 18S rRNA gene based nested PCR using species specific primers. 337 samples were diagnosed. Results Compared to the microscopy the three molecular methods were more sensitive, greatly increasing the estimated prevalence of Plasmodium infection, including P. malariae and P. ovale. A high rate of mixed infections was uncovered with about one third of the villagers infected with more than one malaria parasite species. Dot18S and CYTB sensitivity outranged the "standard" nested PCR method, CYTB being the most sensitive. As a consequence, compared to the "standard" nested PCR method for the detection of Plasmodium spp., the sensitivity of dot18S and CYTB was respectively 95.3% and 97.3%. Consistent detection of Plasmodium spp. by the three molecular methods was obtained for 83% of tested isolates. Contradictory results were mostly related to detection of Plasmodium malariae and Plasmodium ovale in mixed infections, due to an "all-or-none" detection effect at low-level parasitaemia. Conclusion A large reservoir of asymptomatic infections was uncovered using the

Hybrid Metaheuristic Approach for Nonlocal Optimization of Molecular Systems.

Science.gov (United States)

Dresselhaus, Thomas; Yang, Jack; Kumbhar, Sadhana; Waller, Mark P

2013-04-09

Accurate modeling of molecular systems requires a good knowledge of the structure; therefore, conformation searching/optimization is a routine necessity in computational chemistry. Here we present a hybrid metaheuristic optimization (HMO) algorithm, which combines ant colony optimization (ACO) and particle swarm optimization (PSO) for the optimization of molecular systems. The HMO implementation meta-optimizes the parameters of the ACO algorithm on-the-fly by the coupled PSO algorithm. The ACO parameters were optimized on a set of small difluorinated polyenes where the parameters exhibited small variance as the size of the molecule increased. The HMO algorithm was validated by searching for the closed form of around 100 molecular balances. Compared to the gradient-based optimized molecular balance structures, the HMO algorithm was able to find low-energy conformations with a 87% success rate. Finally, the computational effort for generating low-energy conformation(s) for the phenylalanyl-glycyl-glycine tripeptide was approximately 60 CPU hours with the ACO algorithm, in comparison to 4 CPU years required for an exhaustive brute-force calculation.

Modeling of molecular interaction between apoptin, BCR-Abl and CrkL--an alternative approach to conventional rational drug design.

Directory of Open Access Journals (Sweden)

Soumya Panigrahi

Full Text Available In this study we have calculated a 3D structure of apoptin and through modeling and docking approaches, we show its interaction with Bcr-Abl oncoprotein and its downstream signaling components, following which we confirm some of the newly-found interactions by biochemical methods. Bcr-Abl oncoprotein is aberrantly expressed in chronic myelogenous leukaemia (CML. It has several distinct functional domains in addition to the Abl kinase domain. The SH3 and SH2 domains cooperatively play important roles in autoinhibiting its kinase activity. Adapter molecules such as Grb2 and CrkL interact with proline-rich region and activate multiple Bcr-Abl downstream signaling pathways that contribute to growth and survival. Therefore, the oncogenic effect of Bcr-Abl could be inhibited by the interaction of small molecules with these domains. Apoptin is a viral protein with well-documented cancer-selective cytotoxicity. Apoptin attributes such as SH2-like sequence similarity with CrkL SH2 domain, unique SH3 domain binding sequence, presence of proline-rich segments, and its nuclear affinity render the molecule capable of interaction with Bcr-Abl. Despite almost two decades of research, the mode of apoptin's action remains elusive because 3D structure of apoptin is unavailable. We performed in silico three-dimensional modeling of apoptin, molecular docking experiments between apoptin model and the known structure of Bcr-Abl, and the 3D structures of SH2 domains of CrkL and Bcr-Abl. We also biochemically validated some of the interactions that were first predicted in silico. This structure-property relationship of apoptin may help in unlocking its cancer-selective toxic properties. Moreover, such models will guide us in developing of a new class of potent apoptin-like molecules with greater selectivity and potency.

Structural and Molecular Modeling Features of P2X Receptors

Directory of Open Access Journals (Sweden)

Luiz Anastacio Alves

2014-03-01

Full Text Available Currently, adenosine 5'-triphosphate (ATP is recognized as the extracellular messenger that acts through P2 receptors. P2 receptors are divided into two subtypes: P2Y metabotropic receptors and P2X ionotropic receptors, both of which are found in virtually all mammalian cell types studied. Due to the difficulty in studying membrane protein structures by X-ray crystallography or NMR techniques, there is little information about these structures available in the literature. Two structures of the P2X4 receptor in truncated form have been solved by crystallography. Molecular modeling has proven to be an excellent tool for studying ionotropic receptors. Recently, modeling studies carried out on P2X receptors have advanced our knowledge of the P2X receptor structure-function relationships. This review presents a brief history of ion channel structural studies and shows how modeling approaches can be used to address relevant questions about P2X receptors.

A Systems Approach to Refine Disease Taxonomy by Integrating Phenotypic and Molecular Networks

Directory of Open Access Journals (Sweden)

Xuezhong Zhou

2018-05-01

Full Text Available The International Classification of Diseases (ICD relies on clinical features and lags behind the current understanding of the molecular specificity of disease pathobiology, necessitating approaches that incorporate growing biomedical data for classifying diseases to meet the needs of precision medicine. Our analysis revealed that the heterogeneous molecular diversity of disease chapters and the blurred boundary between disease categories in ICD should be further investigated. Here, we propose a new classification of diseases (NCD by developing an algorithm that predicts the additional categories of a disease by integrating multiple networks consisting of disease phenotypes and their molecular profiles. With statistical validations from phenotype-genotype associations and interactome networks, we demonstrate that NCD improves disease specificity owing to its overlapping categories and polyhierarchical structure. Furthermore, NCD captures the molecular diversity of diseases and defines clearer boundaries in terms of both phenotypic similarity and molecular associations, establishing a rational strategy to reform disease taxonomy. Keywords: Disease taxonomy, Network medicine, Disease phenotypes, Molecular profiles, Precision medicine

Microbial production of polyhydroxybutyrate with tailor-made properties: an integrated modelling approach and experimental validation.

Science.gov (United States)

Penloglou, Giannis; Chatzidoukas, Christos; Kiparissides, Costas

2012-01-01

The microbial production of polyhydroxybutyrate (PHB) is a complex process in which the final quantity and quality of the PHB depend on a large number of process operating variables. Consequently, the design and optimal dynamic operation of a microbial process for the efficient production of PHB with tailor-made molecular properties is an extremely interesting problem. The present study investigates how key process operating variables (i.e., nutritional and aeration conditions) affect the biomass production rate and the PHB accumulation in the cells and its associated molecular weight distribution. A combined metabolic/polymerization/macroscopic modelling approach, relating the process performance and product quality with the process variables, was developed and validated using an extensive series of experiments and measurements. The model predicts the dynamic evolution of the biomass growth, the polymer accumulation, the consumption of carbon and nitrogen sources and the average molecular weights of the PHB in a bioreactor, under batch and fed-batch operating conditions. The proposed integrated model was used for the model-based optimization of the production of PHB with tailor-made molecular properties in Azohydromonas lata bacteria. The process optimization led to a high intracellular PHB accumulation (up to 95% g of PHB per g of DCW) and the production of different grades (i.e., different molecular weight distributions) of PHB. Copyright © 2011 Elsevier Inc. All rights reserved.

Molecular Phytopathology: Current Approaches and Main Directions in Diagnostics of Woody Plant Diseases

Directory of Open Access Journals (Sweden)

O. Yu. Baranov

2014-08-01

Full Text Available In the article the authors describe the prospects for diagnosis of woody plants diseases based on the use of modern methods of molecular plant pathology. The metagenomic approach based on the analysis of complex pathogens, including non-pathogenic microflora is described. The use the multicopy universal loci characterized by a number of advantages in determining taxonomic affiliation of infectious agents during phytopathological molecular analysis is proposed.

Reconstruction and validation of RefRec: a global model for the yeast molecular interaction network.

Directory of Open Access Journals (Sweden)

Tommi Aho

2010-05-01

Full Text Available Molecular interaction networks establish all cell biological processes. The networks are under intensive research that is facilitated by new high-throughput measurement techniques for the detection, quantification, and characterization of molecules and their physical interactions. For the common model organism yeast Saccharomyces cerevisiae, public databases store a significant part of the accumulated information and, on the way to better understanding of the cellular processes, there is a need to integrate this information into a consistent reconstruction of the molecular interaction network. This work presents and validates RefRec, the most comprehensive molecular interaction network reconstruction currently available for yeast. The reconstruction integrates protein synthesis pathways, a metabolic network, and a protein-protein interaction network from major biological databases. The core of the reconstruction is based on a reference object approach in which genes, transcripts, and proteins are identified using their primary sequences. This enables their unambiguous identification and non-redundant integration. The obtained total number of different molecular species and their connecting interactions is approximately 67,000. In order to demonstrate the capacity of RefRec for functional predictions, it was used for simulating the gene knockout damage propagation in the molecular interaction network in approximately 590,000 experimentally validated mutant strains. Based on the simulation results, a statistical classifier was subsequently able to correctly predict the viability of most of the strains. The results also showed that the usage of different types of molecular species in the reconstruction is important for accurate phenotype prediction. In general, the findings demonstrate the benefits of global reconstructions of molecular interaction networks. With all the molecular species and their physical interactions explicitly modeled, our

Percolation approach for atomic and molecular cluster formation

International Nuclear Information System (INIS)

Knospe, O.; Seifert, G.

1987-12-01

We apply a percolation approach for the theoretical analysis of mass spectra of molecular microclusters obtained by adiabatic expansion technique. The evolution of the shape of the experimental size distributions as function of stagnation pressure and stagnation temperature are theoretically reproduced by varying the percolation parameter. Remaining discrepancies between theory and experiment are discussed. In addition, the even-odd alternation as well as the 'magic' shell structure within metallic, secondary ion mass spectra are investigated by introducing statistical weights for the cluster formation probabilities. Shell correction energies of atomic clusters as function of cluster-size are deduced from the experimental data. (orig.)

Two-Dimensional Model of Scrolled Packings of Molecular Nanoribbons

Science.gov (United States)

Savin, A. V.; Mazo, M. A.

2018-04-01

A simplified model of the in-plane molecular chain, allowing the description of folded and scrolled packings of molecular nanoribbons of different structures, is proposed. Using this model, possible steady states of single-layer nanoribbons scrolls of graphene, graphane, fluorographene, and fluorographane (graphene hydrogenated on the one side and fluorinated on the other side) are obtained. Their stability is demonstrated and their energy is calculated as a function of the nanoribbon length. It is shown that the scrolled packing is the most energetically favorable nanoribbon conformation at long lengths. The existences of scrolled packings for fluorographene nanoribbons and the existence of two different scroll types corresponding to left- and right-hand Archimedean spirals for fluorographane nanoribbons in the chain model are shown for the first time. The simplicity of the proposed model makes it possible to consider the dynamics of scrolls of rather long molecular nanoribbons at long enough time intervals.

Multiscale approach for the construction of equilibrated all-atom models of a poly(ethylene glycol)-based hydrogel

Science.gov (United States)

Li, Xianfeng; Murthy, N. Sanjeeva; Becker, Matthew L.; Latour, Robert A.

2016-01-01

A multiscale modeling approach is presented for the efficient construction of an equilibrated all-atom model of a cross-linked poly(ethylene glycol) (PEG)-based hydrogel using the all-atom polymer consistent force field (PCFF). The final equilibrated all-atom model was built with a systematic simulation toolset consisting of three consecutive parts: (1) building a global cross-linked PEG-chain network at experimentally determined cross-link density using an on-lattice Monte Carlo method based on the bond fluctuation model, (2) recovering the local molecular structure of the network by transitioning from the lattice model to an off-lattice coarse-grained (CG) model parameterized from PCFF, followed by equilibration using high performance molecular dynamics methods, and (3) recovering the atomistic structure of the network by reverse mapping from the equilibrated CG structure, hydrating the structure with explicitly represented water, followed by final equilibration using PCFF parameterization. The developed three-stage modeling approach has application to a wide range of other complex macromolecular hydrogel systems, including the integration of peptide, protein, and/or drug molecules as side-chains within the hydrogel network for the incorporation of bioactivity for tissue engineering, regenerative medicine, and drug delivery applications. PMID:27013229

Molecular features related to HIV integrase inhibition obtained from structure- and ligand-based approaches.

Directory of Open Access Journals (Sweden)

Luciana L de Carvalho

Full Text Available Among several biological targets to treat AIDS, HIV integrase is a promising enzyme that can be employed to develop new anti-HIV agents. The aim of this work is to propose a mechanistic interpretation of HIV-1 integrase inhibition and to rationalize the molecular features related to the binding affinity of studied ligands. A set of 79 HIV-1 integrase inhibitors and its relationship with biological activity are investigated employing 2D and 3D QSAR models, docking analysis and DFT studies. Analyses of docking poses and frontier molecular orbitals revealed important features on the main ligand-receptor interactions. 2D and 3D models presenting good internal consistency, predictive power and stability were obtained in all cases. Significant correlation coefficients (r(2 = 0.908 and q(2= 0.643 for 2D model; r(2= 0.904 and q(2= 0.719 for 3D model were obtained, indicating the potential of these models for untested compounds. The generated holograms and contribution maps revealed important molecular requirements to HIV-1 IN inhibition and several evidences for molecular modifications. The final models along with information resulting from molecular orbitals, 2D contribution and 3D contour maps should be useful in the design of new inhibitors with increased potency and selectivity within the chemical diversity of the data.

Molecular modeling of nucleic Acid structure: electrostatics and solvation.

Science.gov (United States)

Bergonzo, Christina; Galindo-Murillo, Rodrigo; Cheatham, Thomas E

2014-12-19

This unit presents an overview of computer simulation techniques as applied to nucleic acid systems, ranging from simple in vacuo molecular modeling techniques to more complete all-atom molecular dynamics treatments that include an explicit representation of the environment. The third in a series of four units, this unit focuses on critical issues in solvation and the treatment of electrostatics. UNITS 7.5 & 7.8 introduced the modeling of nucleic acid structure at the molecular level. This included a discussion of how to generate an initial model, how to evaluate the utility or reliability of a given model, and ultimately how to manipulate this model to better understand its structure, dynamics, and interactions. Subject to an appropriate representation of the energy, such as a specifically parameterized empirical force field, the techniques of minimization and Monte Carlo simulation, as well as molecular dynamics (MD) methods, were introduced as a way of sampling conformational space for a better understanding of the relevance of a given model. This discussion highlighted the major limitations with modeling in general. When sampling conformational space effectively, difficult issues are encountered, such as multiple minima or conformational sampling problems, and accurately representing the underlying energy of interaction. In order to provide a realistic model of the underlying energetics for nucleic acids in their native environments, it is crucial to include some representation of solvation (by water) and also to properly treat the electrostatic interactions. These subjects are discussed in detail in this unit. Copyright © 2014 John Wiley & Sons, Inc.

Development of simulation approach for two-dimensional chiral molecular self-assembly driven by hydrogen bond at the liquid/solid interface

Science.gov (United States)

Qin, Yuan; Yao, Man; Hao, Ce; Wan, Lijun; Wang, Yunhe; Chen, Ting; Wang, Dong; Wang, Xudong; Chen, Yonggang

2017-09-01

Two-dimensional (2D) chiral self-assembly system of 5-(benzyloxy)-isophthalic acid derivative/(S)-(+)-2-octanol/highly oriented pyrolytic graphite was studied. A combined density functional theory/molecular mechanics/molecular dynamics (DFT/MM/MD) approach for system of 2D chiral molecular self-assembly driven by hydrogen bond at the liquid/solid interface was thus proposed. Structural models of the chiral assembly were built on the basis of scanning tunneling microscopy (STM) images and simplified for DFT geometry optimization. Merck Molecular Force Field (MMFF) was singled out as the suitable force field by comparing the optimized configurations of MM and DFT. MM and MD simulations for hexagonal unit model which better represented the 2D assemble network were then preformed with MMFF. The adhesion energy, evolution of self-assembly process and characteristic parameters of hydrogen bond were obtained and analyzed. According to the above simulation, the stabilities of the clockwise and counterclockwise enantiomorphous networks were evaluated. The calculational results were supported by STM observations and the feasibility of the simulation method was confirmed by two other systems in the presence of chiral co-absorbers (R)-(-)-2-octanol and achiral co-absorbers 1-octanol. This theoretical simulation method assesses the stability trend of 2D enantiomorphous assemblies with atomic scale and can be applied to the similar hydrogen bond driven 2D chirality of molecular self-assembly system.

Computer-Based Molecular Modelling: Finnish School Teachers' Experiences and Views

Science.gov (United States)

Aksela, Maija; Lundell, Jan

2008-01-01

Modern computer-based molecular modelling opens up new possibilities for chemistry teaching at different levels. This article presents a case study seeking insight into Finnish school teachers' use of computer-based molecular modelling in teaching chemistry, into the different working and teaching methods used, and their opinions about necessary…

Identification of bioflavonoid as fusion inhibitor of dengue virus using molecular docking approach

Directory of Open Access Journals (Sweden)

Asif Mir

Full Text Available Dengue virus with four distinct serotypes belongs to Flavivirus, poses a significant threat to human health and becomes an emerging global problem. Membrane fusion is a central molecular event during viral entry into host cell. To prevent viral infection it is necessary to interrupt the virus replication at an early stage of attachment. Dengue Virus (DENV envelope protein experiences conformational changes and it causes the virus to fuse with host cell. Hinge region movement of domain I and II in envelope protein facilitates the fusion process. Small molecules that bind in this pocket may have the ability to interrupt the conformational changes that trigger fusion process. We chose different flavonoids (baicalein, fisetin, hesperetin, naringenin/ naringin, quercetin and rutin that possess anti dengue activity. Molecular docking analysis was done to examine the inhibitory effect of flavonoids against envelope protein of DENV-2. Results manifest quercetin (flavonoid found in Carica papaya, apple and even in lemon as the only flavone that can interrupt the fusion process of virus by inhibiting the hinge region movement and by blocking the conformational rearrangement in envelope protein. These novel findings using computational approach are worthwhile and will be a bridge to check the efficacy of compounds using appropriate animal model under In vivo studies. This information can be used by new techniques and provides a way to control dengue virus infection. Keywords: Dengue virus, Inhibitor identification, Molecular docking, Interaction analysis

Multiplicity of Mathematical Modeling Strategies to Search for Molecular and Cellular Insights into Bacteria Lung Infection.

Science.gov (United States)

Cantone, Martina; Santos, Guido; Wentker, Pia; Lai, Xin; Vera, Julio

2017-01-01

Even today two bacterial lung infections, namely pneumonia and tuberculosis, are among the 10 most frequent causes of death worldwide. These infections still lack effective treatments in many developing countries and in immunocompromised populations like infants, elderly people and transplanted patients. The interaction between bacteria and the host is a complex system of interlinked intercellular and the intracellular processes, enriched in regulatory structures like positive and negative feedback loops. Severe pathological condition can emerge when the immune system of the host fails to neutralize the infection. This failure can result in systemic spreading of pathogens or overwhelming immune response followed by a systemic inflammatory response. Mathematical modeling is a promising tool to dissect the complexity underlying pathogenesis of bacterial lung infection at the molecular, cellular and tissue levels, and also at the interfaces among levels. In this article, we introduce mathematical and computational modeling frameworks that can be used for investigating molecular and cellular mechanisms underlying bacterial lung infection. Then, we compile and discuss published results on the modeling of regulatory pathways and cell populations relevant for lung infection and inflammation. Finally, we discuss how to make use of this multiplicity of modeling approaches to open new avenues in the search of the molecular and cellular mechanisms underlying bacterial infection in the lung.

Classical and quantum analysis of a hetero-triatomic molecular Bose-Einstein condensate model

International Nuclear Information System (INIS)

Tonel, A.P.; Kuhn, C.C.N.; Foerster, A.; Santos, G.; Roditi, I.; Santos, Z.V.T.

2014-11-01

We investigate an integrable Hamiltonian modelling a hetero-triatomic-molecular Bose-Einstein condensate. This model describes a mixture of two species of atoms in different proportions, which can combine to form a triatomic molecule. Beginning with a classical analysis, we determine the fixed points of the system. Bifurcations of these points separate the parameter space into different regions. Three distinct scenarios are found, varying with the atomic population imbalance. This result suggests the ground state properties of the quantum model exhibits a sensitivity on the atomic population imbalance, which is confirmed by a quantum analysis using different approaches, such as the ground-state expectation values, the behaviour of the quantum dynamics, the energy gap and the ground state fidelity. (author)

Molecular Dynamics Approach in Designing Thermostable Aspergillus niger Xylanase

Science.gov (United States)

Malau, N. D.; Sianturi, M.

2017-03-01

Molecular dynamics methods we have applied as a tool in designing thermostable Aspergillus niger Xylanase, by examining Root Mean Square Deviation (RMSD) and The Stability of the Secondary Structure of enzymes structure at its optimum temperature and compare with its high temperature behavior. As RMSD represents structural fluctuation at a particular temperature, a better understanding of this factor will suggest approaches to bioengineer these enzymes to enhance their thermostability. In this work molecular dynamic simulations of Aspergillus niger xylanase (ANX) have been carried at 400K (optimum catalytic temperature) for 2.5 ns and 500K (ANX reported inactive temperature) for 2.5 ns. Analysis have shown that the Root Mean Square Deviation (RMSD) significant increase at higher temperatures compared at optimum temperature and some of the secondary structures of ANX that have been damaged at high temperature. Structural analysis revealed that the fluctuations of the α-helix and β-sheet regions are larger at higher temperatures compared to the fluctuations at optimum temperature.

Modular and Stochastic Approaches to Molecular Pathway Models of ATM, TGF beta, and WNT Signaling

Science.gov (United States)

Cucinotta, Francis A.; O'Neill, Peter; Ponomarev, Artem; Carra, Claudio; Whalen, Mary; Pluth, Janice M.

2009-01-01

Deterministic pathway models that describe the biochemical interactions of a group of related proteins, their complexes, activation through kinase, etc. are often the basis for many systems biology models. Low dose radiation effects present a unique set of challenges to these models including the importance of stochastic effects due to the nature of radiation tracks and small number of molecules activated, and the search for infrequent events that contribute to cancer risks. We have been studying models of the ATM, TGF -Smad and WNT signaling pathways with the goal of applying pathway models to the investigation of low dose radiation cancer risks. Modeling challenges include introduction of stochastic models of radiation tracks, their relationships to more than one substrate species that perturb pathways, and the identification of a representative set of enzymes that act on the dominant substrates. Because several pathways are activated concurrently by radiation the development of modular pathway approach is of interest.

Modeling of ultrafast THz interactions in molecular crystals

DEFF Research Database (Denmark)

Pedersen, Pernille Klarskov; Clark, Stewart J.; Jepsen, Peter Uhd

2014-01-01

In this paper we present a numerical study of terahertz pulses interacting with crystals of cesium iodide. We model the molecular dynamics of the cesium iodide crystals with the Density Functional Theory software CASTEP, where ultrafast terahertz pulses are implemented to the CASTEP software...... to interact with molecular crystals. We investigate the molecular dynamics of cesium iodide crystals when interacting with realistic terahertz pulses of field strengths from 0 to 50 MV/cm. We find nonlinearities in the response of the CsI crystals at field strengths higher than 10 MV/cm....

Structural Refinement of Proteins by Restrained Molecular Dynamics Simulations with Non-interacting Molecular Fragments.

Directory of Open Access Journals (Sweden)

Rong Shen

2015-10-01

Full Text Available The knowledge of multiple conformational states is a prerequisite to understand the function of membrane transport proteins. Unfortunately, the determination of detailed atomic structures for all these functionally important conformational states with conventional high-resolution approaches is often difficult and unsuccessful. In some cases, biophysical and biochemical approaches can provide important complementary structural information that can be exploited with the help of advanced computational methods to derive structural models of specific conformational states. In particular, functional and spectroscopic measurements in combination with site-directed mutations constitute one important source of information to obtain these mixed-resolution structural models. A very common problem with this strategy, however, is the difficulty to simultaneously integrate all the information from multiple independent experiments involving different mutations or chemical labels to derive a unique structural model consistent with the data. To resolve this issue, a novel restrained molecular dynamics structural refinement method is developed to simultaneously incorporate multiple experimentally determined constraints (e.g., engineered metal bridges or spin-labels, each treated as an individual molecular fragment with all atomic details. The internal structure of each of the molecular fragments is treated realistically, while there is no interaction between different molecular fragments to avoid unphysical steric clashes. The information from all the molecular fragments is exploited simultaneously to constrain the backbone to refine a three-dimensional model of the conformational state of the protein. The method is illustrated by refining the structure of the voltage-sensing domain (VSD of the Kv1.2 potassium channel in the resting state and by exploring the distance histograms between spin-labels attached to T4 lysozyme. The resulting VSD structures are in good

Modeling molecular boiling points using computed interaction energies.

Science.gov (United States)

Peterangelo, Stephen C; Seybold, Paul G

2017-12-20

The noncovalent van der Waals interactions between molecules in liquids are typically described in textbooks as occurring between the total molecular dipoles (permanent, induced, or transient) of the molecules. This notion was tested by examining the boiling points of 67 halogenated hydrocarbon liquids using quantum chemically calculated molecular dipole moments, ionization potentials, and polarizabilities obtained from semi-empirical (AM1 and PM3) and ab initio Hartree-Fock [HF 6-31G(d), HF 6-311G(d,p)], and density functional theory [B3LYP/6-311G(d,p)] methods. The calculated interaction energies and an empirical measure of hydrogen bonding were employed to model the boiling points of the halocarbons. It was found that only terms related to London dispersion energies and hydrogen bonding proved significant in the regression analyses, and the performances of the models generally improved at higher levels of quantum chemical computation. An empirical estimate for the molecular polarizabilities was also tested, and the best models for the boiling points were obtained using either this empirical polarizability itself or the polarizabilities calculated at the B3LYP/6-311G(d,p) level, along with the hydrogen-bonding parameter. The results suggest that the cohesive forces are more appropriately described as resulting from highly localized interactions rather than interactions between the global molecular dipoles.

A comparison of machine learning and Bayesian modelling for molecular serotyping.

Science.gov (United States)

Newton, Richard; Wernisch, Lorenz

2017-08-11

Streptococcus pneumoniae is a human pathogen that is a major cause of infant mortality. Identifying the pneumococcal serotype is an important step in monitoring the impact of vaccines used to protect against disease. Genomic microarrays provide an effective method for molecular serotyping. Previously we developed an empirical Bayesian model for the classification of serotypes from a molecular serotyping array. With only few samples available, a model driven approach was the only option. In the meanwhile, several thousand samples have been made available to us, providing an opportunity to investigate serotype classification by machine learning methods, which could complement the Bayesian model. We compare the performance of the original Bayesian model with two machine learning algorithms: Gradient Boosting Machines and Random Forests. We present our results as an example of a generic strategy whereby a preliminary probabilistic model is complemented or replaced by a machine learning classifier once enough data are available. Despite the availability of thousands of serotyping arrays, a problem encountered when applying machine learning methods is the lack of training data containing mixtures of serotypes; due to the large number of possible combinations. Most of the available training data comprises samples with only a single serotype. To overcome the lack of training data we implemented an iterative analysis, creating artificial training data of serotype mixtures by combining raw data from single serotype arrays. With the enhanced training set the machine learning algorithms out perform the original Bayesian model. However, for serotypes currently lacking sufficient training data the best performing implementation was a combination of the results of the Bayesian Model and the Gradient Boosting Machine. As well as being an effective method for classifying biological data, machine learning can also be used as an efficient method for revealing subtle biological

WE-DE-202-03: Modeling of Biological Processes - What Happens After Early Molecular Damage?

International Nuclear Information System (INIS)

McMahon, S.

2016-01-01

Radiation therapy for the treatment of cancer has been established as a highly precise and effective way to eradicate a localized region of diseased tissue. To achieve further significant gains in the therapeutic ratio, we need to move towards biologically optimized treatment planning. To achieve this goal, we need to understand how the radiation-type dependent patterns of induced energy depositions within the cell (physics) connect via molecular, cellular and tissue reactions to treatment outcome such as tumor control and undesirable effects on normal tissue. Several computational biology approaches have been developed connecting physics to biology. Monte Carlo simulations are the most accurate method to calculate physical dose distributions at the nanometer scale, however simulations at the DNA scale are slow and repair processes are generally not simulated. Alternative models that rely on the random formation of individual DNA lesions within one or two turns of the DNA have been shown to reproduce the clusters of DNA lesions, including single strand breaks (SSBs), double strand breaks (DSBs) without the need for detailed track structure simulations. Efficient computational simulations of initial DNA damage induction facilitate computational modeling of DNA repair and other molecular and cellular processes. Mechanistic, multiscale models provide a useful conceptual framework to test biological hypotheses and help connect fundamental information about track structure and dosimetry at the sub-cellular level to dose-response effects on larger scales. In this symposium we will learn about the current state of the art of computational approaches estimating radiation damage at the cellular and sub-cellular scale. How can understanding the physics interactions at the DNA level be used to predict biological outcome? We will discuss if and how such calculations are relevant to advance our understanding of radiation damage and its repair, or, if the underlying biological

WE-DE-202-03: Modeling of Biological Processes - What Happens After Early Molecular Damage?

Energy Technology Data Exchange (ETDEWEB)

McMahon, S. [Massachusetts General Hospital and Harvard Medical School (United States)

2016-06-15

Radiation therapy for the treatment of cancer has been established as a highly precise and effective way to eradicate a localized region of diseased tissue. To achieve further significant gains in the therapeutic ratio, we need to move towards biologically optimized treatment planning. To achieve this goal, we need to understand how the radiation-type dependent patterns of induced energy depositions within the cell (physics) connect via molecular, cellular and tissue reactions to treatment outcome such as tumor control and undesirable effects on normal tissue. Several computational biology approaches have been developed connecting physics to biology. Monte Carlo simulations are the most accurate method to calculate physical dose distributions at the nanometer scale, however simulations at the DNA scale are slow and repair processes are generally not simulated. Alternative models that rely on the random formation of individual DNA lesions within one or two turns of the DNA have been shown to reproduce the clusters of DNA lesions, including single strand breaks (SSBs), double strand breaks (DSBs) without the need for detailed track structure simulations. Efficient computational simulations of initial DNA damage induction facilitate computational modeling of DNA repair and other molecular and cellular processes. Mechanistic, multiscale models provide a useful conceptual framework to test biological hypotheses and help connect fundamental information about track structure and dosimetry at the sub-cellular level to dose-response effects on larger scales. In this symposium we will learn about the current state of the art of computational approaches estimating radiation damage at the cellular and sub-cellular scale. How can understanding the physics interactions at the DNA level be used to predict biological outcome? We will discuss if and how such calculations are relevant to advance our understanding of radiation damage and its repair, or, if the underlying biological

Tangible Models and Haptic Representations Aid Learning of Molecular Biology Concepts

Science.gov (United States)

Johannes, Kristen; Powers, Jacklyn; Couper, Lisa; Silberglitt, Matt; Davenport, Jodi

2016-01-01

Can novel 3D models help students develop a deeper understanding of core concepts in molecular biology? We adapted 3D molecular models, developed by scientists, for use in high school science classrooms. The models accurately represent the structural and functional properties of complex DNA and Virus molecules, and provide visual and haptic…

A coarse-graining approach for molecular simulation that retains the dynamics of the all-atom reference system by implementing hydrodynamic interactions

Energy Technology Data Exchange (ETDEWEB)

Markutsya, Sergiy [Ames Laboratory, Iowa State University, Ames, Iowa 50011 (United States); Lamm, Monica H., E-mail: mhlamm@iastate.edu [Ames Laboratory, Iowa State University, Ames, Iowa 50011 (United States); Department of Chemical and Biological Engineering, Iowa State University, Ames, Iowa 50011 (United States)

2014-11-07

We report on a new approach for deriving coarse-grained intermolecular forces that retains the frictional contribution that is often discarded by conventional coarse-graining methods. The approach is tested for water and an aqueous glucose solution, and the results from the new implementation for coarse-grained molecular dynamics simulation show remarkable agreement with the dynamics obtained from reference all-atom simulations. The agreement between the structural properties observed in the coarse-grained and all-atom simulations is also preserved. We discuss how this approach may be applied broadly to any existing coarse-graining method where the coarse-grained models are rigorously derived from all-atom reference systems.

A coarse-graining approach for molecular simulation that retains the dynamics of the all-atom reference system by implementing hydrodynamic interactions

International Nuclear Information System (INIS)

Markutsya, Sergiy; Lamm, Monica H.

2014-01-01

We report on a new approach for deriving coarse-grained intermolecular forces that retains the frictional contribution that is often discarded by conventional coarse-graining methods. The approach is tested for water and an aqueous glucose solution, and the results from the new implementation for coarse-grained molecular dynamics simulation show remarkable agreement with the dynamics obtained from reference all-atom simulations. The agreement between the structural properties observed in the coarse-grained and all-atom simulations is also preserved. We discuss how this approach may be applied broadly to any existing coarse-graining method where the coarse-grained models are rigorously derived from all-atom reference systems

Venom Resistance as a Model for Understanding the Molecular Basis of Complex Coevolutionary Adaptations.

Science.gov (United States)

Holding, Matthew L; Drabeck, Danielle H; Jansa, Sharon A; Gibbs, H Lisle

2016-11-01

SynopsisVenom and venom resistance are molecular phenotypes widely considered to have diversified through coevolution between predators and prey. However, while evolutionary and functional studies on venom have been extensive, little is known about the molecular basis, variation, and complexity of venom resistance. We review known mechanisms of venom resistance and relate these mechanisms to their predicted impact on coevolutionary dynamics with venomous enemies. We then describe two conceptual approaches which can be used to examine venom/resistance systems. At the intraspecific level, tests of local adaptation in venom and resistance phenotypes can identify the functional mechanisms governing the outcomes of coevolution. At deeper evolutionary timescales, the combination of phylogenetically informed analyses of protein evolution coupled with studies of protein function promise to elucidate the mode and tempo of evolutionary change on potentially coevolving genes. We highlight case studies that use each approach to extend our knowledge of these systems as well as address larger questions about coevolutionary dynamics. We argue that resistance and venom are phenotypic traits which hold exceptional promise for investigating the mechanisms, dynamics, and outcomes of coevolution at the molecular level. Furthermore, extending the understanding of single gene-for-gene interactions to the whole resistance and venom phenotypes may provide a model system for examining the molecular and evolutionary dynamics of complex multi-gene interactions. © The Author 2016. Published by Oxford University Press on behalf of the Society for Integrative and Comparative Biology. All rights reserved. For permissions please email: journals.permissions@oup.com.

Multi-Scale Modelling of Deformation and Fracture in a Biomimetic Apatite-Protein Composite: Molecular-Scale Processes Lead to Resilience at the μm-Scale.

Directory of Open Access Journals (Sweden)

Dirk Zahn

Full Text Available Fracture mechanisms of an enamel-like hydroxyapatite-collagen composite model are elaborated by means of molecular and coarse-grained dynamics simulation. Using fully atomistic models, we uncover molecular-scale plastic deformation and fracture processes initiated at the organic-inorganic interface. Furthermore, coarse-grained models are developed to investigate fracture patterns at the μm-scale. At the meso-scale, micro-fractures are shown to reduce local stress and thus prevent material failure after loading beyond the elastic limit. On the basis of our multi-scale simulation approach, we provide a molecular scale rationalization of this phenomenon, which seems key to the resilience of hierarchical biominerals, including teeth and bone.

Viscoelasticity in Polymers: Phenomenological to Molecular Mathematical Modelling

National Research Council Canada - National Science Library

Banks, H. T; Luke, N. S

2006-01-01

We report on two recent advances in the modelling of viscoelastic polymers: (i) a new constitutive model which combines the virtual stick-slip continuum "molecular-based" ideas of Johnson and Stacer with the Rouse bead chain ideas; (ii...

A fermionic molecular dynamics technique to model nuclear matter

International Nuclear Information System (INIS)

Vantournhout, K.; Jachowicz, N.; Ryckebusch, J.

2009-01-01

Full text: At sub-nuclear densities of about 10 14 g/cm 3 , nuclear matter arranges itself in a variety of complex shapes. This can be the case in the crust of neutron stars and in core-collapse supernovae. These slab like and rod like structures, designated as nuclear pasta, have been modelled with classical molecular dynamics techniques. We present a technique, based on fermionic molecular dynamics, to model nuclear matter at sub-nuclear densities in a semi classical framework. The dynamical evolution of an antisymmetric ground state is described making the assumption of periodic boundary conditions. Adding the concepts of antisymmetry, spin and probability distributions to classical molecular dynamics, brings the dynamical description of nuclear matter to a quantum mechanical level. Applications of this model vary from investigation of macroscopic observables and the equation of state to the study of fundamental interactions on the microscopic structure of the matter. (author)

Status of Safeguards and Separations Model Development at Plant and Molecular Levels

Energy Technology Data Exchange (ETDEWEB)

de Almeida, Valmor F [ORNL; Hay, Benjamin [ORNL; DePaoli, David W [ORNL

2009-10-01

A primary goal of the Safeguards and Separations IPSC effort is the development of process modeling tools that allow dynamic simulations of separations plant operations under various configurations and conditions, and integration of relevant safeguards analyses. A requirement of the effort is to develop codes on modern, expandable architectures, with flexibility to explore and evaluate a wide range of process options. During FY09, efforts at ORNL have been focused on two priority tasks toward achieving the IPSC goal: (1) a top-down exploration of architecture - Subtask 1: Explore framework for code development and integration for plant-level simulation; and (2) a bottom-up fundamental modeling effort - Subtask 2: Development of molecular-level agent design code. Subtask 1 is important because definition and development of architecture is a key issue for the overall effort, as selection of an overall approach and code/data requirements is a necessary first step in the organization, design and development of separations and safeguards codes that will be incorporated. The agent design effort of Subtask 2 is a molecular-level modeling effort that has a direct impact on a near-term issue of the Separations and Waste Forms Campaign. A current focus of experimental efforts is the development of robust agents and processes for separation of Am/Cm. Development of enhanced agent-design codes will greatly accelerate discovery and experimental testing.

Status of Safeguards and Separations Model Development at Plant and Molecular Levels

International Nuclear Information System (INIS)

de Almeida, Valmor F.; Hay, Benjamin; DePaoli, David W.

2009-01-01

A primary goal of the Safeguards and Separations IPSC effort is the development of process modeling tools that allow dynamic simulations of separations plant operations under various configurations and conditions, and integration of relevant safeguards analyses. A requirement of the effort is to develop codes on modern, expandable architectures, with flexibility to explore and evaluate a wide range of process options. During FY09, efforts at ORNL have been focused on two priority tasks toward achieving the IPSC goal: (1) a top-down exploration of architecture - Subtask 1: Explore framework for code development and integration for plant-level simulation; and (2) a bottom-up fundamental modeling effort - Subtask 2: Development of molecular-level agent design code. Subtask 1 is important because definition and development of architecture is a key issue for the overall effort, as selection of an overall approach and code/data requirements is a necessary first step in the organization, design and development of separations and safeguards codes that will be incorporated. The agent design effort of Subtask 2 is a molecular-level modeling effort that has a direct impact on a near-term issue of the Separations and Waste Forms Campaign. A current focus of experimental efforts is the development of robust agents and processes for separation of Am/Cm. Development of enhanced agent-design codes will greatly accelerate discovery and experimental testing.

Towards a system level understanding of non-model organisms sampled from the environment: a network biology approach.

Science.gov (United States)

Williams, Tim D; Turan, Nil; Diab, Amer M; Wu, Huifeng; Mackenzie, Carolynn; Bartie, Katie L; Hrydziuszko, Olga; Lyons, Brett P; Stentiford, Grant D; Herbert, John M; Abraham, Joseph K; Katsiadaki, Ioanna; Leaver, Michael J; Taggart, John B; George, Stephen G; Viant, Mark R; Chipman, Kevin J; Falciani, Francesco

2011-08-01

The acquisition and analysis of datasets including multi-level omics and physiology from non-model species, sampled from field populations, is a formidable challenge, which so far has prevented the application of systems biology approaches. If successful, these could contribute enormously to improving our understanding of how populations of living organisms adapt to environmental stressors relating to, for example, pollution and climate. Here we describe the first application of a network inference approach integrating transcriptional, metabolic and phenotypic information representative of wild populations of the European flounder fish, sampled at seven estuarine locations in northern Europe with different degrees and profiles of chemical contaminants. We identified network modules, whose activity was predictive of environmental exposure and represented a link between molecular and morphometric indices. These sub-networks represented both known and candidate novel adverse outcome pathways representative of several aspects of human liver pathophysiology such as liver hyperplasia, fibrosis, and hepatocellular carcinoma. At the molecular level these pathways were linked to TNF alpha, TGF beta, PDGF, AGT and VEGF signalling. More generally, this pioneering study has important implications as it can be applied to model molecular mechanisms of compensatory adaptation to a wide range of scenarios in wild populations.

Sensitivity of electrospray molecular dynamics simulations to long-range Coulomb interaction models.

Science.gov (United States)

Mehta, Neil A; Levin, Deborah A

2018-03-01

Molecular dynamics (MD) electrospray simulations of 1-ethyl-3-methylimidazolium tetrafluoroborate (EMIM-BF_{4}) ion liquid were performed with the goal of evaluating the influence of long-range Coulomb models on ion emission characteristics. The direct Coulomb (DC), shifted force Coulomb sum (SFCS), and particle-particle particle-mesh (PPPM) long-range Coulomb models were considered in this work. The DC method with a sufficiently large cutoff radius was found to be the most accurate approach for modeling electrosprays, but, it is computationally expensive. The Coulomb potential energy modeled by the DC method in combination with the radial electric fields were found to be necessary to generate the Taylor cone. The differences observed between the SFCS and the DC in terms of predicting the total ion emission suggest that the former should not be used in MD electrospray simulations. Furthermore, the common assumption of domain periodicity was observed to be detrimental to the accuracy of the capillary-based electrospray simulations.

Molecular Population Genetics.

Science.gov (United States)

Casillas, Sònia; Barbadilla, Antonio

2017-03-01

Molecular population genetics aims to explain genetic variation and molecular evolution from population genetics principles. The field was born 50 years ago with the first measures of genetic variation in allozyme loci, continued with the nucleotide sequencing era, and is currently in the era of population genomics. During this period, molecular population genetics has been revolutionized by progress in data acquisition and theoretical developments. The conceptual elegance of the neutral theory of molecular evolution or the footprint carved by natural selection on the patterns of genetic variation are two examples of the vast number of inspiring findings of population genetics research. Since the inception of the field, Drosophila has been the prominent model species: molecular variation in populations was first described in Drosophila and most of the population genetics hypotheses were tested in Drosophila species. In this review, we describe the main concepts, methods, and landmarks of molecular population genetics, using the Drosophila model as a reference. We describe the different genetic data sets made available by advances in molecular technologies, and the theoretical developments fostered by these data. Finally, we review the results and new insights provided by the population genomics approach, and conclude by enumerating challenges and new lines of inquiry posed by increasingly large population scale sequence data. Copyright © 2017 Casillas and Barbadilla.

Photoelectron angular distributions for states of any mixed character: An experiment-friendly model for atomic, molecular, and cluster anions

International Nuclear Information System (INIS)

Khuseynov, Dmitry; Blackstone, Christopher C.; Culberson, Lori M.; Sanov, Andrei

2014-01-01

We present a model for laboratory-frame photoelectron angular distributions in direct photodetachment from (in principle) any molecular orbital using linearly polarized light. A transparent mathematical approach is used to generalize the Cooper-Zare central-potential model to anionic states of any mixed character. In the limit of atomic-anion photodetachment, the model reproduces the Cooper-Zare formula. In the case of an initial orbital described as a superposition of s and p-type functions, the model yields the previously obtained s-p mixing formula. The formalism is further advanced using the Hanstorp approximation, whereas the relative scaling of the partial-wave cross-sections is assumed to follow the Wigner threshold law. The resulting model describes the energy dependence of photoelectron anisotropy for any atomic, molecular, or cluster anions, usually without requiring a direct calculation of the transition dipole matrix elements. As a benchmark case, we apply the p-d variant of the model to the experimental results for NO − photodetachment and show that the observed anisotropy trend is described well using physically meaningful values of the model parameters. Overall, the presented formalism delivers insight into the photodetachment process and affords a new quantitative strategy for analyzing the photoelectron angular distributions and characterizing mixed-character molecular orbitals using photoelectron imaging spectroscopy of negative ions

Photoelectron angular distributions for states of any mixed character: An experiment-friendly model for atomic, molecular, and cluster anions

Science.gov (United States)

Khuseynov, Dmitry; Blackstone, Christopher C.; Culberson, Lori M.; Sanov, Andrei

2014-09-01

We present a model for laboratory-frame photoelectron angular distributions in direct photodetachment from (in principle) any molecular orbital using linearly polarized light. A transparent mathematical approach is used to generalize the Cooper-Zare central-potential model to anionic states of any mixed character. In the limit of atomic-anion photodetachment, the model reproduces the Cooper-Zare formula. In the case of an initial orbital described as a superposition of s and p-type functions, the model yields the previously obtained s-p mixing formula. The formalism is further advanced using the Hanstorp approximation, whereas the relative scaling of the partial-wave cross-sections is assumed to follow the Wigner threshold law. The resulting model describes the energy dependence of photoelectron anisotropy for any atomic, molecular, or cluster anions, usually without requiring a direct calculation of the transition dipole matrix elements. As a benchmark case, we apply the p-d variant of the model to the experimental results for NO- photodetachment and show that the observed anisotropy trend is described well using physically meaningful values of the model parameters. Overall, the presented formalism delivers insight into the photodetachment process and affords a new quantitative strategy for analyzing the photoelectron angular distributions and characterizing mixed-character molecular orbitals using photoelectron imaging spectroscopy of negative ions.

Synthesis, spectroscopic investigations, DFT studies, molecular docking and antimicrobial potential of certain new indole-isatin molecular hybrids: Experimental and theoretical approaches

Science.gov (United States)

Almutairi, Maha S.; Zakaria, Azza S.; Ignasius, P. Primsa; Al-Wabli, Reem I.; Joe, Isaac Hubert; Attia, Mohamed I.

2018-02-01

Indole-isatin molecular hybrids 5a-i have been synthesized and characterized by different spectroscopic methods to be evaluated as new antimicrobial agents against a panel of Gram positive bacteria, Gram negative bacteria, and moulds. Compound 5h was selected as a representative example of the prepared compounds 5a-i to perform computational investigations. Its vibrational properties have been studied using FT-IR and FT-Raman with the aid of density functional theory approach. The natural bond orbital analysis as well as HOMO and LUMO molecular orbitals investigations of compound 5h were carried out to explore its possible intermolecular delocalization or hyperconjugation and its possible interactions with the target protein. Molecular docking of compound 5h predicted its binding mode with the fungal target protein.

A molecular-mechanics based finite element model for strength prediction of single wall carbon nanotubes

International Nuclear Information System (INIS)

Meo, M.; Rossi, M.

2007-01-01

The aim of this work was to develop a finite element model based on molecular mechanics to predict the ultimate strength and strain of single wallet carbon nanotubes (SWCNT). The interactions between atoms was modelled by combining the use of non-linear elastic and torsional elastic spring. In particular, with this approach, it was tried to combine the molecular mechanics approach with finite element method without providing any not-physical data on the interactions between the carbon atoms, i.e. the CC-bond inertia moment or Young's modulus definition. Mechanical properties as Young's modulus, ultimate strength and strain for several CNTs were calculated. Further, a stress-strain curve for large deformation (up to 70%) is reported for a nanotube Zig-Zag (9,0). The results showed that good agreement with the experimental and numerical results of several authors was obtained. A comparison of the mechanical properties of nanotubes with same diameter and different chirality was carried out. Finally, the influence of the presence of defects on the strength and strain of a SWNT was also evaluated. In particular, the stress-strain curve a nanotube with one-vacancy defect was evaluated and compared with the curve of a pristine one, showing a reduction of the ultimate strength and strain for the defected nanotube. The FE model proposed demonstrate to be a reliable tool to simulate mechanical behaviour of carbon nanotubes both in the linear elastic field and the non-linear elastic field

Phylogenetic molecular function annotation

International Nuclear Information System (INIS)

Engelhardt, Barbara E; Jordan, Michael I; Repo, Susanna T; Brenner, Steven E

2009-01-01

It is now easier to discover thousands of protein sequences in a new microbial genome than it is to biochemically characterize the specific activity of a single protein of unknown function. The molecular functions of protein sequences have typically been predicted using homology-based computational methods, which rely on the principle that homologous proteins share a similar function. However, some protein families include groups of proteins with different molecular functions. A phylogenetic approach for predicting molecular function (sometimes called 'phylogenomics') is an effective means to predict protein molecular function. These methods incorporate functional evidence from all members of a family that have functional characterizations using the evolutionary history of the protein family to make robust predictions for the uncharacterized proteins. However, they are often difficult to apply on a genome-wide scale because of the time-consuming step of reconstructing the phylogenies of each protein to be annotated. Our automated approach for function annotation using phylogeny, the SIFTER (Statistical Inference of Function Through Evolutionary Relationships) methodology, uses a statistical graphical model to compute the probabilities of molecular functions for unannotated proteins. Our benchmark tests showed that SIFTER provides accurate functional predictions on various protein families, outperforming other available methods.

Modeling of metal thin film growth: Linking angstrom-scale molecular dynamics results to micron-scale film topographies

Science.gov (United States)

Hansen, U.; Rodgers, S.; Jensen, K. F.

2000-07-01

A general method for modeling ionized physical vapor deposition is presented. As an example, the method is applied to growth of an aluminum film in the presence of an ionized argon flux. Molecular dynamics techniques are used to examine the surface adsorption, reflection, and sputter reactions taking place during ionized physical vapor deposition. We predict their relative probabilities and discuss their dependence on energy and incident angle. Subsequently, we combine the information obtained from molecular dynamics with a line of sight transport model in a two-dimensional feature, incorporating all effects of reemission and resputtering. This provides a complete growth rate model that allows inclusion of energy- and angular-dependent reaction rates. Finally, a level-set approach is used to describe the morphology of the growing film. We thus arrive at a computationally highly efficient and accurate scheme to model the growth of thin films. We demonstrate the capabilities of the model predicting the major differences on Al film topographies between conventional and ionized sputter deposition techniques studying thin film growth under ionized physical vapor deposition conditions with different Ar fluxes.

Recent developments of the quantum chemical cluster approach for modeling enzyme reactions.

Science.gov (United States)

Siegbahn, Per E M; Himo, Fahmi

2009-06-01

The quantum chemical cluster approach for modeling enzyme reactions is reviewed. Recent applications have used cluster models much larger than before which have given new modeling insights. One important and rather surprising feature is the fast convergence with cluster size of the energetics of the reactions. Even for reactions with significant charge separation it has in some cases been possible to obtain full convergence in the sense that dielectric cavity effects from outside the cluster do not contribute to any significant extent. Direct comparisons between quantum mechanics (QM)-only and QM/molecular mechanics (MM) calculations for quite large clusters in a case where the results differ significantly have shown that care has to be taken when using the QM/MM approach where there is strong charge polarization. Insights from the methods used, generally hybrid density functional methods, have also led to possibilities to give reasonable error limits for the results. Examples are finally given from the most extensive study using the cluster model, the one of oxygen formation at the oxygen-evolving complex in photosystem II.

Designing of phenol-based β-carbonic anhydrase1 inhibitors through QSAR, molecular docking, and MD simulation approach.

Science.gov (United States)

Ahamad, Shahzaib; Hassan, Md Imtaiyaz; Dwivedi, Neeraja

2018-05-01

Tuberculosis (Tb) is an airborne infectious disease caused by Mycobacterium tuberculosis. Beta-carbonic anhydrase 1 ( β-CA1 ) has emerged as one of the potential targets for new antitubercular drug development. In this work, three-dimensional quantitative structure-activity relationships (3D-QSAR), molecular docking, and molecular dynamics (MD) simulation approaches were performed on a series of natural and synthetic phenol-based β-CA1 inhibitors. The developed 3D-QSAR model ( r 2  = 0.94, q 2  = 0.86, and pred_r 2  = 0.74) indicated that the steric and electrostatic factors are important parameters to modulate the bioactivity of phenolic compounds. Based on this indication, we designed 72 new phenolic inhibitors, out of which two compounds (D25 and D50) effectively stabilized β-CA1 receptor and, thus, are potential candidates for new generation antitubercular drug discovery program.

Molecular automata assembly: principles and simulation of bacterial membrane construction.

Science.gov (United States)

Lahoz-Beltra, R

1997-01-01

The motivation to understand the basic rules and principles governing molecular self-assembly may be relevant to explain in the context of molecular biology the self-organization and biological functions exhibited within cells. This paper presents a molecular automata model to simulate molecular self-assembly introducing the concept of molecular programming to simulate the biological function or operation performed by an assembled molecular state machine. The method is illustrated modelling Escherichia coli membrane construction including the assembly and operation of ATP synthase as well as the assembly of the bacterial flagellar motor. Flagellar motor operation was simulated using a different approach based on state machine definition used in virtual reality systems. The proposed methodology provides a modelling framework for simulation of biological functions performed by cellular components and other biological systems suitable to be modelled as molecular state machines.

Theoretical model for calculation of molecular stopping power

International Nuclear Information System (INIS)

Xu, Y.J.

1984-01-01

A modified local plasma model based on the work of Linhard-Winther, Bethe, Brown, and Walske is established. The Gordon-Kim's molecular charged density model is employed to obtain a formula to evaluate the stopping power of many useful molecular systems. The stopping power of H 2 and He gas was calculated for incident proton energy ranging from 100 KeV to 2.5 MeV. The stopping power of O 2 , N 2 , and water vapor was also calculated for incident proton energy ranging from 40 keV to 2.5 MeV. Good agreement with experimental data was obtained. A discussion of molecular effects leading to departure from Bragg's rule is presented. The equipartition rule and the effect of nuclear momentum recoiling in stopping power are also discussed in the appendix. The calculation procedure presented hopefully can easily be extended to include the most useful organic systems such as the molecules composed of carbon, nitrogen, hydrogen and oxygen which are useful in radiation protection field

Spherical convolutions and their application in molecular modelling

DEFF Research Database (Denmark)

Boomsma, Wouter; Frellsen, Jes

2017-01-01

Convolutional neural networks are increasingly used outside the domain of image analysis, in particular in various areas of the natural sciences concerned with spatial data. Such networks often work out-of-the box, and in some cases entire model architectures from image analysis can be carried over...... to other problem domains almost unaltered. Unfortunately, this convenience does not trivially extend to data in non-euclidean spaces, such as spherical data. In this paper, we introduce two strategies for conducting convolutions on the sphere, using either a spherical-polar grid or a grid based...... of spherical convolutions in the context of molecular modelling, by considering structural environments within proteins. We show that the models are capable of learning non-trivial functions in these molecular environments, and that our spherical convolutions generally outperform standard 3D convolutions...

Molecular acidity: An accurate description with information-theoretic approach in density functional reactivity theory.

Science.gov (United States)

Cao, Xiaofang; Rong, Chunying; Zhong, Aiguo; Lu, Tian; Liu, Shubin

2018-01-15

Molecular acidity is one of the important physiochemical properties of a molecular system, yet its accurate calculation and prediction are still an unresolved problem in the literature. In this work, we propose to make use of the quantities from the information-theoretic (IT) approach in density functional reactivity theory and provide an accurate description of molecular acidity from a completely new perspective. To illustrate our point, five different categories of acidic series, singly and doubly substituted benzoic acids, singly substituted benzenesulfinic acids, benzeneseleninic acids, phenols, and alkyl carboxylic acids, have been thoroughly examined. We show that using IT quantities such as Shannon entropy, Fisher information, Ghosh-Berkowitz-Parr entropy, information gain, Onicescu information energy, and relative Rényi entropy, one is able to simultaneously predict experimental pKa values of these different categories of compounds. Because of the universality of the quantities employed in this work, which are all density dependent, our approach should be general and be applicable to other systems as well. © 2017 Wiley Periodicals, Inc. © 2017 Wiley Periodicals, Inc.

Molecular dynamics for fermions

International Nuclear Information System (INIS)

Feldmeier, H.; Schnack, J.

2000-02-01

The time-dependent variational principle for many-body trial states is used to discuss the relation between the approaches of different molecular dynamics models to describe indistinguishable fermions. Early attempts to include effects of the Pauli principle by means of nonlocal potentials as well as more recent models which work with antisymmetrized many-body states are reviewed under these premises. (orig.)

Molecular approaches to child psychopathology.

Science.gov (United States)

Alsobrook, J P; Pauls, D L

1998-04-01

Basic research into the genetics of childhood psychiatric disorders has substantially increased during the last two decades. Specific genetic mutations have been characterized in some developmental disorders (e.g., fragile X syndrome and Prader-Willi syndrome), but thus far identification of etiological gene mutations in psychiatric illnesses has been unsuccessful. Several psychiatric disorders serve as examples of the current state of molecular approaches in child psychopathology. Investigations to date of Gilles de la Tourette's syndrome (GTS) have not resulted in the discovery of a gene of major effect. Some studies have implicated the D2 and D4 dopamine receptors as having a direct role in the etiology of GTS, but other studies have disputed those findings. However, the dopamine D2 receptor may modulate the severity of GTS. Obsessive-compulsive disorder has a reported association with a low-activity allele of the enzyme catechol-O-methyltransferase; however, the low-activity genotype is also seen in a significant proportion of unaffected individuals. For reading disability two distinct phenotypes (phonological awareness and single-word reading) have been linked to separate loci on chromosomes 6 and 15. Attention deficit hyperactivity disorder (ADHD) has a reported association with the dopamine transporter. Findings of a genetic locus for the personality trait of novelty seeking remain controversial.

Reliable Approximation of Long Relaxation Timescales in Molecular Dynamics

Directory of Open Access Journals (Sweden)

Wei Zhang

2017-07-01

Full Text Available Many interesting rare events in molecular systems, like ligand association, protein folding or conformational changes, occur on timescales that often are not accessible by direct numerical simulation. Therefore, rare event approximation approaches like interface sampling, Markov state model building, or advanced reaction coordinate-based free energy estimation have attracted huge attention recently. In this article we analyze the reliability of such approaches. How precise is an estimate of long relaxation timescales of molecular systems resulting from various forms of rare event approximation methods? Our results give a theoretical answer to this question by relating it with the transfer operator approach to molecular dynamics. By doing so we also allow for understanding deep connections between the different approaches.

Multi-Targeted Molecular Effects of Hibiscus sabdariffa Polyphenols: An Opportunity for a Global Approach to Obesity.

Science.gov (United States)

Herranz-López, María; Olivares-Vicente, Mariló; Encinar, José Antonio; Barrajón-Catalán, Enrique; Segura-Carretero, Antonio; Joven, Jorge; Micol, Vicente

2017-08-20

Improper diet can alter gene expression by breaking the energy balance equation and changing metabolic and oxidative stress biomarkers, which can result in the development of obesity-related metabolic disorders. The pleiotropic effects of dietary plant polyphenols are capable of counteracting by modulating different key molecular targets at the cell, as well as through epigenetic modifications. Hibiscus sabdariffa (HS)-derived polyphenols are known to ameliorate various obesity-related conditions. Recent evidence leads to propose the complex nature of the underlying mechanism of action. This multi-targeted mechanism includes the regulation of energy metabolism, oxidative stress and inflammatory pathways, transcription factors, hormones and peptides, digestive enzymes, as well as epigenetic modifications. This article reviews the accumulated evidence on the multiple anti-obesity effects of HS polyphenols in cell and animal models, as well as in humans, and its putative molecular targets. In silico studies reveal the capacity of several HS polyphenols to act as putative ligands for different digestive and metabolic enzymes, which may also deserve further attention. Therefore, a global approach including integrated and networked omics techniques, virtual screening and epigenetic analysis is necessary to fully understand the molecular mechanisms of HS polyphenols and metabolites involved, as well as their possible implications in the design of safe and effective polyphenolic formulations for obesity.

Multi-Targeted Molecular Effects of Hibiscus sabdariffa Polyphenols: An Opportunity for a Global Approach to Obesity

Science.gov (United States)

Herranz-López, María; Olivares-Vicente, Mariló; Barrajón-Catalán, Enrique; Segura-Carretero, Antonio; Joven, Jorge; Micol, Vicente

2017-01-01

Improper diet can alter gene expression by breaking the energy balance equation and changing metabolic and oxidative stress biomarkers, which can result in the development of obesity-related metabolic disorders. The pleiotropic effects of dietary plant polyphenols are capable of counteracting by modulating different key molecular targets at the cell, as well as through epigenetic modifications. Hibiscus sabdariffa (HS)-derived polyphenols are known to ameliorate various obesity-related conditions. Recent evidence leads to propose the complex nature of the underlying mechanism of action. This multi-targeted mechanism includes the regulation of energy metabolism, oxidative stress and inflammatory pathways, transcription factors, hormones and peptides, digestive enzymes, as well as epigenetic modifications. This article reviews the accumulated evidence on the multiple anti-obesity effects of HS polyphenols in cell and animal models, as well as in humans, and its putative molecular targets. In silico studies reveal the capacity of several HS polyphenols to act as putative ligands for different digestive and metabolic enzymes, which may also deserve further attention. Therefore, a global approach including integrated and networked omics techniques, virtual screening and epigenetic analysis is necessary to fully understand the molecular mechanisms of HS polyphenols and metabolites involved, as well as their possible implications in the design of safe and effective polyphenolic formulations for obesity. PMID:28825642

Molecular Dynamics Simulations of Kinetic Models for Chiral Dominance in Soft Condensed Matter

DEFF Research Database (Denmark)

Toxvaerd, Søren

2001-01-01

Molecular dynamics simulation, models for isomerization kinetics, origin of biomolecular chirality......Molecular dynamics simulation, models for isomerization kinetics, origin of biomolecular chirality...

Modeling and simulations for molecular scale hydrodynamics of the moving contact line in immiscible two-phase flows

KAUST Repository

Qian, Tiezheng

2009-10-29

This paper starts with an introduction to the Onsager principle of minimum energy dissipation which governs the optimal paths of deviation and restoration to equilibrium. Then there is a review of the variational approach to moving contact line hydrodynamics. To demonstrate the validity of our continuum hydrodynamic model, numerical results from model calculations and molecular dynamics simulations are presented for immiscible Couette and Poiseuille flows past homogeneous solid surfaces, with remarkable overall agreement. Our continuum model is also used to study the contact line motion on surfaces patterned with stripes of different contact angles (i.e. surfaces of varying wettability). Continuum calculations predict the stick-slip motion for contact lines moving along these patterned surfaces, in quantitative agreement with molecular dynamics simulation results. This periodic motion is tunable through pattern period (geometry) and contrast in wetting property (chemistry). The consequence of stick-slip contact line motion on energy dissipation is discussed. © 2009 IOP Publishing Ltd.

Observational Constraints for Modeling Diffuse Molecular Clouds

Science.gov (United States)

Federman, S. R.

2014-02-01

Ground-based and space-borne observations of diffuse molecular clouds suggest a number of areas where further improvements to modeling efforts is warranted. I will highlight those that have the widest applicability. The range in CO fractionation caused by selective isotope photodissociation, in particular the large 12C16O/13C16O ratios observed toward stars in Ophiuchus, is not reproduced well by current models. Our ongoing laboratory measurements of oscillator strengths and predissociation rates for Rydberg transitions in CO isotopologues may help clarify the situtation. The CH+ abundance continues to draw attention. Small scale structure seen toward ζ Per may provide additional constraints on the possible synthesis routes. The connection between results from optical transitions and those from radio and sub-millimeter wave transitions requires further effort. A study of OH+ and OH toward background stars reveals that these species favor different environments. This brings to focus the need to model each cloud along the line of sight separately, and to allow the physical conditions to vary within an individual cloud, in order to gain further insight into the chemistry. Now that an extensive set of data on molecular excitation is available, the models should seek to reproduce these data to place further constraints on the modeling results.

Variational methods in molecular modeling

CERN Document Server

2017-01-01

This book presents tutorial overviews for many applications of variational methods to molecular modeling. Topics discussed include the Gibbs-Bogoliubov-Feynman variational principle, square-gradient models, classical density functional theories, self-consistent-field theories, phase-field methods, Ginzburg-Landau and Helfrich-type phenomenological models, dynamical density functional theory, and variational Monte Carlo methods. Illustrative examples are given to facilitate understanding of the basic concepts and quantitative prediction of the properties and rich behavior of diverse many-body systems ranging from inhomogeneous fluids, electrolytes and ionic liquids in micropores, colloidal dispersions, liquid crystals, polymer blends, lipid membranes, microemulsions, magnetic materials and high-temperature superconductors. All chapters are written by leading experts in the field and illustrated with tutorial examples for their practical applications to specific subjects. With emphasis placed on physical unders...

Nanotubule and Tour Molecule Based Molecular Electronics: Suggestion for a Hybrid Approach

Science.gov (United States)

Srivastava, Deepak; Saini, Subhash (Technical Monitor)

1998-01-01

Recent experimental and theoretical attempts and results indicate two distinct broad pathways towards future molecular electronic devices and architectures. The first is the approach via Tour type ladder molecules and their junctions which can be fabricated with solution phase chemical approaches. Second are fullerenes or nanotubules and their junctions which may have better conductance, switching and amplifying characteristics but can not be made through well controlled and defined chemical means. A hybrid approach combining the two pathways to take advantage of the characteristics of both is suggested. Dimension and scale of such devices would be somewhere in between isolated molecule and nanotubule based devices but it maybe possible to use self-assembly towards larger functional and logicalunits.

Melting behavior of a model molecular crystalline GeI4

International Nuclear Information System (INIS)

Fuchizaki, Kazuhiro; Asano, Yuta

2015-01-01

A model molecular crystalline GeI 4 was examined using molecular dynamics simulation. The model was constructed in such a way that rigid tetrahedral molecules interact with each other via Lennard-Jones potentials whose centers are located at the vertices of a tetrahedron. Because no other interaction that can “soften” the intermolecular interaction was introduced, the melting curve of the model crystalline material does not exhibit the anomaly that was found for the real substance. However, the current investigation is useful in that it could settle the upper bound of pressure below which the model can predict properties of the molecular liquid. Moreover, singularity-free nature of the melting curve allowed us to analytically treat the melting curve in the light of the Kumari-Dass-Kechin equation. As a result, we could definitely conclude that the well-known Simon equation for the melting curve is merely an approximate expression. The condition for the validity of Simon’s equation was identified. (author)

Quantum Mechanics/Molecular Mechanics Modeling of Drug Metabolism

DEFF Research Database (Denmark)

Lonsdale, Richard; Fort, Rachel M; Rydberg, Patrik

2016-01-01

)-mexiletine in CYP1A2 with hybrid quantum mechanics/molecular mechanics (QM/MM) methods, providing a more detailed and realistic model. Multiple reaction barriers have been calculated at the QM(B3LYP-D)/MM(CHARMM27) level for the direct N-oxidation and H-abstraction/rebound mechanisms. Our calculated barriers......The mechanism of cytochrome P450(CYP)-catalyzed hydroxylation of primary amines is currently unclear and is relevant to drug metabolism; previous small model calculations have suggested two possible mechanisms: direct N-oxidation and H-abstraction/rebound. We have modeled the N-hydroxylation of (R...... indicate that the direct N-oxidation mechanism is preferred and proceeds via the doublet spin state of Compound I. Molecular dynamics simulations indicate that the presence of an ordered water molecule in the active site assists in the binding of mexiletine in the active site...

Continuum multiple-scattering approach to electron-molecule scattering and molecular photoionization

International Nuclear Information System (INIS)

Dehmer, J.L.; Dill, D.

1979-01-01

The multiple-scattering approach to the electronic continuum of molecules is described. The continuum multiple-scattering model (CMSM) was developed as a survey tool and, as such was required to satisfy two requirements. First, it had to have a very broad scope, which means (i) molecules of arbitrary geometry and complexity containing any atom in the periodic system, (ii) continuum electron energies from 0-1000 eV, and (iii) capability to treat a large range of processes involving both photoionization and electron scattering. Second, the structure of the theory was required to lend itself to transparent, physical interpretation of major spectral features such as shape resonances. A comprehensive theoretical framework for the continuum multiple scattering method is presented, as well as its applications to electron-molecule scattering and molecular photoionization. Highlights of recent applications in these two areas are reviewed. The major impact of the resulting studies over the last few years has been to establish the importance of shape resonances in electron collisions and photoionization of practically all (non-hydride) molecules

Diamond-like nanoparticles influence on flavonoids transport: molecular modelling

Science.gov (United States)

Plastun, Inna L.; Agandeeva, Ksenia E.; Bokarev, Andrey N.; Zenkin, Nikita S.

2017-03-01

Intermolecular interaction of diamond-like nanoparticles and flavonoids is investigated by numerical simulation. Using molecular modelling by the density functional theory method, we analyze hydrogen bonds formation and their influence on IR - spectra and structure of molecular complex which is formed due to interaction between flavonoids and nanodiamonds surrounded with carboxylic groups. Enriched adamantane (1,3,5,7 - adamantanetetracarboxylic acid) is used as an example of diamond-like nanoparticles. Intermolecular forces and structure of hydrogen bonds are investigated. IR - spectra and structure parameters of quercetin - adamantanetetracarboxylic acid molecular complex are obtained by numerical simulation using the Gaussian software complex. Received data coincide well with experimental results. Intermolecular interactions and hydrogen bonding structure in the obtained molecular complex are examined. Possibilities of flavonoids interaction with DNA at the molecular level are also considered.

molecular biology approach to the search for novel hiv proteases ...

African Journals Online (AJOL)

... which could be tested in the animal models of HIV infection before subjection to clinical trials. Optimistically, the magic HIV therapeutics may be hidden in such insects and may require the application of molecular biology techniques to unravel. KEY WORDS: Antiretroviral drugs, malaria, proteases, restriction enzymes, ...

A Molecular Theory for Gatekeeper Proteins; FINAL

International Nuclear Information System (INIS)

FRINK, LAURA J. D.; SALINGER, ANDREW G.

1999-01-01

Predicting the behavior of ion channel proteins is important for understanding biological effects of drugs and toxins. These problems involve steady state transport of ions through very small (1-2 atoms wide) pores. FY99 LDRD funding was used to begin investigations of ion channel proteins using a molecular theory approach. Much of our efforts involved establishing the soundness of the approach by direct comparison with grand canonical molecular dynamics simulations of simple model systems. In addition, several dimensional ion channel models have been implemented to demonstrate the viability of the approach, The seed funding provided by this LDRD grant resulted in 50K of DOWOBER funds for FY99, an invitation to submit a full length 0(500K) proposal for consideration to DOWOBER, and start a larger LDRD effort in computational biophysics beginning in FY00

Multi-scale modelling of supercapacitors: From molecular simulations to a transmission line model

Science.gov (United States)

Pean, C.; Rotenberg, B.; Simon, P.; Salanne, M.

2016-09-01

We perform molecular dynamics simulations of a typical nanoporous-carbon based supercapacitor. The organic electrolyte consists in 1-ethyl-3-methylimidazolium and hexafluorophosphate ions dissolved in acetonitrile. We simulate systems at equilibrium, for various applied voltages. This allows us to determine the relevant thermodynamic (capacitance) and transport (in-pore resistivities) properties. These quantities are then injected in a transmission line model for testing its ability to predict the charging properties of the device. The results from this macroscopic model are in good agreement with non-equilibrium molecular dynamics simulations, which validates its use for interpreting electrochemical impedance experiments.

Rapid Molecular Identification of Human Taeniid Cestodes by Pyrosequencing Approach

Science.gov (United States)

Thanchomnang, Tongjit; Tantrawatpan, Chairat; Intapan, Pewpan M.; Sanpool, Oranuch; Janwan, Penchom; Lulitanond, Viraphong; Tourtip, Somjintana; Yamasaki, Hiroshi; Maleewong, Wanchai

2014-01-01

Taenia saginata, T. solium, and T. asiatica are causative agents of taeniasis in humans. The difficulty of morphological identification of human taeniids can lead to misdiagnosis or confusion. To overcome this problem, several molecular methods have been developed, but use of these tends to be time-consuming. Here, a rapid and high-throughput pyrosequencing approach was developed for the identification of three human taeniids originating from various countries. Primers targeting the mitochondrial cytochrome c oxidase subunit 1 (cox1) gene of the three Taenia species were designed. Variations in a 26-nucleotide target region were used for identification. The reproducibility and accuracy of the pyrosequencing technology was confirmed by Sanger sequencing. This technique will be a valuable tool to distinguish between sympatric human taeniids that occur in Thailand, Asia and Pacific countries. This method could potentially be used for the molecular identification of the taeniid species that might be associated with suspicious cysts and lesions, or cyst residues in humans or livestock at the slaughterhouse. PMID:24945530

Grid computing in large pharmaceutical molecular modeling.

Science.gov (United States)

Claus, Brian L; Johnson, Stephen R

2008-07-01

Most major pharmaceutical companies have employed grid computing to expand their compute resources with the intention of minimizing additional financial expenditure. Historically, one of the issues restricting widespread utilization of the grid resources in molecular modeling is the limited set of suitable applications amenable to coarse-grained parallelization. Recent advances in grid infrastructure technology coupled with advances in application research and redesign will enable fine-grained parallel problems, such as quantum mechanics and molecular dynamics, which were previously inaccessible to the grid environment. This will enable new science as well as increase resource flexibility to load balance and schedule existing workloads.

Spectroscopic and molecular modeling study on the interaction of ctDNA with 3′-deoxy-3′-azido doxorubicin

International Nuclear Information System (INIS)

Geng, Shaoguang; Cui, Yanrui; Liu, Qingfeng; Cui, Fengling; Zhang, Guisheng; Chi, Yanwei; Peng, Hao

2013-01-01

The method of synthesizing 3′-deoxy-3′-azido doxorubicin (ADOX) directly from doxorubicin has been developed. This study presents the interaction between ADOX and calf thymus deoxyribonucleic acid (ctDNA) by using spectroscopic methods and molecular modeling techniques. Iodide quenching, fluorescence polarization, viscosity and molecular modeling studies of ADOX–ctDNA interactions indicated that ADOX was an intercalator of ctDNA and preferentially bound to C–G rich regions of ctDNA. Simultaneously, spectroscopic results indicated that the quenching mechanism of ADOX–ctDNA was a static quenching. According to thermodynamic parameters, electrostatic force played roles in the interaction of ADOX with ctDNA. -- Highlights: ●An approach to 3′-deoxy-3′-azido doxorubicin (ADOX) from doxorubicin was developed. ●The quenching mechanism of ADOX with ctDNA was a static quenching type. ●The binding mode between ADOX and ctDNA was intercalative binding. ●The results of molecular docking corroborated results of spectra investigations

Role of molecular testing in the multidisciplinary diagnostic approach of ichthyosis.

Science.gov (United States)

Diociaiuti, Andrea; El Hachem, May; Pisaneschi, Elisa; Giancristoforo, Simona; Genovese, Silvia; Sirleto, Pietro; Boldrini, Renata; Angioni, Adriano

2016-01-13

The term ichthyosis describes a generalized disorder of cornification characterized by scaling and/or hyperkeratosis of different skin regions. Mutations in a broad group of genes related to keratinocyte differentiation and epidermal barrier function have been demonstrated to play a causative role in disease development. Ichthyosis may be classified in syndromic or non-syndromic forms based on the occurrence or absence of extracutaneous signs. In this setting, the diagnosis of ichthyosis is an integrated multistep process requiring a multidisciplinary approach in order to formulate the appropriate diagnostic hypothesis and to address the genetic testing. Due to the complex features of the different ichthyoses and the high number of genes involved we have investigated a group of 64 patients, affected by syndromic and non-syndromic diseases, using Next Generation Sequencing as a new tool for the molecular diagnosis. Using this innovative molecular approach we were able to find pathogenic mutations in 53 out of 64 patients resulting in 82.8 % total detection rate. An interesting result from the analysis of the data is the high rate of novel sequence variations found compared to known mutations and the relevant rate of homozygous mutations. The possibility to analyze a large number of genes associated with various diseases allows to study cases with phenotypes not well-determined, giving the opportunity to make new genotype-phenotype correlation. In some cases there were discrepancies between clinical features and histology or electron microscopy and only molecular analysis allowed to definitively resolve the diagnostic dilemma. The genetic diagnosis of ichthyosis leads to a more accurate and effective genetic counseling, allowing correct evaluation of the risk of recurrence, particularly in families with consanguineous background.

Insights into channel dysfunction from modelling and molecular dynamics simulations.

Science.gov (United States)

Musgaard, Maria; Paramo, Teresa; Domicevica, Laura; Andersen, Ole Juul; Biggin, Philip C

2018-04-01

Developments in structural biology mean that the number of different ion channel structures has increased significantly in recent years. Structures of ion channels enable us to rationalize how mutations may lead to channelopathies. However, determining the structures of ion channels is still not trivial, especially as they necessarily exist in many distinct functional states. Therefore, the use of computational modelling can provide complementary information that can refine working hypotheses of both wild type and mutant ion channels. The simplest but still powerful tool is homology modelling. Many structures are available now that can provide suitable templates for many different types of ion channels, allowing a full three-dimensional interpretation of mutational effects. These structural models, and indeed the structures themselves obtained by X-ray crystallography, and more recently cryo-electron microscopy, can be subjected to molecular dynamics simulations, either as a tool to help explore the conformational dynamics in detail or simply as a means to refine the models further. Here we review how these approaches have been used to improve our understanding of how diseases might be linked to specific mutations in ion channel proteins. This article is part of the Special Issue entitled 'Channelopathies.' Copyright © 2017 The Authors. Published by Elsevier Ltd.. All rights reserved.

Molecular genetics and livestock selection. Approaches, opportunities and risks

International Nuclear Information System (INIS)

Williams, J.L.

2005-01-01

Following domestication, livestock were selected both naturally through adaptation to their environments and by man so that they would fulfil a particular use. As selection methods have become more sophisticated, rapid progress has been made in improving those traits that are easily measured. However, selection has also resulted in decreased diversity. In some cases, improved breeds have replaced local breeds, risking the loss of important survival traits. The advent of molecular genetics provides the opportunity to identify the genes that control particular traits by a gene mapping approach. However, as with selection, the early mapping studies focused on traits that are easy to measure. Where molecular genetics can play a valuable role in livestock production is by providing the means to select effectively for traits that are difficult to measure. Identifying the genes underpinning particular traits requires a population in which these traits are segregating. Fortunately, several experimental populations have been created that have allowed a wide range of traits to be studied. Gene mapping work in these populations has shown that the role of particular genes in controlling variation in a given trait can depend on the genetic background. A second finding is that the most favourable alleles for a trait may in fact. be present in animals that perform poorly for the trait. In the long term, knowledge of -the genes controlling particular traits, and the way they interact with the genetic background, will allow introgression between breeds and the assembly of genotypes that are best suited to particular environments, producing animals with the desired characteristics. If used wisely, this approach will maintain genetic diversity while improving performance over a wide range of desired traits. (author)

Towards a system level understanding of non-model organisms sampled from the environment: a network biology approach.

Directory of Open Access Journals (Sweden)

Tim D Williams

2011-08-01

Full Text Available The acquisition and analysis of datasets including multi-level omics and physiology from non-model species, sampled from field populations, is a formidable challenge, which so far has prevented the application of systems biology approaches. If successful, these could contribute enormously to improving our understanding of how populations of living organisms adapt to environmental stressors relating to, for example, pollution and climate. Here we describe the first application of a network inference approach integrating transcriptional, metabolic and phenotypic information representative of wild populations of the European flounder fish, sampled at seven estuarine locations in northern Europe with different degrees and profiles of chemical contaminants. We identified network modules, whose activity was predictive of environmental exposure and represented a link between molecular and morphometric indices. These sub-networks represented both known and candidate novel adverse outcome pathways representative of several aspects of human liver pathophysiology such as liver hyperplasia, fibrosis, and hepatocellular carcinoma. At the molecular level these pathways were linked to TNF alpha, TGF beta, PDGF, AGT and VEGF signalling. More generally, this pioneering study has important implications as it can be applied to model molecular mechanisms of compensatory adaptation to a wide range of scenarios in wild populations.

New approaches to the treatment of orphan genetic disorders: Mitigating molecular pathologies using chemicals

Directory of Open Access Journals (Sweden)

RENATA V. VELHO

2015-08-01

Full Text Available With the advance and popularization of molecular techniques, the identification of genetic mutations that cause diseases has increased dramatically. Thus, the number of laboratories available to investigate a given disorder and the number of subsequent diagnosis have increased over time. Although it is necessary to identify mutations and provide diagnosis, it is also critical to develop specific therapeutic approaches based on this information. This review aims to highlight recent advances in mutation-targeted therapies with chemicals that mitigate mutational pathology at the molecular level, for disorders that, for the most part, have no effective treatment. Currently, there are several strategies being used to correct different types of mutations, including the following: the identification and characterization of translational readthrough compounds; antisense oligonucleotide-mediated splicing redirection; mismatch repair; and exon skipping. These therapies and other approaches are reviewed in this paper.

New approaches to the treatment of orphan genetic disorders: Mitigating molecular pathologies using chemicals.

Science.gov (United States)

Velho, Renata V; Sperb-Ludwig, Fernanda; Schwartz, Ida V D

2015-08-01

With the advance and popularization of molecular techniques, the identification of genetic mutations that cause diseases has increased dramatically. Thus, the number of laboratories available to investigate a given disorder and the number of subsequent diagnosis have increased over time. Although it is necessary to identify mutations and provide diagnosis, it is also critical to develop specific therapeutic approaches based on this information. This review aims to highlight recent advances in mutation-targeted therapies with chemicals that mitigate mutational pathology at the molecular level, for disorders that, for the most part, have no effective treatment. Currently, there are several strategies being used to correct different types of mutations, including the following: the identification and characterization of translational readthrough compounds; antisense oligonucleotide-mediated splicing redirection; mismatch repair; and exon skipping. These therapies and other approaches are reviewed in this paper.

Cohesion between two clay lamellae: From Primitive Model to Full Molecular Simulation

International Nuclear Information System (INIS)

Carrier, Benoit; Vandamme, Matthieu; Pellenq, Roland; Van Damme, Henri

2012-01-01

Document available in extended abstract form only. The objective of this work is to investigate the range of validity of various models to describe accurately the cohesion between two charged clay lamellae. These models, in order of increasing complexity, are the Derjaguin-Landau-Verwey-Overbeek (DLVO) theory, the primitive model, the explicit solvent primitive model and the full molecular model. We aim at providing a clear picture of which physical mechanisms play a significant role for various interlayer spacings, surface charges and cationic charges. The up-scaling of the mechanical properties starting from the lamellar microstructure of a smectite is usually performed within the framework of the DLVO theory. In this case, the interaction between two charged lamellae with cations between them is the sum of the repulsive double layer electrostatic interaction and of the attractive Van der Waals interaction. However, the Primitive Model shows that concentration fluctuations of counter-ions can generate a strongly attractive ionic correlation force. The Primitive Model is a Monte-Carlo simulation of hydrated counter-ions between two infinite charges surfaces and the water is implicitly modeled by scaling all electrostatic interactions by the dielectric permittivity of bulk water. Nevertheless, for very small inter-layer spacings (1 nm), molecular simulations and experiments show that water is organized in a layered structure and does not behave like bulk water. Therefore, we investigate the role of the solvent in the cohesion of clay lamellae. For this purpose, we use a modified version of the original Primitive Model in which the solvent is modeled by point-dipoles: This model is called the Explicit Solvent Primitive Model. We consider four different systems: A Na + -montmorillonite, a Ca 2+ -montmorillonite, a Na + -vermiculite, a Ca 2+ -vermiculite. The vermiculite layers are twice as charged as the montmorillonite layers. We use a full molecular model as a

Multispectroscopic and molecular modeling approach to investigate the interaction of diclofop-methyl enantiomers with human serum albumin

Energy Technology Data Exchange (ETDEWEB)

Zhang, Ping; Liu, Donghui; Li, Zhe; Shen, Zhigang; Wang, Peng [Department of Applied Chemistry, China Agricultural University, Beijing 100193 (China); Zhou, Meng [Business School, University of Bedfordshire, Luton LU1 3JU (United Kingdom); Zhou, Zhiqiang [Department of Applied Chemistry, China Agricultural University, Beijing 100193 (China); Zhu, Wentao, E-mail: wentaozhu@cau.edu.cn [Department of Applied Chemistry, China Agricultural University, Beijing 100193 (China)

2014-11-15

Pesticides and related environmental contaminants have always been threated to human health due to their intrinsic toxicity. In the context of this contribution, the interaction between diclofop-methyl (DM) enantiomers and human serum albumin (HSA) has been characterized by steady state and three-dimensional fluorescence, molecular modeling, circular dichroism (CD) and ultraviolet–visible (UV–vis) spectroscopy. The binding constants significantly showed the binding was enantioselective and HSA had higher affinity for S-DM. The thermodynamic parameters of the binding reaction (ΔG, ΔH and ΔS) clearly signified that hydrophobic effects and H-bonds contribute to the formation of DM-HSA complex. The alterations of protein secondary structure in the presence of DM enantiomers were confirmed by CD spectroscopy, UV–vis and three-dimensional fluorescence spectroscopy. In addition, both fluorescence probe study and molecular modeling simulation evidenced the binding of DM enantiomers to HSA primarily took place in subdomain IIIA (Sudlow's site II). This investigation highlights the binding mechanism, specific binding sites and binding region of DM enantiomers on human serum albumin at the first time. Besides, such task can provide important insight to the interaction of the physiological protein HSA with chiral aryloxyphenoxypropionate herbicides and give support to the human health risk assessment. - Highlights: • The binding of DM enantiomers to HSA was enantioselective. • HSA had higher affinity for S-DM than R-DM. • Hydrophobic effects and hydrogen bonds were involved in the DM-HSA interaction. • The binding of DM enantiomers to HSA primarily took place in Sudlow's site II. • DM enantiomers could alter the second structure of HSA.

Multispectroscopic and molecular modeling approach to investigate the interaction of diclofop-methyl enantiomers with human serum albumin

International Nuclear Information System (INIS)

Zhang, Ping; Liu, Donghui; Li, Zhe; Shen, Zhigang; Wang, Peng; Zhou, Meng; Zhou, Zhiqiang; Zhu, Wentao

2014-01-01

Pesticides and related environmental contaminants have always been threated to human health due to their intrinsic toxicity. In the context of this contribution, the interaction between diclofop-methyl (DM) enantiomers and human serum albumin (HSA) has been characterized by steady state and three-dimensional fluorescence, molecular modeling, circular dichroism (CD) and ultraviolet–visible (UV–vis) spectroscopy. The binding constants significantly showed the binding was enantioselective and HSA had higher affinity for S-DM. The thermodynamic parameters of the binding reaction (ΔG, ΔH and ΔS) clearly signified that hydrophobic effects and H-bonds contribute to the formation of DM-HSA complex. The alterations of protein secondary structure in the presence of DM enantiomers were confirmed by CD spectroscopy, UV–vis and three-dimensional fluorescence spectroscopy. In addition, both fluorescence probe study and molecular modeling simulation evidenced the binding of DM enantiomers to HSA primarily took place in subdomain IIIA (Sudlow's site II). This investigation highlights the binding mechanism, specific binding sites and binding region of DM enantiomers on human serum albumin at the first time. Besides, such task can provide important insight to the interaction of the physiological protein HSA with chiral aryloxyphenoxypropionate herbicides and give support to the human health risk assessment. - Highlights: • The binding of DM enantiomers to HSA was enantioselective. • HSA had higher affinity for S-DM than R-DM. • Hydrophobic effects and hydrogen bonds were involved in the DM-HSA interaction. • The binding of DM enantiomers to HSA primarily took place in Sudlow's site II. • DM enantiomers could alter the second structure of HSA

Three-stage classical molecular dynamics model for simulation of heavy-ion fusion

Directory of Open Access Journals (Sweden)

Godre Subodh S.

2015-01-01

Full Text Available A three-stage Classical Molecular Dynamics (3S-CMD approach for heavy-ion fusion is developed. In this approach the Classical Rigid-Body Dynamics simulation for heavy-ion collision involving light deformed nucleus is initiated on their Rutherford trajectories at very large initial separation. Collision simulation is then followed by relaxation of the rigid-body constrains for one or both the colliding nuclei at distances close to the barrier when the trajectories of all the nucleons are obtained in a Classical Molecular Dynamics approach. This 3S-CMD approach explicitly takes into account not only the long range Coulomb reorientation of the deformed collision partner but also the internal vibrational excitations of one or both the nuclei at distances close to the barrier. The results of the dynamical simulation for 24Mg+208Pb collision show significant modification of the fusion barrier and calculated fusion cross sections due to internal excitations.

Synopsis Session III and IV 'Water and ion mobility, up-scaling and implementation in model approaches'

International Nuclear Information System (INIS)

2013-01-01

The contributions of Session III 'Water and ion mobility' and Session IV 'Up-scaling and implementation in model approaches' were merged for the proceedings volume. The range of scales we are interested in starts at molecular scale (1-3 Angstrom) to crystal scale (3 Angstrom-2 nm) over particle scale with 2-200 nm dimension to the particle/macro-aggregate scale with 0.2-1500 μm. Methods available to study the particle scale concerning pore structure and connectivity which determines water mobility are under dry conditions N 2 adsorption and Hg intrusion, whereas under the hydrated state methods like X-Ray tomography and X-ray and neutron scattering are available. Going down in size molecular modeling, x-ray and neutron diffraction modeling and water adsorption gravimetry are inter alia available. There are resolution limits to the methods presented in session II (e.g. BIB-SEM) on pore characterization as e.g. the clay matrix characterization being only possible under a limited clay induration and pore throats being on the limit of resolution. These pore throats however are very important for as macroscopic phenomena observed. One methodological approach to bridge the gap between the molecular/crystal scale and the particle/macro-aggregate scale (FIB-SEM) is to use complementary techniques as cryo-NMR, N 2 and water ad-/desorption and TEM

Modeling of amorphous SiCxO6/5 by classical molecular dynamics and first principles calculations

Science.gov (United States)

Liao, Ningbo; Zhang, Miao; Zhou, Hongming; Xue, Wei

2017-02-01

Polymer-derived silicon oxycarbide (SiCO) presents excellent performance for high temperature and lithium-ion battery applications. Current experiments have provided some information on nano-structure of SiCO, while it is very challenging for experiments to take further insight into the molecular structure and its relationship with properties of materials. In this work, molecular dynamics (MD) based on empirical potential and first principle calculation were combined to investigate amorphous SiCxO6/5 ceramics. The amorphous structures of SiCO containing silicon-centered mix bond tetrahedrons and free carbon were successfully reproduced. The calculated radial distribution, angular distribution and Young’s modulus were validated by current experimental data, and more details on molecular structure were discussed. The change in the slope of Young’s modulus is related to the glass transition temperature of the material. The proposed modeling approach can be used to predict the properties of SiCO with different compositions.

Quantum Mechanics/Molecular Mechanics Method Combined with Hybrid All-Atom and Coarse-Grained Model: Theory and Application on Redox Potential Calculations.

Science.gov (United States)

Shen, Lin; Yang, Weitao

2016-04-12

We developed a new multiresolution method that spans three levels of resolution with quantum mechanical, atomistic molecular mechanical, and coarse-grained models. The resolution-adapted all-atom and coarse-grained water model, in which an all-atom structural description of the entire system is maintained during the simulations, is combined with the ab initio quantum mechanics and molecular mechanics method. We apply this model to calculate the redox potentials of the aqueous ruthenium and iron complexes by using the fractional number of electrons approach and thermodynamic integration simulations. The redox potentials are recovered in excellent accordance with the experimental data. The speed-up of the hybrid all-atom and coarse-grained water model renders it computationally more attractive. The accuracy depends on the hybrid all-atom and coarse-grained water model used in the combined quantum mechanical and molecular mechanical method. We have used another multiresolution model, in which an atomic-level layer of water molecules around redox center is solvated in supramolecular coarse-grained waters for the redox potential calculations. Compared with the experimental data, this alternative multilayer model leads to less accurate results when used with the coarse-grained polarizable MARTINI water or big multipole water model for the coarse-grained layer.

Molecular basis of glyphosate resistance: Different approaches through protein engineering

Science.gov (United States)

Pollegioni, Loredano; Schonbrunn, Ernst; Siehl, Daniel

2011-01-01

Glyphosate (N-phosphonomethyl-glycine) is the most-used herbicide in the world: glyphosate-based formulations exhibit broad-spectrum herbicidal activity with minimal human and environmental toxicity. The extraordinary success of this simple small molecule is mainly due to the high specificity of glyphosate towards the plant enzyme enolpyruvylshikimate-3-phosphate synthase in the shikimate pathway leading to biosynthesis of aromatic amino acids. Starting in 1996, transgenic glyphosate-resistant plants were introduced thus allowing the application of the herbicide to the crop (post-emergence) to remove emerged weeds without crop damage. This review focuses on the evolution of mechanisms of resistance to glyphosate as obtained through natural diversity, the gene shuffling approach to molecular evolution, and a rational, structure-based approach to protein engineering. In addition, we offer rationale for the means by which the modifications made have had their intended effect. PMID:21668647

Atomistic modeling of metal surfaces under electric fields: direct coupling of electric fields to a molecular dynamics algorithm

CERN Document Server

Djurabekova, Flyura; Pohjonen, Aarne; Nordlund, Kai

2011-01-01

The effect of electric fields on metal surfaces is fairly well studied, resulting in numerous analytical models developed to understand the mechanisms of ionization of surface atoms observed at very high electric fields, as well as the general behavior of a metal surface in this condition. However, the derivation of analytical models does not include explicitly the structural properties of metals, missing the link between the instantaneous effects owing to the applied field and the consequent response observed in the metal surface as a result of an extended application of an electric field. In the present work, we have developed a concurrent electrodynamic–molecular dynamic model for the dynamical simulation of an electric-field effect and subsequent modification of a metal surface in the framework of an atomistic molecular dynamics (MD) approach. The partial charge induced on the surface atoms by the electric field is assessed by applying the classical Gauss law. The electric forces acting on the partially...

Advances in Time Estimation Methods for Molecular Data.

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Kumar, Sudhir; Hedges, S Blair

2016-04-01

Molecular dating has become central to placing a temporal dimension on the tree of life. Methods for estimating divergence times have been developed for over 50 years, beginning with the proposal of molecular clock in 1962. We categorize the chronological development of these methods into four generations based on the timing of their origin. In the first generation approaches (1960s-1980s), a strict molecular clock was assumed to date divergences. In the second generation approaches (1990s), the equality of evolutionary rates between species was first tested and then a strict molecular clock applied to estimate divergence times. The third generation approaches (since ∼2000) account for differences in evolutionary rates across the tree by using a statistical model, obviating the need to assume a clock or to test the equality of evolutionary rates among species. Bayesian methods in the third generation require a specific or uniform prior on the speciation-process and enable the inclusion of uncertainty in clock calibrations. The fourth generation approaches (since 2012) allow rates to vary from branch to branch, but do not need prior selection of a statistical model to describe the rate variation or the specification of speciation model. With high accuracy, comparable to Bayesian approaches, and speeds that are orders of magnitude faster, fourth generation methods are able to produce reliable timetrees of thousands of species using genome scale data. We found that early time estimates from second generation studies are similar to those of third and fourth generation studies, indicating that methodological advances have not fundamentally altered the timetree of life, but rather have facilitated time estimation by enabling the inclusion of more species. Nonetheless, we feel an urgent need for testing the accuracy and precision of third and fourth generation methods, including their robustness to misspecification of priors in the analysis of large phylogenies and data

Models and algorithms for biomolecules and molecular networks

CERN Document Server

DasGupta, Bhaskar

2016-01-01

By providing expositions to modeling principles, theories, computational solutions, and open problems, this reference presents a full scope on relevant biological phenomena, modeling frameworks, technical challenges, and algorithms. * Up-to-date developments of structures of biomolecules, systems biology, advanced models, and algorithms * Sampling techniques for estimating evolutionary rates and generating molecular structures * Accurate computation of probability landscape of stochastic networks, solving discrete chemical master equations * End-of-chapter exercises

Sex determination in Medfly: A molecular approach

International Nuclear Information System (INIS)

Saccone, G.; Pane, A.; Testa, G.; Santoro, M.; De Martino, G.; Di Paola, F.; Polito, L.C.; Louis, C.

2000-01-01

With the aim of developing new strategies of control to limit the damages inflicted on fruit crops by Ceratitis capitata (Wied.) (Medfly), a biotechnological approach is undertaken whereby female viability would be impaired or male viability would be improved following the introduction of specific genes into the genome of C. capitata. Only males will then be mass produced and released in the infested areas after sterilisation (Louis et al. 1987). Such conditional lethal or 'advantageous' genes could be expressed in transgenic flies either female-specifically or male-specifically by using cis regulative sequences obtained from previously isolated endogenous Ceratitis genes (Saccone et al. 1996, 1998). By using molecular strategies based on a subtractive technique, we have recently isolated male-specifically expressed genes in the Medfly. Furthermore, we present the current status of the research on the Ceratitis dsx gene, showing sex-specific alternative splicing as in Drosophila, and on the tra-inaZ strategy to induce in Drosophila flies female-specific conditional lethality

Molecular approaches to Taenia asiatica.

Science.gov (United States)

Jeon, Hyeong-Kyu; Eom, Keeseon S

2013-02-01

Taenia solium, T. saginata, and T. asiatica are taeniid tapeworms that cause taeniasis in humans and cysticercosis in intermediate host animals. Taeniases remain an important public health concerns in the world. Molecular diagnostic methods using PCR assays have been developed for rapid and accurate detection of human infecting taeniid tapeworms, including the use of sequence-specific DNA probes, PCR-RFLP, and multiplex PCR. More recently, DNA diagnosis using PCR based on histopathological specimens such as 10% formalin-fixed paraffin-embedded and stained sections mounted on slides has been applied to cestode infections. The mitochondrial gene sequence is believed to be a very useful molecular marker for not only studying evolutionary relationships among distantly related taxa, but also for investigating the phylo-biogeography of closely related species. The complete sequence of the human Taenia tapeworms mitochondrial genomes were determined, and its organization and structure were compared to other human-tropic Taenia tapeworms for which complete mitochondrial sequence data were available. The multiplex PCR assay with the Ta4978F, Ts5058F, Tso7421F, and Rev7915 primers will be useful for differential diagnosis, molecular characterization, and epidemiological surveys of human Taenia tapeworms.

Molecular Approaches to Taenia asiatica

Science.gov (United States)

Jeon, Hyeong-Kyu

2013-01-01

Taenia solium, T. saginata, and T. asiatica are taeniid tapeworms that cause taeniasis in humans and cysticercosis in intermediate host animals. Taeniases remain an important public health concerns in the world. Molecular diagnostic methods using PCR assays have been developed for rapid and accurate detection of human infecting taeniid tapeworms, including the use of sequence-specific DNA probes, PCR-RFLP, and multiplex PCR. More recently, DNA diagnosis using PCR based on histopathological specimens such as 10% formalin-fixed paraffin-embedded and stained sections mounted on slides has been applied to cestode infections. The mitochondrial gene sequence is believed to be a very useful molecular marker for not only studying evolutionary relationships among distantly related taxa, but also for investigating the phylo-biogeography of closely related species. The complete sequence of the human Taenia tapeworms mitochondrial genomes were determined, and its organization and structure were compared to other human-tropic Taenia tapeworms for which complete mitochondrial sequence data were available. The multiplex PCR assay with the Ta4978F, Ts5058F, Tso7421F, and Rev7915 primers will be useful for differential diagnosis, molecular characterization, and epidemiological surveys of human Taenia tapeworms. PMID:23467738

Bleomycin induces molecular changes directly relevant to idiopathic pulmonary fibrosis: a model for "active" disease.

Science.gov (United States)

Peng, Ruoqi; Sridhar, Sriram; Tyagi, Gaurav; Phillips, Jonathan E; Garrido, Rosario; Harris, Paul; Burns, Lisa; Renteria, Lorena; Woods, John; Chen, Leena; Allard, John; Ravindran, Palanikumar; Bitter, Hans; Liang, Zhenmin; Hogaboam, Cory M; Kitson, Chris; Budd, David C; Fine, Jay S; Bauer, Carla M T; Stevenson, Christopher S

2013-01-01

The preclinical model of bleomycin-induced lung fibrosis, used to investigate mechanisms related to idiopathic pulmonary fibrosis (IPF), has incorrectly predicted efficacy for several candidate compounds suggesting that it may be of limited value. As an attempt to improve the predictive nature of this model, integrative bioinformatic approaches were used to compare molecular alterations in the lungs of bleomycin-treated mice and patients with IPF. Using gene set enrichment analysis we show for the first time that genes differentially expressed during the fibrotic phase of the single challenge bleomycin model were significantly enriched in the expression profiles of IPF patients. The genes that contributed most to the enrichment were largely involved in mitosis, growth factor, and matrix signaling. Interestingly, these same mitotic processes were increased in the expression profiles of fibroblasts isolated from rapidly progressing, but not slowly progressing, IPF patients relative to control subjects. The data also indicated that TGFβ was not the sole mediator responsible for the changes observed in this model since the ALK-5 inhibitor SB525334 effectively attenuated some but not all of the fibrosis associated with this model. Although some would suggest that repetitive bleomycin injuries may more effectively model IPF-like changes, our data do not support this conclusion. Together, these data highlight that a single bleomycin instillation effectively replicates several of the specific pathogenic molecular changes associated with IPF, and may be best used as a model for patients with active disease.

Bleomycin induces molecular changes directly relevant to idiopathic pulmonary fibrosis: a model for "active" disease.

Directory of Open Access Journals (Sweden)

Ruoqi Peng

Full Text Available The preclinical model of bleomycin-induced lung fibrosis, used to investigate mechanisms related to idiopathic pulmonary fibrosis (IPF, has incorrectly predicted efficacy for several candidate compounds suggesting that it may be of limited value. As an attempt to improve the predictive nature of this model, integrative bioinformatic approaches were used to compare molecular alterations in the lungs of bleomycin-treated mice and patients with IPF. Using gene set enrichment analysis we show for the first time that genes differentially expressed during the fibrotic phase of the single challenge bleomycin model were significantly enriched in the expression profiles of IPF patients. The genes that contributed most to the enrichment were largely involved in mitosis, growth factor, and matrix signaling. Interestingly, these same mitotic processes were increased in the expression profiles of fibroblasts isolated from rapidly progressing, but not slowly progressing, IPF patients relative to control subjects. The data also indicated that TGFβ was not the sole mediator responsible for the changes observed in this model since the ALK-5 inhibitor SB525334 effectively attenuated some but not all of the fibrosis associated with this model. Although some would suggest that repetitive bleomycin injuries may more effectively model IPF-like changes, our data do not support this conclusion. Together, these data highlight that a single bleomycin instillation effectively replicates several of the specific pathogenic molecular changes associated with IPF, and may be best used as a model for patients with active disease.

Molecular processes in cellular arsenic metabolism

International Nuclear Information System (INIS)

Thomas, David J.

2007-01-01

Elucidating molecular processes that underlie accumulation, metabolism and binding of iAs and its methylated metabolites provides a basis for understanding the modes of action by which iAs acts as a toxin and a carcinogen. One approach to this problem is to construct a conceptual model that incorporates available information on molecular processes involved in the influx, metabolism, binding and efflux of arsenicals in cells. This conceptual model is initially conceived as a non-quantitative representation of critical molecular processes that can be used as a framework for experimental design and prediction. However, with refinement and incorporation of additional data, the conceptual model can be expressed in mathematical terms and should be useful for quantitative estimates of the kinetic and dynamic behavior of iAs and its methylated metabolites in cells. Development of a quantitative model will be facilitated by the availability of tools and techniques to manipulate molecular processes underlying transport of arsenicals across cell membranes or expression and activity of enzymes involved in methylation of arsenicals. This model of cellular metabolism might be integrated into more complex pharmacokinetic models for systemic metabolism of iAs and its methylated metabolites. It may also be useful in development of biologically based dose-response models describing the toxic and carcinogenic actions of arsenicals

Modern classification of neoplasms: reconciling differences between morphologic and molecular approaches

International Nuclear Information System (INIS)

Berman, Jules

2005-01-01

For over 150 years, pathologists have relied on histomorphology to classify and diagnose neoplasms. Their success has been stunning, permitting the accurate diagnosis of thousands of different types of neoplasms using only a microscope and a trained eye. In the past two decades, cancer genomics has challenged the supremacy of histomorphology by identifying genetic alterations shared by morphologically diverse tumors and by finding genetic features that distinguish subgroups of morphologically homogeneous tumors. The Developmental Lineage Classification and Taxonomy of Neoplasms groups neoplasms by their embryologic origin. The putative value of this classification is based on the expectation that tumors of a common developmental lineage will share common metabolic pathways and common responses to drugs that target these pathways. The purpose of this manuscript is to show that grouping tumors according to their developmental lineage can reconcile certain fundamental discrepancies resulting from morphologic and molecular approaches to neoplasm classification. In this study, six issues in tumor classification are described that exemplify the growing rift between morphologic and molecular approaches to tumor classification: 1) the morphologic separation between epithelial and non-epithelial tumors; 2) the grouping of tumors based on shared cellular functions; 3) the distinction between germ cell tumors and pluripotent tumors of non-germ cell origin; 4) the distinction between tumors that have lost their differentiation and tumors that arise from uncommitted stem cells; 5) the molecular properties shared by morphologically disparate tumors that have a common developmental lineage, and 6) the problem of re-classifying morphologically identical but clinically distinct subsets of tumors. The discussion of these issues in the context of describing different methods of tumor classification is intended to underscore the clinical value of a robust tumor classification. A

A Comparative Study of Successful Central Nervous System Drugs Using Molecular Modeling

Science.gov (United States)

Kim, Hyosub; Sulaimon, Segun; Menezes, Sandra; Son, Anne; Menezes, Warren J. C.

2011-01-01

Molecular modeling is a powerful tool used for three-dimensional visualization and for exploring electrostatic forces involved in drug transport. This tool enhances student understanding of structure-property relationships, as well as actively engaging them in class. Molecular modeling of several central nervous system (CNS) drugs is used to…

Applications of Molecular and Materials Modeling

Science.gov (United States)

2002-01-01

Chimica Industriale Molecular modeling of solvation Prof. Jacopo Tomasi http://www.dcci.unipi.it/attivita /attivita.html; http://www.dcci.unipi.it...solutions/ cases/notes/scale.html BNFL Sorption of gases in zeolites Dr. Scott L. Owens http://www.bnfl.co.uk/ BAE (British Aerospace Engineering) Rare...permeation of gases ; adhesion and interfacial interactions of siloxane networks; chemical reactivity and catalysis; environmental and cosmetics

Development and application of a 2-electron reduced density matrix approach to electron transport via molecular junctions

Science.gov (United States)

Hoy, Erik P.; Mazziotti, David A.; Seideman, Tamar

2017-11-01

Can an electronic device be constructed using only a single molecule? Since this question was first asked by Aviram and Ratner in the 1970s [Chem. Phys. Lett. 29, 277 (1974)], the field of molecular electronics has exploded with significant experimental advancements in the understanding of the charge transport properties of single molecule devices. Efforts to explain the results of these experiments and identify promising new candidate molecules for molecular devices have led to the development of numerous new theoretical methods including the current standard theoretical approach for studying single molecule charge transport, i.e., the non-equilibrium Green's function formalism (NEGF). By pairing this formalism with density functional theory (DFT), a wide variety of transport problems in molecular junctions have been successfully treated. For some systems though, the conductance and current-voltage curves predicted by common DFT functionals can be several orders of magnitude above experimental results. In addition, since density functional theory relies on approximations to the exact exchange-correlation functional, the predicted transport properties can show significant variation depending on the functional chosen. As a first step to addressing this issue, the authors have replaced density functional theory in the NEGF formalism with a 2-electron reduced density matrix (2-RDM) method, creating a new approach known as the NEGF-RDM method. 2-RDM methods provide a more accurate description of electron correlation compared to density functional theory, and they have lower computational scaling compared to wavefunction based methods of similar accuracy. Additionally, 2-RDM methods are capable of capturing static electron correlation which is untreatable by existing NEGF-DFT methods. When studying dithiol alkane chains and dithiol benzene in model junctions, the authors found that the NEGF-RDM predicts conductances and currents that are 1-2 orders of magnitude below

A simplified tether model for molecular motor transporting cargo

International Nuclear Information System (INIS)

Fang-Zhen, Li; Li-Chun, Jiang

2010-01-01

Molecular motors are proteins or protein complexes which function as transporting engines in biological cells. This paper models the tether between motor and its cargo as a symmetric linear potential. Different from Elston and Peskin's work for which performance of the system was discussed only in some limiting cases, this study produces analytic solutions of the problem for general cases by simplifying the transport system into two physical states, which makes it possible to discuss the dynamics of the motor–cargo system in detail. It turns out that the tether strength between motor and cargo should be greater than a threshold or the motor will fail to transport the cargo, which was not discussed by former researchers yet. Value of the threshold depends on the diffusion coefficients of cargo and motor and also on the strength of the Brownian ratchets dragging the system. The threshold approaches a finite constant when the strength of the ratchet tends to infinity. (general)

Modeling drug- and chemical- induced hepatotoxicity with systems biology approaches

Directory of Open Access Journals (Sweden)

Sudin eBhattacharya

2012-12-01

Full Text Available We provide an overview of computational systems biology approaches as applied to the study of chemical- and drug-induced toxicity. The concept of ‘toxicity pathways’ is described in the context of the 2007 US National Academies of Science report, Toxicity testing in the 21st Century: A Vision and A Strategy. Pathway mapping and modeling based on network biology concepts are a key component of the vision laid out in this report for a more biologically-based analysis of dose-response behavior and the safety of chemicals and drugs. We focus on toxicity of the liver (hepatotoxicity – a complex phenotypic response with contributions from a number of different cell types and biological processes. We describe three case studies of complementary multi-scale computational modeling approaches to understand perturbation of toxicity pathways in the human liver as a result of exposure to environmental contaminants and specific drugs. One approach involves development of a spatial, multicellular virtual tissue model of the liver lobule that combines molecular circuits in individual hepatocytes with cell-cell interactions and blood-mediated transport of toxicants through hepatic sinusoids, to enable quantitative, mechanistic prediction of hepatic dose-response for activation of the AhR toxicity pathway. Simultaneously, methods are being developing to extract quantitative maps of intracellular signaling and transcriptional regulatory networks perturbed by environmental contaminants, using a combination of gene expression and genome-wide protein-DNA interaction data. A predictive physiological model (DILIsymTM to understand drug-induced liver injury (DILI, the most common adverse event leading to termination of clinical development programs and regulatory actions on drugs, is also described. The model initially focuses on reactive metabolite-induced DILI in response to administration of acetaminophen, and spans multiple biological scales.

Molecular modeling used to evaluate CYP2C9-dependent metabolism: homology modeling, molecular dynamics and docking simulations.

Science.gov (United States)

Mendieta-Wejebe, Jessica E; Correa-Basurto, José; García-Segovia, Erika M; Ceballos-Cancino, Gisela; Rosales-Hernández, Martha C

2011-07-01

Cytochrome P450 (CYP) 2C9 is the principal isoform of the CYP2C subfamily in the human liver and is involved in the oxidation of several endogenous and xenobiotic compounds, including many therapeutic drugs. The metabolism of drugs by CYP2C9 can yield either safe or toxic products, which may be related to the recognition and binding modes of the substrates to this isoform. These interactions can be studied using in silico methods such as quantum chemistry, molecular dynamics and docking simulations, which can also be useful for predicting the structure of metabolites. In these types of studies, the ligand and the protein must be tridimensional models; thus, the protein can be built by homology modeling or retrieved from the Protein Data Bank. Therefore, the current review emphasizes the importance of using in silico methods to predict the metabolism of CYP2C9 because these computational tools have allowed the description of the principal characteristics of the active site of this isoform at the molecular level and the chemical properties of its ligands.

Molecular approaches for genetic improvement of seed quality and characterization of genetic diversity in soybean: a critical review.

Science.gov (United States)

Tripathi, Niraj; Khare, Dhirendra

2016-10-01

Soybean is an economically important leguminous crop. Genetic improvements of soybeans have focused on enhancement of seed and oil yield, development of varieties suited to different cropping systems, and breeding resistant/tolerant varieties for various biotic and abiotic stresses. Plant breeders have used conventional breeding techniques for the improvement of these traits in soybean. The conventional breeding process can be greatly accelerated through the application of molecular and genomic approaches. Molecular markers have proved to be a new tool in soybean breeding by enhancing selection efficiency in a rapid and time-bound manner. An overview of molecular approaches for the genetic improvement of soybean seed quality parameters, considering recent applications of marker-assisted selection and 'omics' research, is provided in this article.

XML-based approaches for the integration of heterogeneous bio-molecular data.

Science.gov (United States)

Mesiti, Marco; Jiménez-Ruiz, Ernesto; Sanz, Ismael; Berlanga-Llavori, Rafael; Perlasca, Paolo; Valentini, Giorgio; Manset, David

2009-10-15

The today's public database infrastructure spans a very large collection of heterogeneous biological data, opening new opportunities for molecular biology, bio-medical and bioinformatics research, but raising also new problems for their integration and computational processing. In this paper we survey the most interesting and novel approaches for the representation, integration and management of different kinds of biological data by exploiting XML and the related recommendations and approaches. Moreover, we present new and interesting cutting edge approaches for the appropriate management of heterogeneous biological data represented through XML. XML has succeeded in the integration of heterogeneous biomolecular information, and has established itself as the syntactic glue for biological data sources. Nevertheless, a large variety of XML-based data formats have been proposed, thus resulting in a difficult effective integration of bioinformatics data schemes. The adoption of a few semantic-rich standard formats is urgent to achieve a seamless integration of the current biological resources.

Rapid molecular identification of human taeniid cestodes by pyrosequencing approach.

Directory of Open Access Journals (Sweden)

Tongjit Thanchomnang

Full Text Available Taenia saginata, T. solium, and T. asiatica are causative agents of taeniasis in humans. The difficulty of morphological identification of human taeniids can lead to misdiagnosis or confusion. To overcome this problem, several molecular methods have been developed, but use of these tends to be time-consuming. Here, a rapid and high-throughput pyrosequencing approach was developed for the identification of three human taeniids originating from various countries. Primers targeting the mitochondrial cytochrome c oxidase subunit 1 (cox1 gene of the three Taenia species were designed. Variations in a 26-nucleotide target region were used for identification. The reproducibility and accuracy of the pyrosequencing technology was confirmed by Sanger sequencing. This technique will be a valuable tool to distinguish between sympatric human taeniids that occur in Thailand, Asia and Pacific countries. This method could potentially be used for the molecular identification of the taeniid species that might be associated with suspicious cysts and lesions, or cyst residues in humans or livestock at the slaughterhouse.

Screening of metal-organic frameworks for carbon dioxide capture from flue gas using a combined experimental and modeling approach.

Science.gov (United States)

Yazaydin, A Ozgür; Snurr, Randall Q; Park, Tae-Hong; Koh, Kyoungmoo; Liu, Jian; Levan, M Douglas; Benin, Annabelle I; Jakubczak, Paulina; Lanuza, Mary; Galloway, Douglas B; Low, John J; Willis, Richard R

2009-12-30

A diverse collection of 14 metal-organic frameworks (MOFs) was screened for CO(2) capture from flue gas using a combined experimental and modeling approach. Adsorption measurements are reported for the screened MOFs at room temperature up to 1 bar. These data are used to validate a generalized strategy for molecular modeling of CO(2) and other small molecules in MOFs. MOFs possessing a high density of open metal sites are found to adsorb significant amounts of CO(2) even at low pressure. An excellent correlation is found between the heat of adsorption and the amount of CO(2) adsorbed below 1 bar. Molecular modeling can aid in selection of adsorbents for CO(2) capture from flue gas by screening a large number of MOFs.

Molecular modeling of fentanyl analogs

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LJILJANA DOSEN-MICOVIC

2004-11-01

Full Text Available Fentanyl is a highly potent and clinically widely used narcotic analgesic. A large number of its analogs have been synthesized, some of which (sufentanil and alfentanyl are also in clinical use. Theoretical studies, in recent years, afforded a better understanding of the structure-activity relationships of this class of opiates and allowed insight into the molecular mechanism of the interactions of fentanyl analogs with their receptors. An overview of the current computational techniques for modeling fentanyl analogs, their receptors and ligand-receptor interactions is presented in this paper.

Mitochondrial Molecular Pathophysiology of Nonalcoholic Fatty Liver Disease: A Proteomics Approach

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Natalia Nuño-Lámbarri

2016-03-01

Full Text Available Nonalcoholic fatty liver disease (NAFLD is a chronic liver condition that can progress to nonalcoholic steatohepatitis, cirrhosis and cancer. It is considered an emerging health problem due to malnourishment or a high-fat diet (HFD intake, which is observed worldwide. It is well known that the hepatocytes’ apoptosis phenomenon is one of the most important features of NAFLD. Thus, this review focuses on revealing, through a proteomics approach, the complex network of protein interactions that promote fibrosis, liver cell stress, and apoptosis. According to different types of in vitro and murine models, it has been found that oxidative/nitrative protein stress leads to mitochondrial dysfunction, which plays a major role in stimulating NAFLD damage. Human studies have revealed the importance of novel biomarkers, such as retinol-binding protein 4, lumican, transgelin 2 and hemoglobin, which have a significant role in the disease. The post-genome era has brought proteomics technology, which allows the determination of molecular pathogenesis in NAFLD. This has led to the search for biomarkers which improve early diagnosis and optimal treatment and which may effectively prevent fatal consequences such as cirrhosis or cancer.

Towards refactoring the Molecular Function Ontology with a UML profile for function modeling.

Science.gov (United States)

Burek, Patryk; Loebe, Frank; Herre, Heinrich

2017-10-04

Gene Ontology (GO) is the largest resource for cataloging gene products. This resource grows steadily and, naturally, this growth raises issues regarding the structure of the ontology. Moreover, modeling and refactoring large ontologies such as GO is generally far from being simple, as a whole as well as when focusing on certain aspects or fragments. It seems that human-friendly graphical modeling languages such as the Unified Modeling Language (UML) could be helpful in connection with these tasks. We investigate the use of UML for making the structural organization of the Molecular Function Ontology (MFO), a sub-ontology of GO, more explicit. More precisely, we present a UML dialect, called the Function Modeling Language (FueL), which is suited for capturing functions in an ontologically founded way. FueL is equipped, among other features, with language elements that arise from studying patterns of subsumption between functions. We show how to use this UML dialect for capturing the structure of molecular functions. Furthermore, we propose and discuss some refactoring options concerning fragments of MFO. FueL enables the systematic, graphical representation of functions and their interrelations, including making information explicit that is currently either implicit in MFO or is mainly captured in textual descriptions. Moreover, the considered subsumption patterns lend themselves to the methodical analysis of refactoring options with respect to MFO. On this basis we argue that the approach can increase the comprehensibility of the structure of MFO for humans and can support communication, for example, during revision and further development.

A Splash to Nano-Sized Inorganic Energy-Materials by the Low-Temperature Molecular Precursor Approach.

Science.gov (United States)

Driess, Matthias; Panda, Chakadola; Menezes, Prashanth Wilfried

2018-05-07

The low-temperature synthesis of inorganic materials and their interfaces at the atomic and molecular level provides numerous opportunities for the design and improvement of inorganic materials in heterogeneous catalysis for sustainable chemical energy conversion or other energy-saving areas. Using suitable molecular precursors for functional inorganic nanomaterial synthesis allows for facile control over uniform particle size distribution, stoichiometry, and leads to desired chemical and physical properties. This minireview outlines some advantages of the molecular precursor approach in light of selected recent developments of molecule-to-nanomaterials synthesis for renewable energy applications, relevant for the oxygen evolution reaction (OER), hydrogen evolution reaction (HER) and overall water-splitting. © 2018 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Model-specific selection of molecular targets for heart failure gene therapy

Science.gov (United States)

Katz, Michael G.; Fargnoli, Anthony S.; Tomasulo, Catherine E.; Pritchette, Louella A.; Bridges, Charles R.

2013-01-01

Heart failure (HF) is a complex multifaceted problem of abnormal ventricular function and structure. In recent years, new information has been accumulated allowing for a more detailed understanding of the cellular and molecular alterations that are the underpinnings of diverse causes of HF, including myocardial ischemia, pressure-overload, volume-overload or intrinsic cardiomyopathy. Modern pharmacological approaches to treat HF have had a significant impact on the course of the disease, although they do not reverse the underlying pathological state of the heart. Therefore gene-based therapy holds a great potential as a targeted treatment for cardiovascular diseases. Here, we survey the relative therapeutic efficacy of genetic modulation of β-adrenergic receptor signaling, Ca2+ handling proteins and angiogenesis in the most common extrinsic models of HF. PMID:21954055

A Model of How Different Biology Experts Explain Molecular and Cellular Mechanisms

Science.gov (United States)

Trujillo, Caleb M.; Anderson, Trevor R.; Pelaez, Nancy J.

2015-01-01

Constructing explanations is an essential skill for all science learners. The goal of this project was to model the key components of expert explanation of molecular and cellular mechanisms. As such, we asked: What is an appropriate model of the components of explanation used by biology experts to explain molecular and cellular mechanisms? Do…

Quantitative computational models of molecular self-assembly in systems biology.

Science.gov (United States)

Thomas, Marcus; Schwartz, Russell

2017-05-23

Molecular self-assembly is the dominant form of chemical reaction in living systems, yet efforts at systems biology modeling are only beginning to appreciate the need for and challenges to accurate quantitative modeling of self-assembly. Self-assembly reactions are essential to nearly every important process in cell and molecular biology and handling them is thus a necessary step in building comprehensive models of complex cellular systems. They present exceptional challenges, however, to standard methods for simulating complex systems. While the general systems biology world is just beginning to deal with these challenges, there is an extensive literature dealing with them for more specialized self-assembly modeling. This review will examine the challenges of self-assembly modeling, nascent efforts to deal with these challenges in the systems modeling community, and some of the solutions offered in prior work on self-assembly specifically. The review concludes with some consideration of the likely role of self-assembly in the future of complex biological system models more generally.

Combinatorial computational chemistry approach of tight-binding quantum chemical molecular dynamics method to the design of the automotive catalysts

International Nuclear Information System (INIS)

Ito, Yuki; Jung, Changho; Luo, Yi; Koyama, Michihisa; Endou, Akira; Kubo, Momoji; Imamura, Akira; Miyamoto, Akira

2006-01-01

Recently, we have developed a new tight-binding quantum chemical molecular dynamics program 'Colors' for combinatorial computational chemistry approach. This methodology is based on our original tight-binding approximation and realized over 5000 times acceleration compared to the conventional first-principles molecular dynamics method. In the present study, we applied our new program to the simulations on various realistic large-scale models of the automotive three-way catalysts, ultrafine Pt particle/CeO 2 (111) support. Significant electron transfer from the Pt particle to the CeO 2 (111) surface was observed and it was found to strongly depend on the size of the Pt particle. Furthermore, our simulation results suggest that the reduction of the Ce atom due to the electron transfer from the Pt particle to the CeO 2 surface is a main reason for the strong interaction of the Pt particle and CeO 2 (111) support

A New Approach for Flexible Molecular Docking Based on Swarm Intelligence

Directory of Open Access Journals (Sweden)

Yi Fu

2015-01-01

Full Text Available Molecular docking methods play an important role in the field of computer-aided drug design. In the work, on the basis of the molecular docking program AutoDock, we present QLDock as a tool for flexible molecular docking. For the energy evaluation, the algorithm uses the binding free energy function that is provided by the AutoDock 4.2 tool. The new search algorithm combines the features of a quantum-behaved particle swarm optimization (QPSO algorithm and local search method of Solis and Wets for solving the highly flexible protein-ligand docking problem. We compute the interaction of 23 protein-ligand complexes and compare the results with those of the QDock and AutoDock programs. The experimental results show that our approach leads to substantially lower docking energy and higher docking precision in comparison to Lamarckian genetic algorithm and QPSO algorithm alone. QPSO-ls algorithm was able to identify the correct binding mode of 74% of the complexes. In comparison, the accuracy of QPSO and LGA is 52% and 61%, respectively. This difference in performance rises with increasing complexity of the ligand. Thus, the novel algorithm QPSO-ls may be used to dock ligand with many rotatable bonds with high accuracy.

Molecular approaches to improvement of Jatropha curcas Linn. as a sustainable energy crop.

Science.gov (United States)

Sudhakar Johnson, T; Eswaran, Nalini; Sujatha, M

2011-09-01

With the increase in crude oil prices, climate change concerns and limited reserves of fossil fuel, attention has been diverted to alternate renewable energy sources such as biofuel and biomass. Among the potential biofuel crops, Jatropha curcas L, a non-domesticated shrub, has been gaining importance as the most promising oilseed, as it does not compete with the edible oil supplies. Economic relevance of J. curcas for biodiesel production has promoted world-wide prospecting of its germplasm for crop improvement and breeding. However, lack of adequate genetic variation and non-availability of improved varieties limited its prospects of being a successful energy crop. In this review, we present the progress made in molecular breeding approaches with particular reference to tissue culture and genetic transformation, genetic diversity assessment using molecular markers, large-scale transcriptome and proteome studies, identification of candidate genes for trait improvement, whole genome sequencing and the current interest by various public and private sector companies in commercial-scale cultivation, which highlights the revival of Jatropha as a sustainable energy crop. The information generated from molecular markers, transcriptome profiling and whole genome sequencing could accelerate the genetic upgradation of J. curcas through molecular breeding.

Use of Computational Modeling to Evaluate Hypotheses About the Molecular and Cellular Mechanisms of Bystander Effects

Energy Technology Data Exchange (ETDEWEB)

Zhao, Yuchao; Conolly, Rory B; Andersen, Melvin E.

2006-11-21

This report describes the development of a computational systems biology approach to evaluate the hypotheses of molecular and cellular mechanisms of adaptive response to low dose ionizing radiation. Our concept is that computational models of signaling pathways can be developed and linked to biologically based dose response models to evaluate the underlying molecular mechanisms which lead to adaptive response. For development of quantitatively accurate, predictive models, it will be necessary to describe tissues consisting of multiple cell types where the different types each contribute in their own way to the overall function of the tissue. Such a model will probably need to incorporate not only cell type-specific data but also spatial information on the architecture of the tissue and on intercellular signaling. The scope of the current model was more limited. Data obtained in a number of different biological systems were synthesized to describe a chimeric, “average” population cell. Biochemical signaling pathways involved in sensing of DNA damage and in the activation of cell cycle checkpoint controls and the apoptotic path were also included. As with any computational modeling effort, it was necessary to develop these simplified initial descriptions (models) that can be iteratively refined. This preliminary model is a starting point which, with time, can evolve to a level of refinement where large amounts of detailed biological information are synthesized and a capability for robust predictions of dose- and time-response behaviors is obtained.

Molecular Model of a Quantum Dot Beyond the Constant Interaction Approximation

Science.gov (United States)

Temirov, Ruslan; Green, Matthew F. B.; Friedrich, Niklas; Leinen, Philipp; Esat, Taner; Chmielniak, Pawel; Sarwar, Sidra; Rawson, Jeff; Kögerler, Paul; Wagner, Christian; Rohlfing, Michael; Tautz, F. Stefan

2018-05-01

We present a physically intuitive model of molecular quantum dots beyond the constant interaction approximation. It accurately describes their charging behavior and allows the extraction of important molecular properties that are otherwise experimentally inaccessible. The model is applied to data recorded with a noncontact atomic force microscope on three different molecules that act as a quantum dot when attached to the microscope tip. The results are in excellent agreement with first-principles simulations.

Advanced Pre-clinical Research Approaches and Models to Studying Pediatric Anesthetic Neurotoxicity

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Cheng eWang

2012-10-01

Full Text Available Advances in pediatric and obstetric surgery have resulted in an increase in the duration and complexity of anesthetic procedures. A great deal of concern has recently arisen regarding the safety of anesthesia in infants and children. Because of obvious limitations, it is not possible to thoroughly explore the effects of anesthetic agents on neurons in vivo in human infants or children. However, the availability of some advanced pre-clinical research approaches and models, such as imaging technology both in vitro and in vivo, stem cell and nonhuman primate experimental models, have provided potentially invaluable tools for examining the developmental effects of anesthetic agents. This review discusses the potential application of some sophisticaled research approaches, e.g., calcium imaging, in stem cell-derived in vitro models, especially human embryonic neural stem cells, along with their capacity for proliferation and their potential for differentiation, to dissect relevant mechanisms underlying the etiology of the neurotoxicity associated with developmental exposures to anesthetic agents. Also, this review attempts to discuss several advantages for using the developing rhesus monkey models (in vivo, when combined with dynamic molecular imaging approaches, in addressing critical issues related to the topic of pediatric sedation/anesthesia. These include the relationships between anesthetic-induced neurotoxicity, dose response, time-course and developmental stage at time of exposure (in vivo studies, serving to provide the most expeditious platform toward decreasing the uncertainty in extrapolating pre-clinical data to the human condition.

Molecular Approaches to Understanding Transmission and Source Attribution in Nontyphoidal Salmonella and Their Application in Africa.

Science.gov (United States)

Mather, Alison E; Vaughan, Timothy G; French, Nigel P

2015-11-01

Nontyphoidal Salmonella (NTS) is a frequent cause of diarrhea around the world, yet in many African countries it is more commonly associated with invasive bacterial disease. Various source attribution models have been developed that utilize microbial subtyping data to assign cases of human NTS infection to different animal populations and foods of animal origin. Advances in molecular microbial subtyping approaches, in particular whole-genome sequencing, provide higher resolution data with which to investigate these sources. In this review, we provide updates on the source attribution models developed for Salmonella, and examine the application of whole-genome sequencing data combined with evolutionary modeling to investigate the putative sources and transmission pathways of NTS, with a focus on the epidemiology of NTS in Africa. This is essential information to decide where, what, and how control strategies might be applied most effectively. © The Author 2015. Published by Oxford University Press on behalf of the Infectious Diseases Society of America. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

Application of the AMPLE cluster-and-truncate approach to NMR structures for molecular replacement

Energy Technology Data Exchange (ETDEWEB)

Bibby, Jaclyn [University of Liverpool, Liverpool L69 7ZB (United Kingdom); Keegan, Ronan M. [Research Complex at Harwell, STFC Rutherford Appleton Laboratory, Didcot OX11 0FA (United Kingdom); Mayans, Olga [University of Liverpool, Liverpool L69 7ZB (United Kingdom); Winn, Martyn D. [Science and Technology Facilities Council Daresbury Laboratory, Warrington WA4 4AD (United Kingdom); Rigden, Daniel J., E-mail: drigden@liv.ac.uk [University of Liverpool, Liverpool L69 7ZB (United Kingdom)

2013-11-01

Processing of NMR structures for molecular replacement by AMPLE works well. AMPLE is a program developed for clustering and truncating ab initio protein structure predictions into search models for molecular replacement. Here, it is shown that its core cluster-and-truncate methods also work well for processing NMR ensembles into search models. Rosetta remodelling helps to extend success to NMR structures bearing low sequence identity or high structural divergence from the target protein. Potential future routes to improved performance are considered and practical, general guidelines on using AMPLE are provided.

Theoretical modeling of electronic transport in molecular devices

Science.gov (United States)

Piccinin, Simone

In this thesis a novel approach for simulating electronic transport in nanoscale structures is introduced. We consider an open quantum system (the electrons of structure) accelerated by an external electromotive force and dissipating energy through inelastic scattering with a heat bath (phonons) acting on the electrons. This method can be regarded as a quantum-mechanical extension of the semi-classical Boltzmann transport equation. We use periodic boundary conditions and employ Density Functional Theory to recast the many-particle problem in an effective single-particle mean-field problem. By explicitly treating the dissipation in the electrodes, the behavior of the potential is an outcome of our method, at variance with the scattering approaches based on the Landauer formalism. We study the self-consistent steady-state solution, analyzing the out-of-equilibrium electron distribution, the electrical characteristics, the behavior of the self-consistent potential and the density of states of the system. We apply the method to the study of electronic transport in several molecular devices, consisting of small organic molecules or atomic wires sandwiched between gold surfaces. For gold wires we recover the experimental evidence that transport in short wires is ballistic, independent of the length of the wire and with conductance of one quantum. In benzene-1,4-dithiol we find that the delocalization of the frontier orbitals of the molecule is responsible for the high value of conductance and that, by inserting methylene groups to decouple the sulfur atoms from the carbon ring, the current is reduced, in agreement with the experimental measurements. We study the effect a geometrical distortion in a molecular device, namely the relative rotation of the carbon rings in a biphenyl-4,4'-dithiol molecule. We find that the reduced coupling between pi orbitals of the rings induced by the rotation leads to a reduction of the conductance and that this behavior is captured by a

Prediction of Sliding Friction Coefficient Based on a Novel Hybrid Molecular-Mechanical Model.

Science.gov (United States)

Zhang, Xiaogang; Zhang, Yali; Wang, Jianmei; Sheng, Chenxing; Li, Zhixiong

2018-08-01

Sliding friction is a complex phenomenon which arises from the mechanical and molecular interactions of asperities when examined in a microscale. To reveal and further understand the effects of micro scaled mechanical and molecular components of friction coefficient on overall frictional behavior, a hybrid molecular-mechanical model is developed to investigate the effects of main factors, including different loads and surface roughness values, on the sliding friction coefficient in a boundary lubrication condition. Numerical modelling was conducted using a deterministic contact model and based on the molecular-mechanical theory of friction. In the contact model, with given external loads and surface topographies, the pressure distribution, real contact area, and elastic/plastic deformation of each single asperity contact were calculated. Then asperity friction coefficient was predicted by the sum of mechanical and molecular components of friction coefficient. The mechanical component was mainly determined by the contact width and elastic/plastic deformation, and the molecular component was estimated as a function of the contact area and interfacial shear stress. Numerical results were compared with experimental results and a good agreement was obtained. The model was then used to predict friction coefficients in different operating and surface conditions. Numerical results explain why applied load has a minimum effect on the friction coefficients. They also provide insight into the effect of surface roughness on the mechanical and molecular components of friction coefficients. It is revealed that the mechanical component dominates the friction coefficient when the surface roughness is large (Rq > 0.2 μm), while the friction coefficient is mainly determined by the molecular component when the surface is relatively smooth (Rq < 0.2 μm). Furthermore, optimal roughness values for minimizing the friction coefficient are recommended.

Energetics and efficiency of a molecular motor model

DEFF Research Database (Denmark)

C. Fogedby, Hans; Svane, Axel

2013-01-01

The energetics and efficiency of a linear molecular motor model proposed by Mogilner et al. (Phys. Lett. 237, 297 (1998)) is analyzed from an analytical point of view. The model which is based on protein friction with a track is described by coupled Langevin equations for the motion in combination...... when incorporating the full motor dynamics, owing to the strong dissipation associated with the motor action....

Molecular self-assembly approaches for supramolecular electronic and organic electronic devices

Science.gov (United States)

Yip, Hin-Lap

Molecular self-assembly represents an efficient bottom-up strategy to generate structurally well-defined aggregates of semiconducting pi-conjugated materials. The capability of tuning the chemical structures, intermolecular interactions and nanostructures through molecular engineering and novel materials processing renders it possible to tailor a large number of unprecedented properties such as charge transport, energy transfer and light harvesting. This approach does not only benefit traditional electronic devices based on bulk materials, but also generate a new research area so called "supramolecular electronics" in which electronic devices are built up with individual supramolecular nanostructures with size in the sub-hundred nanometers range. My work combined molecular self-assembly together with several novel materials processing techniques to control the nucleation and growth of organic semiconducting nanostructures from different type of pi-conjugated materials. By tailoring the interactions between the molecules using hydrogen bonds and pi-pi stacking, semiconducting nanoplatelets and nanowires with tunable sizes can be fabricated in solution. These supramolecular nanostructures were further patterned and aligned on solid substrates through printing and chemical templating methods. The capability to control the different hierarchies of organization on surface provides an important platform to study their structural-induced electronic properties. In addition to using molecular self-assembly to create different organic nanostructures, functional self-assembled monolayer (SAM) formed by spontaneous chemisorption on surfaces was used to tune the interfacial property in organic solar cells. Devices showed dramatically improved performance when appropriate SAMs were applied to optimize the contact property for efficiency charge collection.

Probing molecular mechanisms of the Hsp90 chaperone: biophysical modeling identifies key regulators of functional dynamics.

Directory of Open Access Journals (Sweden)

Anshuman Dixit

Full Text Available Deciphering functional mechanisms of the Hsp90 chaperone machinery is an important objective in cancer biology aiming to facilitate discovery of targeted anti-cancer therapies. Despite significant advances in understanding structure and function of molecular chaperones, organizing molecular principles that control the relationship between conformational diversity and functional mechanisms of the Hsp90 activity lack a sufficient quantitative characterization. We combined molecular dynamics simulations, principal component analysis, the energy landscape model and structure-functional analysis of Hsp90 regulatory interactions to systematically investigate functional dynamics of the molecular chaperone. This approach has identified a network of conserved regions common to the Hsp90 chaperones that could play a universal role in coordinating functional dynamics, principal collective motions and allosteric signaling of Hsp90. We have found that these functional motifs may be utilized by the molecular chaperone machinery to act collectively as central regulators of Hsp90 dynamics and activity, including the inter-domain communications, control of ATP hydrolysis, and protein client binding. These findings have provided support to a long-standing assertion that allosteric regulation and catalysis may have emerged via common evolutionary routes. The interaction networks regulating functional motions of Hsp90 may be determined by the inherent structural architecture of the molecular chaperone. At the same time, the thermodynamics-based "conformational selection" of functional states is likely to be activated based on the nature of the binding partner. This mechanistic model of Hsp90 dynamics and function is consistent with the notion that allosteric networks orchestrating cooperative protein motions can be formed by evolutionary conserved and sparsely connected residue clusters. Hence, allosteric signaling through a small network of distantly connected

Modeling ramp compression experiments using large-scale molecular dynamics simulation.

Energy Technology Data Exchange (ETDEWEB)

Mattsson, Thomas Kjell Rene; Desjarlais, Michael Paul; Grest, Gary Stephen; Templeton, Jeremy Alan; Thompson, Aidan Patrick; Jones, Reese E.; Zimmerman, Jonathan A.; Baskes, Michael I. (University of California, San Diego); Winey, J. Michael (Washington State University); Gupta, Yogendra Mohan (Washington State University); Lane, J. Matthew D.; Ditmire, Todd (University of Texas at Austin); Quevedo, Hernan J. (University of Texas at Austin)

2011-10-01

Molecular dynamics simulation (MD) is an invaluable tool for studying problems sensitive to atomscale physics such as structural transitions, discontinuous interfaces, non-equilibrium dynamics, and elastic-plastic deformation. In order to apply this method to modeling of ramp-compression experiments, several challenges must be overcome: accuracy of interatomic potentials, length- and time-scales, and extraction of continuum quantities. We have completed a 3 year LDRD project with the goal of developing molecular dynamics simulation capabilities for modeling the response of materials to ramp compression. The techniques we have developed fall in to three categories (i) molecular dynamics methods (ii) interatomic potentials (iii) calculation of continuum variables. Highlights include the development of an accurate interatomic potential describing shock-melting of Beryllium, a scaling technique for modeling slow ramp compression experiments using fast ramp MD simulations, and a technique for extracting plastic strain from MD simulations. All of these methods have been implemented in Sandia's LAMMPS MD code, ensuring their widespread availability to dynamic materials research at Sandia and elsewhere.

FROM ATOMISTIC TO SYSTEMATIC COARSE-GRAINED MODELS FOR MOLECULAR SYSTEMS

KAUST Repository

Harmandaris, Vagelis; Kalligiannaki, Evangelia; Katsoulakis, Markos; Plechac, Petr

2017-01-01

The development of systematic (rigorous) coarse-grained mesoscopic models for complex molecular systems is an intense research area. Here we first give an overview of methods for obtaining optimal parametrized coarse-grained models, starting from

Diffusion-controlled interface kinetics-inclusive system-theoretic propagation models for molecular communication systems

Science.gov (United States)

Chude-Okonkwo, Uche A. K.; Malekian, Reza; Maharaj, B. T.

2015-12-01

Inspired by biological systems, molecular communication has been proposed as a new communication paradigm that uses biochemical signals to transfer information from one nano device to another over a short distance. The biochemical nature of the information transfer process implies that for molecular communication purposes, the development of molecular channel models should take into consideration diffusion phenomenon as well as the physical/biochemical kinetic possibilities of the process. The physical and biochemical kinetics arise at the interfaces between the diffusion channel and the transmitter/receiver units. These interfaces are herein termed molecular antennas. In this paper, we present the deterministic propagation model of the molecular communication between an immobilized nanotransmitter and nanoreceiver, where the emission and reception kinetics are taken into consideration. Specifically, we derived closed-form system-theoretic models and expressions for configurations that represent different communication systems based on the type of molecular antennas used. The antennas considered are the nanopores at the transmitter and the surface receptor proteins/enzymes at the receiver. The developed models are simulated to show the influence of parameters such as the receiver radius, surface receptor protein/enzyme concentration, and various reaction rate constants. Results show that the effective receiver surface area and the rate constants are important to the system's output performance. Assuming high rate of catalysis, the analysis of the frequency behavior of the developed propagation channels in the form of transfer functions shows significant difference introduce by the inclusion of the molecular antennas into the diffusion-only model. It is also shown that for t > > 0 and with the information molecules' concentration greater than the Michaelis-Menten kinetic constant of the systems, the inclusion of surface receptors proteins and enzymes in the models

Molecular modeling of protonic acid doping of emeraldine base polyaniline for chemical sensors

NARCIS (Netherlands)

Chen, X.; Yuan, C.A.; Wong, C.K.Y.; Ye, H.; Leung, S.Y.Y.; Zhang, G.

2012-01-01

We proposed a molecular modeling methodology to study the protonic acid doping of emeraldine base polyaniline which can used in gas detection. The commercial forcefield COMPASS was used for the polymer and protonic acid molecules. The molecular model, which is capable of representing the polyaniline

Numerical methodologies for investigation of moderate-velocity flow using a hybrid computational fluid dynamics - molecular dynamics simulation approach

International Nuclear Information System (INIS)

Ko, Soon Heum; Kim, Na Yong; Nikitopoulos, Dimitris E.; Moldovan, Dorel; Jha, Shantenu

2014-01-01

Numerical approaches are presented to minimize the statistical errors inherently present due to finite sampling and the presence of thermal fluctuations in the molecular region of a hybrid computational fluid dynamics (CFD) - molecular dynamics (MD) flow solution. Near the fluid-solid interface the hybrid CFD-MD simulation approach provides a more accurate solution, especially in the presence of significant molecular-level phenomena, than the traditional continuum-based simulation techniques. It also involves less computational cost than the pure particle-based MD. Despite these advantages the hybrid CFD-MD methodology has been applied mostly in flow studies at high velocities, mainly because of the higher statistical errors associated with low velocities. As an alternative to the costly increase of the size of the MD region to decrease statistical errors, we investigate a few numerical approaches that reduce sampling noise of the solution at moderate-velocities. These methods are based on sampling of multiple simulation replicas and linear regression of multiple spatial/temporal samples. We discuss the advantages and disadvantages of each technique in the perspective of solution accuracy and computational cost.

Genome to Phenome: A Systems Biology Approach to PTSD Using an Animal Model.

Science.gov (United States)

Chakraborty, Nabarun; Meyerhoff, James; Jett, Marti; Hammamieh, Rasha

2017-01-01

Post-traumatic stress disorder (PTSD) is a debilitating illness that imposes significant emotional and financial burdens on military families. The understanding of PTSD etiology remains elusive; nonetheless, it is clear that PTSD is manifested by a cluster of symptoms including hyperarousal, reexperiencing of traumatic events, and avoidance of trauma reminders. With these characteristics in mind, several rodent models have been developed eliciting PTSD-like features. Animal models with social dimensions are of particular interest, since the social context plays a major role in the development and manifestation of PTSD.For civilians, a core trauma that elicits PTSD might be characterized by a singular life-threatening event such as a car accident. In contrast, among war veterans, PTSD might be triggered by repeated threats and a cumulative psychological burden that coalesced in the combat zone. In capturing this fundamental difference, the aggressor-exposed social stress (Agg-E SS) model imposes highly threatening conspecific trauma on naïve mice repeatedly and randomly.There is abundant evidence that suggests the potential role of genetic contributions to risk factors for PTSD. Specific observations include putatively heritable attributes of the disorder, the cited cases of atypical brain morphology, and the observed neuroendocrine shifts away from normative. Taken together, these features underscore the importance of multi-omics investigations to develop a comprehensive picture. More daunting will be the task of downstream analysis with integration of these heterogeneous genotypic and phenotypic data types to deliver putative clinical biomarkers. Researchers are advocating for a systems biology approach, which has demonstrated an increasingly robust potential for integrating multidisciplinary data. By applying a systems biology approach here, we have connected the tissue-specific molecular perturbations to the behaviors displayed by mice subjected to Agg-E SS. A

Molecular finite-size effects in stochastic models of equilibrium chemical systems.

Science.gov (United States)

Cianci, Claudia; Smith, Stephen; Grima, Ramon

2016-02-28

The reaction-diffusion master equation (RDME) is a standard modelling approach for understanding stochastic and spatial chemical kinetics. An inherent assumption is that molecules are point-like. Here, we introduce the excluded volume reaction-diffusion master equation (vRDME) which takes into account volume exclusion effects on stochastic kinetics due to a finite molecular radius. We obtain an exact closed form solution of the RDME and of the vRDME for a general chemical system in equilibrium conditions. The difference between the two solutions increases with the ratio of molecular diameter to the compartment length scale. We show that an increase in the fraction of excluded space can (i) lead to deviations from the classical inverse square root law for the noise-strength, (ii) flip the skewness of the probability distribution from right to left-skewed, (iii) shift the equilibrium of bimolecular reactions so that more product molecules are formed, and (iv) strongly modulate the Fano factors and coefficients of variation. These volume exclusion effects are found to be particularly pronounced for chemical species not involved in chemical conservation laws. Finally, we show that statistics obtained using the vRDME are in good agreement with those obtained from Brownian dynamics with excluded volume interactions.

Bleomycin Induces Molecular Changes Directly Relevant to Idiopathic Pulmonary Fibrosis: A Model for “Active” Disease

Science.gov (United States)

Tyagi, Gaurav; Phillips, Jonathan E.; Garrido, Rosario; Harris, Paul; Burns, Lisa; Renteria, Lorena; Woods, John; Chen, Leena; Allard, John; Ravindran, Palanikumar; Bitter, Hans; Liang, Zhenmin; Hogaboam, Cory M.; Kitson, Chris; Budd, David C.; Fine, Jay S.; Bauer, Carla MT.; Stevenson, Christopher S.

2013-01-01

The preclinical model of bleomycin-induced lung fibrosis, used to investigate mechanisms related to idiopathic pulmonary fibrosis (IPF), has incorrectly predicted efficacy for several candidate compounds suggesting that it may be of limited value. As an attempt to improve the predictive nature of this model, integrative bioinformatic approaches were used to compare molecular alterations in the lungs of bleomycin-treated mice and patients with IPF. Using gene set enrichment analysis we show for the first time that genes differentially expressed during the fibrotic phase of the single challenge bleomycin model were significantly enriched in the expression profiles of IPF patients. The genes that contributed most to the enrichment were largely involved in mitosis, growth factor, and matrix signaling. Interestingly, these same mitotic processes were increased in the expression profiles of fibroblasts isolated from rapidly progressing, but not slowly progressing, IPF patients relative to control subjects. The data also indicated that TGFβ was not the sole mediator responsible for the changes observed in this model since the ALK-5 inhibitor SB525334 effectively attenuated some but not all of the fibrosis associated with this model. Although some would suggest that repetitive bleomycin injuries may more effectively model IPF-like changes, our data do not support this conclusion. Together, these data highlight that a single bleomycin instillation effectively replicates several of the specific pathogenic molecular changes associated with IPF, and may be best used as a model for patients with active disease. PMID:23565148

Global energy modeling - A biophysical approach

Energy Technology Data Exchange (ETDEWEB)

Dale, Michael

2010-09-15

This paper contrasts the standard economic approach to energy modelling with energy models using a biophysical approach. Neither of these approaches includes changing energy-returns-on-investment (EROI) due to declining resource quality or the capital intensive nature of renewable energy sources. Both of these factors will become increasingly important in the future. An extension to the biophysical approach is outlined which encompasses a dynamic EROI function that explicitly incorporates technological learning. The model is used to explore several scenarios of long-term future energy supply especially concerning the global transition to renewable energy sources in the quest for a sustainable energy system.

Molecular simulation of receptors of physiologically active compounds for purposes of medical chemistry

Science.gov (United States)

Baskin, Igor I.; Palyulin, Vladimir A.; Zefirov, Nikolai S.

2009-06-01

The general strategy of the molecular simulation of biological receptors and their interaction with ligands is considered. The procedures for construction of 3D protein models, molecular docking, evaluation of model quality, determination of the free energy of protein binding with ligands are discussed. The methods of molecular design of new medicaments based on molecular models of biological targets: virtual screening and de novo design, are presented. Examples of the above-listed approaches for the simulation of a number of pharmacologically significant receptors, analysis of receptor-ligand interactions and design of new biologically active organic compounds are given.

Molecular simulation of receptors of physiologically active compounds for purposes of medical chemistry

International Nuclear Information System (INIS)

Baskin, Igor I; Palyulin, Vladimir A; Zefirov, Nikolai S

2009-01-01

The general strategy of the molecular simulation of biological receptors and their interaction with ligands is considered. The procedures for construction of 3D protein models, molecular docking, evaluation of model quality, determination of the free energy of protein binding with ligands are discussed. The methods of molecular design of new medicaments based on molecular models of biological targets: virtual screening and de novo design, are presented. Examples of the above-listed approaches for the simulation of a number of pharmacologically significant receptors, analysis of receptor-ligand interactions and design of new biologically active organic compounds are given.

Molecular simulation of receptors of physiologically active compounds for purposes of medical chemistry

Energy Technology Data Exchange (ETDEWEB)

Baskin, Igor I; Palyulin, Vladimir A; Zefirov, Nikolai S [Department of Chemistry, M.V. Lomonosov Moscow State University, Moscow (Russian Federation)

2009-06-30

The general strategy of the molecular simulation of biological receptors and their interaction with ligands is considered. The procedures for construction of 3D protein models, molecular docking, evaluation of model quality, determination of the free energy of protein binding with ligands are discussed. The methods of molecular design of new medicaments based on molecular models of biological targets: virtual screening and de novo design, are presented. Examples of the above-listed approaches for the simulation of a number of pharmacologically significant receptors, analysis of receptor-ligand interactions and design of new biologically active organic compounds are given.

VHDL-AMS Simulation Framework for Molecular-FET Device-to-Circuit Modeling and Design

Directory of Open Access Journals (Sweden)

Mariagrazia Graziano

2018-01-01

Full Text Available We concentrate on Molecular-FET as a device and present a new modular framework based on VHDL-AMS. We have implemented different Molecular-FET models within the framework. The framework allows comparison between the models in terms of the capability to calculate accurate I-V characteristics. It also provides the option to analyze the impact of Molecular-FET and its implementation in the circuit with the extension of its use in an architecture based on the crossbar configuration. This analysis evidences the effect of choices of technological parameters, the ability of models to capture the impact of physical quantities, and the importance of considering defects at circuit fabrication level. The comparison tackles the computational efforts of different models and techniques and discusses the trade-off between accuracy and performance as a function of the circuit analysis final requirements. We prove this methodology using three different models and test them on a 16-bit tree adder included in Pentium 4 that, to the best of our knowledge, is the biggest circuits based on molecular device ever designed and analyzed.

Molecular weight kinetics and chain scission models for dextran polymers during ultrasonic degradation.

Science.gov (United States)

Pu, Yuanyuan; Zou, Qingsong; Hou, Dianzhi; Zhang, Yiping; Chen, Shan

2017-01-20

Ultrasonic degradation of six dextran samples with different initial molecular weights (IMW) has been performed to investigate the degradation behavior and chain scission mechanism of dextrans. The weight-average molecular weight (Mw) and polydispersity index (D value) were monitored by High Performance Gel Permeation Chromatography (HPGPC). Results showed that Mw and D value decreased with increasing ultrasonic time, resulting in a more homologous dextran solution with lower molecular weight. A significant degradation occurred in dextrans with higher IMW, particularly at the initial stage of the ultrasonic treatment. The Malhotra model was found to well describe the molecular weight kinetics for all dextran samples. Experimental data was fitted into two chain scission models to study dextran chain scission mechanism and the model performance was compared. Results indicated that the midpoint scission model agreed well with experimental results, with a linear regression factor of R 2 >0.99. Copyright © 2016 Elsevier Ltd. All rights reserved.

Identification of control targets in Boolean molecular network models via computational algebra.

Science.gov (United States)

Murrugarra, David; Veliz-Cuba, Alan; Aguilar, Boris; Laubenbacher, Reinhard

2016-09-23

Many problems in biomedicine and other areas of the life sciences can be characterized as control problems, with the goal of finding strategies to change a disease or otherwise undesirable state of a biological system into another, more desirable, state through an intervention, such as a drug or other therapeutic treatment. The identification of such strategies is typically based on a mathematical model of the process to be altered through targeted control inputs. This paper focuses on processes at the molecular level that determine the state of an individual cell, involving signaling or gene regulation. The mathematical model type considered is that of Boolean networks. The potential control targets can be represented by a set of nodes and edges that can be manipulated to produce a desired effect on the system. This paper presents a method for the identification of potential intervention targets in Boolean molecular network models using algebraic techniques. The approach exploits an algebraic representation of Boolean networks to encode the control candidates in the network wiring diagram as the solutions of a system of polynomials equations, and then uses computational algebra techniques to find such controllers. The control methods in this paper are validated through the identification of combinatorial interventions in the signaling pathways of previously reported control targets in two well studied systems, a p53-mdm2 network and a blood T cell lymphocyte granular leukemia survival signaling network. Supplementary data is available online and our code in Macaulay2 and Matlab are available via http://www.ms.uky.edu/~dmu228/ControlAlg . This paper presents a novel method for the identification of intervention targets in Boolean network models. The results in this paper show that the proposed methods are useful and efficient for moderately large networks.

Evaluating fossil calibrations for dating phylogenies in light of rates of molecular evolution: a comparison of three approaches.

Science.gov (United States)

Lukoschek, Vimoksalehi; Scott Keogh, J; Avise, John C

2012-01-01

Evolutionary and biogeographic studies increasingly rely on calibrated molecular clocks to date key events. Although there has been significant recent progress in development of the techniques used for molecular dating, many issues remain. In particular, controversies abound over the appropriate use and placement of fossils for calibrating molecular clocks. Several methods have been proposed for evaluating candidate fossils; however, few studies have compared the results obtained by different approaches. Moreover, no previous study has incorporated the effects of nucleotide saturation from different data types in the evaluation of candidate fossils. In order to address these issues, we compared three approaches for evaluating fossil calibrations: the single-fossil cross-validation method of Near, Meylan, and Shaffer (2005. Assessing concordance of fossil calibration points in molecular clock studies: an example using turtles. Am. Nat. 165:137-146), the empirical fossil coverage method of Marshall (2008. A simple method for bracketing absolute divergence times on molecular phylogenies using multiple fossil calibration points. Am. Nat. 171:726-742), and the Bayesian multicalibration method of Sanders and Lee (2007. Evaluating molecular clock calibrations using Bayesian analyses with soft and hard bounds. Biol. Lett. 3:275-279) and explicitly incorporate the effects of data type (nuclear vs. mitochondrial DNA) for identifying the most reliable or congruent fossil calibrations. We used advanced (Caenophidian) snakes as a case study; however, our results are applicable to any taxonomic group with multiple candidate fossils, provided appropriate taxon sampling and sufficient molecular sequence data are available. We found that data type strongly influenced which fossil calibrations were identified as outliers, regardless of which method was used. Despite the use of complex partitioned models of sequence evolution and multiple calibrations throughout the tree, saturation

Molecular concepts of water splitting. Nature's approach

International Nuclear Information System (INIS)

Cox, Nicholas; Lubitz, Wolfgang

2013-01-01

Based on studies of natural systems, much has also been learned concerning the design principles required for biomimetic catalysis of water splitting and hydrogen evolution. In summary, these include use of abundant and inexpensive metals, the effective protection of the active sites in functional environments, repair/replacement of active components in case of damage, and the optimization of reaction rates. Biomimetic chemistry aims to mimic all these features; many labs are working toward this goal by developing new approaches in the design and synthesis of such systems, encompassing not only the catalytic center, but also smart matrices and assembly via self-organization. More stable catalysts that do not require self-repair may be obtained from fully artificial (inorganic) catalytic systems that are totally different from the biological ones and only apply some basic principles learned from nature. Metals other than Mn/Ca, Fe, and Ni could be used (e.g. Co) in new ligand spheres and other matrices. For light harvesting, charge separation/stabilization, and the effective coupling of the oxidizing/reducing equivalents to the redox catalysts, different methods have been proposed - for example, covalently linked molecular donor-acceptor systems, photo-voltaic devices, semiconductor-based systems, and photoactive metal complexes. The aim of all these approaches is to develop catalytic systems that split water with sunlight into hydrogen and oxygen while displaying high efficiency and long-term stability. Such a system - either biological, biomimetic, or bioinspired - has the potential to be used on a large scale to produce 'solar fuels' (e.g. hydrogen or secondary products thereof). (orig.)

Hierarchical modeling of molecular energies using a deep neural network

Science.gov (United States)

Lubbers, Nicholas; Smith, Justin S.; Barros, Kipton

2018-06-01

We introduce the Hierarchically Interacting Particle Neural Network (HIP-NN) to model molecular properties from datasets of quantum calculations. Inspired by a many-body expansion, HIP-NN decomposes properties, such as energy, as a sum over hierarchical terms. These terms are generated from a neural network—a composition of many nonlinear transformations—acting on a representation of the molecule. HIP-NN achieves the state-of-the-art performance on a dataset of 131k ground state organic molecules and predicts energies with 0.26 kcal/mol mean absolute error. With minimal tuning, our model is also competitive on a dataset of molecular dynamics trajectories. In addition to enabling accurate energy predictions, the hierarchical structure of HIP-NN helps to identify regions of model uncertainty.

A polarizable QM/MM approach to the molecular dynamics of amide groups solvated in water

Energy Technology Data Exchange (ETDEWEB)

Schwörer, Magnus; Wichmann, Christoph; Tavan, Paul, E-mail: tavan@physik.uni-muenchen.de [Lehrstuhl für BioMolekulare Optik, Ludwig-Maximilians Universität München, Oettingenstr. 67, 80538 München (Germany)

2016-03-21

The infrared (IR) spectra of polypeptides are dominated by the so-called amide bands. Because they originate from the strongly polar and polarizable amide groups (AGs) making up the backbone, their spectral positions sensitively depend on the local electric fields. Aiming at accurate computations of these IR spectra by molecular dynamics (MD) simulations, which derive atomic forces from a hybrid quantum and molecular mechanics (QM/MM) Hamiltonian, here we consider the effects of solvation in bulk liquid water on the amide bands of the AG model compound N-methyl-acetamide (NMA). As QM approach to NMA we choose grid-based density functional theory (DFT). For the surrounding MM water, we develop, largely based on computations, a polarizable molecular mechanics (PMM) model potential called GP6P, which features six Gaussian electrostatic sources (one induced dipole, five static partial charge distributions) and, therefore, avoids spurious distortions of the DFT electron density in hybrid DFT/PMM simulations. Bulk liquid GP6P is shown to have favorable properties at the thermodynamic conditions of the parameterization and beyond. Lennard-Jones (LJ) parameters of the DFT fragment NMA are optimized by comparing radial distribution functions in the surrounding GP6P liquid with reference data obtained from a “first-principles” DFT-MD simulation. Finally, IR spectra of NMA in GP6P water are calculated from extended DFT/PMM-MD trajectories, in which the NMA is treated by three different DFT functionals (BP, BLYP, B3LYP). Method-specific frequency scaling factors are derived from DFT-MD simulations of isolated NMA. The DFT/PMM-MD simulations with GP6P and with the optimized LJ parameters then excellently predict the effects of aqueous solvation and deuteration observed in the IR spectra of NMA. As a result, the methods required to accurately compute such spectra by DFT/PMM-MD also for larger peptides in aqueous solution are now at hand.

Temperature effects on multiphase reactions of organic molecular markers: A modeling study

Science.gov (United States)

Pratap, Vikram; Chen, Ying; Yao, Guangming; Nakao, Shunsuke

2018-04-01

Various molecular markers are used in source apportionment studies. In early studies, molecular markers were assumed to be inert. However, recent studies suggest that molecular markers can decay rapidly through multiphase reactions, which makes interpretation of marker measurements challenging. This study presents a simplified model to account for the effects of temperature and relative humidity on the lifetime of molecular markers through a shift in gas-particle partitioning as well as a change in viscosity of the condensed phase. As a model case, this study examines the stability of levoglucosan, a key marker species of biomass burning, over a wide temperature range relevant to summertime and wintertime. Despite the importance of wood combustion for space heating in winter, the lifetime of levoglucosan in wintertime is not well understood. The model predicts that in low-temperature conditions, levoglucosan predominantly remains in the particle phase, and therefore its loss due to gas-phase oxidation reactions is significantly reduced. Furthermore, the movement of the levoglucosan from the bulk of the particle to the particle surface is reduced due to low diffusivity in the semi-solid state. The simplified model developed in this study reasonably reproduces upper and lower bounds of the lifetime of levoglucosan investigated in previous studies. The model results show that the levoglucosan depletion after seven days reduces significantly from ∼98% at 25 °C to marker (lifetime > 1 week) even at 60% relative humidity irrespective of the assumed fragility parameter D that controls estimated diffusivity. The model shows that lifetime of an organic molecular marker strongly depends on assumed D especially when a semi-volatile marker is in semi-solid organic aerosol.

The mechanical properties modeling of nano-scale materials by molecular dynamics

NARCIS (Netherlands)

Yuan, C.; Driel, W.D. van; Poelma, R.; Zhang, G.Q.

2012-01-01

We propose a molecular modeling strategy which is capable of mod-eling the mechanical properties on nano-scale low-dielectric (low-k) materials. Such modeling strategy has been also validated by the bulking force of carbon nano tube (CNT). This modeling framework consists of model generation method,

Comparisons of Multilevel Modeling and Structural Equation Modeling Approaches to Actor-Partner Interdependence Model.

Science.gov (United States)

Hong, Sehee; Kim, Soyoung

2018-01-01

There are basically two modeling approaches applicable to analyzing an actor-partner interdependence model: the multilevel modeling (hierarchical linear model) and the structural equation modeling. This article explains how to use these two models in analyzing an actor-partner interdependence model and how these two approaches work differently. As an empirical example, marital conflict data were used to analyze an actor-partner interdependence model. The multilevel modeling and the structural equation modeling produced virtually identical estimates for a basic model. However, the structural equation modeling approach allowed more realistic assumptions on measurement errors and factor loadings, rendering better model fit indices.

A theoretical approach to sputtering due to molecular ion bombardment, 1

International Nuclear Information System (INIS)

Karashima, Shosuke; Ootoshi, Tsukuru; Kamiyama, Masahide; Kim, Pil-Hyon; Namba, Susumu.

1981-01-01

A shock wave model is proposed to explain theoretically the non-linear effects in sputtering phenomena by molecular ion bombardments. In this theory the sputtering processes are separated into two parts; one is due to linear effects and another is due to non-linear effects. The treatment of the linear parts is based on the statistical model by Schwarz and Helms concerning a broad range of atomic collision cascades. The non-linear parts are treated by the model of shock wave due to overlapping cascades, and useful equations to calculate the sputtering yields and the dynamical quantities in the system are derived. (author)

Quantum mechanics/coarse-grained molecular mechanics (QM/CG-MM).

Science.gov (United States)

Sinitskiy, Anton V; Voth, Gregory A

2018-01-07

Numerous molecular systems, including solutions, proteins, and composite materials, can be modeled using mixed-resolution representations, of which the quantum mechanics/molecular mechanics (QM/MM) approach has become the most widely used. However, the QM/MM approach often faces a number of challenges, including the high cost of repetitive QM computations, the slow sampling even for the MM part in those cases where a system under investigation has a complex dynamics, and a difficulty in providing a simple, qualitative interpretation of numerical results in terms of the influence of the molecular environment upon the active QM region. In this paper, we address these issues by combining QM/MM modeling with the methodology of "bottom-up" coarse-graining (CG) to provide the theoretical basis for a systematic quantum-mechanical/coarse-grained molecular mechanics (QM/CG-MM) mixed resolution approach. A derivation of the method is presented based on a combination of statistical mechanics and quantum mechanics, leading to an equation for the effective Hamiltonian of the QM part, a central concept in the QM/CG-MM theory. A detailed analysis of different contributions to the effective Hamiltonian from electrostatic, induction, dispersion, and exchange interactions between the QM part and the surroundings is provided, serving as a foundation for a potential hierarchy of QM/CG-MM methods varying in their accuracy and computational cost. A relationship of the QM/CG-MM methodology to other mixed resolution approaches is also discussed.

Quantum mechanics/coarse-grained molecular mechanics (QM/CG-MM)

Science.gov (United States)

Sinitskiy, Anton V.; Voth, Gregory A.

2018-01-01

Numerous molecular systems, including solutions, proteins, and composite materials, can be modeled using mixed-resolution representations, of which the quantum mechanics/molecular mechanics (QM/MM) approach has become the most widely used. However, the QM/MM approach often faces a number of challenges, including the high cost of repetitive QM computations, the slow sampling even for the MM part in those cases where a system under investigation has a complex dynamics, and a difficulty in providing a simple, qualitative interpretation of numerical results in terms of the influence of the molecular environment upon the active QM region. In this paper, we address these issues by combining QM/MM modeling with the methodology of "bottom-up" coarse-graining (CG) to provide the theoretical basis for a systematic quantum-mechanical/coarse-grained molecular mechanics (QM/CG-MM) mixed resolution approach. A derivation of the method is presented based on a combination of statistical mechanics and quantum mechanics, leading to an equation for the effective Hamiltonian of the QM part, a central concept in the QM/CG-MM theory. A detailed analysis of different contributions to the effective Hamiltonian from electrostatic, induction, dispersion, and exchange interactions between the QM part and the surroundings is provided, serving as a foundation for a potential hierarchy of QM/CG-MM methods varying in their accuracy and computational cost. A relationship of the QM/CG-MM methodology to other mixed resolution approaches is also discussed.

Facilitating Students' Interaction with Real Gas Properties Using a Discovery-Based Approach and Molecular Dynamics Simulations

Science.gov (United States)

Sweet, Chelsea; Akinfenwa, Oyewumi; Foley, Jonathan J., IV

2018-01-01

We present an interactive discovery-based approach to studying the properties of real gases using simple, yet realistic, molecular dynamics software. Use of this approach opens up a variety of opportunities for students to interact with the behaviors and underlying theories of real gases. Students can visualize gas behavior under a variety of…

Parallel computations of molecular dynamics trajectories using the stochastic path approach

Science.gov (United States)

Zaloj, Veaceslav; Elber, Ron

2000-06-01

A novel protocol to parallelize molecular dynamics trajectories is discussed and tested on a cluster of PCs running the NT operating system. The new technique does not propagate the solution in small time steps, but uses instead a global optimization of a functional of the whole trajectory. The new approach is especially attractive for parallel and distributed computing and its advantages (and disadvantages) are presented. Two numerical examples are discussed: (a) A conformational transition in a solvated dipeptide, and (b) The R→T conformational transition in solvated hemoglobin.

A phenomenological approach to modeling chemical dynamics in nonlinear and two-dimensional spectroscopy.

Science.gov (United States)

Ramasesha, Krupa; De Marco, Luigi; Horning, Andrew D; Mandal, Aritra; Tokmakoff, Andrei

2012-04-07

We present an approach for calculating nonlinear spectroscopic observables, which overcomes the approximations inherent to current phenomenological models without requiring the computational cost of performing molecular dynamics simulations. The trajectory mapping method uses the semi-classical approximation to linear and nonlinear response functions, and calculates spectra from trajectories of the system's transition frequencies and transition dipole moments. It rests on identifying dynamical variables important to the problem, treating the dynamics of these variables stochastically, and then generating correlated trajectories of spectroscopic quantities by mapping from the dynamical variables. This approach allows one to describe non-Gaussian dynamics, correlated dynamics between variables of the system, and nonlinear relationships between spectroscopic variables of the system and the bath such as non-Condon effects. We illustrate the approach by applying it to three examples that are often not adequately treated by existing analytical models--the non-Condon effect in the nonlinear infrared spectra of water, non-Gaussian dynamics inherent to strongly hydrogen bonded systems, and chemical exchange processes in barrier crossing reactions. The methods described are generally applicable to nonlinear spectroscopy throughout the optical, infrared and terahertz regions.

A Multi-Model Approach for System Diagnosis

DEFF Research Database (Denmark)

Niemann, Hans Henrik; Poulsen, Niels Kjølstad; Bækgaard, Mikkel Ask Buur

2007-01-01

A multi-model approach for system diagnosis is presented in this paper. The relation with fault diagnosis as well as performance validation is considered. The approach is based on testing a number of pre-described models and find which one is the best. It is based on an active approach......,i.e. an auxiliary input to the system is applied. The multi-model approach is applied on a wind turbine system....

Novel approaches to develop community-built biological network models for potential drug discovery.

Science.gov (United States)

Talikka, Marja; Bukharov, Natalia; Hayes, William S; Hofmann-Apitius, Martin; Alexopoulos, Leonidas; Peitsch, Manuel C; Hoeng, Julia

2017-08-01

Hundreds of thousands of data points are now routinely generated in clinical trials by molecular profiling and NGS technologies. A true translation of this data into knowledge is not possible without analysis and interpretation in a well-defined biology context. Currently, there are many public and commercial pathway tools and network models that can facilitate such analysis. At the same time, insights and knowledge that can be gained is highly dependent on the underlying biological content of these resources. Crowdsourcing can be employed to guarantee the accuracy and transparency of the biological content underlining the tools used to interpret rich molecular data. Areas covered: In this review, the authors describe crowdsourcing in drug discovery. The focal point is the efforts that have successfully used the crowdsourcing approach to verify and augment pathway tools and biological network models. Technologies that enable the building of biological networks with the community are also described. Expert opinion: A crowd of experts can be leveraged for the entire development process of biological network models, from ontologies to the evaluation of their mechanistic completeness. The ultimate goal is to facilitate biomarker discovery and personalized medicine by mechanistically explaining patients' differences with respect to disease prevention, diagnosis, and therapy outcome.

A kinetic model of trp-cage folding from multiple biased molecular dynamics simulations.

Directory of Open Access Journals (Sweden)

Fabrizio Marinelli

2009-08-01

Full Text Available Trp-cage is a designed 20-residue polypeptide that, in spite of its size, shares several features with larger globular proteins.Although the system has been intensively investigated experimentally and theoretically, its folding mechanism is not yet fully understood. Indeed, some experiments suggest a two-state behavior, while others point to the presence of intermediates. In this work we show that the results of a bias-exchange metadynamics simulation can be used for constructing a detailed thermodynamic and kinetic model of the system. The model, although constructed from a biased simulation, has a quality similar to those extracted from the analysis of long unbiased molecular dynamics trajectories. This is demonstrated by a careful benchmark of the approach on a smaller system, the solvated Ace-Ala3-Nme peptide. For theTrp-cage folding, the model predicts that the relaxation time of 3100 ns observed experimentally is due to the presence of a compact molten globule-like conformation. This state has an occupancy of only 3% at 300 K, but acts as a kinetic trap.Instead, non-compact structures relax to the folded state on the sub-microsecond timescale. The model also predicts the presence of a state at Calpha-RMSD of 4.4 A from the NMR structure in which the Trp strongly interacts with Pro12. This state can explain the abnormal temperature dependence of the Pro12-delta3 and Gly11-alpha3 chemical shifts. The structures of the two most stable misfolded intermediates are in agreement with NMR experiments on the unfolded protein. Our work shows that, using biased molecular dynamics trajectories, it is possible to construct a model describing in detail the Trp-cage folding kinetics and thermodynamics in agreement with experimental data.

Cross-link guided molecular modeling with ROSETTA.

Directory of Open Access Journals (Sweden)

Abdullah Kahraman

Full Text Available Chemical cross-links identified by mass spectrometry generate distance restraints that reveal low-resolution structural information on proteins and protein complexes. The technology to reliably generate such data has become mature and robust enough to shift the focus to the question of how these distance restraints can be best integrated into molecular modeling calculations. Here, we introduce three workflows for incorporating distance restraints generated by chemical cross-linking and mass spectrometry into ROSETTA protocols for comparative and de novo modeling and protein-protein docking. We demonstrate that the cross-link validation and visualization software Xwalk facilitates successful cross-link data integration. Besides the protocols we introduce XLdb, a database of chemical cross-links from 14 different publications with 506 intra-protein and 62 inter-protein cross-links, where each cross-link can be mapped on an experimental structure from the Protein Data Bank. Finally, we demonstrate on a protein-protein docking reference data set the impact of virtual cross-links on protein docking calculations and show that an inter-protein cross-link can reduce on average the RMSD of a docking prediction by 5.0 Å. The methods and results presented here provide guidelines for the effective integration of chemical cross-link data in molecular modeling calculations and should advance the structural analysis of particularly large and transient protein complexes via hybrid structural biology methods.

Benchmarking the stochastic time-dependent variational approach for excitation dynamics in molecular aggregates

Energy Technology Data Exchange (ETDEWEB)

Chorošajev, Vladimir [Department of Theoretical Physics, Faculty of Physics, Vilnius University, Sauletekio 9-III, 10222 Vilnius (Lithuania); Gelzinis, Andrius; Valkunas, Leonas [Department of Theoretical Physics, Faculty of Physics, Vilnius University, Sauletekio 9-III, 10222 Vilnius (Lithuania); Department of Molecular Compound Physics, Center for Physical Sciences and Technology, Sauletekio 3, 10222 Vilnius (Lithuania); Abramavicius, Darius, E-mail: darius.abramavicius@ff.vu.lt [Department of Theoretical Physics, Faculty of Physics, Vilnius University, Sauletekio 9-III, 10222 Vilnius (Lithuania)

2016-12-20

Highlights: • The Davydov ansatze can be used for finite temperature simulations with an extension. • The accuracy is high if the system is strongly coupled to the environmental phonons. • The approach can simulate time-resolved fluorescence spectra. - Abstract: Time dependent variational approach is a convenient method to characterize the excitation dynamics in molecular aggregates for different strengths of system-bath interaction a, which does not require any additional perturbative schemes. Until recently, however, this method was only applicable in zero temperature case. It has become possible to extend this method for finite temperatures with the introduction of stochastic time dependent variational approach. Here we present a comparison between this approach and the exact hierarchical equations of motion approach for describing excitation dynamics in a broad range of temperatures. We calculate electronic population evolution, absorption and auxiliary time resolved fluorescence spectra in different regimes and find that the stochastic approach shows excellent agreement with the exact approach when the system-bath coupling is sufficiently large and temperatures are high. The differences between the two methods are larger, when temperatures are lower or the system-bath coupling is small.

Thermodynamic Models from Fluctuation Solution Theory Analysis of Molecular Simulations

DEFF Research Database (Denmark)

Christensen, Steen; Peters, Günther H.j.; Hansen, Flemming Yssing

2007-01-01

Fluctuation solution theory (FST) is employed to analyze results of molecular dynamics (MD) simulations of liquid mixtures. The objective is to generate parameters for macroscopic GE-models, here the modified Margules model. We present a strategy for choosing the number of parameters included...

Moving contact lines: linking molecular dynamics and continuum-scale modelling.

Science.gov (United States)

Smith, Edward R; Theodorakis, Panagiotis E; Craster, Richard V; Matar, Omar K

2018-05-04

Despite decades of research, the modelling of moving contact lines has remained a formidable challenge in fluid dynamics whose resolution will impact numerous industrial, biological, and daily-life applications. On the one hand, molecular dynamics (MD) simulation has the ability to provide unique insight into the microscopic details that determine the dynamic behavior of the contact line, which is not possible with either continuum-scale simulations or experiments. On the other hand, continuum-based models provide the link to the macroscopic description of the system. In this Feature Article, we explore the complex range of physical factors, including the presence of surfactants, which govern the contact line motion through MD simulations. We also discuss links between continuum- and molecular-scale modelling, and highlight the opportunities for future developments in this area.

A stochastic phase-field model determined from molecular dynamics

KAUST Repository

von Schwerin, Erik

2010-03-17

The dynamics of dendritic growth of a crystal in an undercooled melt is determined by macroscopic diffusion-convection of heat and by capillary forces acting on the nanometer scale of the solid-liquid interface width. Its modelling is useful for instance in processing techniques based on casting. The phase-field method is widely used to study evolution of such microstructural phase transformations on a continuum level; it couples the energy equation to a phenomenological Allen-Cahn/Ginzburg-Landau equation modelling the dynamics of an order parameter determining the solid and liquid phases, including also stochastic fluctuations to obtain the qualitatively correct result of dendritic side branching. This work presents a method to determine stochastic phase-field models from atomistic formulations by coarse-graining molecular dynamics. It has three steps: (1) a precise quantitative atomistic definition of the phase-field variable, based on the local potential energy; (2) derivation of its coarse-grained dynamics model, from microscopic Smoluchowski molecular dynamics (that is Brownian or over damped Langevin dynamics); and (3) numerical computation of the coarse-grained model functions. The coarse-grained model approximates Gibbs ensemble averages of the atomistic phase-field, by choosing coarse-grained drift and diffusion functions that minimize the approximation error of observables in this ensemble average. © EDP Sciences, SMAI, 2010.

A stochastic phase-field model determined from molecular dynamics

KAUST Repository

von Schwerin, Erik; Szepessy, Anders

2010-01-01

The dynamics of dendritic growth of a crystal in an undercooled melt is determined by macroscopic diffusion-convection of heat and by capillary forces acting on the nanometer scale of the solid-liquid interface width. Its modelling is useful for instance in processing techniques based on casting. The phase-field method is widely used to study evolution of such microstructural phase transformations on a continuum level; it couples the energy equation to a phenomenological Allen-Cahn/Ginzburg-Landau equation modelling the dynamics of an order parameter determining the solid and liquid phases, including also stochastic fluctuations to obtain the qualitatively correct result of dendritic side branching. This work presents a method to determine stochastic phase-field models from atomistic formulations by coarse-graining molecular dynamics. It has three steps: (1) a precise quantitative atomistic definition of the phase-field variable, based on the local potential energy; (2) derivation of its coarse-grained dynamics model, from microscopic Smoluchowski molecular dynamics (that is Brownian or over damped Langevin dynamics); and (3) numerical computation of the coarse-grained model functions. The coarse-grained model approximates Gibbs ensemble averages of the atomistic phase-field, by choosing coarse-grained drift and diffusion functions that minimize the approximation error of observables in this ensemble average. © EDP Sciences, SMAI, 2010.

Developing a physiologically based approach for modeling plutonium decorporation therapy with DTPA.

Science.gov (United States)

Kastl, Manuel; Giussani, Augusto; Blanchardon, Eric; Breustedt, Bastian; Fritsch, Paul; Hoeschen, Christoph; Lopez, Maria Antonia

2014-11-01

To develop a physiologically based compartmental approach for modeling plutonium decorporation therapy with the chelating agent Diethylenetriaminepentaacetic acid (Ca-DTPA/Zn-DTPA). Model calculations were performed using the software package SAAM II (©The Epsilon Group, Charlottesville, Virginia, USA). The Luciani/Polig compartmental model with age-dependent description of the bone recycling processes was used for the biokinetics of plutonium. The Luciani/Polig model was slightly modified in order to account for the speciation of plutonium in blood and for the different affinities for DTPA of the present chemical species. The introduction of two separate blood compartments, describing low-molecular-weight complexes of plutonium (Pu-LW) and transferrin-bound plutonium (Pu-Tf), respectively, and one additional compartment describing plutonium in the interstitial fluids was performed successfully. The next step of the work is the modeling of the chelation process, coupling the physiologically modified structure with the biokinetic model for DTPA. RESULTS of animal studies performed under controlled conditions will enable to better understand the principles of the involved mechanisms.

Intracellular antibody capture: A molecular biology approach to inhibitors of protein-protein interactions.

Science.gov (United States)

Zhang, Jing; Rabbitts, Terence H

2014-11-01

Many proteins of interest in basic biology, translational research studies and for clinical targeting in diseases reside inside the cell and function by interacting with other macromolecules. Protein complexes control basic processes such as development and cell division but also abnormal cell growth when mutations occur such as found in cancer. Interfering with protein-protein interactions is an important aspiration in both basic and disease biology but small molecule inhibitors have been difficult and expensive to isolate. Recently, we have adapted molecular biology techniques to develop a simple set of protocols for isolation of high affinity antibody fragments (in the form of single VH domains) that function within the reducing environment of higher organism cells and can bind to their target molecules. The method called Intracellular Antibody Capture (IAC) has been used to develop inhibitory anti-RAS and anti-LMO2 single domains that have been used for target validation of these antigens in pre-clinical cancer models and illustrate the efficacy of the IAC approach to generation of drug surrogates. Future use of inhibitory VH antibody fragments as drugs in their own right (we term these macrodrugs to distinguish them from small molecule drugs) requires their delivery to target cells in vivo but they can also be templates for small molecule drug development that emulate the binding sites of the antibody fragments. This article is part of a Special Issue entitled: Recent advances in molecular engineering of antibody. Copyright © 2014 Elsevier B.V. All rights reserved.

Polarization effects in molecular mechanical force fields

Energy Technology Data Exchange (ETDEWEB)

Cieplak, Piotr [Burnham Institute for Medical Research, 10901 North Torrey Pines Road, La Jolla, CA 92120 (United States); Dupradeau, Francois-Yves [UMR CNRS 6219-Faculte de Pharmacie, Universite de Picardie Jules Verne, 1 rue des Louvels, F-80037 Amiens (France); Duan, Yong [Genome Center and Department of Applied Science, University of California, Davis, One Shields Avenue, Davis, CA 95616 (United States); Wang Junmei, E-mail: pcieplak@burnham.or [Department of Pharmacology, University of Texas Southwestern Medical Center, 6001 Forest Park Boulevard, ND9.136, Dallas, TX 75390-9050 (United States)

2009-08-19

The focus here is on incorporating electronic polarization into classical molecular mechanical force fields used for macromolecular simulations. First, we briefly examine currently used molecular mechanical force fields and the current status of intermolecular forces as viewed by quantum mechanical approaches. Next, we demonstrate how some components of quantum mechanical energy are effectively incorporated into classical molecular mechanical force fields. Finally, we assess the modeling methods of one such energy component-polarization energy-and present an overview of polarizable force fields and their current applications. Incorporating polarization effects into current force fields paves the way to developing potentially more accurate, though more complex, parameterizations that can be used for more realistic molecular simulations. (topical review)

Molecular modeling for the design of novel performance chemicals and materials

CERN Document Server

Rai, Beena

2012-01-01

Molecular modeling (MM) tools offer significant benefits in the design of industrial chemical plants and material processing operations. While the role of MM in biological fields is well established, in most cases MM works as an accessory in novel products/materials development rather than a tool for direct innovation. As a result, MM engineers and practitioners are often seized with the question: ""How do I leverage these tools to develop novel materials or chemicals in my industry?"" Molecular Modeling for the Design of Novel Performance Chemicals and Materials answers this important questio

Forcefields based molecular modeling on the mechanical and physical properties of emeraldine base polyaniline

NARCIS (Netherlands)

Chen, X.; Yuan, C.A.; Wong, K.Y.; Zhang, G.Q.

2010-01-01

Molecular dynamics (MD) and molecular mechanical (MM) analysis are carried out to provide reliable and accurate model for emeraldine base polyaniline. This study validate the forcefields and model with the physical and mechanical properties of the polyaniline. The temperature effects on non-bond

A molecular dynamics approach to barrodiffusion

Science.gov (United States)

Cooley, James; Marciante, Mathieu; Murillo, Michael

2016-10-01

Unexpected phenomena in the reaction rates for Inertial Confinement Fusion (ICF) capsules have led to a renewed interest in the thermo-dynamically driven diffusion process for the past 10 years, often described collectively as barodiffusion. In the current context, barodiffusion would manifest as a process that separates ions of differing mass and charge ratios due to pressure and temperature gradients set-up through shock structures in the capsule core. Barrodiffusion includes additional mass transfer terms that account for the irreversible transport of species due to gradients in the system, both thermodynamic and electric e.g, i = - ρD [ ∇c +kp ∇ln(pi) +kT(i) ∇ln(Ti) +kt(e) ∇ln(Te) +eke/Ti ∇ϕ ] . Several groups have attacked this phenomena using continuum scale models and supplemented with kinetic theory to derive coefficients for the different diffusion terms based on assumptions about the collisional processes. In contrast, we have applied a molecular dynamics (MD) simulation to this system to gain a first-principle understanding of the rate kinetics and to assess the accuracy of the differin

Molecular modeling of auxin transport inhibitors

International Nuclear Information System (INIS)

Gardner, G.; Black-Schaefer, C.; Bures, M.G.

1990-01-01

Molecular modeling techniques have been used to study the chemical and steric properties of auxin transport inhibitors. These bind to a specific site on the plant plasma membrane characterized by its affinity for N-1-naphthylphthalamic acid (NPA). A three-dimensional model was derived from critical features of ligands for the NPA receptor, and a suggested binding conformation is proposed. This model, along with three-dimensional structural searching techniques, was then used to search the Abbott corporate database of chemical structures. Of the 467 compounds that satisfied the search criteria, 77 representative molecules were evaluated for their ability to compete for [ 3 H]NPA binding to corn microsomal membranes. Nineteen showed activity that ranged from 16 to 85% of the maximum NPA binding. Four of the most active of these, from chemical classes not included in the original compound set, also inhibited polar auxin transport through corn coleoptile sections

Expression profiling of a genetic animal model of depression reveals novel molecular pathways underlying depressive-like behaviours.

Directory of Open Access Journals (Sweden)

Ekaterini Blaveri

2010-09-01

Full Text Available The Flinders model is a validated genetic rat model of depression that exhibits a number of behavioural, neurochemical and pharmacological features consistent with those observed in human depression.In this study we have used genome-wide microarray expression profiling of the hippocampus and prefrontal/frontal cortex of Flinders Depression Sensitive (FSL and control Flinders Depression Resistant (FRL lines to understand molecular basis for the differences between the two lines. We profiled two independent cohorts of Flinders animals derived from the same colony six months apart, each cohort statistically powered to allow independent as well as combined analysis. Using this approach, we were able to validate using real-time-PCR a core set of gene expression differences that showed statistical significance in each of the temporally distinct cohorts, representing consistently maintained features of the model. Small but statistically significant increases were confirmed for cholinergic (chrm2, chrna7 and serotonergic receptors (Htr1a, Htr2a in FSL rats consistent with known neurochemical changes in the model. Much larger gene changes were validated in a number of novel genes as exemplified by TMEM176A, which showed 35-fold enrichment in the cortex and 30-fold enrichment in hippocampus of FRL animals relative to FSL.These data provide significant insights into the molecular differences underlying the Flinders model, and have potential relevance to broader depression research.

Bio-AIMS Collection of Chemoinformatics Web Tools based on Molecular Graph Information and Artificial Intelligence Models.

Science.gov (United States)

Munteanu, Cristian R; Gonzalez-Diaz, Humberto; Garcia, Rafael; Loza, Mabel; Pazos, Alejandro

2015-01-01

The molecular information encoding into molecular descriptors is the first step into in silico Chemoinformatics methods in Drug Design. The Machine Learning methods are a complex solution to find prediction models for specific biological properties of molecules. These models connect the molecular structure information such as atom connectivity (molecular graphs) or physical-chemical properties of an atom/group of atoms to the molecular activity (Quantitative Structure - Activity Relationship, QSAR). Due to the complexity of the proteins, the prediction of their activity is a complicated task and the interpretation of the models is more difficult. The current review presents a series of 11 prediction models for proteins, implemented as free Web tools on an Artificial Intelligence Model Server in Biosciences, Bio-AIMS (http://bio-aims.udc.es/TargetPred.php). Six tools predict protein activity, two models evaluate drug - protein target interactions and the other three calculate protein - protein interactions. The input information is based on the protein 3D structure for nine models, 1D peptide amino acid sequence for three tools and drug SMILES formulas for two servers. The molecular graph descriptor-based Machine Learning models could be useful tools for in silico screening of new peptides/proteins as future drug targets for specific treatments.

Molecular dynamics for irradiation driven chemistry

DEFF Research Database (Denmark)

Sushko, Gennady B.; Solov'yov, Ilia A.; Solov'yov, Andrey V.

2016-01-01

A new molecular dynamics (MD) approach for computer simulations of irradiation driven chemical transformations of complex molecular systems is suggested. The approach is based on the fact that irradiation induced quantum transformations can often be treated as random, fast and local processes...... that describe the classical MD of complex molecular systems under irradiation. The proposed irradiation driven molecular dynamics (IDMD) methodology is designed for the molecular level description of the irradiation driven chemistry. The IDMD approach is implemented into the MBN Explorer software package...... involving small molecules or molecular fragments. We advocate that the quantum transformations, such as molecular bond breaks, creation and annihilation of dangling bonds, electronic charge redistributions, changes in molecular topologies, etc., could be incorporated locally into the molecular force fields...

Toluene model for molecular dynamics simulations in the ranges 298

NARCIS (Netherlands)

Fioroni, M.; Vogt, D.

2004-01-01

An all-atom model for toluene is presented in the framework of classical molecular dynamics (MD). The model has been parametrized under the GROMOS96 force field to reproduce the physicochemical properties of the neat liquid. Four new atom types have been introduced, distinguishing between carbons

Approaches to USJ Formation Beyond Molecular Implantation

International Nuclear Information System (INIS)

Hatem, C.; Renau, A.; Godet, L.; Kontos, A.; Papasouliotis, G.; England, J.; Arevalo, E.

2008-01-01

As junction depth requirements approach sub 10 nm and the sensitivity to residual implant damage continues to increase, the capability to produce abrupt, shallow profiles while maintaining low residual damage becomes a difficult challenge. Implantation induced amorphization has been widely applied to reduce channeling tails of implanted dopant profiles for integrated circuit manufacturing. This has been required to meet aggressive junction depth targets. The problem, however, is that pre-amorphization creates high defect densities that remain near the former amorphous-crystalline interface post anneal. These end of range (EOR) defects become of greater concern as the industry begins to move towards millisecond anneal technologies. Millisecond anneal, while capable of close to diffusionless activation and abrupt junctions, has caused concern for its inability to fully repair these EOR defects. There has been a recent focus on removing traditional PAI through molecular implantation with limited success. Towards this end we have investigated alternative techniques to reduce EOR damage while maintaining the junction depth, sheet resistance and abruptness. Here we describe the results of two of these techniques. The subsequent reduction in EOR through the use of each process and the resultant Rs, junction depth and abruptness are detailed.

A multi-state coarse grained modeling approach for an intrinsically disordered peptide

Science.gov (United States)

Ramezanghorbani, Farhad; Dalgicdir, Cahit; Sayar, Mehmet

2017-09-01

Many proteins display a marginally stable tertiary structure, which can be altered via external stimuli. Since a majority of coarse grained (CG) models are aimed at structure prediction, their success for an intrinsically disordered peptide's conformational space with marginal stability and sensitivity to external stimuli cannot be taken for granted. In this study, by using the LKα 14 peptide as a test system, we demonstrate a bottom-up approach for constructing a multi-state CG model, which can capture the conformational behavior of this peptide in three distinct environments with a unique set of interaction parameters. LKα 14 is disordered in dilute solutions; however, it strictly adopts the α -helix conformation upon aggregation or when in contact with a hydrophobic/hydrophilic interface. Our bottom-up approach combines a generic base model, that is unbiased for any particular secondary structure, with nonbonded interactions which represent hydrogen bonds, electrostatics, and hydrophobic forces. We demonstrate that by using carefully designed all atom potential of mean force calculations from all three states of interest, one can get a balanced representation of the nonbonded interactions. Our CG model behaves intrinsically disordered in bulk water, folds into an α -helix in the presence of an interface or a neighboring peptide, and is stable as a tetrameric unit, successfully reproducing the all atom molecular dynamics simulations and experimental results.

Quantum mechanics/molecular mechanics modeling of photoelectron spectra: the carbon 1s core-electron binding energies of ethanol-water solutions.

Science.gov (United States)

Löytynoja, T; Niskanen, J; Jänkälä, K; Vahtras, O; Rinkevicius, Z; Ågren, H

2014-11-20

Using ethanol-water solutions as illustration, we demonstrate the capability of the hybrid quantum mechanics/molecular mechanics (QM/MM) paradigm to simulate core photoelectron spectroscopy: the binding energies and the chemical shifts. An integrated approach with QM/MM binding energy calculations coupled to preceding molecular dynamics sampling is adopted to generate binding energies averaged over the solute-solvent configurations available at a particular temperature and pressure and thus allowing for a statistical assessment with confidence levels for the final binding energies. The results are analyzed in terms of the contributions in the molecular mechanics model-electrostatic, polarization, and van der Waals-with atom or bond granulation of the corresponding MM charge and polarizability force-fields. The role of extramolecular charge transfer screening of the core-hole and explicit hydrogen bonding is studied by extending the QM core to cover the first solvation shell. The results are compared to those obtained from pure electrostatic and polarizable continuum models. Particularly, the dependence of the carbon 1s binding energies with respect to the ethanol concentration is studied. Our results indicate that QM/MM can be used as an all-encompassing model to study photoelectron binding energies and chemical shifts in solvent environments.

Application and evaluation of a molecular approach for detection of the schistosomicidal effect of Mirazid® (myrrh in the murine model

Directory of Open Access Journals (Sweden)

Wael M. Lotfy

2013-11-01

Full Text Available The conventional PCR technique was used for studying the schistosomicidal effect of Mirazid® in the murine model. Results of the molecular study were compared with the parasitological results (ova and worm count. The used PCR technique was more sensitive than the Kato-Katz thick smears. Mirazid® showed some schistosomicidal effects against murine Schistosoma mansoni. However, it was not efficient enough to cure any of the studied mice.

A new approach to calculate charge carrier transport mobility in organic molecular crystals from imaginary time path integral simulations

International Nuclear Information System (INIS)

Song, Linze; Shi, Qiang

2015-01-01

We present a new non-perturbative method to calculate the charge carrier mobility using the imaginary time path integral approach, which is based on the Kubo formula for the conductivity, and a saddle point approximation to perform the analytic continuation. The new method is first tested using a benchmark calculation from the numerical exact hierarchical equations of motion method. Imaginary time path integral Monte Carlo simulations are then performed to explore the temperature dependence of charge carrier delocalization and mobility in organic molecular crystals (OMCs) within the Holstein and Holstein-Peierls models. The effects of nonlocal electron-phonon interaction on mobility in different charge transport regimes are also investigated

Panel 4: Recent Advances in Otitis Media in Molecular Biology, Biochemistry, Genetics, and Animal Models

Science.gov (United States)

Li, Jian-Dong; Hermansson, Ann; Ryan, Allen F.; Bakaletz, Lauren O.; Brown, Steve D.; Cheeseman, Michael T.; Juhn, Steven K.; Jung, Timothy T. K.; Lim, David J.; Lim, Jae Hyang; Lin, Jizhen; Moon, Sung-Kyun; Post, J. Christopher

2014-01-01

Background Otitis media (OM) is the most common childhood bacterial infection and also the leading cause of conductive hearing loss in children. Currently, there is an urgent need for developing novel therapeutic agents for treating OM based on full understanding of molecular pathogenesis in the areas of molecular biology, biochemistry, genetics, and animal model studies in OM. Objective To provide a state-of-the-art review concerning recent advances in OM in the areas of molecular biology, biochemistry, genetics, and animal model studies and to discuss the future directions of OM studies in these areas. Data Sources and Review Methods A structured search of the current literature (since June 2007). The authors searched PubMed for published literature in the areas of molecular biology, biochemistry, genetics, and animal model studies in OM. Results Over the past 4 years, significant progress has been made in the areas of molecular biology, biochemistry, genetics, and animal model studies in OM. These studies brought new insights into our understanding of the molecular and biochemical mechanisms underlying the molecular pathogenesis of OM and helped identify novel therapeutic targets for OM. Conclusions and Implications for Practice Our understanding of the molecular pathogenesis of OM has been significantly advanced, particularly in the areas of inflammation, innate immunity, mucus overproduction, mucosal hyperplasia, middle ear and inner ear interaction, genetics, genome sequencing, and animal model studies. Although these studies are still in their experimental stages, they help identify new potential therapeutic targets. Future preclinical and clinical studies will help to translate these exciting experimental research findings into clinical applications. PMID:23536532

A molecular modeling approach to understand the structure and conformation relationship of (GlcpA)Xylan.

Science.gov (United States)

Guo, Qingbin; Kang, Ji; Wu, Yan; Cui, Steve W; Hu, Xinzhong; Yada, Rickey Y

2015-12-10

The structure and conformation relationships of a heteropolysaccharide (GlcpA)Xylan in terms of various molecular weights, Xylp/GlcpA ratio and the distribution of GlcpA along xylan chain were investigated using computer modeling. The adiabatic contour maps of xylobiose, XylpXylp(GlcpA) and (GlcpA)XylpXylp(GlcpA) indicated that the insertion of the side group (GlcpA) influenced the accessible conformational space of xylobiose molecule. RIS-Metropolis Monte Carlo method indicated that insertion of GlcpA side chain induced a lowering effect of the calculated chain extension at low GlcpA:Xylp ratio (GlcpA:Xylp = 1:3). The chain, however, became extended when the ratio of GlcpA:Xylp above 2/3. It was also shown that the spatial extension of the polymer chains was dependent on the distribution of side chain: the random distribution demonstrated the most flexible structure compared to block and alternative distribution. The present studies provide a unique insight into the dependence of both side chain ratio and distribution on the stiffness and flexibility of various (GlcpA)Xylan molecules. Copyright © 2015. Published by Elsevier Ltd.

A comparison of molecular dynamics and diffuse interface model predictions of Lennard-Jones fluid evaporation

Energy Technology Data Exchange (ETDEWEB)

Barbante, Paolo [Dipartimento di Matematica, Politecnico di Milano - Piazza Leonardo da Vinci 32 - 20133 Milano (Italy); Frezzotti, Aldo; Gibelli, Livio [Dipartimento di Scienze e Tecnologie Aerospaziali, Politecnico di Milano - Via La Masa 34 - 20156 Milano (Italy)

2014-12-09

The unsteady evaporation of a thin planar liquid film is studied by molecular dynamics simulations of Lennard-Jones fluid. The obtained results are compared with the predictions of a diffuse interface model in which capillary Korteweg contributions are added to hydrodynamic equations, in order to obtain a unified description of the liquid bulk, liquid-vapor interface and vapor region. Particular care has been taken in constructing a diffuse interface model matching the thermodynamic and transport properties of the Lennard-Jones fluid. The comparison of diffuse interface model and molecular dynamics results shows that, although good agreement is obtained in equilibrium conditions, remarkable deviations of diffuse interface model predictions from the reference molecular dynamics results are observed in the simulation of liquid film evaporation. It is also observed that molecular dynamics results are in good agreement with preliminary results obtained from a composite model which describes the liquid film by a standard hydrodynamic model and the vapor by the Boltzmann equation. The two mathematical model models are connected by kinetic boundary conditions assuming unit evaporation coefficient.

A Model of How Different Biology Experts Explain Molecular and Cellular Mechanisms

Science.gov (United States)

Trujillo, Caleb M.; Anderson, Trevor R.; Pelaez, Nancy J.

2015-01-01

Constructing explanations is an essential skill for all science learners. The goal of this project was to model the key components of expert explanation of molecular and cellular mechanisms. As such, we asked: What is an appropriate model of the components of explanation used by biology experts to explain molecular and cellular mechanisms? Do explanations made by experts from different biology subdisciplines at a university support the validity of this model? Guided by the modeling framework of R. S. Justi and J. K. Gilbert, the validity of an initial model was tested by asking seven biologists to explain a molecular mechanism of their choice. Data were collected from interviews, artifacts, and drawings, and then subjected to thematic analysis. We found that biologists explained the specific activities and organization of entities of the mechanism. In addition, they contextualized explanations according to their biological and social significance; integrated explanations with methods, instruments, and measurements; and used analogies and narrated stories. The derived methods, analogies, context, and how themes informed the development of our final MACH model of mechanistic explanations. Future research will test the potential of the MACH model as a guiding framework for instruction to enhance the quality of student explanations. PMID:25999313

Molecular modeling of polymer composite-analyte interactions in electronic nose sensors

Science.gov (United States)

Shevade, A. V.; Ryan, M. A.; Homer, M. L.; Manfreda, A. M.; Zhou, H.; Manatt, K. S.

2003-01-01

We report a molecular modeling study to investigate the polymer-carbon black (CB) composite-analyte interactions in resistive sensors. These sensors comprise the JPL electronic nose (ENose) sensing array developed for monitoring breathing air in human habitats. The polymer in the composite is modeled based on its stereoisomerism and sequence isomerism, while the CB is modeled as uncharged naphthalene rings with no hydrogens. The Dreiding 2.21 force field is used for the polymer, solvent molecules and graphite parameters are assigned to the carbon black atoms. A combination of molecular mechanics (MM) and molecular dynamics (NPT-MD and NVT-MD) techniques are used to obtain the equilibrium composite structure by inserting naphthalene rings in the polymer matrix. Polymers considered for this work include poly(4-vinylphenol), polyethylene oxide, and ethyl cellulose. Analytes studied are representative of both inorganic and organic compounds. The results are analyzed for the composite microstructure by calculating the radial distribution profiles as well as for the sensor response by predicting the interaction energies of the analytes with the composites. c2003 Elsevier Science B.V. All rights reserved.

Molecular modeling in the development of metal radiopharmaceuticals

International Nuclear Information System (INIS)

Green, M.A.

1993-10-01

We began this project with a compilation of a structural library to serve as a data base containing descriptions of the molecular features of metal-labeled radiopharmaceuticals known to efficiently cross the blood-brain barrier. Such a data base is needed in order to identify structural features (size, shape, molecular surface areas and volumes) that are critical in allowing blood-brain barrier penetration. Nine metal complexes have been added to this structural library. We have completed a detailed comparison of four molecular mechanics computer programs QUANTA, SYBYL, BOYD, and MM2DREW to assess their applicability to modeling the structures of low molecular weight metal complexes. We tested the ability of each program to reproduce the crystallographic structures of 38 complexes between nickel(II) and saturated N-donor ligands. The programs were evaluated in terns of their ability to reproduce structural features such as bond lengths, bond angles, and torsion angles. Recently, we investigated the synthesis and characterization of lipophilic cationic gallium complexes with hexadentate bis(salicylaldimine) ligands. This work identified the first gallium-68 radiopharrnaceuticals that can be injected intravenously and that subsequently exhibit significant myocardial uptake followed by prolonged myocardial retention of 68 Ga radioactivity. Tracers of this type remain under investigation as agents for evaluation of myocardial perfusion with positron emission tomography

Quantum molecular dynamics study of the Su-Schrieffer-Heeger model

NARCIS (Netherlands)

Michielsen, Kristel; Raedt, Hans De

A quantum molecular dynamics technique is presented to compute the static and dynamic properties of a system of fermions coupled to classical degrees of freedom. The method is employed to investigate the properties of the Su-Schrieffer-Heeger model, an electron-phonon model which is often used to

Molecular Modeling of Interfacial Behaviors of Nanomaterials

Science.gov (United States)

2007-05-01

potential was originally designed for the modeling of mixed covalent- ionic bonding and was successfully used to describe oxides in crystalline, glassy, and...is separates from the bulk liquid polymer, i.e., the structure of this layer, as influenced by that of the meatal surface, is significantly more...Striolo, J. Kieffer, and P. Cummings, ’Evaluation of Force- fields for molecular simulation of polyhedral oligomeric silsesquioxanes,’ J. Phys. Chem

SLS Navigation Model-Based Design Approach

Science.gov (United States)

Oliver, T. Emerson; Anzalone, Evan; Geohagan, Kevin; Bernard, Bill; Park, Thomas

2018-01-01

The SLS Program chose to implement a Model-based Design and Model-based Requirements approach for managing component design information and system requirements. This approach differs from previous large-scale design efforts at Marshall Space Flight Center where design documentation alone conveyed information required for vehicle design and analysis and where extensive requirements sets were used to scope and constrain the design. The SLS Navigation Team has been responsible for the Program-controlled Design Math Models (DMMs) which describe and represent the performance of the Inertial Navigation System (INS) and the Rate Gyro Assemblies (RGAs) used by Guidance, Navigation, and Controls (GN&C). The SLS Navigation Team is also responsible for the navigation algorithms. The navigation algorithms are delivered for implementation on the flight hardware as a DMM. For the SLS Block 1-B design, the additional GPS Receiver hardware is managed as a DMM at the vehicle design level. This paper provides a discussion of the processes and methods used to engineer, design, and coordinate engineering trades and performance assessments using SLS practices as applied to the GN&C system, with a particular focus on the Navigation components. These include composing system requirements, requirements verification, model development, model verification and validation, and modeling and analysis approaches. The Model-based Design and Requirements approach does not reduce the effort associated with the design process versus previous processes used at Marshall Space Flight Center. Instead, the approach takes advantage of overlap between the requirements development and management process, and the design and analysis process by efficiently combining the control (i.e. the requirement) and the design mechanisms. The design mechanism is the representation of the component behavior and performance in design and analysis tools. The focus in the early design process shifts from the development and

Molecular modelling of a chemodosimeter for the selective detection ...

Indian Academy of Sciences (India)

Wintec

Molecular modelling of a chemodosimeter for the selective detection of. As(III) ion in water. † ... high levels of arsenic cause severe skin diseases in- cluding skin cancer ..... Special Attention to Groundwater in SE Asia (eds) D. Chakraborti, A ...

Structural modeling and molecular simulation analysis of HvAP2/EREBP from barley.

Science.gov (United States)

Pandey, Bharati; Sharma, Pradeep; Tyagi, Chetna; Goyal, Sukriti; Grover, Abhinav; Sharma, Indu

2016-06-01

AP2/ERF transcription factors play a critical role in plant development and stress adaptation. This study reports the three-dimensional ab initio-based model of AP2/EREBP protein of barley and its interaction with DNA. Full-length coding sequence of HvAP2/EREBP gene isolated from two Indian barley cultivars, RD 2503 and RD 31, was used to model the protein. Of five protein models obtained, the one with lowest C-score was chosen for further analysis. The N- and C-terminal regions of HvAP2 protein were found to be highly disordered. The dynamic properties of AP2/EREBP and its interaction with DNA were investigated by molecular dynamics simulation. Analysis of trajectories from simulation yielded the equilibrated conformation between 2-10ns for protein and 7-15ns for protein-DNA complex. We established relationship between DNA having GCC box and DNA-binding domain of HvAP2/EREBP was established by modeling 11-base-pair-long nucleotide sequence and HvAP2/EREBP protein using ab initio method. Analysis of protein-DNA interaction showed that a β-sheet motif constituting amino acid residues THR105, ARG100, ARG93, and ARG83 seems to play important role in stabilizing the complex as they form strong hydrogen bond interactions with the DNA motif. Taken together, this study provides first-hand comprehensive information detailing structural conformation and interactions of HvAP2/EREBP proteins in barley. The study intensifies the role of computational approaches for preliminary examination of unknown proteins in the absence of experimental information. It also provides molecular insight into protein-DNA binding for understanding and enhancing abiotic stress resistance for improving the water use efficiency in crop plants.

Density-Dependent Formulation of Dispersion-Repulsion Interactions in Hybrid Multiscale Quantum/Molecular Mechanics (QM/MM) Models

DEFF Research Database (Denmark)

Curutchet, Carles; Cupellini, Lorenzo; Kongsted, Jacob

2018-01-01

embedding approaches, respectively, nonelectrostatic dispersion and repulsion interactions are instead commonly described through classical potentials despite their quantum mechanical origin. Here we present an extension of the Tkatchenko-Scheffler semiempirical van der Waals (vdWTS) scheme aimed......Mixed multiscale quantum/molecular mechanics (QM/MM) models are widely used to explore the structure, reactivity, and electronic properties of complex chemical systems. Whereas such models typically include electrostatics and potentially polarization in so-called electrostatic and polarizable...... at describing dispersion and repulsion interactions between quantum and classical regions within a QM/MM polarizable embedding framework. Starting from the vdWTSexpression, we define a dispersion and a repulsion term, both of them density-dependent and consistently based on a Lennard-Jones-like potential. We...

An integrated approach of network-based systems biology, molecular docking, and molecular dynamics approach to unravel the role of existing antiviral molecules against AIDS-associated cancer.

Science.gov (United States)

Omer, Ankur; Singh, Poonam

2017-05-01

A serious challenge in cancer treatment is to reposition the activity of various already known drug candidates against cancer. There is a need to rewrite and systematically analyze the detailed mechanistic aspect of cellular networks to gain insight into the novel role played by various molecules. Most Human Immunodeficiency Virus infection-associated cancers are caused by oncogenic viruses like Human Papilloma Viruses and Epstein-Bar Virus. As the onset of AIDS-associated cancers marks the severity of AIDS, there might be possible interconnections between the targets and mechanism of both the diseases. We have explored the possibility of certain antiviral compounds to act against major AIDS-associated cancers: Kaposi's Sarcoma, Non-Hodgkin Lymphoma, and Cervical Cancer with the help of systems pharmacology approach that includes screening for targets and molecules through the construction of a series of drug-target and drug-target-diseases network. Two molecules (Calanolide A and Chaetochromin B) and the target "HRAS" were finally screened with the help of molecular docking and molecular dynamics simulation. The results provide novel antiviral molecules against HRAS target to treat AIDS defining cancers and an insight for understanding the pharmacological, therapeutic aspects of similar unexplored molecules against various cancers.

The one-sample PARAFAC approach reveals molecular size distributions of fluorescent components in dissolved organic matter

DEFF Research Database (Denmark)

Wünsch, Urban; Murphy, Kathleen R.; Stedmon, Colin

2017-01-01

Molecular size plays an important role in dissolved organic matter (DOM) biogeochemistry, but its relationship with the fluorescent fraction of DOM (FDOM) remains poorly resolved. Here high-performance size exclusion chromatography (HPSEC) was coupled to fluorescence emission-excitation (EEM...... but not their spectral properties. Thus, in contrast to absorption measurements, bulk fluorescence is unlikely to reliably indicate the average molecular size of DOM. The one-sample approach enables robust and independent cross-site comparisons without large-scale sampling efforts and introduces new analytical...... opportunities for elucidating the origins and biogeochemical properties of FDOM...

Topochemical approach to efficiently produce main-chain poly(bile acid)s with high molecular weights.

Science.gov (United States)

Li, Weina; Li, Xuesong; Zhu, Wei; Li, Changxu; Xu, Dan; Ju, Yong; Li, Guangtao

2011-07-21

Based on a topochemical approach, a strategy for efficiently producing main-chain poly(bile acid)s in the solid state was developed. This strategy allows for facile and scalable synthesis of main-chain poly(bile acid)s not only with high molecular weights, but also with quantitative conversions and yields.

Molecular interaction of PCB153 to human serum albumin: Insights from spectroscopic and molecular modeling studies

Energy Technology Data Exchange (ETDEWEB)

Han, Chao; Fang, Senbiao; Cao, Huiming; Lu, Yan; Ma, Yaqiong [School of Pharmacy, Lanzhou University, Lanzhou 730000 (China); Wei, Dongfeng [Institute of Basic Research in Clinical Medicine, China Academy of Chinese Medical Sciences, Beijing 100700 (China); Xie, Xiaoyun [College of Earth and Environmental Science, Lanzhou University, Lanzhou 730000 (China); Liu, Xiaohua [School of Pharmacy, Lanzhou University, Lanzhou 730000 (China); Li, Xin [College of Food and Bioengineering, Henan University of Science and Technology, Luoyang 471003 (China); Fei, Dongqing [School of Pharmacy, Lanzhou University, Lanzhou 730000 (China); Zhao, Chunyan, E-mail: zhaochy07@lzu.edu.cn [School of Pharmacy, Lanzhou University, Lanzhou 730000 (China)

2013-03-15

Highlights: ► We identify the binding mode of PCB153 to human serum albumin (HSA). ► Spectroscopic and molecular modeling results reveal that PCB153 binds at the site II. ► The interaction is mainly governed by hydrophobic and hydrogen bond forces. ► The work helps to probe transporting, distribution and toxicity effect of PCBs. -- Abstract: Polychlorinated biphenyls (PCBs) possessed much potential hazard to environment because of its chemical stability and biological toxicity. Here, we identified the binding mode of a representative compound, PCB153, to human serum albumin (HSA) using fluorescence and molecular dynamics simulation methods. The fluorescence study showed that the intrinsic fluorescence of HSA was quenched by addition of PCB153 through a static quenching mechanism. The thermodynamic analysis proved the binding behavior was mainly governed by hydrophobic force. Furthermore, as evidenced by site marker displacement experiments using two probe compounds, it revealed that PCB153 acted exactly on subdomain IIIA (site II) of HSA. On the other hand, the molecular dynamics studies as well as free energy calculations made another important contribution to understand the conformational changes of HSA and the stability of HSA-PCB153 system. Molecular docking revealed PCB153 can bind in a large hydrophobic activity of subdomain IIIA by the hydrophobic interaction and hydrogen bond interactions between chlorine atoms and residue ASN391. The present work provided reasonable models helping us further understand the transporting, distribution and toxicity effect of PCBs when it spread into human blood serum.

Application of Molecular Modeling to Urokinase Inhibitors Development

Directory of Open Access Journals (Sweden)

V. B. Sulimov

2014-01-01

Full Text Available Urokinase-type plasminogen activator (uPA plays an important role in the regulation of diverse physiologic and pathologic processes. Experimental research has shown that elevated uPA expression is associated with cancer progression, metastasis, and shortened survival in patients, whereas suppression of proteolytic activity of uPA leads to evident decrease of metastasis. Therefore, uPA has been considered as a promising molecular target for development of anticancer drugs. The present study sets out to develop the new selective uPA inhibitors using computer-aided structural based drug design methods. Investigation involves the following stages: computer modeling of the protein active site, development and validation of computer molecular modeling methods: docking (SOL program, postprocessing (DISCORE program, direct generalized docking (FLM program, and the application of the quantum chemical calculations (MOPAC package, search of uPA inhibitors among molecules from databases of ready-made compounds to find new uPA inhibitors, and design of new chemical structures and their optimization and experimental examination. On the basis of known uPA inhibitors and modeling results, 18 new compounds have been designed, calculated using programs mentioned above, synthesized, and tested in vitro. Eight of them display inhibitory activity and two of them display activity about 10 μM.

Naumovozyma castellii: an alternative model for budding yeast molecular biology.

Science.gov (United States)

Karademir Andersson, Ahu; Cohn, Marita

2017-03-01

Naumovozyma castellii (Saccharomyces castellii) is a member of the budding yeast family Saccharomycetaceae. It has been extensively used as a model organism for telomere biology research and has gained increasing interest as a budding yeast model for functional analyses owing to its amenability to genetic modifications. Owing to the suitable phylogenetic distance to S. cerevisiae, the whole genome sequence of N. castellii has provided unique data for comparative genomic studies, and it played a key role in the establishment of the timing of the whole genome duplication and the evolutionary events that took place in the subsequent genomic evolution of the Saccharomyces lineage. Here we summarize the historical background of its establishment as a laboratory yeast species, and the development of genetic and molecular tools and strains. We review the research performed on N. castellii, focusing on areas where it has significantly contributed to the discovery of new features of molecular biology and to the advancement of our understanding of molecular evolution. Copyright © 2016 John Wiley & Sons, Ltd. Copyright © 2016 John Wiley & Sons, Ltd.

Molecular Models for DSMC Simulations of Metal Vapor Deposition

OpenAIRE

Venkattraman, A; Alexeenko, Alina A

2010-01-01

The direct simulation Monte Carlo (DSMC) method is applied here to model the electron‐beam (e‐beam) physical vapor deposition of copper thin films. A suitable molecular model for copper‐copper interactions have been determined based on comparisons with experiments for a 2D slit source. The model for atomic copper vapor is then used in axi‐symmetric DSMC simulations for analysis of a typical e‐beam metal deposition system with a cup crucible. The dimensional and non‐dimensional mass fluxes obt...

A New Experimental Polytrauma Model in Rats: Molecular Characterization of the Early Inflammatory Response

Directory of Open Access Journals (Sweden)

Sebastian Weckbach

2012-01-01

Full Text Available Background. The molecular mechanisms of the immune response after polytrauma are highly complex and far from fully understood. In this paper, we characterize a new standardized polytrauma model in rats based on the early molecular inflammatory and apoptotic response. Methods. Male Wistar rats (250 g, 6–10/group were anesthetized and exposed to chest trauma (ChT, closed head injury (CHI, or Tib/Fib fracture including a soft tissue trauma (Fx + STT or to the following combination of injuries: (1 ChT; (2 ChT + Fx + STT; (3 ChT + CHI; (4 CHI; (5 polytrauma (PT = ChT + CHI + Fx + STT. Sham-operated rats served as negative controls. The inflammatory response was quantified at 2 hours and 4 hours after trauma by analysis of “key” inflammatory mediators, including selected cytokines and complement components, in serum and bronchoalveolar (BAL fluid samples. Results. Polytraumatized (PT rats showed a significant systemic and intrapulmonary release of cytokines, chemokines, and complement anaphylatoxins, compared to rats with isolated injuries or selected combinations of injuries. Conclusion. This new rat model appears to closely mimic the early immunological response of polytrauma observed in humans and may provide a valid basis for evaluation of the complex pathophysiology and future therapeutic immune modulatory approaches in experimental polytrauma.

A New Experimental Polytrauma Model in Rats: Molecular Characterization of the Early Inflammatory Response

Science.gov (United States)

Weckbach, Sebastian; Perl, Mario; Heiland, Tim; Braumüller, Sonja; Stahel, Philip F.; Flierl, Michael A.; Ignatius, Anita; Gebhard, Florian; Huber-Lang, Markus

2012-01-01

Background. The molecular mechanisms of the immune response after polytrauma are highly complex and far from fully understood. In this paper, we characterize a new standardized polytrauma model in rats based on the early molecular inflammatory and apoptotic response. Methods. Male Wistar rats (250 g, 6–10/group) were anesthetized and exposed to chest trauma (ChT), closed head injury (CHI), or Tib/Fib fracture including a soft tissue trauma (Fx + STT) or to the following combination of injuries: (1) ChT; (2) ChT + Fx + STT; (3) ChT + CHI; (4) CHI; (5) polytrauma (PT = ChT + CHI + Fx + STT). Sham-operated rats served as negative controls. The inflammatory response was quantified at 2 hours and 4 hours after trauma by analysis of “key” inflammatory mediators, including selected cytokines and complement components, in serum and bronchoalveolar (BAL) fluid samples. Results. Polytraumatized (PT) rats showed a significant systemic and intrapulmonary release of cytokines, chemokines, and complement anaphylatoxins, compared to rats with isolated injuries or selected combinations of injuries. Conclusion. This new rat model appears to closely mimic the early immunological response of polytrauma observed in humans and may provide a valid basis for evaluation of the complex pathophysiology and future therapeutic immune modulatory approaches in experimental polytrauma. PMID:22481866

Machine learning molecular dynamics for the simulation of infrared spectra.

Science.gov (United States)

Gastegger, Michael; Behler, Jörg; Marquetand, Philipp

2017-10-01

Machine learning has emerged as an invaluable tool in many research areas. In the present work, we harness this power to predict highly accurate molecular infrared spectra with unprecedented computational efficiency. To account for vibrational anharmonic and dynamical effects - typically neglected by conventional quantum chemistry approaches - we base our machine learning strategy on ab initio molecular dynamics simulations. While these simulations are usually extremely time consuming even for small molecules, we overcome these limitations by leveraging the power of a variety of machine learning techniques, not only accelerating simulations by several orders of magnitude, but also greatly extending the size of systems that can be treated. To this end, we develop a molecular dipole moment model based on environment dependent neural network charges and combine it with the neural network potential approach of Behler and Parrinello. Contrary to the prevalent big data philosophy, we are able to obtain very accurate machine learning models for the prediction of infrared spectra based on only a few hundreds of electronic structure reference points. This is made possible through the use of molecular forces during neural network potential training and the introduction of a fully automated sampling scheme. We demonstrate the power of our machine learning approach by applying it to model the infrared spectra of a methanol molecule, n -alkanes containing up to 200 atoms and the protonated alanine tripeptide, which at the same time represents the first application of machine learning techniques to simulate the dynamics of a peptide. In all of these case studies we find an excellent agreement between the infrared spectra predicted via machine learning models and the respective theoretical and experimental spectra.

Evolutionary history of genus Macrobrachium inferred from mitochondrial markers: a molecular clock approach.

Science.gov (United States)

Jose, Deepak; Harikrishnan, Mahadevan

2018-04-17

Caridea, an infraorder of shrimps coming under Pleocyemata was first reported from the oceans before 417 million years followed by their radiation recorded during the Permian period. Hitherto, about 3877 extant caridean species were accounted within which one quarter constitute freshwater species. Freshwater prawns of genus Macrobrachium (Infraorder Caridea; Family Palaemonidae), with more than 240 species are inhabitants of diverse aquatic habitats like coastal lagoons, lakes, tropical streams, ponds and rivers. Previous studies on Macrobrachium relied on the highly variable morphological characters which were insufficient for accurate diagnosis of natural species groups. Present study focuses on the utility of molecular markers (viz. COI and 16S rRNA) for resolving the evolutionary history of genus Macrobrachium using a combination of phylogeny and timescale components. It is for the first time a molecular clock approach had been carried out towards genus Macrobrachium in a broad aspect with the incorporation of congeners inhabiting diverse geographical realms including endemic species M. striatum from South West coast of India. Molecular results obtained revealed the phylogenetic relationships between congeners of genus Macrobrachium at intra/inter-continental level along with the corresponding evolutionary time estimates.

Rule-based modeling: a computational approach for studying biomolecular site dynamics in cell signaling systems

Science.gov (United States)

Chylek, Lily A.; Harris, Leonard A.; Tung, Chang-Shung; Faeder, James R.; Lopez, Carlos F.

2013-01-01

Rule-based modeling was developed to address the limitations of traditional approaches for modeling chemical kinetics in cell signaling systems. These systems consist of multiple interacting biomolecules (e.g., proteins), which themselves consist of multiple parts (e.g., domains, linear motifs, and sites of phosphorylation). Consequently, biomolecules that mediate information processing generally have the potential to interact in multiple ways, with the number of possible complexes and post-translational modification states tending to grow exponentially with the number of binary interactions considered. As a result, only large reaction networks capture all possible consequences of the molecular interactions that occur in a cell signaling system, which is problematic because traditional modeling approaches for chemical kinetics (e.g., ordinary differential equations) require explicit network specification. This problem is circumvented through representation of interactions in terms of local rules. With this approach, network specification is implicit and model specification is concise. Concise representation results in a coarse graining of chemical kinetics, which is introduced because all reactions implied by a rule inherit the rate law associated with that rule. Coarse graining can be appropriate if interactions are modular, and the coarseness of a model can be adjusted as needed. Rules can be specified using specialized model-specification languages, and recently developed tools designed for specification of rule-based models allow one to leverage powerful software engineering capabilities. A rule-based model comprises a set of rules, which can be processed by general-purpose simulation and analysis tools to achieve different objectives (e.g., to perform either a deterministic or stochastic simulation). PMID:24123887

Rule-based modeling: a computational approach for studying biomolecular site dynamics in cell signaling systems.

Science.gov (United States)

Chylek, Lily A; Harris, Leonard A; Tung, Chang-Shung; Faeder, James R; Lopez, Carlos F; Hlavacek, William S

2014-01-01

Rule-based modeling was developed to address the limitations of traditional approaches for modeling chemical kinetics in cell signaling systems. These systems consist of multiple interacting biomolecules (e.g., proteins), which themselves consist of multiple parts (e.g., domains, linear motifs, and sites of phosphorylation). Consequently, biomolecules that mediate information processing generally have the potential to interact in multiple ways, with the number of possible complexes and posttranslational modification states tending to grow exponentially with the number of binary interactions considered. As a result, only large reaction networks capture all possible consequences of the molecular interactions that occur in a cell signaling system, which is problematic because traditional modeling approaches for chemical kinetics (e.g., ordinary differential equations) require explicit network specification. This problem is circumvented through representation of interactions in terms of local rules. With this approach, network specification is implicit and model specification is concise. Concise representation results in a coarse graining of chemical kinetics, which is introduced because all reactions implied by a rule inherit the rate law associated with that rule. Coarse graining can be appropriate if interactions are modular, and the coarseness of a model can be adjusted as needed. Rules can be specified using specialized model-specification languages, and recently developed tools designed for specification of rule-based models allow one to leverage powerful software engineering capabilities. A rule-based model comprises a set of rules, which can be processed by general-purpose simulation and analysis tools to achieve different objectives (e.g., to perform either a deterministic or stochastic simulation). © 2013 Wiley Periodicals, Inc.

Evolutionary modeling-based approach for model errors correction

Directory of Open Access Journals (Sweden)

S. Q. Wan

2012-08-01

Full Text Available The inverse problem of using the information of historical data to estimate model errors is one of the science frontier research topics. In this study, we investigate such a problem using the classic Lorenz (1963 equation as a prediction model and the Lorenz equation with a periodic evolutionary function as an accurate representation of reality to generate "observational data."

On the basis of the intelligent features of evolutionary modeling (EM, including self-organization, self-adaptive and self-learning, the dynamic information contained in the historical data can be identified and extracted by computer automatically. Thereby, a new approach is proposed to estimate model errors based on EM in the present paper. Numerical tests demonstrate the ability of the new approach to correct model structural errors. In fact, it can actualize the combination of the statistics and dynamics to certain extent.

MOlecular MAterials Property Prediction Package (MOMAP) 1.0: a software package for predicting the luminescent properties and mobility of organic functional materials

Science.gov (United States)

Niu, Yingli; Li, Wenqiang; Peng, Qian; Geng, Hua; Yi, Yuanping; Wang, Linjun; Nan, Guangjun; Wang, Dong; Shuai, Zhigang

2018-04-01

MOlecular MAterials Property Prediction Package (MOMAP) is a software toolkit for molecular materials property prediction. It focuses on luminescent properties and charge mobility properties. This article contains a brief descriptive introduction of key features, theoretical models and algorithms of the software, together with examples that illustrate the performance. First, we present the theoretical models and algorithms for molecular luminescent properties calculation, which includes the excited-state radiative/non-radiative decay rate constant and the optical spectra. Then, a multi-scale simulation approach and its algorithm for the molecular charge mobility are described. This approach is based on hopping model and combines with Kinetic Monte Carlo and molecular dynamics simulations, and it is especially applicable for describing a large category of organic semiconductors, whose inter-molecular electronic coupling is much smaller than intra-molecular charge reorganisation energy.

HEDR modeling approach

International Nuclear Information System (INIS)

Shipler, D.B.; Napier, B.A.

1992-07-01

This report details the conceptual approaches to be used in calculating radiation doses to individuals throughout the various periods of operations at the Hanford Site. The report considers the major environmental transport pathways--atmospheric, surface water, and ground water--and projects and appropriate modeling technique for each. The modeling sequence chosen for each pathway depends on the available data on doses, the degree of confidence justified by such existing data, and the level of sophistication deemed appropriate for the particular pathway and time period being considered

Molecular modeling of polycarbonate materials: Glass transition and mechanical properties

Science.gov (United States)

Palczynski, Karol; Wilke, Andreas; Paeschke, Manfred; Dzubiella, Joachim

2017-09-01

Linking the experimentally accessible macroscopic properties of thermoplastic polymers to their microscopic static and dynamic properties is a key requirement for targeted material design. Classical molecular dynamics simulations enable us to study the structural and dynamic behavior of molecules on microscopic scales, and statistical physics provides a framework for relating these properties to the macroscopic properties. We take a first step toward creating an automated workflow for the theoretical prediction of thermoplastic material properties by developing an expeditious method for parameterizing a simple yet surprisingly powerful coarse-grained bisphenol-A polycarbonate model which goes beyond previous coarse-grained models and successfully reproduces the thermal expansion behavior, the glass transition temperature as a function of the molecular weight, and several elastic properties.

Scalable and fast heterogeneous molecular simulation with predictive parallelization schemes

International Nuclear Information System (INIS)

Guzman, Horacio V.; Junghans, Christoph; Kremer, Kurt; Stuehn, Torsten

2017-01-01

Multiscale and inhomogeneous molecular systems are challenging topics in the field of molecular simulation. In particular, modeling biological systems in the context of multiscale simulations and exploring material properties are driving a permanent development of new simulation methods and optimization algorithms. In computational terms, those methods require parallelization schemes that make a productive use of computational resources for each simulation and from its genesis. Here, we introduce the heterogeneous domain decomposition approach, which is a combination of an heterogeneity-sensitive spatial domain decomposition with an a priori rearrangement of subdomain walls. Within this approach and paper, the theoretical modeling and scaling laws for the force computation time are proposed and studied as a function of the number of particles and the spatial resolution ratio. We also show the new approach capabilities, by comparing it to both static domain decomposition algorithms and dynamic load-balancing schemes. Specifically, two representative molecular systems have been simulated and compared to the heterogeneous domain decomposition proposed in this work. Finally, these two systems comprise an adaptive resolution simulation of a biomolecule solvated in water and a phase-separated binary Lennard-Jones fluid.

Scalable and fast heterogeneous molecular simulation with predictive parallelization schemes

Science.gov (United States)

Guzman, Horacio V.; Junghans, Christoph; Kremer, Kurt; Stuehn, Torsten

2017-11-01

Multiscale and inhomogeneous molecular systems are challenging topics in the field of molecular simulation. In particular, modeling biological systems in the context of multiscale simulations and exploring material properties are driving a permanent development of new simulation methods and optimization algorithms. In computational terms, those methods require parallelization schemes that make a productive use of computational resources for each simulation and from its genesis. Here, we introduce the heterogeneous domain decomposition approach, which is a combination of an heterogeneity-sensitive spatial domain decomposition with an a priori rearrangement of subdomain walls. Within this approach, the theoretical modeling and scaling laws for the force computation time are proposed and studied as a function of the number of particles and the spatial resolution ratio. We also show the new approach capabilities, by comparing it to both static domain decomposition algorithms and dynamic load-balancing schemes. Specifically, two representative molecular systems have been simulated and compared to the heterogeneous domain decomposition proposed in this work. These two systems comprise an adaptive resolution simulation of a biomolecule solvated in water and a phase-separated binary Lennard-Jones fluid.

Systems approaches to computational modeling of the oral microbiome

Directory of Open Access Journals (Sweden)

Dimiter V. Dimitrov

2013-07-01

Full Text Available Current microbiome research has generated tremendous amounts of data providing snapshots of molecular activity in a variety of organisms, environments, and cell types. However, turning this knowledge into whole system level of understanding on pathways and processes has proven to be a challenging task. In this review we highlight the applicability of bioinformatics and visualization techniques to large collections of data in order to better understand the information that contains related diet – oral microbiome – host mucosal transcriptome interactions. In particular we focus on systems biology of Porphyromonas gingivalis in the context of high throughput computational methods tightly integrated with translational systems medicine. Those approaches have applications for both basic research, where we can direct specific laboratory experiments in model organisms and cell cultures, to human disease, where we can validate new mechanisms and biomarkers for prevention and treatment of chronic disorders

Molecular Modeling of Enzyme Dynamics Towards Understanding Solvent Effects

DEFF Research Database (Denmark)

Wedberg, Nils Hejle Rasmus Ingemar

This thesis describes the development of a molecular simulation methodology to study properties of enzymes in non-aqueous media at fixed thermodynamic water activities. The methodology is applied in a molecular dynamics study of the industrially important enzyme Candida antarctica lipase B (CALB...... of enzyme kinetics in non-aqueous media, it has been a fruitful approach to fix the enzyme hydration level by controlling the water activity of the medium. In this work, a protocol is therefore developed for determining the water activity in non-aqueous protein simulations. The method relies on determining...... integration, while for small systems, it seems to be even better. The method is applied to compute the excess Gibbs energy of the mixtures of water and organic solvents used in the simulations of CALB. This allows to determine the water activity of the simulated systems and thus to compare protein properties...

Exploring pyrazolo[3,4-d]pyrimidine phosphodiesterase 1 (PDE1) inhibitors: a predictive approach combining comparative validated multiple molecular modelling techniques.

Science.gov (United States)

Amin, Sk Abdul; Bhargava, Sonam; Adhikari, Nilanjan; Gayen, Shovanlal; Jha, Tarun

2018-02-01

Phosphodiesterase 1 (PDE1) is a potential target for a number of neurodegenerative disorders such as Schizophrenia, Parkinson's and Alzheimer's diseases. A number of pyrazolo[3,4-d]pyrimidine PDE1 inhibitors were subjected to different molecular modelling techniques [such as regression-based quantitative structure-activity relationship (QSAR): multiple linear regression, support vector machine and artificial neural network; classification-based QSAR: Bayesian modelling and Recursive partitioning; Monte Carlo based QSAR; Open3DQSAR; pharmacophore mapping and molecular docking analyses] to get a detailed knowledge about the physicochemical and structural requirements for higher inhibitory activity. The planarity of the pyrimidinone ring plays an important role for PDE1 inhibition. The N-methylated function at the 5th position of the pyrazolo[3,4-d]pyrimidine core is required for interacting with the PDE1 enzyme. The cyclopentyl ring fused with the parent scaffold is necessary for PDE1 binding potency. The phenylamino substitution at 3rd position is crucial for PDE1 inhibition. The N2-substitution at the pyrazole moiety is important for PDE1 inhibition compared to the N1-substituted analogues. Moreover, the p-substituted benzyl side chain at N2-position helps to enhance the PDE1 inhibitory profile. Depending on these observations, some new molecules are predicted that may possess better PDE1 inhibition.

Molecular modeling studies of structural properties of polyvinyl alcohol: a comparative study using INTERFACE force field.

Science.gov (United States)

Radosinski, Lukasz; Labus, Karolina

2017-10-05

Polyvinyl alcohol (PVA) is a material with a variety of applications in separation, biotechnology, and biomedicine. Using combined Monte Carlo and molecular dynamics techniques, we present an extensive comparative study of second- and third-generation force fields Universal, COMPASS, COMPASS II, PCFF, and the newly developed INTERFACE, as applied to this system. In particular, we show that an INTERFACE force field provides a possibility of composing a reliable atomistic model to reproduce density change of PVA matrix in a narrow temperature range (298-348 K) and calculate a thermal expansion coefficient with reasonable accuracy. Thus, the INTERFACE force field may be used to predict mechanical properties of the PVA system, being a scaffold for hydrogels, with much greater accuracy than latter approaches. Graphical abstract Molecular Dynamics and Monte Carlo studies indicate that it is possible to predict properties of the PVA in narrow temperature range by using the INTERFACE force field.

Sequential application of ligand and structure based modeling approaches to index chemicals for their hH4R antagonism.

Directory of Open Access Journals (Sweden)

Matteo Pappalardo

Full Text Available The human histamine H4 receptor (hH4R, a member of the G-protein coupled receptors (GPCR family, is an increasingly attractive drug target. It plays a key role in many cell pathways and many hH4R ligands are studied for the treatment of several inflammatory, allergic and autoimmune disorders, as well as for analgesic activity. Due to the challenging difficulties in the experimental elucidation of hH4R structure, virtual screening campaigns are normally run on homology based models. However, a wealth of information about the chemical properties of GPCR ligands has also accumulated over the last few years and an appropriate combination of these ligand-based knowledge with structure-based molecular modeling studies emerges as a promising strategy for computer-assisted drug design. Here, two chemoinformatics techniques, the Intelligent Learning Engine (ILE and Iterative Stochastic Elimination (ISE approach, were used to index chemicals for their hH4R bioactivity. An application of the prediction model on external test set composed of more than 160 hH4R antagonists picked from the chEMBL database gave enrichment factor of 16.4. A virtual high throughput screening on ZINC database was carried out, picking ∼ 4000 chemicals highly indexed as H4R antagonists' candidates. Next, a series of 3D models of hH4R were generated by molecular modeling and molecular dynamics simulations performed in fully atomistic lipid membranes. The efficacy of the hH4R 3D models in discrimination between actives and non-actives were checked and the 3D model with the best performance was chosen for further docking studies performed on the focused library. The output of these docking studies was a consensus library of 11 highly active scored drug candidates. Our findings suggest that a sequential combination of ligand-based chemoinformatics approaches with structure-based ones has the potential to improve the success rate in discovering new biologically active GPCR drugs and

Sequential application of ligand and structure based modeling approaches to index chemicals for their hH4R antagonism.

Science.gov (United States)

Pappalardo, Matteo; Shachaf, Nir; Basile, Livia; Milardi, Danilo; Zeidan, Mouhammed; Raiyn, Jamal; Guccione, Salvatore; Rayan, Anwar

2014-01-01

The human histamine H4 receptor (hH4R), a member of the G-protein coupled receptors (GPCR) family, is an increasingly attractive drug target. It plays a key role in many cell pathways and many hH4R ligands are studied for the treatment of several inflammatory, allergic and autoimmune disorders, as well as for analgesic activity. Due to the challenging difficulties in the experimental elucidation of hH4R structure, virtual screening campaigns are normally run on homology based models. However, a wealth of information about the chemical properties of GPCR ligands has also accumulated over the last few years and an appropriate combination of these ligand-based knowledge with structure-based molecular modeling studies emerges as a promising strategy for computer-assisted drug design. Here, two chemoinformatics techniques, the Intelligent Learning Engine (ILE) and Iterative Stochastic Elimination (ISE) approach, were used to index chemicals for their hH4R bioactivity. An application of the prediction model on external test set composed of more than 160 hH4R antagonists picked from the chEMBL database gave enrichment factor of 16.4. A virtual high throughput screening on ZINC database was carried out, picking ∼ 4000 chemicals highly indexed as H4R antagonists' candidates. Next, a series of 3D models of hH4R were generated by molecular modeling and molecular dynamics simulations performed in fully atomistic lipid membranes. The efficacy of the hH4R 3D models in discrimination between actives and non-actives were checked and the 3D model with the best performance was chosen for further docking studies performed on the focused library. The output of these docking studies was a consensus library of 11 highly active scored drug candidates. Our findings suggest that a sequential combination of ligand-based chemoinformatics approaches with structure-based ones has the potential to improve the success rate in discovering new biologically active GPCR drugs and increase the

A Network Biology Approach to Discover the Molecular Biomarker Associated with Hepatocellular Carcinoma

Directory of Open Access Journals (Sweden)

Liwei Zhuang

2014-01-01

Full Text Available In recent years, high throughput technologies such as microarray platform have provided a new avenue for hepatocellular carcinoma (HCC investigation. Traditionally, gene sets enrichment analysis of survival related genes is commonly used to reveal the underlying functional mechanisms. However, this approach usually produces too many candidate genes and cannot discover detailed signaling transduction cascades, which greatly limits their clinical application such as biomarker development. In this study, we have proposed a network biology approach to discover novel biomarkers from multidimensional omics data. This approach effectively combines clinical survival data with topological characteristics of human protein interaction networks and patients expression profiling data. It can produce novel network based biomarkers together with biological understanding of molecular mechanism. We have analyzed eighty HCC expression profiling arrays and identified that extracellular matrix and programmed cell death are the main themes related to HCC progression. Compared with traditional enrichment analysis, this approach can provide concrete and testable hypothesis on functional mechanism. Furthermore, the identified subnetworks can potentially be used as suitable targets for therapeutic intervention in HCC.

A Statistical Approach For Modeling Tropical Cyclones. Synthetic Hurricanes Generator Model

Energy Technology Data Exchange (ETDEWEB)

Pasqualini, Donatella [Los Alamos National Lab. (LANL), Los Alamos, NM (United States)

2016-05-11

This manuscript brie y describes a statistical ap- proach to generate synthetic tropical cyclone tracks to be used in risk evaluations. The Synthetic Hur- ricane Generator (SynHurG) model allows model- ing hurricane risk in the United States supporting decision makers and implementations of adaptation strategies to extreme weather. In the literature there are mainly two approaches to model hurricane hazard for risk prediction: deterministic-statistical approaches, where the storm key physical parameters are calculated using physi- cal complex climate models and the tracks are usually determined statistically from historical data; and sta- tistical approaches, where both variables and tracks are estimated stochastically using historical records. SynHurG falls in the second category adopting a pure stochastic approach.

Vibrational infrared and Raman spectra of polypeptides: Fragments-in-fragments within molecular tailoring approach

Energy Technology Data Exchange (ETDEWEB)

Sahu, Nityananda; Gadre, Shridhar R., E-mail: gadre@iitk.ac.in [Department of Chemistry, Indian Institute of Technology Kanpur, Kanpur 208 016 (India)

2016-03-21

The present work reports the calculation of vibrational infrared (IR) and Raman spectra of large molecular systems employing molecular tailoring approach (MTA). Further, it extends the grafting procedure for the accurate evaluation of IR and Raman spectra of large molecular systems, employing a new methodology termed as Fragments-in-Fragments (FIF), within MTA. Unlike the previous MTA-based studies, the accurate estimation of the requisite molecular properties is achieved without performing any full calculations (FC). The basic idea of the grafting procedure is implemented by invoking the nearly basis-set-independent nature of the MTA-based error vis-à-vis the respective FCs. FIF has been tested out for the estimation of the above molecular properties for three isomers, viz., β-strand, 3{sub 10}- and α-helix of acetyl(alanine){sub n}NH{sub 2} (n = 10, 15) polypeptides, three conformers of doubly protonated gramicidin S decapeptide and trpzip2 protein (PDB id: 1LE1), respectively, employing BP86/TZVP, M06/6-311G**, and M05-2X/6-31G** levels of theory. For most of the cases, a maximum difference of 3 cm{sup −1} is achieved between the grafted-MTA frequencies and the corresponding FC values. Further, a comparison of the BP86/TZVP level IR and Raman spectra of α-helical (alanine){sub 20} and its N-deuterated derivative shows an excellent agreement with the existing experimental spectra. In view of the requirement of only MTA-based calculations and the ability of FIF to work at any level of theory, the current methodology provides a cost-effective solution for obtaining accurate spectra of large molecular systems.

Molecular dynamics for irradiation driven chemistry: application to the FEBID process*

Science.gov (United States)

Sushko, Gennady B.; Solov'yov, Ilia A.; Solov'yov, Andrey V.

2016-10-01

A new molecular dynamics (MD) approach for computer simulations of irradiation driven chemical transformations of complex molecular systems is suggested. The approach is based on the fact that irradiation induced quantum transformations can often be treated as random, fast and local processes involving small molecules or molecular fragments. We advocate that the quantum transformations, such as molecular bond breaks, creation and annihilation of dangling bonds, electronic charge redistributions, changes in molecular topologies, etc., could be incorporated locally into the molecular force fields that describe the classical MD of complex molecular systems under irradiation. The proposed irradiation driven molecular dynamics (IDMD) methodology is designed for the molecular level description of the irradiation driven chemistry. The IDMD approach is implemented into the MBN Explorer software package capable to operate with a large library of classical potentials, many-body force fields and their combinations. IDMD opens a broad range of possibilities for modelling of irradiation driven modifications and chemistry of complex molecular systems ranging from radiotherapy cancer treatments to the modern technologies such as focused electron beam deposition (FEBID). As an example, the new methodology is applied for studying the irradiation driven chemistry caused by FEBID of tungsten hexacarbonyl W(CO)6 precursor molecules on a hydroxylated SiO2 surface. It is demonstrated that knowing the interaction parameters for the fragments of the molecular system arising in the course of irradiation one can reproduce reasonably well experimental observations and make predictions about the morphology and molecular composition of nanostructures that emerge on the surface during the FEBID process.

Prediction of mechanical properties for hexagonal boron nitride nanosheets using molecular mechanics model

Energy Technology Data Exchange (ETDEWEB)

Natsuki, Toshiaki [Shinshu University, Faculty of Textile Science and Technology, Ueda (Japan); Shinshu University, Institute of Carbon Science and Technology, Nagano (Japan); Natsuki, Jun [Shinshu University, Institute of Carbon Science and Technology, Nagano (Japan)

2017-04-15

Mechanical behaviors of nanomaterials are not easy to be evaluated in the laboratory because of their extremely small size and difficulty controlling. Thus, a suitable model for the estimation of the mechanical properties for nanomaterials becomes very important. In this study, the elastic properties of boron nitride (BN) nanosheets, including the elastic modulus, the shear modulus, and the Poisson's ratio, are predicted using a molecular mechanics model. The molecular mechanics force filed is established to directly incorporate the Morse potential function into the constitutive model of nanostructures. According to the molecular mechanics model, the chirality effect of hexagonal BN nanosheets on the elastic modulus is investigated through a closed-form solution. The simulated result shows that BN nanosheets exhibit an isotropic elastic property. The present analysis yields a set of very simple formulas and is able to be served as a good approximation on the mechanical properties for the BN nanosheets. (orig.)

Prediction of mechanical properties for hexagonal boron nitride nanosheets using molecular mechanics model

International Nuclear Information System (INIS)

Natsuki, Toshiaki; Natsuki, Jun

2017-01-01

Mechanical behaviors of nanomaterials are not easy to be evaluated in the laboratory because of their extremely small size and difficulty controlling. Thus, a suitable model for the estimation of the mechanical properties for nanomaterials becomes very important. In this study, the elastic properties of boron nitride (BN) nanosheets, including the elastic modulus, the shear modulus, and the Poisson's ratio, are predicted using a molecular mechanics model. The molecular mechanics force filed is established to directly incorporate the Morse potential function into the constitutive model of nanostructures. According to the molecular mechanics model, the chirality effect of hexagonal BN nanosheets on the elastic modulus is investigated through a closed-form solution. The simulated result shows that BN nanosheets exhibit an isotropic elastic property. The present analysis yields a set of very simple formulas and is able to be served as a good approximation on the mechanical properties for the BN nanosheets. (orig.)

Application of various FLD modelling approaches

Science.gov (United States)

Banabic, D.; Aretz, H.; Paraianu, L.; Jurco, P.

2005-07-01

This paper focuses on a comparison between different modelling approaches to predict the forming limit diagram (FLD) for sheet metal forming under a linear strain path using the recently introduced orthotropic yield criterion BBC2003 (Banabic D et al 2005 Int. J. Plasticity 21 493-512). The FLD models considered here are a finite element based approach, the well known Marciniak-Kuczynski model, the modified maximum force criterion according to Hora et al (1996 Proc. Numisheet'96 Conf. (Dearborn/Michigan) pp 252-6), Swift's diffuse (Swift H W 1952 J. Mech. Phys. Solids 1 1-18) and Hill's classical localized necking approach (Hill R 1952 J. Mech. Phys. Solids 1 19-30). The FLD of an AA5182-O aluminium sheet alloy has been determined experimentally in order to quantify the predictive capabilities of the models mentioned above.

A neural network approach to the study of internal energy flow in molecular systems

International Nuclear Information System (INIS)

Sumpter, B.G.; Getino, C.; Noid, D.W.

1992-01-01

Neural networks are used to develop a new technique for efficient analysis of data obtained from molecular-dynamics calculations and is applied to the study of mode energy flow in molecular systems. The methodology is based on teaching an appropriate neural network the relationship between phase-space points along a classical trajectory and mode energies for stretch, bend, and torsion vibrations. Results are discussed for reactive and nonreactive classical trajectories of hydrogen peroxide (H 2 O 2 ) on a semiempirical potential-energy surface. The neural-network approach is shown to produce reasonably accurate values for the mode energies, with average errors between 1% and 12%, and is applicable to any region within the 24-dimensional phase space of H 2 O 2 . In addition, the generic knowledge learned by the neural network allows calculations to be made for other molecular systems. Results are discussed for a series of tetratomic molecules: H 2 X 2 , X=C, N, O, Si, S, or Se, and preliminary results are given for energy flow predictions in macromolecules

A Unified Approach to Modeling and Programming

DEFF Research Database (Denmark)

Madsen, Ole Lehrmann; Møller-Pedersen, Birger

2010-01-01

of this paper is to go back to the future and get inspiration from SIMULA and propose a unied approach. In addition to reintroducing the contributions of SIMULA and the Scandinavian approach to object-oriented programming, we do this by discussing a number of issues in modeling and programming and argue3 why we......SIMULA was a language for modeling and programming and provided a unied approach to modeling and programming in contrast to methodologies based on structured analysis and design. The current development seems to be going in the direction of separation of modeling and programming. The goal...

Theoretical and experimental approach on the molecular interactions of the DL-Alanine with an electrolytic environment

Science.gov (United States)

Cantero-López, Plinio; Yañez-Osses, Osvaldo; Páez-Meza, Manuel Silvestre; López, Johana E.; Páez-Hernández, Dayán; Arratia-Pérez, Ramiro

2017-11-01

The molecular interactions that promote the stability of proteins and amino acids in saline solutions is a central topic of molecular biophysics. However, a well-supported molecular picture of the phenomena has not been established yet. In this paper, we studied as model system the mix between DL-Alanine in aqueous solutions of STP (Na2S2O3·5H2O) at different temperatures, from volumetric and viscometric properties. The thermophysical properties obtained indicate the presence of a strong preferential solvation, structure-making action and a possible salt in effect. Quantum chemical calculations and molecular dynamic (MD) simulations provide a new insight to support these arguments.

Technical note: Comparison of methane ebullition modelling approaches used in terrestrial wetland models

Science.gov (United States)

Peltola, Olli; Raivonen, Maarit; Li, Xuefei; Vesala, Timo

2018-02-01

Emission via bubbling, i.e. ebullition, is one of the main methane (CH4) emission pathways from wetlands to the atmosphere. Direct measurement of gas bubble formation, growth and release in the peat-water matrix is challenging and in consequence these processes are relatively unknown and are coarsely represented in current wetland CH4 emission models. In this study we aimed to evaluate three ebullition modelling approaches and their effect on model performance. This was achieved by implementing the three approaches in one process-based CH4 emission model. All the approaches were based on some kind of threshold: either on CH4 pore water concentration (ECT), pressure (EPT) or free-phase gas volume (EBG) threshold. The model was run using 4 years of data from a boreal sedge fen and the results were compared with eddy covariance measurements of CH4 fluxes.Modelled annual CH4 emissions were largely unaffected by the different ebullition modelling approaches; however, temporal variability in CH4 emissions varied an order of magnitude between the approaches. Hence the ebullition modelling approach drives the temporal variability in modelled CH4 emissions and therefore significantly impacts, for instance, high-frequency (daily scale) model comparison and calibration against measurements. The modelling approach based on the most recent knowledge of the ebullition process (volume threshold, EBG) agreed the best with the measured fluxes (R2 = 0.63) and hence produced the most reasonable results, although there was a scale mismatch between the measurements (ecosystem scale with heterogeneous ebullition locations) and model results (single horizontally homogeneous peat column). The approach should be favoured over the two other more widely used ebullition modelling approaches and researchers are encouraged to implement it into their CH4 emission models.

Structure-Activity Relationships on the Molecular Descriptors Family Project at the End

Directory of Open Access Journals (Sweden)

Lorentz JÄNTSCHI

2007-12-01

Full Text Available Molecular Descriptors Family (MDF on the Structure-Activity Relationships (SAR, a promising approach in investigation and quantification of the link between 2D and 3D structural information and the activity, and its potential in the analysis of the biological active compounds is summarized. The approach, attempts to correlate molecular descriptors family generated and calculated on a set of biological active compounds with their observed activity. The estimation as well as prediction abilities of the approach are presented. The obtained MDF SAR models can be used to predict the biological activity of unknown substrates in a series of compounds.

Animal models and therapeutic molecular targets of cancer: utility and limitations

Directory of Open Access Journals (Sweden)

Cekanova M

2014-10-01

Full Text Available Maria Cekanova, Kusum Rathore Department of Small Animal Clinical Sciences, College of Veterinary Medicine, The University of Tennessee, Knoxville, TN, USA Abstract: Cancer is the term used to describe over 100 diseases that share several common hallmarks. Despite prevention, early detection, and novel therapies, cancer is still the second leading cause of death in the USA. Successful bench-to-bedside translation of basic scientific findings about cancer into therapeutic interventions for patients depends on the selection of appropriate animal experimental models. Cancer research uses animal and human cancer cell lines in vitro to study biochemical pathways in these cancer cells. In this review, we summarize the important animal models of cancer with focus on their advantages and limitations. Mouse cancer models are well known, and are frequently used for cancer research. Rodent models have revolutionized our ability to study gene and protein functions in vivo and to better understand their molecular pathways and mechanisms. Xenograft and chemically or genetically induced mouse cancers are the most commonly used rodent cancer models. Companion animals with spontaneous neoplasms are still an underexploited tool for making rapid advances in human and veterinary cancer therapies by testing new drugs and delivery systems that have shown promise in vitro and in vivo in mouse models. Companion animals have a relatively high incidence of cancers, with biological behavior, response to therapy, and response to cytotoxic agents similar to those in humans. Shorter overall lifespan and more rapid disease progression are factors contributing to the advantages of a companion animal model. In addition, the current focus is on discovering molecular targets for new therapeutic drugs to improve survival and quality of life in cancer patients. Keywords: mouse cancer model, companion animal cancer model, dogs, cats, molecular targets

MOLECULAR VALIDATED MODEL FOR ADSORPTION OF PROTONATED DYE ON LDH

Directory of Open Access Journals (Sweden)

B. M. Braga

Full Text Available Abstract Hydrotalcite-like compounds are anionic clays of scientific and technological interest for their use as ion exchange materials, catalysts and modified electrodes. Surface phenomenon are important for all these applications. Although conventional analytical methods have enabled progress in understanding the behavior of anionic clays in solution, an evaluation at the atomic scale of the dynamics of their ionic interactions has never been performed. Molecular simulation has become an extremely useful tool to provide this perspective. Our purpose is to validate a simplified model for the adsorption of 5-benzoyl-4-hydroxy-2-methoxy-benzenesulfonic acid (MBSA, a prototype molecule of anionic dyes, onto a hydrotalcite surface. Monte Carlo simulations were performed in the canonical ensemble with MBSA ions and a pore model of hydrotalcite using UFF and ClayFF force fields. The proposed molecular model has allowed us to reproduce experimental data of atomic force microscopy. Influences of protonation during the adsorption process are also presented.

Molecular and morphological approaches for species delimitation and hybridization investigations of two Cichla species

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Andrea A. F. Mourão

Full Text Available ABSTRACT The hybridization is a widely-discussed issue in several studies with fish species. For some authors, hybridization may be related with diversification and speciation of several groups, or also with the extinction of populations or species. Difficulties to differentiate species and hybrids may be a problem to correctly apply a management of wild species, because hybrid lineages, especially the advanced ones, may resemble the parental species. The genus Cichla Bloch & Schneider, 1801 constitutes an interesting experimental model, considering that hybridization and taxonomic uncertainties hinder a correct identification. Considering these problems, in this study, we developed genetic methodologies and applied meristic and morphometric approaches in wild samples in order to identify species and for test a possible hybridization between Cichla kelberi Kullander & Ferreira, 2006 and Cichla piquiti Kullander & Ferreira, 2006. For this, C. kelberi, C. piquiti and potential hybrid ( carijó individuals were collected in Paraná and Tietê rivers (SP, Brazil. For meristic and morphometric methods, the individuals were analyzed using the statistical software Pcord 5:31, while for molecular methods, primers for PCR-multiplex were designed and enzyme for PCR-RFLP were selected, under the species-specific nucleotide. All results indicated that the carijó is not an interspecific hybrid, because it presented identical genetic pattern and morphology closed to C. piquiti. Thus, we propose that carijó is a C. piquiti morphotype. In addition, this study promotes a new molecular tool that could be used in future research, monitoring and management programs of the genus Cichla.

Exploring the boundaries of molecular modeling : a study of nanochannels and transmembrane proteins

NARCIS (Netherlands)

Spijker, P.

2009-01-01

Many interesting physical and biological phenomena can be investigated using molecular modeling techniques, either theoretically or by using computer simulation methods, such as molecular dynamics and Monte Carlo simulations. Due to the increasing power of computer processing units, these simulation

Computer aided molecular design with combined molecular modeling and group contribution

DEFF Research Database (Denmark)

Harper, Peter Mathias; Gani, Rafiqul; Kolar, Petr

1999-01-01

Computer-aided molecular design (CAMD) provides a means for determining molecules or mixtures of molecules (CAMMD) having a desirable set of physicochemical properties. The application range of CAMD is restricted due to limitations on the complexity of the generated molecular structures and on th......Computer-aided molecular design (CAMD) provides a means for determining molecules or mixtures of molecules (CAMMD) having a desirable set of physicochemical properties. The application range of CAMD is restricted due to limitations on the complexity of the generated molecular structures...

HIV-1 entry inhibition by small-molecule CCR5 antagonists: A combined molecular modeling and mutant study using a high-throughput assay

International Nuclear Information System (INIS)