Probabilistic validation of protein NMR chemical shift assignments

International Nuclear Information System (INIS)

Dashti, Hesam; Tonelli, Marco; Lee, Woonghee; Westler, William M.; Cornilescu, Gabriel; Ulrich, Eldon L.; Markley, John L.

2016-01-01

Data validation plays an important role in ensuring the reliability and reproducibility of studies. NMR investigations of the functional properties, dynamics, chemical kinetics, and structures of proteins depend critically on the correctness of chemical shift assignments. We present a novel probabilistic method named ARECA for validating chemical shift assignments that relies on the nuclear Overhauser effect data. ARECA has been evaluated through its application to 26 case studies and has been shown to be complementary to, and usually more reliable than, approaches based on chemical shift databases. ARECA is available online at http://areca.nmrfam.wisc.edu/ http://areca.nmrfam.wisc.edu/

Probabilistic validation of protein NMR chemical shift assignments

Energy Technology Data Exchange (ETDEWEB)

Dashti, Hesam [University of Wisconsin-Madison, Graduate Program in Biophysics, Biochemistry Department (United States); Tonelli, Marco; Lee, Woonghee; Westler, William M.; Cornilescu, Gabriel [University of Wisconsin-Madison, Biochemistry Department, National Magnetic Resonance Facility at Madison (United States); Ulrich, Eldon L. [University of Wisconsin-Madison, BioMagResBank, Biochemistry Department (United States); Markley, John L., E-mail: markley@nmrfam.wisc.edu, E-mail: jmarkley@wisc.edu [University of Wisconsin-Madison, Biochemistry Department, National Magnetic Resonance Facility at Madison (United States)

2016-01-15

Data validation plays an important role in ensuring the reliability and reproducibility of studies. NMR investigations of the functional properties, dynamics, chemical kinetics, and structures of proteins depend critically on the correctness of chemical shift assignments. We present a novel probabilistic method named ARECA for validating chemical shift assignments that relies on the nuclear Overhauser effect data. ARECA has been evaluated through its application to 26 case studies and has been shown to be complementary to, and usually more reliable than, approaches based on chemical shift databases. ARECA is available online at http://areca.nmrfam.wisc.edu/ http://areca.nmrfam.wisc.edu/.

MolProbity: all-atom structure validation for macromolecular crystallography

International Nuclear Information System (INIS)

Chen, Vincent B.; Arendall, W. Bryan III; Headd, Jeffrey J.; Keedy, Daniel A.; Immormino, Robert M.; Kapral, Gary J.; Murray, Laura W.; Richardson, Jane S.; Richardson, David C.

2010-01-01

MolProbity structure validation will diagnose most local errors in macromolecular crystal structures and help to guide their correction. MolProbity is a structure-validation web service that provides broad-spectrum solidly based evaluation of model quality at both the global and local levels for both proteins and nucleic acids. It relies heavily on the power and sensitivity provided by optimized hydrogen placement and all-atom contact analysis, complemented by updated versions of covalent-geometry and torsion-angle criteria. Some of the local corrections can be performed automatically in MolProbity and all of the diagnostics are presented in chart and graphical forms that help guide manual rebuilding. X-ray crystallography provides a wealth of biologically important molecular data in the form of atomic three-dimensional structures of proteins, nucleic acids and increasingly large complexes in multiple forms and states. Advances in automation, in everything from crystallization to data collection to phasing to model building to refinement, have made solving a structure using crystallography easier than ever. However, despite these improvements, local errors that can affect biological interpretation are widespread at low resolution and even high-resolution structures nearly all contain at least a few local errors such as Ramachandran outliers, flipped branched protein side chains and incorrect sugar puckers. It is critical both for the crystallographer and for the end user that there are easy and reliable methods to diagnose and correct these sorts of errors in structures. MolProbity is the authors’ contribution to helping solve this problem and this article reviews its general capabilities, reports on recent enhancements and usage, and presents evidence that the resulting improvements are now beneficially affecting the global database

Annotating the protein-RNA interaction sites in proteins using evolutionary information and protein backbone structure.

Science.gov (United States)

Li, Tao; Li, Qian-Zhong

2012-11-07

RNA-protein interactions play important roles in various biological processes. The precise detection of RNA-protein interaction sites is very important for understanding essential biological processes and annotating the function of the proteins. In this study, based on various features from amino acid sequence and structure, including evolutionary information, solvent accessible surface area and torsion angles (φ, ψ) in the backbone structure of the polypeptide chain, a computational method for predicting RNA-binding sites in proteins is proposed. When the method is applied to predict RNA-binding sites in three datasets: RBP86 containing 86 protein chains, RBP107 containing 107 proteins chains and RBP109 containing 109 proteins chains, better sensitivities and specificities are obtained compared to previously published methods in five-fold cross-validation tests. In order to make further examination for the efficiency of our method, the RBP107 dataset is used as training set, RBP86 and RBP109 datasets are used as the independent test sets. In addition, as examples of our prediction, RNA-binding sites in a few proteins are presented. The annotated results are consistent with the PDB annotation. These results show that our method is useful for annotating RNA binding sites of novel proteins.

Protein Structure Prediction by Protein Threading

Science.gov (United States)

Xu, Ying; Liu, Zhijie; Cai, Liming; Xu, Dong

The seminal work of Bowie, Lüthy, and Eisenberg (Bowie et al., 1991) on "the inverse protein folding problem" laid the foundation of protein structure prediction by protein threading. By using simple measures for fitness of different amino acid types to local structural environments defined in terms of solvent accessibility and protein secondary structure, the authors derived a simple and yet profoundly novel approach to assessing if a protein sequence fits well with a given protein structural fold. Their follow-up work (Elofsson et al., 1996; Fischer and Eisenberg, 1996; Fischer et al., 1996a,b) and the work by Jones, Taylor, and Thornton (Jones et al., 1992) on protein fold recognition led to the development of a new brand of powerful tools for protein structure prediction, which we now term "protein threading." These computational tools have played a key role in extending the utility of all the experimentally solved structures by X-ray crystallography and nuclear magnetic resonance (NMR), providing structural models and functional predictions for many of the proteins encoded in the hundreds of genomes that have been sequenced up to now.

MSX-3D: a tool to validate 3D protein models using mass spectrometry.

Science.gov (United States)

Heymann, Michaël; Paramelle, David; Subra, Gilles; Forest, Eric; Martinez, Jean; Geourjon, Christophe; Deléage, Gilbert

2008-12-01

The technique of chemical cross-linking followed by mass spectrometry has proven to bring valuable information about the protein structure and interactions between proteic subunits. It is an effective and efficient way to experimentally investigate some aspects of a protein structure when NMR and X-ray crystallography data are lacking. We introduce MSX-3D, a tool specifically geared to validate protein models using mass spectrometry. In addition to classical peptides identifications, it allows an interactive 3D visualization of the distance constraints derived from a cross-linking experiment. Freely available at http://proteomics-pbil.ibcp.fr

Structural deformation upon protein-protein interaction: a structural alphabet approach.

Science.gov (United States)

Martin, Juliette; Regad, Leslie; Lecornet, Hélène; Camproux, Anne-Claude

2008-02-28

In a number of protein-protein complexes, the 3D structures of bound and unbound partners significantly differ, supporting the induced fit hypothesis for protein-protein binding. In this study, we explore the induced fit modifications on a set of 124 proteins available in both bound and unbound forms, in terms of local structure. The local structure is described thanks to a structural alphabet of 27 structural letters that allows a detailed description of the backbone. Using a control set to distinguish induced fit from experimental error and natural protein flexibility, we show that the fraction of structural letters modified upon binding is significantly greater than in the control set (36% versus 28%). This proportion is even greater in the interface regions (41%). Interface regions preferentially involve coils. Our analysis further reveals that some structural letters in coil are not favored in the interface. We show that certain structural letters in coil are particularly subject to modifications at the interface, and that the severity of structural change also varies. These information are used to derive a structural letter substitution matrix that summarizes the local structural changes observed in our data set. We also illustrate the usefulness of our approach to identify common binding motifs in unrelated proteins. Our study provides qualitative information about induced fit. These results could be of help for flexible docking.

Structural deformation upon protein-protein interaction: A structural alphabet approach

Directory of Open Access Journals (Sweden)

Lecornet Hélène

2008-02-01

Full Text Available Abstract Background In a number of protein-protein complexes, the 3D structures of bound and unbound partners significantly differ, supporting the induced fit hypothesis for protein-protein binding. Results In this study, we explore the induced fit modifications on a set of 124 proteins available in both bound and unbound forms, in terms of local structure. The local structure is described thanks to a structural alphabet of 27 structural letters that allows a detailed description of the backbone. Using a control set to distinguish induced fit from experimental error and natural protein flexibility, we show that the fraction of structural letters modified upon binding is significantly greater than in the control set (36% versus 28%. This proportion is even greater in the interface regions (41%. Interface regions preferentially involve coils. Our analysis further reveals that some structural letters in coil are not favored in the interface. We show that certain structural letters in coil are particularly subject to modifications at the interface, and that the severity of structural change also varies. These information are used to derive a structural letter substitution matrix that summarizes the local structural changes observed in our data set. We also illustrate the usefulness of our approach to identify common binding motifs in unrelated proteins. Conclusion Our study provides qualitative information about induced fit. These results could be of help for flexible docking.

The AUDANA algorithm for automated protein 3D structure determination from NMR NOE data

Energy Technology Data Exchange (ETDEWEB)

Lee, Woonghee, E-mail: whlee@nmrfam.wisc.edu [University of Wisconsin-Madison, National Magnetic Resonance Facility at Madison and Biochemistry Department (United States); Petit, Chad M. [University of Alabama at Birmingham, Department of Biochemistry and Molecular Genetics (United States); Cornilescu, Gabriel; Stark, Jaime L.; Markley, John L., E-mail: markley@nmrfam.wisc.edu [University of Wisconsin-Madison, National Magnetic Resonance Facility at Madison and Biochemistry Department (United States)

2016-06-15

We introduce AUDANA (Automated Database-Assisted NOE Assignment), an algorithm for determining three-dimensional structures of proteins from NMR data that automates the assignment of 3D-NOE spectra, generates distance constraints, and conducts iterative high temperature molecular dynamics and simulated annealing. The protein sequence, chemical shift assignments, and NOE spectra are the only required inputs. Distance constraints generated automatically from ambiguously assigned NOE peaks are validated during the structure calculation against information from an enlarged version of the freely available PACSY database that incorporates information on protein structures deposited in the Protein Data Bank (PDB). This approach yields robust sets of distance constraints and 3D structures. We evaluated the performance of AUDANA with input data for 14 proteins ranging in size from 6 to 25 kDa that had 27–98 % sequence identity to proteins in the database. In all cases, the automatically calculated 3D structures passed stringent validation tests. Structures were determined with and without database support. In 9/14 cases, database support improved the agreement with manually determined structures in the PDB and in 11/14 cases, database support lowered the r.m.s.d. of the family of 20 structural models.

The AUDANA algorithm for automated protein 3D structure determination from NMR NOE data

International Nuclear Information System (INIS)

Lee, Woonghee; Petit, Chad M.; Cornilescu, Gabriel; Stark, Jaime L.; Markley, John L.

2016-01-01

We introduce AUDANA (Automated Database-Assisted NOE Assignment), an algorithm for determining three-dimensional structures of proteins from NMR data that automates the assignment of 3D-NOE spectra, generates distance constraints, and conducts iterative high temperature molecular dynamics and simulated annealing. The protein sequence, chemical shift assignments, and NOE spectra are the only required inputs. Distance constraints generated automatically from ambiguously assigned NOE peaks are validated during the structure calculation against information from an enlarged version of the freely available PACSY database that incorporates information on protein structures deposited in the Protein Data Bank (PDB). This approach yields robust sets of distance constraints and 3D structures. We evaluated the performance of AUDANA with input data for 14 proteins ranging in size from 6 to 25 kDa that had 27–98 % sequence identity to proteins in the database. In all cases, the automatically calculated 3D structures passed stringent validation tests. Structures were determined with and without database support. In 9/14 cases, database support improved the agreement with manually determined structures in the PDB and in 11/14 cases, database support lowered the r.m.s.d. of the family of 20 structural models.

Protein Secondary Structure Prediction Using AutoEncoder Network and Bayes Classifier

Science.gov (United States)

Wang, Leilei; Cheng, Jinyong

2018-03-01

Protein secondary structure prediction is belong to bioinformatics,and it's important in research area. In this paper, we propose a new prediction way of protein using bayes classifier and autoEncoder network. Our experiments show some algorithms including the construction of the model, the classification of parameters and so on. The data set is a typical CB513 data set for protein. In terms of accuracy, the method is the cross validation based on the 3-fold. Then we can get the Q3 accuracy. Paper results illustrate that the autoencoder network improved the prediction accuracy of protein secondary structure.

ValidatorDB: database of up-to-date validation results for ligands and non-standard residues from the Protein Data Bank.

Science.gov (United States)

Sehnal, David; Svobodová Vařeková, Radka; Pravda, Lukáš; Ionescu, Crina-Maria; Geidl, Stanislav; Horský, Vladimír; Jaiswal, Deepti; Wimmerová, Michaela; Koča, Jaroslav

2015-01-01

Following the discovery of serious errors in the structure of biomacromolecules, structure validation has become a key topic of research, especially for ligands and non-standard residues. ValidatorDB (freely available at http://ncbr.muni.cz/ValidatorDB) offers a new step in this direction, in the form of a database of validation results for all ligands and non-standard residues from the Protein Data Bank (all molecules with seven or more heavy atoms). Model molecules from the wwPDB Chemical Component Dictionary are used as reference during validation. ValidatorDB covers the main aspects of validation of annotation, and additionally introduces several useful validation analyses. The most significant is the classification of chirality errors, allowing the user to distinguish between serious issues and minor inconsistencies. Other such analyses are able to report, for example, completely erroneous ligands, alternate conformations or complete identity with the model molecules. All results are systematically classified into categories, and statistical evaluations are performed. In addition to detailed validation reports for each molecule, ValidatorDB provides summaries of the validation results for the entire PDB, for sets of molecules sharing the same annotation (three-letter code) or the same PDB entry, and for user-defined selections of annotations or PDB entries. © The Author(s) 2014. Published by Oxford University Press on behalf of Nucleic Acids Research.

Accuracy issues involved in modeling in vivo protein structures using PM7.

Science.gov (United States)

Martin, Benjamin P; Brandon, Christopher J; Stewart, James J P; Braun-Sand, Sonja B

2015-08-01

Using the semiempirical method PM7, an attempt has been made to quantify the error in prediction of the in vivo structure of proteins relative to X-ray structures. Three important contributory factors are the experimental limitations of X-ray structures, the difference between the crystal and solution environments, and the errors due to PM7. The geometries of 19 proteins from the Protein Data Bank that had small R values, that is, high accuracy structures, were optimized and the resulting drop in heat of formation was calculated. Analysis of the changes showed that about 10% of this decrease in heat of formation was caused by faults in PM7, the balance being attributable to the X-ray structure and the difference between the crystal and solution environments. A previously unknown fault in PM7 was revealed during tests to validate the geometries generated using PM7. Clashscores generated by the Molprobity molecular mechanics structure validation program showed that PM7 was predicting unrealistically close contacts between nonbonding atoms in regions where the local geometry is dominated by very weak noncovalent interactions. The origin of this fault was traced to an underestimation of the core-core repulsion between atoms at distances smaller than the equilibrium distance. © 2015 The Authors. Proteins: Structure, Function, and Bioinformatics Published By Wiley Periodicals, Inc.

Benchmarking protein classification algorithms via supervised cross-validation

NARCIS (Netherlands)

Kertész-Farkas, A.; Dhir, S.; Sonego, P.; Pacurar, M.; Netoteia, S.; Nijveen, H.; Kuzniar, A.; Leunissen, J.A.M.; Kocsor, A.; Pongor, S.

2008-01-01

Development and testing of protein classification algorithms are hampered by the fact that the protein universe is characterized by groups vastly different in the number of members, in average protein size, similarity within group, etc. Datasets based on traditional cross-validation (k-fold,

Protein structure validation and refinement using amide proton chemical shifts derived from quantum mechanics

DEFF Research Database (Denmark)

Christensen, Anders Steen; Linnet, Troels Emtekær; Borg, Mikael

2013-01-01

We present the ProCS method for the rapid and accurate prediction of protein backbone amide proton chemical shifts - sensitive probes of the geometry of key hydrogen bonds that determine protein structure. ProCS is parameterized against quantum mechanical (QM) calculations and reproduces high level...

Predicting DNA-binding proteins and binding residues by complex structure prediction and application to human proteome.

Directory of Open Access Journals (Sweden)

Huiying Zhao

Full Text Available As more and more protein sequences are uncovered from increasingly inexpensive sequencing techniques, an urgent task is to find their functions. This work presents a highly reliable computational technique for predicting DNA-binding function at the level of protein-DNA complex structures, rather than low-resolution two-state prediction of DNA-binding as most existing techniques do. The method first predicts protein-DNA complex structure by utilizing the template-based structure prediction technique HHblits, followed by binding affinity prediction based on a knowledge-based energy function (Distance-scaled finite ideal-gas reference state for protein-DNA interactions. A leave-one-out cross validation of the method based on 179 DNA-binding and 3797 non-binding protein domains achieves a Matthews correlation coefficient (MCC of 0.77 with high precision (94% and high sensitivity (65%. We further found 51% sensitivity for 82 newly determined structures of DNA-binding proteins and 56% sensitivity for the human proteome. In addition, the method provides a reasonably accurate prediction of DNA-binding residues in proteins based on predicted DNA-binding complex structures. Its application to human proteome leads to more than 300 novel DNA-binding proteins; some of these predicted structures were validated by known structures of homologous proteins in APO forms. The method [SPOT-Seq (DNA] is available as an on-line server at http://sparks-lab.org.

APSY-NMR for protein backbone assignment in high-throughput structural biology

Energy Technology Data Exchange (ETDEWEB)

Dutta, Samit Kumar; Serrano, Pedro; Proudfoot, Andrew; Geralt, Michael [The Scripps Research Institute, Department of Integrative Structural and Computational Biology (United States); Pedrini, Bill [Paul Scherrer Institute (PSI), SwissFEL Project (Switzerland); Herrmann, Torsten [Université de Lyon, Institut des Sciences Analytiques, Centre de RMN à Très Hauts Champs, UMR 5280 CNRS, ENS Lyon, UCB Lyon 1 (France); Wüthrich, Kurt, E-mail: wuthrich@scripps.edu [The Scripps Research Institute, Department of Integrative Structural and Computational Biology (United States)

2015-01-15

A standard set of three APSY-NMR experiments has been used in daily practice to obtain polypeptide backbone NMR assignments in globular proteins with sizes up to about 150 residues, which had been identified as targets for structure determination by the Joint Center for Structural Genomics (JCSG) under the auspices of the Protein Structure Initiative (PSI). In a representative sample of 30 proteins, initial fully automated data analysis with the software UNIO-MATCH-2014 yielded complete or partial assignments for over 90 % of the residues. For most proteins the APSY data acquisition was completed in less than 30 h. The results of the automated procedure provided a basis for efficient interactive validation and extension to near-completion of the assignments by reference to the same 3D heteronuclear-resolved [{sup 1}H,{sup 1}H]-NOESY spectra that were subsequently used for the collection of conformational constraints. High-quality structures were obtained for all 30 proteins, using the J-UNIO protocol, which includes extensive automation of NMR structure determination.

Correlated mutations in protein sequences: Phylogenetic and structural effects

Energy Technology Data Exchange (ETDEWEB)

Lapedes, A.S. [Los Alamos National Lab., NM (United States). Theoretical Div.]|[Santa Fe Inst., NM (United States); Giraud, B.G. [C.E.N. Saclay, Gif/Yvette (France). Service Physique Theorique; Liu, L.C. [Los Alamos National Lab., NM (United States). Theoretical Div.; Stormo, G.D. [Univ. of Colorado, Boulder, CO (United States). Dept. of Molecular, Cellular and Developmental Biology

1998-12-01

Covariation analysis of sets of aligned sequences for RNA molecules is relatively successful in elucidating RNA secondary structure, as well as some aspects of tertiary structure. Covariation analysis of sets of aligned sequences for protein molecules is successful in certain instances in elucidating certain structural and functional links, but in general, pairs of sites displaying highly covarying mutations in protein sequences do not necessarily correspond to sites that are spatially close in the protein structure. In this paper the authors identify two reasons why naive use of covariation analysis for protein sequences fails to reliably indicate sequence positions that are spatially proximate. The first reason involves the bias introduced in calculation of covariation measures due to the fact that biological sequences are generally related by a non-trivial phylogenetic tree. The authors present a null-model approach to solve this problem. The second reason involves linked chains of covariation which can result in pairs of sites displaying significant covariation even though they are not spatially proximate. They present a maximum entropy solution to this classic problem of causation versus correlation. The methodologies are validated in simulation.

Protein Structure Validation and Refinement Using Chemical Shifts Derived from Quantum Mechanics

DEFF Research Database (Denmark)

Bratholm, Lars Andersen

to within 3 A. Furthermore, a fast quantum mechanics based chemical shift predictor was developed together with methodology for using chemical shifts in structure simulations. The developed predictor was used for renement of several protein structures and for reducing the computational cost of quantum...... mechanics / molecular mechanics (QM/MM) computations of chemical shieldings. Several improvements to the predictor is ongoing, where among other things, kernel based machine learning techniques have successfully been used to improve the quantum mechanical level of theory used in the predictions....

Functional structural motifs for protein-ligand, protein-protein, and protein-nucleic acid interactions and their connection to supersecondary structures.

Science.gov (United States)

Kinjo, Akira R; Nakamura, Haruki

2013-01-01

Protein functions are mediated by interactions between proteins and other molecules. One useful approach to analyze protein functions is to compare and classify the structures of interaction interfaces of proteins. Here, we describe the procedures for compiling a database of interface structures and efficiently comparing the interface structures. To do so requires a good understanding of the data structures of the Protein Data Bank (PDB). Therefore, we also provide a detailed account of the PDB exchange dictionary necessary for extracting data that are relevant for analyzing interaction interfaces and secondary structures. We identify recurring structural motifs by classifying similar interface structures, and we define a coarse-grained representation of supersecondary structures (SSS) which represents a sequence of two or three secondary structure elements including their relative orientations as a string of four to seven letters. By examining the correspondence between structural motifs and SSS strings, we show that no SSS string has particularly high propensity to be found interaction interfaces in general, indicating any SSS can be used as a binding interface. When individual structural motifs are examined, there are some SSS strings that have high propensity for particular groups of structural motifs. In addition, it is shown that while the SSS strings found in particular structural motifs for nonpolymer and protein interfaces are as abundant as in other structural motifs that belong to the same subunit, structural motifs for nucleic acid interfaces exhibit somewhat stronger preference for SSS strings. In regard to protein folds, many motif-specific SSS strings were found across many folds, suggesting that SSS may be a useful description to investigate the universality of ligand binding modes.

Structural system identification: Structural dynamics model validation

Energy Technology Data Exchange (ETDEWEB)

Red-Horse, J.R.

1997-04-01

Structural system identification is concerned with the development of systematic procedures and tools for developing predictive analytical models based on a physical structure`s dynamic response characteristics. It is a multidisciplinary process that involves the ability (1) to define high fidelity physics-based analysis models, (2) to acquire accurate test-derived information for physical specimens using diagnostic experiments, (3) to validate the numerical simulation model by reconciling differences that inevitably exist between the analysis model and the experimental data, and (4) to quantify uncertainties in the final system models and subsequent numerical simulations. The goal of this project was to develop structural system identification techniques and software suitable for both research and production applications in code and model validation.

Testing of the preliminary OMERACT validation criteria for a biomarker to be regarded as reflecting structural damage endpoints in rheumatoid arthritis clinical trials: the example of C-reactive protein

NARCIS (Netherlands)

Keeling, Stephanie O.; Landewe, Robert; van der Heijde, Desiree; Bathon, Joan; Boers, Maarten; Garnero, Patrick; Geusens, Piet; El-Gabalawy, Hani; Inman, Robert D.; Kraus, Virginia B.; Kvien, Tore K.; Mease, Philip J.; Ostergaard, Mikkel; Ritchlin, Chris; Syversen, Silje W.; Maksymowych, Walter P.

2007-01-01

A list of 14 criteria for guiding the validation of a soluble biomarker as reflecting structural damage endpoints in rheumatoid arthritis (RA) clinical trials was drafted by an international working group after a Delphi consensus exercise. C-reactive protein (CRP), a soluble biomarker extensively

Electrostatics of cysteine residues in proteins: Parameterization and validation of a simple model

Science.gov (United States)

Salsbury, Freddie R.; Poole, Leslie B.; Fetrow, Jacquelyn S.

2013-01-01

One of the most popular and simple models for the calculation of pKas from a protein structure is the semi-macroscopic electrostatic model MEAD. This model requires empirical parameters for each residue to calculate pKas. Analysis of current, widely used empirical parameters for cysteine residues showed that they did not reproduce expected cysteine pKas; thus, we set out to identify parameters consistent with the CHARMM27 force field that capture both the behavior of typical cysteines in proteins and the behavior of cysteines which have perturbed pKas. The new parameters were validated in three ways: (1) calculation across a large set of typical cysteines in proteins (where the calculations are expected to reproduce expected ensemble behavior); (2) calculation across a set of perturbed cysteines in proteins (where the calculations are expected to reproduce the shifted ensemble behavior); and (3) comparison to experimentally determined pKa values (where the calculation should reproduce the pKa within experimental error). Both the general behavior of cysteines in proteins and the perturbed pKa in some proteins can be predicted reasonably well using the newly determined empirical parameters within the MEAD model for protein electrostatics. This study provides the first general analysis of the electrostatics of cysteines in proteins, with specific attention paid to capturing both the behavior of typical cysteines in a protein and the behavior of cysteines whose pKa should be shifted, and validation of force field parameters for cysteine residues. PMID:22777874

Protein Data Bank (PDB): The Single Global Macromolecular Structure Archive.

Science.gov (United States)

Burley, Stephen K; Berman, Helen M; Kleywegt, Gerard J; Markley, John L; Nakamura, Haruki; Velankar, Sameer

2017-01-01

The Protein Data Bank (PDB)--the single global repository of experimentally determined 3D structures of biological macromolecules and their complexes--was established in 1971, becoming the first open-access digital resource in the biological sciences. The PDB archive currently houses ~130,000 entries (May 2017). It is managed by the Worldwide Protein Data Bank organization (wwPDB; wwpdb.org), which includes the RCSB Protein Data Bank (RCSB PDB; rcsb.org), the Protein Data Bank Japan (PDBj; pdbj.org), the Protein Data Bank in Europe (PDBe; pdbe.org), and BioMagResBank (BMRB; www.bmrb.wisc.edu). The four wwPDB partners operate a unified global software system that enforces community-agreed data standards and supports data Deposition, Biocuration, and Validation of ~11,000 new PDB entries annually (deposit.wwpdb.org). The RCSB PDB currently acts as the archive keeper, ensuring disaster recovery of PDB data and coordinating weekly updates. wwPDB partners disseminate the same archival data from multiple FTP sites, while operating complementary websites that provide their own views of PDB data with selected value-added information and links to related data resources. At present, the PDB archives experimental data, associated metadata, and 3D-atomic level structural models derived from three well-established methods: crystallography, nuclear magnetic resonance spectroscopy (NMR), and electron microscopy (3DEM). wwPDB partners are working closely with experts in related experimental areas (small-angle scattering, chemical cross-linking/mass spectrometry, Forster energy resonance transfer or FRET, etc.) to establish a federation of data resources that will support sustainable archiving and validation of 3D structural models and experimental data derived from integrative or hybrid methods.

Electrostatics of cysteine residues in proteins: parameterization and validation of a simple model.

Science.gov (United States)

Salsbury, Freddie R; Poole, Leslie B; Fetrow, Jacquelyn S

2012-11-01

One of the most popular and simple models for the calculation of pK(a) s from a protein structure is the semi-macroscopic electrostatic model MEAD. This model requires empirical parameters for each residue to calculate pK(a) s. Analysis of current, widely used empirical parameters for cysteine residues showed that they did not reproduce expected cysteine pK(a) s; thus, we set out to identify parameters consistent with the CHARMM27 force field that capture both the behavior of typical cysteines in proteins and the behavior of cysteines which have perturbed pK(a) s. The new parameters were validated in three ways: (1) calculation across a large set of typical cysteines in proteins (where the calculations are expected to reproduce expected ensemble behavior); (2) calculation across a set of perturbed cysteines in proteins (where the calculations are expected to reproduce the shifted ensemble behavior); and (3) comparison to experimentally determined pK(a) values (where the calculation should reproduce the pK(a) within experimental error). Both the general behavior of cysteines in proteins and the perturbed pK(a) in some proteins can be predicted reasonably well using the newly determined empirical parameters within the MEAD model for protein electrostatics. This study provides the first general analysis of the electrostatics of cysteines in proteins, with specific attention paid to capturing both the behavior of typical cysteines in a protein and the behavior of cysteines whose pK(a) should be shifted, and validation of force field parameters for cysteine residues. Copyright © 2012 Wiley Periodicals, Inc.

Design of compound libraries based on natural product scaffolds and protein structure similarity clustering (PSSC)

NARCIS (Netherlands)

Balamurugan, Rengarajan; Dekker, Frank J; Waldmann, Herbert; Dekker, Frans

Recent advances in structural biology, bioinformatics and combinatorial chemistry have significantly impacted the discovery of small molecules that modulate protein functions. Natural products which have evolved to bind to proteins may serve as biologically validated starting points for the design

Building a better fragment library for de novo protein structure prediction.

Directory of Open Access Journals (Sweden)

Saulo H P de Oliveira

Full Text Available Fragment-based approaches are the current standard for de novo protein structure prediction. These approaches rely on accurate and reliable fragment libraries to generate good structural models. In this work, we describe a novel method for structure fragment library generation and its application in fragment-based de novo protein structure prediction. The importance of correct testing procedures in assessing the quality of fragment libraries is demonstrated. In particular, the exclusion of homologs to the target from the libraries to correctly simulate a de novo protein structure prediction scenario, something which surprisingly is not always done. We demonstrate that fragments presenting different predominant predicted secondary structures should be treated differently during the fragment library generation step and that exhaustive and random search strategies should both be used. This information was used to develop a novel method, Flib. On a validation set of 41 structurally diverse proteins, Flib libraries presents both a higher precision and coverage than two of the state-of-the-art methods, NNMake and HHFrag. Flib also achieves better precision and coverage on the set of 275 protein domains used in the two previous experiments of the the Critical Assessment of Structure Prediction (CASP9 and CASP10. We compared Flib libraries against NNMake libraries in a structure prediction context. Of the 13 cases in which a correct answer was generated, Flib models were more accurate than NNMake models for 10. "Flib is available for download at: http://www.stats.ox.ac.uk/research/proteins/resources".

Building a Better Fragment Library for De Novo Protein Structure Prediction

Science.gov (United States)

de Oliveira, Saulo H. P.; Shi, Jiye; Deane, Charlotte M.

2015-01-01

Fragment-based approaches are the current standard for de novo protein structure prediction. These approaches rely on accurate and reliable fragment libraries to generate good structural models. In this work, we describe a novel method for structure fragment library generation and its application in fragment-based de novo protein structure prediction. The importance of correct testing procedures in assessing the quality of fragment libraries is demonstrated. In particular, the exclusion of homologs to the target from the libraries to correctly simulate a de novo protein structure prediction scenario, something which surprisingly is not always done. We demonstrate that fragments presenting different predominant predicted secondary structures should be treated differently during the fragment library generation step and that exhaustive and random search strategies should both be used. This information was used to develop a novel method, Flib. On a validation set of 41 structurally diverse proteins, Flib libraries presents both a higher precision and coverage than two of the state-of-the-art methods, NNMake and HHFrag. Flib also achieves better precision and coverage on the set of 275 protein domains used in the two previous experiments of the the Critical Assessment of Structure Prediction (CASP9 and CASP10). We compared Flib libraries against NNMake libraries in a structure prediction context. Of the 13 cases in which a correct answer was generated, Flib models were more accurate than NNMake models for 10. “Flib is available for download at: http://www.stats.ox.ac.uk/research/proteins/resources”. PMID:25901595

Structural classification of proteins using texture descriptors extracted from the cellular automata image.

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Kavianpour, Hamidreza; Vasighi, Mahdi

2017-02-01

Nowadays, having knowledge about cellular attributes of proteins has an important role in pharmacy, medical science and molecular biology. These attributes are closely correlated with the function and three-dimensional structure of proteins. Knowledge of protein structural class is used by various methods for better understanding the protein functionality and folding patterns. Computational methods and intelligence systems can have an important role in performing structural classification of proteins. Most of protein sequences are saved in databanks as characters and strings and a numerical representation is essential for applying machine learning methods. In this work, a binary representation of protein sequences is introduced based on reduced amino acids alphabets according to surrounding hydrophobicity index. Many important features which are hidden in these long binary sequences can be clearly displayed through their cellular automata images. The extracted features from these images are used to build a classification model by support vector machine. Comparing to previous studies on the several benchmark datasets, the promising classification rates obtained by tenfold cross-validation imply that the current approach can help in revealing some inherent features deeply hidden in protein sequences and improve the quality of predicting protein structural class.

Oligomeric protein structure networks: insights into protein-protein interactions

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Brinda KV

2005-12-01

Full Text Available Abstract Background Protein-protein association is essential for a variety of cellular processes and hence a large number of investigations are being carried out to understand the principles of protein-protein interactions. In this study, oligomeric protein structures are viewed from a network perspective to obtain new insights into protein association. Structure graphs of proteins have been constructed from a non-redundant set of protein oligomer crystal structures by considering amino acid residues as nodes and the edges are based on the strength of the non-covalent interactions between the residues. The analysis of such networks has been carried out in terms of amino acid clusters and hubs (highly connected residues with special emphasis to protein interfaces. Results A variety of interactions such as hydrogen bond, salt bridges, aromatic and hydrophobic interactions, which occur at the interfaces are identified in a consolidated manner as amino acid clusters at the interface, from this study. Moreover, the characterization of the highly connected hub-forming residues at the interfaces and their comparison with the hubs from the non-interface regions and the non-hubs in the interface regions show that there is a predominance of charged interactions at the interfaces. Further, strong and weak interfaces are identified on the basis of the interaction strength between amino acid residues and the sizes of the interface clusters, which also show that many protein interfaces are stronger than their monomeric protein cores. The interface strengths evaluated based on the interface clusters and hubs also correlate well with experimentally determined dissociation constants for known complexes. Finally, the interface hubs identified using the present method correlate very well with experimentally determined hotspots in the interfaces of protein complexes obtained from the Alanine Scanning Energetics database (ASEdb. A few predictions of interface hot

Computational tools for experimental determination and theoretical prediction of protein structure

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O`Donoghue, S.; Rost, B.

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. The authors intend to review the state of the art in the experimental determination of protein 3D structure (focus on nuclear magnetic resonance), and in the theoretical prediction of protein function and of protein structure in 1D, 2D and 3D from sequence. All the atomic resolution structures determined so far have been derived from either X-ray crystallography (the majority so far) or Nuclear Magnetic Resonance (NMR) Spectroscopy (becoming increasingly more important). The authors briefly describe the physical methods behind both of these techniques; the major computational methods involved will be covered in some detail. They highlight parallels and differences between the methods, and also the current limitations. Special emphasis will be given to techniques which have application to ab initio structure prediction. Large scale sequencing techniques increase the gap between the number of known proteins sequences and that of known protein structures. They describe the scope and principles of methods that contribute successfully to closing that gap. Emphasis will be given on the specification of adequate testing procedures to validate such methods.

Modularity in protein structures: study on all-alpha proteins.

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Khan, Taushif; Ghosh, Indira

2015-01-01

Modularity is known as one of the most important features of protein's robust and efficient design. The architecture and topology of proteins play a vital role by providing necessary robust scaffolds to support organism's growth and survival in constant evolutionary pressure. These complex biomolecules can be represented by several layers of modular architecture, but it is pivotal to understand and explore the smallest biologically relevant structural component. In the present study, we have developed a component-based method, using protein's secondary structures and their arrangements (i.e. patterns) in order to investigate its structural space. Our result on all-alpha protein shows that the known structural space is highly populated with limited set of structural patterns. We have also noticed that these frequently observed structural patterns are present as modules or "building blocks" in large proteins (i.e. higher secondary structure content). From structural descriptor analysis, observed patterns are found to be within similar deviation; however, frequent patterns are found to be distinctly occurring in diverse functions e.g. in enzymatic classes and reactions. In this study, we are introducing a simple approach to explore protein structural space using combinatorial- and graph-based geometry methods, which can be used to describe modularity in protein structures. Moreover, analysis indicates that protein function seems to be the driving force that shapes the known structure space.

Mapping monomeric threading to protein-protein structure prediction.

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Guerler, Aysam; Govindarajoo, Brandon; Zhang, Yang

2013-03-25

The key step of template-based protein-protein structure prediction is the recognition of complexes from experimental structure libraries that have similar quaternary fold. Maintaining two monomer and dimer structure libraries is however laborious, and inappropriate library construction can degrade template recognition coverage. We propose a novel strategy SPRING to identify complexes by mapping monomeric threading alignments to protein-protein interactions based on the original oligomer entries in the PDB, which does not rely on library construction and increases the efficiency and quality of complex template recognitions. SPRING is tested on 1838 nonhomologous protein complexes which can recognize correct quaternary template structures with a TM score >0.5 in 1115 cases after excluding homologous proteins. The average TM score of the first model is 60% and 17% higher than that by HHsearch and COTH, respectively, while the number of targets with an interface RMSD benchmark proteins. Although the relative performance of SPRING and ZDOCK depends on the level of homology filters, a combination of the two methods can result in a significantly higher model quality than ZDOCK at all homology thresholds. These data demonstrate a new efficient approach to quaternary structure recognition that is ready to use for genome-scale modeling of protein-protein interactions due to the high speed and accuracy.

The RCSB protein data bank: integrative view of protein, gene and 3D structural information.

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Rose, Peter W; Prlić, Andreas; Altunkaya, Ali; Bi, Chunxiao; Bradley, Anthony R; Christie, Cole H; Costanzo, Luigi Di; Duarte, Jose M; Dutta, Shuchismita; Feng, Zukang; Green, Rachel Kramer; Goodsell, David S; Hudson, Brian; Kalro, Tara; Lowe, Robert; Peisach, Ezra; Randle, Christopher; Rose, Alexander S; Shao, Chenghua; Tao, Yi-Ping; Valasatava, Yana; Voigt, Maria; Westbrook, John D; Woo, Jesse; Yang, Huangwang; Young, Jasmine Y; Zardecki, Christine; Berman, Helen M; Burley, Stephen K

2017-01-04

The Research Collaboratory for Structural Bioinformatics Protein Data Bank (RCSB PDB, http://rcsb.org), the US data center for the global PDB archive, makes PDB data freely available to all users, from structural biologists to computational biologists and beyond. New tools and resources have been added to the RCSB PDB web portal in support of a 'Structural View of Biology.' Recent developments have improved the User experience, including the high-speed NGL Viewer that provides 3D molecular visualization in any web browser, improved support for data file download and enhanced organization of website pages for query, reporting and individual structure exploration. Structure validation information is now visible for all archival entries. PDB data have been integrated with external biological resources, including chromosomal position within the human genome; protein modifications; and metabolic pathways. PDB-101 educational materials have been reorganized into a searchable website and expanded to include new features such as the Geis Digital Archive. © The Author(s) 2016. Published by Oxford University Press on behalf of Nucleic Acids Research.

Structural and Function Prediction of Musa acuminata subsp. Malaccensis Protein

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Anum Munir

2016-03-01

Full Text Available Hypothetical proteins (HPs are the proteins whose presence has been anticipated, yet in vivo function has not been built up. Illustrating the structural and functional privileged insights of these HPs might likewise prompt a superior comprehension of the protein-protein associations or networks in diverse types of life. Bananas (Musa acuminata spp., including sweet and cooking types, are giant perennial monocotyledonous herbs of the order Zingiberales, a sister grouped to the all-around considered Poales, which incorporate oats. Bananas are crucial for nourishment security in numerous tropical and subtropical nations and the most prominent organic product in industrialized nations. In the present study, the hypothetical protein of M. acuminata (Banana was chosen for analysis and modeling by distinctive bioinformatics apparatuses and databases. As indicated by primary and secondary structure analysis, XP_009393594.1 is a stable hydrophobic protein containing a noteworthy extent of α-helices; Homology modeling was done utilizing SWISS-MODEL server where the templates identity with XP_009393594.1 protein was less which demonstrated novelty of our protein. Ab initio strategy was conducted to produce its 3D structure. A few evaluations of quality assessment and validation parameters determined the generated protein model as stable with genuinely great quality. Functional analysis was completed by ProtFun 2.2, and KEGG (KAAS, recommended that the hypothetical protein is a transcription factor with cytoplasmic domain as zinc finger. The protein was observed to be vital for translation process, involved in metabolism, signaling and cellular processes, genetic information processing and Zinc ion binding. It is suggested that further test approval would help to anticipate the structures and functions of other uncharacterized proteins of different plants and living being.

Protein enriched pasta: structure and digestibility of its protein network.

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Laleg, Karima; Barron, Cécile; Santé-Lhoutellier, Véronique; Walrand, Stéphane; Micard, Valérie

2016-02-01

Wheat (W) pasta was enriched in 6% gluten (G), 35% faba (F) or 5% egg (E) to increase its protein content (13% to 17%). The impact of the enrichment on the multiscale structure of the pasta and on in vitro protein digestibility was studied. Increasing the protein content (W- vs. G-pasta) strengthened pasta structure at molecular and macroscopic scales but reduced its protein digestibility by 3% by forming a higher covalently linked protein network. Greater changes in the macroscopic and molecular structure of the pasta were obtained by varying the nature of protein used for enrichment. Proteins in G- and E-pasta were highly covalently linked (28-32%) resulting in a strong pasta structure. Conversely, F-protein (98% SDS-soluble) altered the pasta structure by diluting gluten and formed a weak protein network (18% covalent link). As a result, protein digestibility in F-pasta was significantly higher (46%) than in E- (44%) and G-pasta (39%). The effect of low (55 °C, LT) vs. very high temperature (90 °C, VHT) drying on the protein network structure and digestibility was shown to cause greater molecular changes than pasta formulation. Whatever the pasta, a general strengthening of its structure, a 33% to 47% increase in covalently linked proteins and a higher β-sheet structure were observed. However, these structural differences were evened out after the pasta was cooked, resulting in identical protein digestibility in LT and VHT pasta. Even after VHT drying, F-pasta had the best amino acid profile with the highest protein digestibility, proof of its nutritional interest.

Structure-based barcoding of proteins.

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Metri, Rahul; Jerath, Gaurav; Kailas, Govind; Gacche, Nitin; Pal, Adityabarna; Ramakrishnan, Vibin

2014-01-01

A reduced representation in the format of a barcode has been developed to provide an overview of the topological nature of a given protein structure from 3D coordinate file. The molecular structure of a protein coordinate file from Protein Data Bank is first expressed in terms of an alpha-numero code and further converted to a barcode image. The barcode representation can be used to compare and contrast different proteins based on their structure. The utility of this method has been exemplified by comparing structural barcodes of proteins that belong to same fold family, and across different folds. In addition to this, we have attempted to provide an illustration to (i) the structural changes often seen in a given protein molecule upon interaction with ligands and (ii) Modifications in overall topology of a given protein during evolution. The program is fully downloadable from the website http://www.iitg.ac.in/probar/. © 2013 The Protein Society.

Taking advantage of local structure descriptors to analyze interresidue contacts in protein structures and protein complexes.

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Martin, Juliette; Regad, Leslie; Etchebest, Catherine; Camproux, Anne-Claude

2008-11-15

Interresidue protein contacts in proteins structures and at protein-protein interface are classically described by the amino acid types of interacting residues and the local structural context of the contact, if any, is described using secondary structures. In this study, we present an alternate analysis of interresidue contact using local structures defined by the structural alphabet introduced by Camproux et al. This structural alphabet allows to describe a 3D structure as a sequence of prototype fragments called structural letters, of 27 different types. Each residue can then be assigned to a particular local structure, even in loop regions. The analysis of interresidue contacts within protein structures defined using Voronoï tessellations reveals that pairwise contact specificity is greater in terms of structural letters than amino acids. Using a simple heuristic based on specificity score comparison, we find that 74% of the long-range contacts within protein structures are better described using structural letters than amino acid types. The investigation is extended to a set of protein-protein complexes, showing that the similar global rules apply as for intraprotein contacts, with 64% of the interprotein contacts best described by local structures. We then present an evaluation of pairing functions integrating structural letters to decoy scoring and show that some complexes could benefit from the use of structural letter-based pairing functions.

CMsearch: simultaneous exploration of protein sequence space and structure space improves not only protein homology detection but also protein structure prediction

KAUST Repository

Cui, Xuefeng

2016-06-15

Motivation: Protein homology detection, a fundamental problem in computational biology, is an indispensable step toward predicting protein structures and understanding protein functions. Despite the advances in recent decades on sequence alignment, threading and alignment-free methods, protein homology detection remains a challenging open problem. Recently, network methods that try to find transitive paths in the protein structure space demonstrate the importance of incorporating network information of the structure space. Yet, current methods merge the sequence space and the structure space into a single space, and thus introduce inconsistency in combining different sources of information. Method: We present a novel network-based protein homology detection method, CMsearch, based on cross-modal learning. Instead of exploring a single network built from the mixture of sequence and structure space information, CMsearch builds two separate networks to represent the sequence space and the structure space. It then learns sequence–structure correlation by simultaneously taking sequence information, structure information, sequence space information and structure space information into consideration. Results: We tested CMsearch on two challenging tasks, protein homology detection and protein structure prediction, by querying all 8332 PDB40 proteins. Our results demonstrate that CMsearch is insensitive to the similarity metrics used to define the sequence and the structure spaces. By using HMM–HMM alignment as the sequence similarity metric, CMsearch clearly outperforms state-of-the-art homology detection methods and the CASP-winning template-based protein structure prediction methods.

The Protein Data Bank in Europe (PDBe): bringing structure to biology

International Nuclear Information System (INIS)

Velankar, Sameer; Kleywegt, Gerard J.

2011-01-01

Some future challenges for the PDB and its guardians are discussed and current and future activities in structural bioinformatics at the Protein Data Bank in Europe (PDBe) are described. The Protein Data Bank in Europe (PDBe) is the European partner in the Worldwide PDB and as such handles depositions of X-ray, NMR and EM data and structure models. PDBe also provides advanced bioinformatics services based on data from the PDB and related resources. Some of the challenges facing the PDB and its guardians are discussed, as well as some of the areas on which PDBe activities will focus in the future (advanced services, ligands, integration, validation and experimental data). Finally, some recent developments at PDBe are described

The Protein Data Bank in Europe (PDBe): bringing structure to biology

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Velankar, Sameer; Kleywegt, Gerard J., E-mail: gerard@ebi.ac.uk [Protein Data Bank in Europe (PDBe), EMBL-EBI, Wellcome Trust Genome Campus, Hinxton, Cambridge CB10 1SD (United Kingdom)

2011-04-01

Some future challenges for the PDB and its guardians are discussed and current and future activities in structural bioinformatics at the Protein Data Bank in Europe (PDBe) are described. The Protein Data Bank in Europe (PDBe) is the European partner in the Worldwide PDB and as such handles depositions of X-ray, NMR and EM data and structure models. PDBe also provides advanced bioinformatics services based on data from the PDB and related resources. Some of the challenges facing the PDB and its guardians are discussed, as well as some of the areas on which PDBe activities will focus in the future (advanced services, ligands, integration, validation and experimental data). Finally, some recent developments at PDBe are described.

Structure homology and interaction redundancy for discovering virus–host protein interactions

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de Chassey, Benoît; Meyniel-Schicklin, Laurène; Aublin-Gex, Anne; Navratil, Vincent; Chantier, Thibaut; André, Patrice; Lotteau, Vincent

2013-01-01

Virus–host interactomes are instrumental to understand global perturbations of cellular functions induced by infection and discover new therapies. The construction of such interactomes is, however, technically challenging and time consuming. Here we describe an original method for the prediction of high-confidence interactions between viral and human proteins through a combination of structure and high-quality interactome data. Validation was performed for the NS1 protein of the influenza virus, which led to the identification of new host factors that control viral replication. PMID:24008843

Structure homology and interaction redundancy for discovering virus-host protein interactions.

Science.gov (United States)

de Chassey, Benoît; Meyniel-Schicklin, Laurène; Aublin-Gex, Anne; Navratil, Vincent; Chantier, Thibaut; André, Patrice; Lotteau, Vincent

2013-10-01

Virus-host interactomes are instrumental to understand global perturbations of cellular functions induced by infection and discover new therapies. The construction of such interactomes is, however, technically challenging and time consuming. Here we describe an original method for the prediction of high-confidence interactions between viral and human proteins through a combination of structure and high-quality interactome data. Validation was performed for the NS1 protein of the influenza virus, which led to the identification of new host factors that control viral replication.

SDSL-ESR-based protein structure characterization.

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Strancar, Janez; Kavalenka, Aleh; Urbancic, Iztok; Ljubetic, Ajasja; Hemminga, Marcus A

2010-03-01

As proteins are key molecules in living cells, knowledge about their structure can provide important insights and applications in science, biotechnology, and medicine. However, many protein structures are still a big challenge for existing high-resolution structure-determination methods, as can be seen in the number of protein structures published in the Protein Data Bank. This is especially the case for less-ordered, more hydrophobic and more flexible protein systems. The lack of efficient methods for structure determination calls for urgent development of a new class of biophysical techniques. This work attempts to address this problem with a novel combination of site-directed spin labelling electron spin resonance spectroscopy (SDSL-ESR) and protein structure modelling, which is coupled by restriction of the conformational spaces of the amino acid side chains. Comparison of the application to four different protein systems enables us to generalize the new method and to establish a general procedure for determination of protein structure.

Protein secondary structure prediction using modular reciprocal bidirectional recurrent neural networks.

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Babaei, Sepideh; Geranmayeh, Amir; Seyyedsalehi, Seyyed Ali

2010-12-01

The supervised learning of recurrent neural networks well-suited for prediction of protein secondary structures from the underlying amino acids sequence is studied. Modular reciprocal recurrent neural networks (MRR-NN) are proposed to model the strong correlations between adjacent secondary structure elements. Besides, a multilayer bidirectional recurrent neural network (MBR-NN) is introduced to capture the long-range intramolecular interactions between amino acids in formation of the secondary structure. The final modular prediction system is devised based on the interactive integration of the MRR-NN and the MBR-NN structures to arbitrarily engage the neighboring effects of the secondary structure types concurrent with memorizing the sequential dependencies of amino acids along the protein chain. The advanced combined network augments the percentage accuracy (Q₃) to 79.36% and boosts the segment overlap (SOV) up to 70.09% when tested on the PSIPRED dataset in three-fold cross-validation. Copyright © 2010 Elsevier Ireland Ltd. All rights reserved.

p15PAF is an intrinsically disordered protein with nonrandom structural preferences at sites of interaction with other proteins.

Science.gov (United States)

De Biasio, Alfredo; Ibáñez de Opakua, Alain; Cordeiro, Tiago N; Villate, Maider; Merino, Nekane; Sibille, Nathalie; Lelli, Moreno; Diercks, Tammo; Bernadó, Pau; Blanco, Francisco J

2014-02-18

We present to our knowledge the first structural characterization of the proliferating-cell-nuclear-antigen-associated factor p15(PAF), showing that it is monomeric and intrinsically disordered in solution but has nonrandom conformational preferences at sites of protein-protein interactions. p15(PAF) is a 12 kDa nuclear protein that acts as a regulator of DNA repair during DNA replication. The p15(PAF) gene is overexpressed in several types of human cancer. The nearly complete NMR backbone assignment of p15(PAF) allowed us to measure 86 N-H(N) residual dipolar couplings. Our residual dipolar coupling analysis reveals nonrandom conformational preferences in distinct regions, including the proliferating-cell-nuclear-antigen-interacting protein motif (PIP-box) and the KEN-box (recognized by the ubiquitin ligase that targets p15(PAF) for degradation). In accordance with these findings, analysis of the (15)N R2 relaxation rates shows a relatively reduced mobility for the residues in these regions. The agreement between the experimental small angle x-ray scattering curve of p15(PAF) and that computed from a statistical coil ensemble corrected for the presence of local secondary structural elements further validates our structural model for p15(PAF). The coincidence of these transiently structured regions with protein-protein interaction and posttranslational modification sites suggests a possible role for these structures as molecular recognition elements for p15(PAF). Copyright © 2014 Biophysical Society. Published by Elsevier Inc. All rights reserved.

Determination and validation of mTOR kinase-domain 3D structure by homology modeling

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Lakhlili W

2015-07-01

Full Text Available Wiame Lakhlili,1 Gwénaël Chevé,2 Abdelaziz Yasri,2 Azeddine Ibrahimi1 1Laboratoire de Biotechnologie (MedBiotech, Faculté de Médecine et de Pharmacie de Rabat, Université Mohammed V de Rabat, Rabat, Morroco; 2OriBase Pharma, Cap Gamma, Parc Euromédecine, Montpellier, France Abstract: The AKT/mammalian target of rapamycin (mTOR pathway is considered as one of the commonly activated and deregulated signaling pathways in human cancer. mTOR is associated with other proteins in two molecular complexes: mTOR complex 1/Raptor and the mTOR complex 2/Rictor. Using the crystal structure of the related lipid kinase PI3Kγ, we built a model of the catalytic region of mTOR. The modeling of the three-dimensional (3D structure of the mTOR was performed by homology modeling program SWISS-MODEL. The quality and validation of the obtained model were performed using PROCHECK and PROVE softwares. The overall stereochemical property of the protein was assessed by the Ramachandran plot. The model validation was also done by docking of known inhibitors. In this paper, we describe and validate a 3D model for the mTOR catalytic site.Keywords: mTOR, homology modeling, mTOR kinase-domain, docking

Structure and non-structure of centrosomal proteins.

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Dos Santos, Helena G; Abia, David; Janowski, Robert; Mortuza, Gulnahar; Bertero, Michela G; Boutin, Maïlys; Guarín, Nayibe; Méndez-Giraldez, Raúl; Nuñez, Alfonso; Pedrero, Juan G; Redondo, Pilar; Sanz, María; Speroni, Silvia; Teichert, Florian; Bruix, Marta; Carazo, José M; Gonzalez, Cayetano; Reina, José; Valpuesta, José M; Vernos, Isabelle; Zabala, Juan C; Montoya, Guillermo; Coll, Miquel; Bastolla, Ugo; Serrano, Luis

2013-01-01

Here we perform a large-scale study of the structural properties and the expression of proteins that constitute the human Centrosome. Centrosomal proteins tend to be larger than generic human proteins (control set), since their genes contain in average more exons (20.3 versus 14.6). They are rich in predicted disordered regions, which cover 57% of their length, compared to 39% in the general human proteome. They also contain several regions that are dually predicted to be disordered and coiled-coil at the same time: 55 proteins (15%) contain disordered and coiled-coil fragments that cover more than 20% of their length. Helices prevail over strands in regions homologous to known structures (47% predicted helical residues against 17% predicted as strands), and even more in the whole centrosomal proteome (52% against 7%), while for control human proteins 34.5% of the residues are predicted as helical and 12.8% are predicted as strands. This difference is mainly due to residues predicted as disordered and helical (30% in centrosomal and 9.4% in control proteins), which may correspond to alpha-helix forming molecular recognition features (α-MoRFs). We performed expression assays for 120 full-length centrosomal proteins and 72 domain constructs that we have predicted to be globular. These full-length proteins are often insoluble: Only 39 out of 120 expressed proteins (32%) and 19 out of 72 domains (26%) were soluble. We built or retrieved structural models for 277 out of 361 human proteins whose centrosomal localization has been experimentally verified. We could not find any suitable structural template with more than 20% sequence identity for 84 centrosomal proteins (23%), for which around 74% of the residues are predicted to be disordered or coiled-coils. The three-dimensional models that we built are available at http://ub.cbm.uam.es/centrosome/models/index.php.

Structure validation of the Josephin domain of ataxin-3: Conclusive evidence for an open conformation

International Nuclear Information System (INIS)

Nicastro, Giuseppe; Habeck, Michael; Masino, Laura; Svergun, Dmitri I.; Pastore, Annalisa

2006-01-01

The availability of new and fast tools in structure determination has led to a more than exponential growth of the number of structures solved per year. It is therefore increasingly essential to assess the accuracy of the new structures by reliable approaches able to assist validation. Here, we discuss a specific example in which the use of different complementary techniques, which include Bayesian methods and small angle scattering, resulted essential for validating the two currently available structures of the Josephin domain of ataxin-3, a protein involved in the ubiquitin/proteasome pathway and responsible for neurodegenerative spinocerebellar ataxia of type 3. Taken together, our results demonstrate that only one of the two structures is compatible with the experimental information. Based on the high precision of our refined structure, we show that Josephin contains an open cleft which could be directly implicated in the interaction with polyubiquitin chains and other partners

Criteria to Extract High-Quality Protein Data Bank Subsets for Structure Users.

Science.gov (United States)

Carugo, Oliviero; Djinović-Carugo, Kristina

2016-01-01

It is often necessary to build subsets of the Protein Data Bank to extract structural trends and average values. For this purpose it is mandatory that the subsets are non-redundant and of high quality. The first problem can be solved relatively easily at the sequence level or at the structural level. The second, on the contrary, needs special attention. It is not sufficient, in fact, to consider the crystallographic resolution and other feature must be taken into account: the absence of strings of residues from the electron density maps and from the files deposited in the Protein Data Bank; the B-factor values; the appropriate validation of the structural models; the quality of the electron density maps, which is not uniform; and the temperature of the diffraction experiments. More stringent criteria produce smaller subsets, which can be enlarged with more tolerant selection criteria. The incessant growth of the Protein Data Bank and especially of the number of high-resolution structures is allowing the use of more stringent selection criteria, with a consequent improvement of the quality of the subsets of the Protein Data Bank.

BLAST-based structural annotation of protein residues using Protein Data Bank.

Science.gov (United States)

Singh, Harinder; Raghava, Gajendra P S

2016-01-25

In the era of next-generation sequencing where thousands of genomes have been already sequenced; size of protein databases is growing with exponential rate. Structural annotation of these proteins is one of the biggest challenges for the computational biologist. Although, it is easy to perform BLAST search against Protein Data Bank (PDB) but it is difficult for a biologist to annotate protein residues from BLAST search. A web-server StarPDB has been developed for structural annotation of a protein based on its similarity with known protein structures. It uses standard BLAST software for performing similarity search of a query protein against protein structures in PDB. This server integrates wide range modules for assigning different types of annotation that includes, Secondary-structure, Accessible surface area, Tight-turns, DNA-RNA and Ligand modules. Secondary structure module allows users to predict regular secondary structure states to each residue in a protein. Accessible surface area predict the exposed or buried residues in a protein. Tight-turns module is designed to predict tight turns like beta-turns in a protein. DNA-RNA module developed for predicting DNA and RNA interacting residues in a protein. Similarly, Ligand module of server allows one to predicted ligands, metal and nucleotides ligand interacting residues in a protein. In summary, this manuscript presents a web server for comprehensive annotation of a protein based on similarity search. It integrates number of visualization tools that facilitate users to understand structure and function of protein residues. This web server is available freely for scientific community from URL http://crdd.osdd.net/raghava/starpdb .

Structure Prediction of Outer Membrane Protease Protein of Salmonella typhimurium Using Computational Techniques

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Rozina Tabassum

2016-03-01

Full Text Available Salmonella typhimurium, a facultative gram-negative intracellular pathogen belonging to family Enterobacteriaceae, is the most frequent cause of human gastroenteritis worldwide. PgtE gene product, outer membrane protease emerges important in the intracellular phases of salmonellosis. The pgtE gene product of S. typhimurium was predicted to be capable of proteolyzing T7 RNA polymerase and localize in the outer membrane of these gram negative bacteria. PgtE product of S. enterica and OmpT of E. coli, having high sequence similarity have been revealed to degrade macrophages, causing salmonellosis and other diseases. The three-dimensional structure of the protein was not available through Protein Data Bank (PDB creating lack of structural information about E protein. In our study, by performing Comparative model building, the three dimensional structure of outer membrane protease protein was generated using the backbone of the crystal structure of Pla of Yersinia pestis, retrieved from PDB, with MODELLER (9v8. Quality of the model was assessed by validation tool PROCHECK, web servers like ERRAT and ProSA are used to certify the reliability of the predicted model. This information might offer clues for better understanding of E protein and consequently for developmet of better therapeutic treatment against pathogenic role of this protein in salmonellosis and other diseases.

Protein flexibility: coordinate uncertainties and interpretation of structural differences

Energy Technology Data Exchange (ETDEWEB)

Rashin, Alexander A., E-mail: alexander-rashin@hotmail.com [BioChemComp Inc., 543 Sagamore Avenue, Teaneck, NJ 07666 (United States); LH Baker Center for Bioinformatics and Department of Biochemistry, Biophysics and Molecular Biology, 112 Office and Lab Building, Iowa State University, Ames, IA 50011-3020 (United States); Rashin, Abraham H. L. [BioChemComp Inc., 543 Sagamore Avenue, Teaneck, NJ 07666 (United States); Rutgers, The State University of New Jersey, 22371 BPO WAY, Piscataway, NJ 08854-8123 (United States); Jernigan, Robert L. [LH Baker Center for Bioinformatics and Department of Biochemistry, Biophysics and Molecular Biology, 112 Office and Lab Building, Iowa State University, Ames, IA 50011-3020 (United States); BioChemComp Inc., 543 Sagamore Avenue, Teaneck, NJ 07666 (United States)

2009-11-01

Criteria for the interpretability of coordinate differences and a new method for identifying rigid-body motions and nonrigid deformations in protein conformational changes are developed and applied to functionally induced and crystallization-induced conformational changes. Valid interpretations of conformational movements in protein structures determined by X-ray crystallography require that the movement magnitudes exceed their uncertainty threshold. Here, it is shown that such thresholds can be obtained from the distance difference matrices (DDMs) of 1014 pairs of independently determined structures of bovine ribonuclease A and sperm whale myoglobin, with no explanations provided for reportedly minor coordinate differences. The smallest magnitudes of reportedly functional motions are just above these thresholds. Uncertainty thresholds can provide objective criteria that distinguish between true conformational changes and apparent ‘noise’, showing that some previous interpretations of protein coordinate changes attributed to external conditions or mutations may be doubtful or erroneous. The use of uncertainty thresholds, DDMs, the newly introduced CDDMs (contact distance difference matrices) and a novel simple rotation algorithm allows a more meaningful classification and description of protein motions, distinguishing between various rigid-fragment motions and nonrigid conformational deformations. It is also shown that half of 75 pairs of identical molecules, each from the same asymmetric crystallographic cell, exhibit coordinate differences that range from just outside the coordinate uncertainty threshold to the full magnitude of large functional movements. Thus, crystallization might often induce protein conformational changes that are comparable to those related to or induced by the protein function.

Development and Fit-for-Purpose Validation of a Soluble Human Programmed Death-1 Protein Assay.

Science.gov (United States)

Ni, Yan G; Yuan, Xiling; Newitt, John A; Peterson, Jon E; Gleason, Carol R; Haulenbeek, Jonathan; Santockyte, Rasa; Lafont, Virginie; Marsilio, Frank; Neely, Robert J; DeSilva, Binodh; Piccoli, Steven P

2015-07-01

Programmed death-1 (PD-1) protein is a co-inhibitory receptor which negatively regulates immune cell activation and permits tumors to evade normal immune defense. Anti-PD-1 antibodies have been shown to restore immune cell activation and effector function-an exciting breakthrough in cancer immunotherapy. Recent reports have documented a soluble form of PD-1 (sPD-1) in the circulation of normal and disease state individuals. A clinical assay to quantify sPD-1 would contribute to the understanding of sPD-1-function and facilitate the development of anti-PD-1 drugs. Here, we report the development and validation of a sPD-1 protein assay. The assay validation followed the framework for full validation of a biotherapeutic pharmacokinetic assay. A purified recombinant human PD-1 protein was characterized extensively and was identified as the assay reference material which mimics the endogenous analyte in structure and function. The lower limit of quantitation (LLOQ) was determined to be 100 pg/mL, with a dynamic range spanning three logs to 10,000 pg/mL. The intra- and inter-assay imprecision were ≤15%, and the assay bias (percent deviation) was ≤10%. Potential matrix effects were investigated in sera from both normal healthy volunteers and selected cancer patients. Bulk-prepared frozen standards and pre-coated Streptavidin plates were used in the assay to ensure consistency in assay performance over time. This assay appears to specifically measure total sPD-1 protein since the human anti-PD-1 antibody, nivolumab, and the endogenous ligands of PD-1 protein, PDL-1 and PDL-2, do not interfere with the assay.

NAPS: Network Analysis of Protein Structures

Science.gov (United States)

Chakrabarty, Broto; Parekh, Nita

2016-01-01

Traditionally, protein structures have been analysed by the secondary structure architecture and fold arrangement. An alternative approach that has shown promise is modelling proteins as a network of non-covalent interactions between amino acid residues. The network representation of proteins provide a systems approach to topological analysis of complex three-dimensional structures irrespective of secondary structure and fold type and provide insights into structure-function relationship. We have developed a web server for network based analysis of protein structures, NAPS, that facilitates quantitative and qualitative (visual) analysis of residue–residue interactions in: single chains, protein complex, modelled protein structures and trajectories (e.g. from molecular dynamics simulations). The user can specify atom type for network construction, distance range (in Å) and minimal amino acid separation along the sequence. NAPS provides users selection of node(s) and its neighbourhood based on centrality measures, physicochemical properties of amino acids or cluster of well-connected residues (k-cliques) for further analysis. Visual analysis of interacting domains and protein chains, and shortest path lengths between pair of residues are additional features that aid in functional analysis. NAPS support various analyses and visualization views for identifying functional residues, provide insight into mechanisms of protein folding, domain-domain and protein–protein interactions for understanding communication within and between proteins. URL:http://bioinf.iiit.ac.in/NAPS/. PMID:27151201

Structure determination of an integral membrane protein at room temperature from crystals in situ

International Nuclear Information System (INIS)

Axford, Danny; Foadi, James; Hu, Nien-Jen; Choudhury, Hassanul Ghani; Iwata, So; Beis, Konstantinos; Evans, Gwyndaf; Alguel, Yilmaz

2015-01-01

The X-ray structure determination of an integral membrane protein using synchrotron diffraction data measured in situ at room temperature is demonstrated. The structure determination of an integral membrane protein using synchrotron X-ray diffraction data collected at room temperature directly in vapour-diffusion crystallization plates (in situ) is demonstrated. Exposing the crystals in situ eliminates manual sample handling and, since it is performed at room temperature, removes the complication of cryoprotection and potential structural anomalies induced by sample cryocooling. Essential to the method is the ability to limit radiation damage by recording a small amount of data per sample from many samples and subsequently assembling the resulting data sets using specialized software. The validity of this procedure is established by the structure determination of Haemophilus influenza TehA at 2.3 Å resolution. The method presented offers an effective protocol for the fast and efficient determination of membrane-protein structures at room temperature using third-generation synchrotron beamlines

Structure determination of an integral membrane protein at room temperature from crystals in situ

Energy Technology Data Exchange (ETDEWEB)

Axford, Danny [Diamond Light Source, Harwell Science and Innovation Campus, Oxfordshire OX11 0DE (United Kingdom); Foadi, James [Diamond Light Source, Harwell Science and Innovation Campus, Oxfordshire OX11 0DE (United Kingdom); Imperial College London, London SW7 2AZ (United Kingdom); Hu, Nien-Jen; Choudhury, Hassanul Ghani [Diamond Light Source, Harwell Science and Innovation Campus, Oxfordshire OX11 0DE (United Kingdom); Imperial College London, London SW7 2AZ (United Kingdom); Rutherford Appleton Laboratory, Oxfordshire OX11 0FA (United Kingdom); Iwata, So [Diamond Light Source, Harwell Science and Innovation Campus, Oxfordshire OX11 0DE (United Kingdom); Diamond Light Source, Harwell Science and Innovation Campus, Oxfordshire OX11 0DE (United Kingdom); Imperial College London, London SW7 2AZ (United Kingdom); Rutherford Appleton Laboratory, Oxfordshire OX11 0FA (United Kingdom); Kyoto University, Kyoto 606-8501 (Japan); Beis, Konstantinos [Diamond Light Source, Harwell Science and Innovation Campus, Oxfordshire OX11 0DE (United Kingdom); Imperial College London, London SW7 2AZ (United Kingdom); Rutherford Appleton Laboratory, Oxfordshire OX11 0FA (United Kingdom); Evans, Gwyndaf, E-mail: gwyndaf.evans@diamond.ac.uk [Diamond Light Source, Harwell Science and Innovation Campus, Oxfordshire OX11 0DE (United Kingdom); Alguel, Yilmaz, E-mail: gwyndaf.evans@diamond.ac.uk [Diamond Light Source, Harwell Science and Innovation Campus, Oxfordshire OX11 0DE (United Kingdom); Imperial College London, London SW7 2AZ (United Kingdom); Rutherford Appleton Laboratory, Oxfordshire OX11 0FA (United Kingdom)

2015-05-14

The X-ray structure determination of an integral membrane protein using synchrotron diffraction data measured in situ at room temperature is demonstrated. The structure determination of an integral membrane protein using synchrotron X-ray diffraction data collected at room temperature directly in vapour-diffusion crystallization plates (in situ) is demonstrated. Exposing the crystals in situ eliminates manual sample handling and, since it is performed at room temperature, removes the complication of cryoprotection and potential structural anomalies induced by sample cryocooling. Essential to the method is the ability to limit radiation damage by recording a small amount of data per sample from many samples and subsequently assembling the resulting data sets using specialized software. The validity of this procedure is established by the structure determination of Haemophilus influenza TehA at 2.3 Å resolution. The method presented offers an effective protocol for the fast and efficient determination of membrane-protein structures at room temperature using third-generation synchrotron beamlines.

Fast loop modeling for protein structures

Science.gov (United States)

Zhang, Jiong; Nguyen, Son; Shang, Yi; Xu, Dong; Kosztin, Ioan

2015-03-01

X-ray crystallography is the main method for determining 3D protein structures. In many cases, however, flexible loop regions of proteins cannot be resolved by this approach. This leads to incomplete structures in the protein data bank, preventing further computational study and analysis of these proteins. For instance, all-atom molecular dynamics (MD) simulation studies of structure-function relationship require complete protein structures. To address this shortcoming, we have developed and implemented an efficient computational method for building missing protein loops. The method is database driven and uses deep learning and multi-dimensional scaling algorithms. We have implemented the method as a simple stand-alone program, which can also be used as a plugin in existing molecular modeling software, e.g., VMD. The quality and stability of the generated structures are assessed and tested via energy scoring functions and by equilibrium MD simulations. The proposed method can also be used in template-based protein structure prediction. Work supported by the National Institutes of Health [R01 GM100701]. Computer time was provided by the University of Missouri Bioinformatics Consortium.

Validation of protein models by a neural network approach

Directory of Open Access Journals (Sweden)

Fantucci Piercarlo

2008-01-01

Full Text Available Abstract Background The development and improvement of reliable computational methods designed to evaluate the quality of protein models is relevant in the context of protein structure refinement, which has been recently identified as one of the bottlenecks limiting the quality and usefulness of protein structure prediction. Results In this contribution, we present a computational method (Artificial Intelligence Decoys Evaluator: AIDE which is able to consistently discriminate between correct and incorrect protein models. In particular, the method is based on neural networks that use as input 15 structural parameters, which include energy, solvent accessible surface, hydrophobic contacts and secondary structure content. The results obtained with AIDE on a set of decoy structures were evaluated using statistical indicators such as Pearson correlation coefficients, Znat, fraction enrichment, as well as ROC plots. It turned out that AIDE performances are comparable and often complementary to available state-of-the-art learning-based methods. Conclusion In light of the results obtained with AIDE, as well as its comparison with available learning-based methods, it can be concluded that AIDE can be successfully used to evaluate the quality of protein structures. The use of AIDE in combination with other evaluation tools is expected to further enhance protein refinement efforts.

Prediction of protein–protein interactions: unifying evolution and structure at protein interfaces

International Nuclear Information System (INIS)

Tuncbag, Nurcan; Gursoy, Attila; Keskin, Ozlem

2011-01-01

The vast majority of the chores in the living cell involve protein–protein interactions. Providing details of protein interactions at the residue level and incorporating them into protein interaction networks are crucial toward the elucidation of a dynamic picture of cells. Despite the rapid increase in the number of structurally known protein complexes, we are still far away from a complete network. Given experimental limitations, computational modeling of protein interactions is a prerequisite to proceed on the way to complete structural networks. In this work, we focus on the question 'how do proteins interact?' rather than 'which proteins interact?' and we review structure-based protein–protein interaction prediction approaches. As a sample approach for modeling protein interactions, PRISM is detailed which combines structural similarity and evolutionary conservation in protein interfaces to infer structures of complexes in the protein interaction network. This will ultimately help us to understand the role of protein interfaces in predicting bound conformations

Structural anatomy of telomere OB proteins.

Science.gov (United States)

Horvath, Martin P

2011-10-01

Telomere DNA-binding proteins protect the ends of chromosomes in eukaryotes. A subset of these proteins are constructed with one or more OB folds and bind with G+T-rich single-stranded DNA found at the extreme termini. The resulting DNA-OB protein complex interacts with other telomere components to coordinate critical telomere functions of DNA protection and DNA synthesis. While the first crystal and NMR structures readily explained protection of telomere ends, the picture of how single-stranded DNA becomes available to serve as primer and template for synthesis of new telomere DNA is only recently coming into focus. New structures of telomere OB fold proteins alongside insights from genetic and biochemical experiments have made significant contributions towards understanding how protein-binding OB proteins collaborate with DNA-binding OB proteins to recruit telomerase and DNA polymerase for telomere homeostasis. This review surveys telomere OB protein structures alongside highly comparable structures derived from replication protein A (RPA) components, with the goal of providing a molecular context for understanding telomere OB protein evolution and mechanism of action in protection and synthesis of telomere DNA.

Protein Structure and the Sequential Structure of mRNA

DEFF Research Database (Denmark)

Brunak, Søren; Engelbrecht, Jacob

1996-01-01

entries in the Brookhaven Protein Data Bank produced 719 protein chains with matching mRNA sequence, amino acid sequence, and secondary structure assignment, By neural network analysis, we found strong signals in mRNA sequence regions surrounding helices and sheets, These signals do not originate from......A direct comparison of experimentally determined protein structures and their corresponding protein coding mRNA sequences has been performed, We examine whether real world data support the hypothesis that clusters of rare codons correlate with the location of structural units in the resulting...... protein, The degeneracy of the genetic code allows for a biased selection of codons which may control the translational rate of the ribosome, and may thus in vivo have a catalyzing effect on the folding of the polypeptide chain, A complete search for GenBank nucleotide sequences coding for structural...

Automated protein structure modeling with SWISS-MODEL Workspace and the Protein Model Portal.

Science.gov (United States)

Bordoli, Lorenza; Schwede, Torsten

2012-01-01

Comparative protein structure modeling is a computational approach to build three-dimensional structural models for proteins using experimental structures of related protein family members as templates. Regular blind assessments of modeling accuracy have demonstrated that comparative protein structure modeling is currently the most reliable technique to model protein structures. Homology models are often sufficiently accurate to substitute for experimental structures in a wide variety of applications. Since the usefulness of a model for specific application is determined by its accuracy, model quality estimation is an essential component of protein structure prediction. Comparative protein modeling has become a routine approach in many areas of life science research since fully automated modeling systems allow also nonexperts to build reliable models. In this chapter, we describe practical approaches for automated protein structure modeling with SWISS-MODEL Workspace and the Protein Model Portal.

Automated Protein Structure Modeling with SWISS-MODEL Workspace and the Protein Model Portal

OpenAIRE

Bordoli, Lorenza; Schwede, Torsten

2012-01-01

Comparative protein structure modeling is a computational approach to build three-dimensional structural models for proteins using experimental structures of related protein family members as templates. Regular blind assessments of modeling accuracy have demonstrated that comparative protein structure modeling is currently the most reliable technique to model protein structures. Homology models are often sufficiently accurate to substitute for experimental structures in a wide variety of appl...

Tchebichef image moment approach to the prediction of protein secondary structures based on circular dichroism.

Science.gov (United States)

Li, Sha Sha; Li, Bao Qiong; Liu, Jin Jin; Lu, Shao Hua; Zhai, Hong Lin

2018-04-20

Circular dichroism (CD) spectroscopy is a widely used technique for the evaluation of protein secondary structures that has a significant impact for the understanding of molecular biology. However, the quantitative analysis of protein secondary structures based on CD spectra is still a hard work due to the serious overlap of the spectra corresponding to different structural motifs. Here, Tchebichef image moment (TM) approach is introduced for the first time, which can effectively extract the chemical features in CD spectra for the quantitative analysis of protein secondary structures. The proposed approach was applied to analyze reference set. and the obtained results were evaluated by the strict statistical parameters such as correlation coefficient, cross-validation correlation coefficient and root mean squared error. Compared with several specialized prediction methods, TM approach provided satisfactory results, especially for turns and unordered structures. Our study indicates that TM approach can be regarded as a feasible tool for the analysis of the secondary structures of proteins based on CD spectra. An available TMs package is provided and can be used directly for secondary structures prediction. This article is protected by copyright. All rights reserved. © 2018 Wiley Periodicals, Inc.

Endogenous protein "barcode" for data validation and normalization in quantitative MS analysis.

Science.gov (United States)

Lee, Wooram; Lazar, Iulia M

2014-07-01

Quantitative proteomic experiments with mass spectrometry detection are typically conducted by using stable isotope labeling and label-free quantitation approaches. Proteins with housekeeping functions and stable expression level such actin, tubulin, and glyceraldehyde-3-phosphate dehydrogenase are frequently used as endogenous controls. Recent studies have shown that the expression level of such common housekeeping proteins is, in fact, dependent on various factors such as cell type, cell cycle, or disease status and can change in response to a biochemical stimulation. The interference of such phenomena can, therefore, substantially compromise their use for data validation, alter the interpretation of results, and lead to erroneous conclusions. In this work, we advance the concept of a protein "barcode" for data normalization and validation in quantitative proteomic experiments. The barcode comprises a novel set of proteins that was generated from cell cycle experiments performed with MCF7, an estrogen receptor positive breast cancer cell line, and MCF10A, a nontumorigenic immortalized breast cell line. The protein set was selected from a list of ~3700 proteins identified in different cellular subfractions and cell cycle stages of MCF7/MCF10A cells, based on the stability of spectral count data generated with an LTQ ion trap mass spectrometer. A total of 11 proteins qualified as endogenous standards for the nuclear and 62 for the cytoplasmic barcode, respectively. The validation of the protein sets was performed with a complementary SKBR3/Her2+ cell line.

Beta-structures in fibrous proteins.

Science.gov (United States)

Kajava, Andrey V; Squire, John M; Parry, David A D

2006-01-01

The beta-form of protein folding, one of the earliest protein structures to be defined, was originally observed in studies of silks. It was then seen in early studies of synthetic polypeptides and, of course, is now known to be present in a variety of guises as an essential component of globular protein structures. However, in the last decade or so it has become clear that the beta-conformation of chains is present not only in many of the amyloid structures associated with, for example, Alzheimer's Disease, but also in the prion structures associated with the spongiform encephalopathies. Furthermore, X-ray crystallography studies have revealed the high incidence of the beta-fibrous proteins among virulence factors of pathogenic bacteria and viruses. Here we describe the basic forms of the beta-fold, summarize the many different new forms of beta-structural fibrous arrangements that have been discovered, and review advances in structural studies of amyloid and prion fibrils. These and other issues are described in detail in later chapters.

The interface of protein structure, protein biophysics, and molecular evolution

Science.gov (United States)

Liberles, David A; Teichmann, Sarah A; Bahar, Ivet; Bastolla, Ugo; Bloom, Jesse; Bornberg-Bauer, Erich; Colwell, Lucy J; de Koning, A P Jason; Dokholyan, Nikolay V; Echave, Julian; Elofsson, Arne; Gerloff, Dietlind L; Goldstein, Richard A; Grahnen, Johan A; Holder, Mark T; Lakner, Clemens; Lartillot, Nicholas; Lovell, Simon C; Naylor, Gavin; Perica, Tina; Pollock, David D; Pupko, Tal; Regan, Lynne; Roger, Andrew; Rubinstein, Nimrod; Shakhnovich, Eugene; Sjölander, Kimmen; Sunyaev, Shamil; Teufel, Ashley I; Thorne, Jeffrey L; Thornton, Joseph W; Weinreich, Daniel M; Whelan, Simon

2012-01-01

Abstract The interface of protein structural biology, protein biophysics, molecular evolution, and molecular population genetics forms the foundations for a mechanistic understanding of many aspects of protein biochemistry. Current efforts in interdisciplinary protein modeling are in their infancy and the state-of-the art of such models is described. Beyond the relationship between amino acid substitution and static protein structure, protein function, and corresponding organismal fitness, other considerations are also discussed. More complex mutational processes such as insertion and deletion and domain rearrangements and even circular permutations should be evaluated. The role of intrinsically disordered proteins is still controversial, but may be increasingly important to consider. Protein geometry and protein dynamics as a deviation from static considerations of protein structure are also important. Protein expression level is known to be a major determinant of evolutionary rate and several considerations including selection at the mRNA level and the role of interaction specificity are discussed. Lastly, the relationship between modeling and needed high-throughput experimental data as well as experimental examination of protein evolution using ancestral sequence resurrection and in vitro biochemistry are presented, towards an aim of ultimately generating better models for biological inference and prediction. PMID:22528593

GIS: a comprehensive source for protein structure similarities.

Science.gov (United States)

Guerler, Aysam; Knapp, Ernst-Walter

2010-07-01

A web service for analysis of protein structures that are sequentially or non-sequentially similar was generated. Recently, the non-sequential structure alignment algorithm GANGSTA+ was introduced. GANGSTA+ can detect non-sequential structural analogs for proteins stated to possess novel folds. Since GANGSTA+ ignores the polypeptide chain connectivity of secondary structure elements (i.e. alpha-helices and beta-strands), it is able to detect structural similarities also between proteins whose sequences were reshuffled during evolution. GANGSTA+ was applied in an all-against-all comparison on the ASTRAL40 database (SCOP version 1.75), which consists of >10,000 protein domains yielding about 55 x 10(6) possible protein structure alignments. Here, we provide the resulting protein structure alignments as a public web-based service, named GANGSTA+ Internet Services (GIS). We also allow to browse the ASTRAL40 database of protein structures with GANGSTA+ relative to an externally given protein structure using different constraints to select specific results. GIS allows us to analyze protein structure families according to the SCOP classification scheme. Additionally, users can upload their own protein structures for pairwise protein structure comparison, alignment against all protein structures of the ASTRAL40 database (SCOP version 1.75) or symmetry analysis. GIS is publicly available at http://agknapp.chemie.fu-berlin.de/gplus.

Neural Networks for protein Structure Prediction

DEFF Research Database (Denmark)

Bohr, Henrik

1998-01-01

This is a review about neural network applications in bioinformatics. Especially the applications to protein structure prediction, e.g. prediction of secondary structures, prediction of surface structure, fold class recognition and prediction of the 3-dimensional structure of protein backbones...

Protein Molecular Structures, Protein SubFractions, and Protein Availability Affected by Heat Processing: A Review

International Nuclear Information System (INIS)

Yu, P.

2007-01-01

The utilization and availability of protein depended on the types of protein and their specific susceptibility to enzymatic hydrolysis (inhibitory activities) in the gastrointestine and was highly associated with protein molecular structures. Studying internal protein structure and protein subfraction profiles leaded to an understanding of the components that make up a whole protein. An understanding of the molecular structure of the whole protein was often vital to understanding its digestive behavior and nutritive value in animals. In this review, recently obtained information on protein molecular structural effects of heat processing was reviewed, in relation to protein characteristics affecting digestive behavior and nutrient utilization and availability. The emphasis of this review was on (1) using the newly advanced synchrotron technology (S-FTIR) as a novel approach to reveal protein molecular chemistry affected by heat processing within intact plant tissues; (2) revealing the effects of heat processing on the profile changes of protein subfractions associated with digestive behaviors and kinetics manipulated by heat processing; (3) prediction of the changes of protein availability and supply after heat processing, using the advanced DVE/OEB and NRC-2001 models, and (4) obtaining information on optimal processing conditions of protein as intestinal protein source to achieve target values for potential high net absorbable protein in the small intestine. The information described in this article may give better insight in the mechanisms involved and the intrinsic protein molecular structural changes occurring upon processing.

Structure based alignment and clustering of proteins (STRALCP)

Science.gov (United States)

Zemla, Adam T.; Zhou, Carol E.; Smith, Jason R.; Lam, Marisa W.

2013-06-18

Disclosed are computational methods of clustering a set of protein structures based on local and pair-wise global similarity values. Pair-wise local and global similarity values are generated based on pair-wise structural alignments for each protein in the set of protein structures. Initially, the protein structures are clustered based on pair-wise local similarity values. The protein structures are then clustered based on pair-wise global similarity values. For each given cluster both a representative structure and spans of conserved residues are identified. The representative protein structure is used to assign newly-solved protein structures to a group. The spans are used to characterize conservation and assign a "structural footprint" to the cluster.

Understanding Protein-Protein Interactions Using Local Structural Features

DEFF Research Database (Denmark)

Planas-Iglesias, Joan; Bonet, Jaume; García-García, Javier

2013-01-01

Protein-protein interactions (PPIs) play a relevant role among the different functions of a cell. Identifying the PPI network of a given organism (interactome) is useful to shed light on the key molecular mechanisms within a biological system. In this work, we show the role of structural features...... interacting and non-interacting protein pairs to classify the structural features that sustain the binding (or non-binding) behavior. Our study indicates that not only the interacting region but also the rest of the protein surface are important for the interaction fate. The interpretation...... to score the likelihood of the interaction between two proteins and to develop a method for the prediction of PPIs. We have tested our method on several sets with unbalanced ratios of interactions and non-interactions to simulate real conditions, obtaining accuracies higher than 25% in the most unfavorable...

Efficient protein structure search using indexing methods.

Science.gov (United States)

Kim, Sungchul; Sael, Lee; Yu, Hwanjo

2013-01-01

Understanding functions of proteins is one of the most important challenges in many studies of biological processes. The function of a protein can be predicted by analyzing the functions of structurally similar proteins, thus finding structurally similar proteins accurately and efficiently from a large set of proteins is crucial. A protein structure can be represented as a vector by 3D-Zernike Descriptor (3DZD) which compactly represents the surface shape of the protein tertiary structure. This simplified representation accelerates the searching process. However, computing the similarity of two protein structures is still computationally expensive, thus it is hard to efficiently process many simultaneous requests of structurally similar protein search. This paper proposes indexing techniques which substantially reduce the search time to find structurally similar proteins. In particular, we first exploit two indexing techniques, i.e., iDistance and iKernel, on the 3DZDs. After that, we extend the techniques to further improve the search speed for protein structures. The extended indexing techniques build and utilize an reduced index constructed from the first few attributes of 3DZDs of protein structures. To retrieve top-k similar structures, top-10 × k similar structures are first found using the reduced index, and top-k structures are selected among them. We also modify the indexing techniques to support θ-based nearest neighbor search, which returns data points less than θ to the query point. The results show that both iDistance and iKernel significantly enhance the searching speed. In top-k nearest neighbor search, the searching time is reduced 69.6%, 77%, 77.4% and 87.9%, respectively using iDistance, iKernel, the extended iDistance, and the extended iKernel. In θ-based nearest neighbor serach, the searching time is reduced 80%, 81%, 95.6% and 95.6% using iDistance, iKernel, the extended iDistance, and the extended iKernel, respectively.

A 'periodic table' for protein structures.

Science.gov (United States)

Taylor, William R

2002-04-11

Current structural genomics programs aim systematically to determine the structures of all proteins coded in both human and other genomes, providing a complete picture of the number and variety of protein structures that exist. In the past, estimates have been made on the basis of the incomplete sample of structures currently known. These estimates have varied greatly (between 1,000 and 10,000; see for example refs 1 and 2), partly because of limited sample size but also owing to the difficulties of distinguishing one structure from another. This distinction is usually topological, based on the fold of the protein; however, in strict topological terms (neglecting to consider intra-chain cross-links), protein chains are open strings and hence are all identical. To avoid this trivial result, topologies are determined by considering secondary links in the form of intra-chain hydrogen bonds (secondary structure) and tertiary links formed by the packing of secondary structures. However, small additions to or loss of structure can make large changes to these perceived topologies and such subjective solutions are neither robust nor amenable to automation. Here I formalize both secondary and tertiary links to allow the rigorous and automatic definition of protein topology.

Structure of human Rad51 protein filament from molecular modeling and site-specific linear dichroism spectroscopy

KAUST Repository

Reymer, A.; Frykholm, K.; Morimatsu, K.; Takahashi, M.; Norden, B.

2009-01-01

for central and N-terminal parts of pure (uncomplexed) Rad51 protein by aid of linear dichroism spectroscopy, providing angular orientations of substituted tyrosine residues of Rad51-dsDNA filaments in solution. The structure, validated by comparison

Protein structure recognition: From eigenvector analysis to structural threading method

Science.gov (United States)

Cao, Haibo

In this work, we try to understand the protein folding problem using pair-wise hydrophobic interaction as the dominant interaction for the protein folding process. We found a strong correlation between amino acid sequence and the corresponding native structure of the protein. Some applications of this correlation were discussed in this dissertation include the domain partition and a new structural threading method as well as the performance of this method in the CASP5 competition. In the first part, we give a brief introduction to the protein folding problem. Some essential knowledge and progress from other research groups was discussed. This part include discussions of interactions among amino acids residues, lattice HP model, and the designablity principle. In the second part, we try to establish the correlation between amino acid sequence and the corresponding native structure of the protein. This correlation was observed in our eigenvector study of protein contact matrix. We believe the correlation is universal, thus it can be used in automatic partition of protein structures into folding domains. In the third part, we discuss a threading method based on the correlation between amino acid sequence and ominant eigenvector of the structure contact-matrix. A mathematically straightforward iteration scheme provides a self-consistent optimum global sequence-structure alignment. The computational efficiency of this method makes it possible to search whole protein structure databases for structural homology without relying on sequence similarity. The sensitivity and specificity of this method is discussed, along with a case of blind test prediction. In the appendix, we list the overall performance of this threading method in CASP5 blind test in comparison with other existing approaches.

Protein Structure Recognition: From Eigenvector Analysis to Structural Threading Method

Energy Technology Data Exchange (ETDEWEB)

Cao, Haibo [Iowa State Univ., Ames, IA (United States)

2003-01-01

In this work, they try to understand the protein folding problem using pair-wise hydrophobic interaction as the dominant interaction for the protein folding process. They found a strong correlation between amino acid sequences and the corresponding native structure of the protein. Some applications of this correlation were discussed in this dissertation include the domain partition and a new structural threading method as well as the performance of this method in the CASP5 competition. In the first part, they give a brief introduction to the protein folding problem. Some essential knowledge and progress from other research groups was discussed. This part includes discussions of interactions among amino acids residues, lattice HP model, and the design ability principle. In the second part, they try to establish the correlation between amino acid sequence and the corresponding native structure of the protein. This correlation was observed in the eigenvector study of protein contact matrix. They believe the correlation is universal, thus it can be used in automatic partition of protein structures into folding domains. In the third part, they discuss a threading method based on the correlation between amino acid sequences and ominant eigenvector of the structure contact-matrix. A mathematically straightforward iteration scheme provides a self-consistent optimum global sequence-structure alignment. The computational efficiency of this method makes it possible to search whole protein structure databases for structural homology without relying on sequence similarity. The sensitivity and specificity of this method is discussed, along with a case of blind test prediction. In the appendix, they list the overall performance of this threading method in CASP5 blind test in comparison with other existing approaches.

Protein Structure Recognition: From Eigenvector Analysis to Structural Threading Method

International Nuclear Information System (INIS)

Haibo Cao

2003-01-01

In this work, they try to understand the protein folding problem using pair-wise hydrophobic interaction as the dominant interaction for the protein folding process. They found a strong correlation between amino acid sequences and the corresponding native structure of the protein. Some applications of this correlation were discussed in this dissertation include the domain partition and a new structural threading method as well as the performance of this method in the CASP5 competition. In the first part, they give a brief introduction to the protein folding problem. Some essential knowledge and progress from other research groups was discussed. This part includes discussions of interactions among amino acids residues, lattice HP model, and the design ability principle. In the second part, they try to establish the correlation between amino acid sequence and the corresponding native structure of the protein. This correlation was observed in the eigenvector study of protein contact matrix. They believe the correlation is universal, thus it can be used in automatic partition of protein structures into folding domains. In the third part, they discuss a threading method based on the correlation between amino acid sequences and ominant eigenvector of the structure contact-matrix. A mathematically straightforward iteration scheme provides a self-consistent optimum global sequence-structure alignment. The computational efficiency of this method makes it possible to search whole protein structure databases for structural homology without relying on sequence similarity. The sensitivity and specificity of this method is discussed, along with a case of blind test prediction. In the appendix, they list the overall performance of this threading method in CASP5 blind test in comparison with other existing approaches

Structures composing protein domains.

Science.gov (United States)

Kubrycht, Jaroslav; Sigler, Karel; Souček, Pavel; Hudeček, Jiří

2013-08-01

This review summarizes available data concerning intradomain structures (IS) such as functionally important amino acid residues, short linear motifs, conserved or disordered regions, peptide repeats, broadly occurring secondary structures or folds, etc. IS form structural features (units or elements) necessary for interactions with proteins or non-peptidic ligands, enzyme reactions and some structural properties of proteins. These features have often been related to a single structural level (e.g. primary structure) mostly requiring certain structural context of other levels (e.g. secondary structures or supersecondary folds) as follows also from some examples reported or demonstrated here. In addition, we deal with some functionally important dynamic properties of IS (e.g. flexibility and different forms of accessibility), and more special dynamic changes of IS during enzyme reactions and allosteric regulation. Selected notes concern also some experimental methods, still more necessary tools of bioinformatic processing and clinically interesting relationships. Copyright © 2013 Elsevier Masson SAS. All rights reserved.

Current strategies for protein production and purification enabling membrane protein structural biology.

Science.gov (United States)

Pandey, Aditya; Shin, Kyungsoo; Patterson, Robin E; Liu, Xiang-Qin; Rainey, Jan K

2016-12-01

Membrane proteins are still heavily under-represented in the protein data bank (PDB), owing to multiple bottlenecks. The typical low abundance of membrane proteins in their natural hosts makes it necessary to overexpress these proteins either in heterologous systems or through in vitro translation/cell-free expression. Heterologous expression of proteins, in turn, leads to multiple obstacles, owing to the unpredictability of compatibility of the target protein for expression in a given host. The highly hydrophobic and (or) amphipathic nature of membrane proteins also leads to challenges in producing a homogeneous, stable, and pure sample for structural studies. Circumventing these hurdles has become possible through the introduction of novel protein production protocols; efficient protein isolation and sample preparation methods; and, improvement in hardware and software for structural characterization. Combined, these advances have made the past 10-15 years very exciting and eventful for the field of membrane protein structural biology, with an exponential growth in the number of solved membrane protein structures. In this review, we focus on both the advances and diversity of protein production and purification methods that have allowed this growth in structural knowledge of membrane proteins through X-ray crystallography, nuclear magnetic resonance (NMR) spectroscopy, and cryo-electron microscopy (cryo-EM).

Combining protein sequence, structure, and dynamics: A novel approach for functional evolution analysis of PAS domain superfamily.

Science.gov (United States)

Dong, Zheng; Zhou, Hongyu; Tao, Peng

2018-02-01

PAS domains are widespread in archaea, bacteria, and eukaryota, and play important roles in various functions. In this study, we aim to explore functional evolutionary relationship among proteins in the PAS domain superfamily in view of the sequence-structure-dynamics-function relationship. We collected protein sequences and crystal structure data from RCSB Protein Data Bank of the PAS domain superfamily belonging to three biological functions (nucleotide binding, photoreceptor activity, and transferase activity). Protein sequences were aligned and then used to select sequence-conserved residues and build phylogenetic tree. Three-dimensional structure alignment was also applied to obtain structure-conserved residues. The protein dynamics were analyzed using elastic network model (ENM) and validated by molecular dynamics (MD) simulation. The result showed that the proteins with same function could be grouped by sequence similarity, and proteins in different functional groups displayed statistically significant difference in their vibrational patterns. Interestingly, in all three functional groups, conserved amino acid residues identified by sequence and structure conservation analysis generally have a lower fluctuation than other residues. In addition, the fluctuation of conserved residues in each biological function group was strongly correlated with the corresponding biological function. This research suggested a direct connection in which the protein sequences were related to various functions through structural dynamics. This is a new attempt to delineate functional evolution of proteins using the integrated information of sequence, structure, and dynamics. © 2017 The Protein Society.

Protein structure similarity from principle component correlation analysis

Directory of Open Access Journals (Sweden)

Chou James

2006-01-01

Full Text Available Abstract Background Owing to rapid expansion of protein structure databases in recent years, methods of structure comparison are becoming increasingly effective and important in revealing novel information on functional properties of proteins and their roles in the grand scheme of evolutionary biology. Currently, the structural similarity between two proteins is measured by the root-mean-square-deviation (RMSD in their best-superimposed atomic coordinates. RMSD is the golden rule of measuring structural similarity when the structures are nearly identical; it, however, fails to detect the higher order topological similarities in proteins evolved into different shapes. We propose new algorithms for extracting geometrical invariants of proteins that can be effectively used to identify homologous protein structures or topologies in order to quantify both close and remote structural similarities. Results We measure structural similarity between proteins by correlating the principle components of their secondary structure interaction matrix. In our approach, the Principle Component Correlation (PCC analysis, a symmetric interaction matrix for a protein structure is constructed with relationship parameters between secondary elements that can take the form of distance, orientation, or other relevant structural invariants. When using a distance-based construction in the presence or absence of encoded N to C terminal sense, there are strong correlations between the principle components of interaction matrices of structurally or topologically similar proteins. Conclusion The PCC method is extensively tested for protein structures that belong to the same topological class but are significantly different by RMSD measure. The PCC analysis can also differentiate proteins having similar shapes but different topological arrangements. Additionally, we demonstrate that when using two independently defined interaction matrices, comparison of their maximum

Protein secondary structure prediction for a single-sequence using hidden semi-Markov models

Directory of Open Access Journals (Sweden)

Borodovsky Mark

2006-03-01

Full Text Available Abstract Background The accuracy of protein secondary structure prediction has been improving steadily towards the 88% estimated theoretical limit. There are two types of prediction algorithms: Single-sequence prediction algorithms imply that information about other (homologous proteins is not available, while algorithms of the second type imply that information about homologous proteins is available, and use it intensively. The single-sequence algorithms could make an important contribution to studies of proteins with no detected homologs, however the accuracy of protein secondary structure prediction from a single-sequence is not as high as when the additional evolutionary information is present. Results In this paper, we further refine and extend the hidden semi-Markov model (HSMM initially considered in the BSPSS algorithm. We introduce an improved residue dependency model by considering the patterns of statistically significant amino acid correlation at structural segment borders. We also derive models that specialize on different sections of the dependency structure and incorporate them into HSMM. In addition, we implement an iterative training method to refine estimates of HSMM parameters. The three-state-per-residue accuracy and other accuracy measures of the new method, IPSSP, are shown to be comparable or better than ones for BSPSS as well as for PSIPRED, tested under the single-sequence condition. Conclusions We have shown that new dependency models and training methods bring further improvements to single-sequence protein secondary structure prediction. The results are obtained under cross-validation conditions using a dataset with no pair of sequences having significant sequence similarity. As new sequences are added to the database it is possible to augment the dependency structure and obtain even higher accuracy. Current and future advances should contribute to the improvement of function prediction for orphan proteins inscrutable

SDSL-ESR-based protein structure characterization

NARCIS (Netherlands)

Strancar, J.; Kavalenka, A.A.; Urbancic, I.; Ljubetic, A.; Hemminga, M.A.

2010-01-01

As proteins are key molecules in living cells, knowledge about their structure can provide important insights and applications in science, biotechnology, and medicine. However, many protein structures are still a big challenge for existing high-resolution structure-determination methods, as can be

Decoding Structural Properties of a Partially Unfolded Protein Substrate: En Route to Chaperone Binding.

Science.gov (United States)

Nagpal, Suhani; Tiwari, Satyam; Mapa, Koyeli; Thukral, Lipi

2015-01-01

Many proteins comprising of complex topologies require molecular chaperones to achieve their unique three-dimensional folded structure. The E.coli chaperone, GroEL binds with a large number of unfolded and partially folded proteins, to facilitate proper folding and prevent misfolding and aggregation. Although the major structural components of GroEL are well defined, scaffolds of the non-native substrates that determine chaperone-mediated folding have been difficult to recognize. Here we performed all-atomistic and replica-exchange molecular dynamics simulations to dissect non-native ensemble of an obligate GroEL folder, DapA. Thermodynamics analyses of unfolding simulations revealed populated intermediates with distinct structural characteristics. We found that surface exposed hydrophobic patches are significantly increased, primarily contributed from native and non-native β-sheet elements. We validate the structural properties of these conformers using experimental data, including circular dichroism (CD), 1-anilinonaphthalene-8-sulfonic acid (ANS) binding measurements and previously reported hydrogen-deutrium exchange coupled to mass spectrometry (HDX-MS). Further, we constructed network graphs to elucidate long-range intra-protein connectivity of native and intermediate topologies, demonstrating regions that serve as central "hubs". Overall, our results implicate that genomic variations (or mutations) in the distinct regions of protein structures might disrupt these topological signatures disabling chaperone-mediated folding, leading to formation of aggregates.

Steady-state structural fluctuation is a predictor of the necessity of pausing-mediated co-translational folding for small proteins.

Science.gov (United States)

Huang, Wenxi; Liu, Wanting; Jin, Jingjie; Xiao, Qilan; Lu, Ruibin; Chen, Wei; Xiong, Sheng; Zhang, Gong

2018-03-25

Translational pausing coordinates protein synthesis and co-translational folding. It is a common factor that facilitates the correct folding of large, multi-domain proteins. For small proteins, pausing sites rarely occurs in the gene body, and the 3'-end pausing sites are only essential for the folding of a fraction of proteins. The determinant of the necessity of the pausings remains obscure. In this study, we demonstrated that the steady-state structural fluctuation is a predictor of the necessity of pausing-mediated co-translational folding for small proteins. Validated by experiments with 5 model proteins, we found that the rigid protein structures do not, while the flexible structures do need 3'-end pausings to fold correctly. Therefore, rational optimization of translational pausing can improve soluble expression of small proteins with flexible structures, but not the rigid ones. The rigidity of the structure can be quantitatively estimated in silico using molecular dynamic simulation. Nevertheless, we also found that the translational pausing optimization increases the fitness of the expression host, and thus benefits the recombinant protein production, independent from the soluble expression. These results shed light on the structural basis of the translational pausing and provided a practical tool for industrial protein fermentation. Copyright © 2017. Published by Elsevier Inc.

A New Method for Determining Structure Ensemble: Application to a RNA Binding Di-Domain Protein.

Science.gov (United States)

Liu, Wei; Zhang, Jingfeng; Fan, Jing-Song; Tria, Giancarlo; Grüber, Gerhard; Yang, Daiwen

2016-05-10

Structure ensemble determination is the basis of understanding the structure-function relationship of a multidomain protein with weak domain-domain interactions. Paramagnetic relaxation enhancement has been proven a powerful tool in the study of structure ensembles, but there exist a number of challenges such as spin-label flexibility, domain dynamics, and overfitting. Here we propose a new (to our knowledge) method to describe structure ensembles using a minimal number of conformers. In this method, individual domains are considered rigid; the position of each spin-label conformer and the structure of each protein conformer are defined by three and six orthogonal parameters, respectively. First, the spin-label ensemble is determined by optimizing the positions and populations of spin-label conformers against intradomain paramagnetic relaxation enhancements with a genetic algorithm. Subsequently, the protein structure ensemble is optimized using a more efficient genetic algorithm-based approach and an overfitting indicator, both of which were established in this work. The method was validated using a reference ensemble with a set of conformers whose populations and structures are known. This method was also applied to study the structure ensemble of the tandem di-domain of a poly (U) binding protein. The determined ensemble was supported by small-angle x-ray scattering and nuclear magnetic resonance relaxation data. The ensemble obtained suggests an induced fit mechanism for recognition of target RNA by the protein. Copyright © 2016 Biophysical Society. Published by Elsevier Inc. All rights reserved.

Comparison of NMR and crystal structures highlights conformational isomerism in protein active sites

International Nuclear Information System (INIS)

Serrano, Pedro; Pedrini, Bill; Geralt, Michael; Jaudzems, Kristaps; Mohanty, Biswaranjan; Horst, Reto; Herrmann, Torsten; Elsliger, Marc-André; Wilson, Ian A.; Wüthrich, Kurt

2010-01-01

millisecond time scale that appears to be frozen in the crystals. These observations suggest that a search for molecular regions showing increased structural disorder and slow dynamic processes in solution while being well ordered in the corresponding crystal structure might be a valid initial step in the challenge of identifying putative active sites in functionally unannotated proteins with known three-dimensional structure

PREFMD: a web server for protein structure refinement via molecular dynamics simulations.

Science.gov (United States)

Heo, Lim; Feig, Michael

2018-03-15

Refinement of protein structure models is a long-standing problem in structural bioinformatics. Molecular dynamics-based methods have emerged as an avenue to achieve consistent refinement. The PREFMD web server implements an optimized protocol based on the method successfully tested in CASP11. Validation with recent CASP refinement targets shows consistent and more significant improvement in global structure accuracy over other state-of-the-art servers. PREFMD is freely available as a web server at http://feiglab.org/prefmd. Scripts for running PREFMD as a stand-alone package are available at https://github.com/feiglab/prefmd.git. feig@msu.edu. Supplementary data are available at Bioinformatics online.

Amino acid code of protein secondary structure.

Science.gov (United States)

Shestopalov, B V

2003-01-01

The calculation of protein three-dimensional structure from the amino acid sequence is a fundamental problem to be solved. This paper presents principles of the code theory of protein secondary structure, and their consequence--the amino acid code of protein secondary structure. The doublet code model of protein secondary structure, developed earlier by the author (Shestopalov, 1990), is part of this theory. The theory basis are: 1) the name secondary structure is assigned to the conformation, stabilized only by the nearest (intraresidual) and middle-range (at a distance no more than that between residues i and i + 5) interactions; 2) the secondary structure consists of regular (alpha-helical and beta-structural) and irregular (coil) segments; 3) the alpha-helices, beta-strands and coil segments are encoded, respectively, by residue pairs (i, i + 4), (i, i + 2), (i, i = 1), according to the numbers of residues per period, 3.6, 2, 1; 4) all such pairs in the amino acid sequence are codons for elementary structural elements, or structurons; 5) the codons are divided into 21 types depending on their strength, i.e. their encoding capability; 6) overlappings of structurons of one and the same structure generate the longer segments of this structure; 7) overlapping of structurons of different structures is forbidden, and therefore selection of codons is required, the codon selection is hierarchic; 8) the code theory of protein secondary structure generates six variants of the amino acid code of protein secondary structure. There are two possible kinds of model construction based on the theory: the physical one using physical properties of amino acid residues, and the statistical one using results of statistical analysis of a great body of structural data. Some evident consequences of the theory are: a) the theory can be used for calculating the secondary structure from the amino acid sequence as a partial solution of the problem of calculation of protein three

Detecting mutually exclusive interactions in protein-protein interaction maps.

KAUST Repository

Sánchez Claros, Carmen

2012-06-08

Comprehensive protein interaction maps can complement genetic and biochemical experiments and allow the formulation of new hypotheses to be tested in the system of interest. The computational analysis of the maps may help to focus on interesting cases and thereby to appropriately prioritize the validation experiments. We show here that, by automatically comparing and analyzing structurally similar regions of proteins of known structure interacting with a common partner, it is possible to identify mutually exclusive interactions present in the maps with a sensitivity of 70% and a specificity higher than 85% and that, in about three fourth of the correctly identified complexes, we also correctly recognize at least one residue (five on average) belonging to the interaction interface. Given the present and continuously increasing number of proteins of known structure, the requirement of the knowledge of the structure of the interacting proteins does not substantially impact on the coverage of our strategy that can be estimated to be around 25%. We also introduce here the Estrella server that embodies this strategy, is designed for users interested in validating specific hypotheses about the functional role of a protein-protein interaction and it also allows access to pre-computed data for seven organisms.

Detecting mutually exclusive interactions in protein-protein interaction maps.

KAUST Repository

Sá nchez Claros, Carmen; Tramontano, Anna

2012-01-01

Comprehensive protein interaction maps can complement genetic and biochemical experiments and allow the formulation of new hypotheses to be tested in the system of interest. The computational analysis of the maps may help to focus on interesting cases and thereby to appropriately prioritize the validation experiments. We show here that, by automatically comparing and analyzing structurally similar regions of proteins of known structure interacting with a common partner, it is possible to identify mutually exclusive interactions present in the maps with a sensitivity of 70% and a specificity higher than 85% and that, in about three fourth of the correctly identified complexes, we also correctly recognize at least one residue (five on average) belonging to the interaction interface. Given the present and continuously increasing number of proteins of known structure, the requirement of the knowledge of the structure of the interacting proteins does not substantially impact on the coverage of our strategy that can be estimated to be around 25%. We also introduce here the Estrella server that embodies this strategy, is designed for users interested in validating specific hypotheses about the functional role of a protein-protein interaction and it also allows access to pre-computed data for seven organisms.

Oligomerisation status and evolutionary conservation of interfaces of protein structural domain superfamilies.

Science.gov (United States)

Sukhwal, Anshul; Sowdhamini, Ramanathan

2013-07-01

Protein-protein interactions are important in carrying out many biological processes and functions. These interactions may be either permanent or of temporary nature. Several studies have employed tools like solvent accessibility and graph theory to identify these interactions, but still more studies need to be performed to quantify and validate them. Although we now have many databases available with predicted and experimental results on protein-protein interactions, we still do not have many databases which focus on providing structural details of the interacting complexes, their oligomerisation state and homologues. In this work, protein-protein interactions have been thoroughly investigated within the structural regime and quantified for their strength using calculated pseudoenergies. The PPCheck server, an in-house webserver, has been used for calculating the pseudoenergies like van der Waals, hydrogen bonds and electrostatic energy based on distances between atoms of amino acids from two interacting proteins. PPCheck can be visited at . Based on statistical data, as obtained by studying established protein-protein interacting complexes from earlier studies, we came to a conclusion that an average protein-protein interface consisted of about 51 to 150 amino acid residues and the generalized energy per residue ranged from -2 kJ mol(-1) to -6 kJ mol(-1). We found that some of the proteins have an exceptionally higher number of amino acids at the interface and it was purely because of their elaborate interface or extended topology i.e. some of their secondary structure regions or loops were either inter-mixing or running parallel to one another or they were taking part in domain swapping. Residue networks were prepared for all the amino acids of the interacting proteins involved in different types of interactions (like van der Waals, hydrogen-bonding, electrostatic or intramolecular interactions) and were analysed between the query domain-interacting partner pair

Structural Validation of the Holistic Wellness Assessment

Science.gov (United States)

Brown, Charlene; Applegate, E. Brooks; Yildiz, Mustafa

2015-01-01

The Holistic Wellness Assessment (HWA) is a relatively new assessment instrument based on an emergent transdisciplinary model of wellness. This study validated the factor structure identified via exploratory factor analysis (EFA), assessed test-retest reliability, and investigated concurrent validity of the HWA in three separate samples. The…

Overcoming barriers to membrane protein structure determination.

Science.gov (United States)

Bill, Roslyn M; Henderson, Peter J F; Iwata, So; Kunji, Edmund R S; Michel, Hartmut; Neutze, Richard; Newstead, Simon; Poolman, Bert; Tate, Christopher G; Vogel, Horst

2011-04-01

After decades of slow progress, the pace of research on membrane protein structures is beginning to quicken thanks to various improvements in technology, including protein engineering and microfocus X-ray diffraction. Here we review these developments and, where possible, highlight generic new approaches to solving membrane protein structures based on recent technological advances. Rational approaches to overcoming the bottlenecks in the field are urgently required as membrane proteins, which typically comprise ~30% of the proteomes of organisms, are dramatically under-represented in the structural database of the Protein Data Bank.

The Identification and Validation of Novel Small Proteins in Pseudomonas Putida KT-2440

DEFF Research Database (Denmark)

Yang, Xiaochen; Long, Katherine

2014-01-01

and activities and may lead to the discovery of novel antimicrobial agents. Our project focuses on the identification, validation and characterization of novel s-­‐proteins in the bacterium Pseudomonas putida KT-­2440. As there is virtually no information on s-­‐proteins in pseudomonads, the first step......, total protein samples are prepared, fractionated, and analyzed with mass spectrometry (MS/MS). The MS/MS data are compared to a custom database containing >80000 putative sORF sequences to identify candidates for validation. A total of 56 and 22 putative sORFs were obtained from MS/MS data...... and bioinformatics prediction, respectively, where there is no overlap between the putative sORFs obtained from the two approaches. The sequences encoding the putative sORFs will be integrated onto the Tn7 site on the chromosome as well as on a plasmid expression vector for validation....

CMsearch: simultaneous exploration of protein sequence space and structure space improves not only protein homology detection but also protein structure prediction

KAUST Repository

Cui, Xuefeng; Lu, Zhiwu; Wang, Sheng; Jing-Yan Wang, Jim; Gao, Xin

2016-01-01

Motivation: Protein homology detection, a fundamental problem in computational biology, is an indispensable step toward predicting protein structures and understanding protein functions. Despite the advances in recent decades on sequence alignment

Structural determination of intact proteins using mass spectrometry

Science.gov (United States)

Kruppa, Gary [San Francisco, CA; Schoeniger, Joseph S [Oakland, CA; Young, Malin M [Livermore, CA

2008-05-06

The present invention relates to novel methods of determining the sequence and structure of proteins. Specifically, the present invention allows for the analysis of intact proteins within a mass spectrometer. Therefore, preparatory separations need not be performed prior to introducing a protein sample into the mass spectrometer. Also disclosed herein are new instrumental developments for enhancing the signal from the desired modified proteins, methods for producing controlled protein fragments in the mass spectrometer, eliminating complex microseparations, and protein preparatory chemical steps necessary for cross-linking based protein structure determination.Additionally, the preferred method of the present invention involves the determination of protein structures utilizing a top-down analysis of protein structures to search for covalent modifications. In the preferred method, intact proteins are ionized and fragmented within the mass spectrometer.

Structural basis for target protein recognition by the protein disulfide reductase thioredoxin

DEFF Research Database (Denmark)

Maeda, Kenji; Hägglund, Per; Finnie, Christine

2006-01-01

Thioredoxin is ubiquitous and regulates various target proteins through disulfide bond reduction. We report the structure of thioredoxin (HvTrxh2 from barley) in a reaction intermediate complex with a protein substrate, barley alpha-amylase/subtilisin inhibitor (BASI). The crystal structure...... of this mixed disulfide shows a conserved hydrophobic motif in thioredoxin interacting with a sequence of residues from BASI through van der Waals contacts and backbone-backbone hydrogen bonds. The observed structural complementarity suggests that the recognition of features around protein disulfides plays...... a major role in the specificity and protein disulfide reductase activity of thioredoxin. This novel insight into the function of thioredoxin constitutes a basis for comprehensive understanding of its biological role. Moreover, comparison with structurally related proteins shows that thioredoxin shares...

Testing of the preliminary OMERACT validation criteria for a biomarker to be regarded as reflecting structural damage endpoints in rheumatoid arthritis clinical trials: the example of C-reactive protein

DEFF Research Database (Denmark)

Keeling, Stephanie O; Landewe, Robert; van der Heijde, Desiree

2007-01-01

OBJECTIVE: A list of 14 criteria for guiding the validation of a soluble biomarker as reflecting structural damage endpoints in rheumatoid arthritis (RA) clinical trials was drafted by an international working group after a Delphi consensus exercise. C-reactive protein (CRP), a soluble biomarker...... of individual criteria in the draft set. METHODS: A systematic literature review was conducted to elicit evidence in support of each specific criterion composing the 14-criteria draft set. A summary of the key literature findings per criterion was presented to both the working group and to participants...

Protein structure: geometry, topology and classification

Energy Technology Data Exchange (ETDEWEB)

Taylor, William R.; May, Alex C.W.; Brown, Nigel P.; Aszodi, Andras [Division of Mathematical Biology, National Institute for Medical Research, London (United Kingdom)

2001-04-01

The structural principals of proteins are reviewed and analysed from a geometric perspective with a view to revealing the underlying regularities in their construction. Computer methods for the automatic comparison and classification of these structures are then reviewed with an analysis of the statistical significance of comparing different shapes. Following an analysis of the current state of the classification of proteins, more abstract geometric and topological representations are explored, including the occurrence of knotted topologies. The review concludes with a consideration of the origin of higher-level symmetries in protein structure. (author)

Use of designed sequences in protein structure recognition.

Science.gov (United States)

Kumar, Gayatri; Mudgal, Richa; Srinivasan, Narayanaswamy; Sandhya, Sankaran

2018-05-09

Knowledge of the protein structure is a pre-requisite for improved understanding of molecular function. The gap in the sequence-structure space has increased in the post-genomic era. Grouping related protein sequences into families can aid in narrowing the gap. In the Pfam database, structure description is provided for part or full-length proteins of 7726 families. For the remaining 52% of the families, information on 3-D structure is not yet available. We use the computationally designed sequences that are intermediately related to two protein domain families, which are already known to share the same fold. These strategically designed sequences enable detection of distant relationships and here, we have employed them for the purpose of structure recognition of protein families of yet unknown structure. We first measured the success rate of our approach using a dataset of protein families of known fold and achieved a success rate of 88%. Next, for 1392 families of yet unknown structure, we made structural assignments for part/full length of the proteins. Fold association for 423 domains of unknown function (DUFs) are provided as a step towards functional annotation. The results indicate that knowledge-based filling of gaps in protein sequence space is a lucrative approach for structure recognition. Such sequences assist in traversal through protein sequence space and effectively function as 'linkers', where natural linkers between distant proteins are unavailable. This article was reviewed by Oliviero Carugo, Christine Orengo and Srikrishna Subramanian.

Decoding Structural Properties of a Partially Unfolded Protein Substrate: En Route to Chaperone Binding

Science.gov (United States)

Nagpal, Suhani; Tiwari, Satyam; Mapa, Koyeli; Thukral, Lipi

2015-01-01

Many proteins comprising of complex topologies require molecular chaperones to achieve their unique three-dimensional folded structure. The E.coli chaperone, GroEL binds with a large number of unfolded and partially folded proteins, to facilitate proper folding and prevent misfolding and aggregation. Although the major structural components of GroEL are well defined, scaffolds of the non-native substrates that determine chaperone-mediated folding have been difficult to recognize. Here we performed all-atomistic and replica-exchange molecular dynamics simulations to dissect non-native ensemble of an obligate GroEL folder, DapA. Thermodynamics analyses of unfolding simulations revealed populated intermediates with distinct structural characteristics. We found that surface exposed hydrophobic patches are significantly increased, primarily contributed from native and non-native β-sheet elements. We validate the structural properties of these conformers using experimental data, including circular dichroism (CD), 1-anilinonaphthalene-8-sulfonic acid (ANS) binding measurements and previously reported hydrogen-deutrium exchange coupled to mass spectrometry (HDX-MS). Further, we constructed network graphs to elucidate long-range intra-protein connectivity of native and intermediate topologies, demonstrating regions that serve as central “hubs”. Overall, our results implicate that genomic variations (or mutations) in the distinct regions of protein structures might disrupt these topological signatures disabling chaperone-mediated folding, leading to formation of aggregates. PMID:26394388

PONDEROSA, an automated 3D-NOESY peak picking program, enables automated protein structure determination.

Science.gov (United States)

Lee, Woonghee; Kim, Jin Hae; Westler, William M; Markley, John L

2011-06-15

PONDEROSA (Peak-picking Of Noe Data Enabled by Restriction of Shift Assignments) accepts input information consisting of a protein sequence, backbone and sidechain NMR resonance assignments, and 3D-NOESY ((13)C-edited and/or (15)N-edited) spectra, and returns assignments of NOESY crosspeaks, distance and angle constraints, and a reliable NMR structure represented by a family of conformers. PONDEROSA incorporates and integrates external software packages (TALOS+, STRIDE and CYANA) to carry out different steps in the structure determination. PONDEROSA implements internal functions that identify and validate NOESY peak assignments and assess the quality of the calculated three-dimensional structure of the protein. The robustness of the analysis results from PONDEROSA's hierarchical processing steps that involve iterative interaction among the internal and external modules. PONDEROSA supports a variety of input formats: SPARKY assignment table (.shifts) and spectrum file formats (.ucsf), XEASY proton file format (.prot), and NMR-STAR format (.star). To demonstrate the utility of PONDEROSA, we used the package to determine 3D structures of two proteins: human ubiquitin and Escherichia coli iron-sulfur scaffold protein variant IscU(D39A). The automatically generated structural constraints and ensembles of conformers were as good as or better than those determined previously by much less automated means. The program, in the form of binary code along with tutorials and reference manuals, is available at http://ponderosa.nmrfam.wisc.edu/.

PDB2CD visualises dynamics within protein structures.

Science.gov (United States)

Janes, Robert W

2017-10-01

Proteins tend to have defined conformations, a key factor in enabling their function. Atomic resolution structures of proteins are predominantly obtained by either solution nuclear magnetic resonance (NMR) or crystal structure methods. However, when considering a protein whose structure has been determined by both these approaches, on many occasions, the resultant conformations are subtly different, as illustrated by the examples in this study. The solution NMR approach invariably results in a cluster of structures whose conformations satisfy the distance boundaries imposed by the data collected; it might be argued that this is evidence of the dynamics of proteins when in solution. In crystal structures, the proteins are often in an energy minimum state which can result in an increase in the extent of regular secondary structure present relative to the solution state depicted by NMR, because the more dynamic ends of alpha helices and beta strands can become ordered at the lower temperatures. This study examines a novel way to display the differences in conformations within an NMR ensemble and between these and a crystal structure of a protein. Circular dichroism (CD) spectroscopy can be used to characterise protein structures in solution. Using the new bioinformatics tool, PDB2CD, which generates CD spectra from atomic resolution protein structures, the differences between, and possible dynamic range of, conformations adopted by a protein can be visualised.

Course 12: Proteins: Structural, Thermodynamic and Kinetic Aspects

Science.gov (United States)

Finkelstein, A. V.

1 Introduction 2 Overview of protein architectures and discussion of physical background of their natural selection 2.1 Protein structures 2.2 Physical selection of protein structures 3 Thermodynamic aspects of protein folding 3.1 Reversible denaturation of protein structures 3.2 What do denatured proteins look like? 3.3 Why denaturation of a globular protein is the first-order phase transition 3.4 "Gap" in energy spectrum: The main characteristic that distinguishes protein chains from random polymers 4 Kinetic aspects of protein folding 4.1 Protein folding in vivo 4.2 Protein folding in vitro (in the test-tube) 4.3 Theory of protein folding rates and solution of the Levinthal paradox

Protein interfacial structure and nanotoxicology

Energy Technology Data Exchange (ETDEWEB)

White, John W. [Research School of Chemistry, Australian National University, Canberra (Australia)], E-mail: jww@rsc.anu.edu.au; Perriman, Adam W.; McGillivray, Duncan J.; Lin, J.-M. [Research School of Chemistry, Australian National University, Canberra (Australia)

2009-02-21

Here we briefly recapitulate the use of X-ray and neutron reflectometry at the air-water interface to find protein structures and thermodynamics at interfaces and test a possibility for understanding those interactions between nanoparticles and proteins which lead to nanoparticle toxicology through entry into living cells. Stable monomolecular protein films have been made at the air-water interface and, with a specially designed vessel, the substrate changed from that which the air-water interfacial film was deposited. This procedure allows interactions, both chemical and physical, between introduced species and the monomolecular film to be studied by reflectometry. The method is briefly illustrated here with some new results on protein-protein interaction between {beta}-casein and {kappa}-casein at the air-water interface using X-rays. These two proteins are an essential component of the structure of milk. In the experiments reported, specific and directional interactions appear to cause different interfacial structures if first, a {beta}-casein monolayer is attacked by a {kappa}-casein solution compared to the reverse. The additional contrast associated with neutrons will be an advantage here. We then show the first results of experiments on the interaction of a {beta}-casein monolayer with a nanoparticle titanium oxide sol, foreshadowing the study of the nanoparticle 'corona' thought to be important for nanoparticle-cell wall penetration.

Protein interfacial structure and nanotoxicology

International Nuclear Information System (INIS)

White, John W.; Perriman, Adam W.; McGillivray, Duncan J.; Lin, J.-M.

2009-01-01

Here we briefly recapitulate the use of X-ray and neutron reflectometry at the air-water interface to find protein structures and thermodynamics at interfaces and test a possibility for understanding those interactions between nanoparticles and proteins which lead to nanoparticle toxicology through entry into living cells. Stable monomolecular protein films have been made at the air-water interface and, with a specially designed vessel, the substrate changed from that which the air-water interfacial film was deposited. This procedure allows interactions, both chemical and physical, between introduced species and the monomolecular film to be studied by reflectometry. The method is briefly illustrated here with some new results on protein-protein interaction between β-casein and κ-casein at the air-water interface using X-rays. These two proteins are an essential component of the structure of milk. In the experiments reported, specific and directional interactions appear to cause different interfacial structures if first, a β-casein monolayer is attacked by a κ-casein solution compared to the reverse. The additional contrast associated with neutrons will be an advantage here. We then show the first results of experiments on the interaction of a β-casein monolayer with a nanoparticle titanium oxide sol, foreshadowing the study of the nanoparticle 'corona' thought to be important for nanoparticle-cell wall penetration.

PSAIA – Protein Structure and Interaction Analyzer

Directory of Open Access Journals (Sweden)

Vlahoviček Kristian

2008-04-01

Full Text Available Abstract Background PSAIA (Protein Structure and Interaction Analyzer was developed to compute geometric parameters for large sets of protein structures in order to predict and investigate protein-protein interaction sites. Results In addition to most relevant established algorithms, PSAIA offers a new method PIADA (Protein Interaction Atom Distance Algorithm for the determination of residue interaction pairs. We found that PIADA produced more satisfactory results than comparable algorithms implemented in PSAIA. Particular advantages of PSAIA include its capacity to combine different methods to detect the locations and types of interactions between residues and its ability, without any further automation steps, to handle large numbers of protein structures and complexes. Generally, the integration of a variety of methods enables PSAIA to offer easier automation of analysis and greater reliability of results. PSAIA can be used either via a graphical user interface or from the command-line. Results are generated in either tabular or XML format. Conclusion In a straightforward fashion and for large sets of protein structures, PSAIA enables the calculation of protein geometric parameters and the determination of location and type for protein-protein interaction sites. XML formatted output enables easy conversion of results to various formats suitable for statistic analysis. Results from smaller data sets demonstrated the influence of geometry on protein interaction sites. Comprehensive analysis of properties of large data sets lead to new information useful in the prediction of protein-protein interaction sites.

The structure of a cholesterol-trapping protein

Science.gov (United States)

cholesterol-trapping protein Contact: Dan Krotz, dakrotz@lbl.gov Berkeley Lab Science Beat Lab website index Institute researchers determined the three-dimensional structure of a protein that controls cholesterol level in the bloodstream. Knowing the structure of the protein, a cellular receptor that ensnares

Protein structure determination by exhaustive search of Protein Data Bank derived databases.

Science.gov (United States)

Stokes-Rees, Ian; Sliz, Piotr

2010-12-14

Parallel sequence and structure alignment tools have become ubiquitous and invaluable at all levels in the study of biological systems. We demonstrate the application and utility of this same parallel search paradigm to the process of protein structure determination, benefitting from the large and growing corpus of known structures. Such searches were previously computationally intractable. Through the method of Wide Search Molecular Replacement, developed here, they can be completed in a few hours with the aide of national-scale federated cyberinfrastructure. By dramatically expanding the range of models considered for structure determination, we show that small (less than 12% structural coverage) and low sequence identity (less than 20% identity) template structures can be identified through multidimensional template scoring metrics and used for structure determination. Many new macromolecular complexes can benefit significantly from such a technique due to the lack of known homologous protein folds or sequences. We demonstrate the effectiveness of the method by determining the structure of a full-length p97 homologue from Trichoplusia ni. Example cases with the MHC/T-cell receptor complex and the EmoB protein provide systematic estimates of minimum sequence identity, structure coverage, and structural similarity required for this method to succeed. We describe how this structure-search approach and other novel computationally intensive workflows are made tractable through integration with the US national computational cyberinfrastructure, allowing, for example, rapid processing of the entire Structural Classification of Proteins protein fragment database.

Improving the Accuracy of NMR Structures of Large Proteins Using Pseudocontact Shifts as Long-Range Restraints

Energy Technology Data Exchange (ETDEWEB)

Gaponenko, Vadim [National Cancer Institute, Structural Biophysics Laboratory (United States); Sarma, Siddhartha P. [Indian Institute of Science, Molecular Biophysics Unit (India); Altieri, Amanda S. [National Cancer Institute, Structural Biophysics Laboratory (United States); Horita, David A. [Wake Forest University School of Medicine, Department of Biochemistry (United States); Li, Jess; Byrd, R. Andrew [National Cancer Institute, Structural Biophysics Laboratory (United States)], E-mail: rabyrd@ncifcrf.gov

2004-03-15

We demonstrate improved accuracy in protein structure determination for large ({>=}30 kDa), deuterated proteins (e.g. STAT4{sub NT}) via the combination of pseudocontact shifts for amide and methyl protons with the available NOEs in methyl-protonated proteins. The improved accuracy is cross validated by Q-factors determined from residual dipolar couplings measured as a result of magnetic susceptibility alignment. The paramagnet is introduced via binding to thiol-reactive EDTA, and multiple sites can be serially engineered to obtain data from alternative orientations of the paramagnetic anisotropic susceptibility tensor. The technique is advantageous for systems where the target protein has strong interactions with known alignment media.

Function and structure of GFP-like proteins in the protein data bank.

Science.gov (United States)

Ong, Wayne J-H; Alvarez, Samuel; Leroux, Ivan E; Shahid, Ramza S; Samma, Alex A; Peshkepija, Paola; Morgan, Alicia L; Mulcahy, Shawn; Zimmer, Marc

2011-04-01

The RCSB protein databank contains 266 crystal structures of green fluorescent proteins (GFP) and GFP-like proteins. This is the first systematic analysis of all the GFP-like structures in the pdb. We have used the pdb to examine the function of fluorescent proteins (FP) in nature, aspects of excited state proton transfer (ESPT) in FPs, deformation from planarity of the chromophore and chromophore maturation. The conclusions reached in this review are that (1) The lid residues are highly conserved, particularly those on the "top" of the β-barrel. They are important to the function of GFP-like proteins, perhaps in protecting the chromophore or in β-barrel formation. (2) The primary/ancestral function of GFP-like proteins may well be to aid in light induced electron transfer. (3) The structural prerequisites for light activated proton pumps exist in many structures and it's possible that like bioluminescence, proton pumps are secondary functions of GFP-like proteins. (4) In most GFP-like proteins the protein matrix exerts a significant strain on planar chromophores forcing most GFP-like proteins to adopt non-planar chromophores. These chromophoric deviations from planarity play an important role in determining the fluorescence quantum yield. (5) The chemospatial characteristics of the chromophore cavity determine the isomerization state of the chromophore. The cavities of highlighter proteins that can undergo cis/trans isomerization have chemospatial properties that are common to both cis and trans GFP-like proteins.

Classification of proteins: available structural space for molecular modeling.

Science.gov (United States)

Andreeva, Antonina

2012-01-01

The wealth of available protein structural data provides unprecedented opportunity to study and better understand the underlying principles of protein folding and protein structure evolution. A key to achieving this lies in the ability to analyse these data and to organize them in a coherent classification scheme. Over the past years several protein classifications have been developed that aim to group proteins based on their structural relationships. Some of these classification schemes explore the concept of structural neighbourhood (structural continuum), whereas other utilize the notion of protein evolution and thus provide a discrete rather than continuum view of protein structure space. This chapter presents a strategy for classification of proteins with known three-dimensional structure. Steps in the classification process along with basic definitions are introduced. Examples illustrating some fundamental concepts of protein folding and evolution with a special focus on the exceptions to them are presented.

The Expanded FindCore Method for Identification of a Core Atom Set for Assessment of Protein Structure Prediction

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Snyder, David A.; Grullon, Jennifer; Huang, Yuanpeng J.; Tejero, Roberto; Montelione, Gaetano T.

2014-01-01

Maximizing the scientific impact of NMR-based structure determination requires robust and statistically sound methods for assessing the precision of NMR-derived structures. In particular, a method to define a core atom set for calculating superimpositions and validating structure predictions is critical to the use of NMR-derived structures as targets in the CASP competition. FindCore (D.A. Snyder and G.T. Montelione PROTEINS 2005;59:673–686) is a superimposition independent method for identifying a core atom set, and partitioning that set into domains. However, as FindCore optimizes superimposition by sensitively excluding not-well-defined atoms, the FindCore core may not comprise all atoms suitable for use in certain applications of NMR structures, including the CASP assessment process. Adapting the FindCore approach to assess predicted models against experimental NMR structures in CASP10 required modification of the FindCore method. This paper describes conventions and a standard protocol to calculate an “Expanded FindCore” atom set suitable for validation and application in biological and biophysical contexts. A key application of the Expanded FindCore method is to identify a core set of atoms in the experimental NMR structure for which it makes sense to validate predicted protein structure models. We demonstrate the application of this Expanded FindCore method in characterizing well-defined regions of 18 NMR-derived CASP10 target structures. The Expanded FindCore protocol defines “expanded core atom sets” that match an expert’s intuition of which parts of the structure are sufficiently well-defined to use in assessing CASP model predictions. We also illustrate the impact of this analysis on the CASP GDT assessment scores. PMID:24327305

Protein structural similarity search by Ramachandran codes

Directory of Open Access Journals (Sweden)

Chang Chih-Hung

2007-08-01

Full Text Available Abstract Background Protein structural data has increased exponentially, such that fast and accurate tools are necessary to access structure similarity search. To improve the search speed, several methods have been designed to reduce three-dimensional protein structures to one-dimensional text strings that are then analyzed by traditional sequence alignment methods; however, the accuracy is usually sacrificed and the speed is still unable to match sequence similarity search tools. Here, we aimed to improve the linear encoding methodology and develop efficient search tools that can rapidly retrieve structural homologs from large protein databases. Results We propose a new linear encoding method, SARST (Structural similarity search Aided by Ramachandran Sequential Transformation. SARST transforms protein structures into text strings through a Ramachandran map organized by nearest-neighbor clustering and uses a regenerative approach to produce substitution matrices. Then, classical sequence similarity search methods can be applied to the structural similarity search. Its accuracy is similar to Combinatorial Extension (CE and works over 243,000 times faster, searching 34,000 proteins in 0.34 sec with a 3.2-GHz CPU. SARST provides statistically meaningful expectation values to assess the retrieved information. It has been implemented into a web service and a stand-alone Java program that is able to run on many different platforms. Conclusion As a database search method, SARST can rapidly distinguish high from low similarities and efficiently retrieve homologous structures. It demonstrates that the easily accessible linear encoding methodology has the potential to serve as a foundation for efficient protein structural similarity search tools. These search tools are supposed applicable to automated and high-throughput functional annotations or predictions for the ever increasing number of published protein structures in this post-genomic era.

Proteins with Novel Structure, Function and Dynamics

Science.gov (United States)

Pohorille, Andrew

2014-01-01

Recently, a small enzyme that ligates two RNA fragments with the rate of 10(exp 6) above background was evolved in vitro (Seelig and Szostak, Nature 448:828-831, 2007). This enzyme does not resemble any contemporary protein (Chao et al., Nature Chem. Biol. 9:81-83, 2013). It consists of a dynamic, catalytic loop, a small, rigid core containing two zinc ions coordinated by neighboring amino acids, and two highly flexible tails that might be unimportant for protein function. In contrast to other proteins, this enzyme does not contain ordered secondary structure elements, such as alpha-helix or beta-sheet. The loop is kept together by just two interactions of a charged residue and a histidine with a zinc ion, which they coordinate on the opposite side of the loop. Such structure appears to be very fragile. Surprisingly, computer simulations indicate otherwise. As the coordinating, charged residue is mutated to alanine, another, nearby charged residue takes its place, thus keeping the structure nearly intact. If this residue is also substituted by alanine a salt bridge involving two other, charged residues on the opposite sides of the loop keeps the loop in place. These adjustments are facilitated by high flexibility of the protein. Computational predictions have been confirmed experimentally, as both mutants retain full activity and overall structure. These results challenge our notions about what is required for protein activity and about the relationship between protein dynamics, stability and robustness. We hypothesize that small, highly dynamic proteins could be both active and fault tolerant in ways that many other proteins are not, i.e. they can adjust to retain their structure and activity even if subjected to mutations in structurally critical regions. This opens the doors for designing proteins with novel functions, structures and dynamics that have not been yet considered.

Structure and function of nanoparticle-protein conjugates

International Nuclear Information System (INIS)

Aubin-Tam, M-E; Hamad-Schifferli, K

2008-01-01

Conjugation of proteins to nanoparticles has numerous applications in sensing, imaging, delivery, catalysis, therapy and control of protein structure and activity. Therefore, characterizing the nanoparticle-protein interface is of great importance. A variety of covalent and non-covalent linking chemistries have been reported for nanoparticle attachment. Site-specific labeling is desirable in order to control the protein orientation on the nanoparticle, which is crucial in many applications such as fluorescence resonance energy transfer. We evaluate methods for successful site-specific attachment. Typically, a specific protein residue is linked directly to the nanoparticle core or to the ligand. As conjugation often affects the protein structure and function, techniques to probe structure and activity are assessed. We also examine how molecular dynamics simulations of conjugates would complete those experimental techniques in order to provide atomistic details on the effect of nanoparticle attachment. Characterization studies of nanoparticle-protein complexes show that the structure and function are influenced by the chemistry of the nanoparticle ligand, the nanoparticle size, the nanoparticle material, the stoichiometry of the conjugates, the labeling site on the protein and the nature of the linkage (covalent versus non-covalent)

Protein structure database search and evolutionary classification.

Science.gov (United States)

Yang, Jinn-Moon; Tung, Chi-Hua

2006-01-01

As more protein structures become available and structural genomics efforts provide structural models in a genome-wide strategy, there is a growing need for fast and accurate methods for discovering homologous proteins and evolutionary classifications of newly determined structures. We have developed 3D-BLAST, in part, to address these issues. 3D-BLAST is as fast as BLAST and calculates the statistical significance (E-value) of an alignment to indicate the reliability of the prediction. Using this method, we first identified 23 states of the structural alphabet that represent pattern profiles of the backbone fragments and then used them to represent protein structure databases as structural alphabet sequence databases (SADB). Our method enhanced BLAST as a search method, using a new structural alphabet substitution matrix (SASM) to find the longest common substructures with high-scoring structured segment pairs from an SADB database. Using personal computers with Intel Pentium4 (2.8 GHz) processors, our method searched more than 10 000 protein structures in 1.3 s and achieved a good agreement with search results from detailed structure alignment methods. [3D-BLAST is available at http://3d-blast.life.nctu.edu.tw].

Modeling protein structures: construction and their applications.

Science.gov (United States)

Ring, C S; Cohen, F E

1993-06-01

Although no general solution to the protein folding problem exists, the three-dimensional structures of proteins are being successfully predicted when experimentally derived constraints are used in conjunction with heuristic methods. In the case of interleukin-4, mutagenesis data and CD spectroscopy were instrumental in the accurate assignment of secondary structure. In addition, the tertiary structure was highly constrained by six cysteines separated by many residues that formed three disulfide bridges. Although the correct structure was a member of a short list of plausible structures, the "best" structure was the topological enantiomer of the experimentally determined conformation. For many proteases, other experimentally derived structures can be used as templates to identify the secondary structure elements. In a procedure called modeling by homology, the structure of a known protein is used as a scaffold to predict the structure of another related protein. This method has been used to model a serine and a cysteine protease that are important in the schistosome and malarial life cycles, respectively. The model structures were then used to identify putative small molecule enzyme inhibitors computationally. Experiments confirm that some of these nonpeptidic compounds are active at concentrations of less than 10 microM.

Identification and validation of novel small proteins in Pseudomonas putida

DEFF Research Database (Denmark)

Yang, Xiaochen; Ingemann Jensen, Sheila; Wulff, Tune

2016-01-01

Small proteins of fifty amino acids or less have been understudied due to difficulties that impede their annotation and detection. In order to obtain information on small open reading frames (sORFs) in P. putida, bioinformatic and proteomic approaches were used to identify putative small open...... reading frames (sORFs) in the well-characterized strain KT2440. A plasmid-based system was established for sORF validation, enabling expression of C-terminal sequential peptide affinity (SPA) tagged variants and their detection via protein immunoblotting. Out of 22 tested putative sORFs, the expression...... of fourteen sORFs was confirmed, where all except one are novel. All of the validated sORFs except one are located adjacent to annotated genes on the same strand and three are in close proximity to genes with known functions. These include an ABC transporter operon and the two transcriptional regulators Fis...

Improving the accuracy of protein secondary structure prediction using structural alignment

Directory of Open Access Journals (Sweden)

Gallin Warren J

2006-06-01

Full Text Available Abstract Background The accuracy of protein secondary structure prediction has steadily improved over the past 30 years. Now many secondary structure prediction methods routinely achieve an accuracy (Q3 of about 75%. We believe this accuracy could be further improved by including structure (as opposed to sequence database comparisons as part of the prediction process. Indeed, given the large size of the Protein Data Bank (>35,000 sequences, the probability of a newly identified sequence having a structural homologue is actually quite high. Results We have developed a method that performs structure-based sequence alignments as part of the secondary structure prediction process. By mapping the structure of a known homologue (sequence ID >25% onto the query protein's sequence, it is possible to predict at least a portion of that query protein's secondary structure. By integrating this structural alignment approach with conventional (sequence-based secondary structure methods and then combining it with a "jury-of-experts" system to generate a consensus result, it is possible to attain very high prediction accuracy. Using a sequence-unique test set of 1644 proteins from EVA, this new method achieves an average Q3 score of 81.3%. Extensive testing indicates this is approximately 4–5% better than any other method currently available. Assessments using non sequence-unique test sets (typical of those used in proteome annotation or structural genomics indicate that this new method can achieve a Q3 score approaching 88%. Conclusion By using both sequence and structure databases and by exploiting the latest techniques in machine learning it is possible to routinely predict protein secondary structure with an accuracy well above 80%. A program and web server, called PROTEUS, that performs these secondary structure predictions is accessible at http://wishart.biology.ualberta.ca/proteus. For high throughput or batch sequence analyses, the PROTEUS programs

Prediction of Protein Structural Classes for Low-Similarity Sequences Based on Consensus Sequence and Segmented PSSM

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Yunyun Liang

2015-01-01

Full Text Available Prediction of protein structural classes for low-similarity sequences is useful for understanding fold patterns, regulation, functions, and interactions of proteins. It is well known that feature extraction is significant to prediction of protein structural class and it mainly uses protein primary sequence, predicted secondary structure sequence, and position-specific scoring matrix (PSSM. Currently, prediction solely based on the PSSM has played a key role in improving the prediction accuracy. In this paper, we propose a novel method called CSP-SegPseP-SegACP by fusing consensus sequence (CS, segmented PsePSSM, and segmented autocovariance transformation (ACT based on PSSM. Three widely used low-similarity datasets (1189, 25PDB, and 640 are adopted in this paper. Then a 700-dimensional (700D feature vector is constructed and the dimension is decreased to 224D by using principal component analysis (PCA. To verify the performance of our method, rigorous jackknife cross-validation tests are performed on 1189, 25PDB, and 640 datasets. Comparison of our results with the existing PSSM-based methods demonstrates that our method achieves the favorable and competitive performance. This will offer an important complementary to other PSSM-based methods for prediction of protein structural classes for low-similarity sequences.

Exploring the universe of protein structures beyond the Protein Data Bank.

Science.gov (United States)

Cossio, Pilar; Trovato, Antonio; Pietrucci, Fabio; Seno, Flavio; Maritan, Amos; Laio, Alessandro

2010-11-04

It is currently believed that the atlas of existing protein structures is faithfully represented in the Protein Data Bank. However, whether this atlas covers the full universe of all possible protein structures is still a highly debated issue. By using a sophisticated numerical approach, we performed an exhaustive exploration of the conformational space of a 60 amino acid polypeptide chain described with an accurate all-atom interaction potential. We generated a database of around 30,000 compact folds with at least of secondary structure corresponding to local minima of the potential energy. This ensemble plausibly represents the universe of protein folds of similar length; indeed, all the known folds are represented in the set with good accuracy. However, we discover that the known folds form a rather small subset, which cannot be reproduced by choosing random structures in the database. Rather, natural and possible folds differ by the contact order, on average significantly smaller in the former. This suggests the presence of an evolutionary bias, possibly related to kinetic accessibility, towards structures with shorter loops between contacting residues. Beside their conceptual relevance, the new structures open a range of practical applications such as the development of accurate structure prediction strategies, the optimization of force fields, and the identification and design of novel folds.

Solution NMR structure determination of proteins revisited

International Nuclear Information System (INIS)

Billeter, Martin; Wagner, Gerhard; Wuethrich, Kurt

2008-01-01

This 'Perspective' bears on the present state of protein structure determination by NMR in solution. The focus is on a comparison of the infrastructure available for NMR structure determination when compared to protein crystal structure determination by X-ray diffraction. The main conclusion emerges that the unique potential of NMR to generate high resolution data also on dynamics, interactions and conformational equilibria has contributed to a lack of standard procedures for structure determination which would be readily amenable to improved efficiency by automation. To spark renewed discussion on the topic of NMR structure determination of proteins, procedural steps with high potential for improvement are identified

K-nearest uphill clustering in the protein structure space

KAUST Repository

Cui, Xuefeng; Gao, Xin

2016-01-01

The protein structure classification problem, which is to assign a protein structure to a cluster of similar proteins, is one of the most fundamental problems in the construction and application of the protein structure space. Early manually curated

Binding free energy analysis of protein-protein docking model structures by evERdock.

Science.gov (United States)

Takemura, Kazuhiro; Matubayasi, Nobuyuki; Kitao, Akio

2018-03-14

To aid the evaluation of protein-protein complex model structures generated by protein docking prediction (decoys), we previously developed a method to calculate the binding free energies for complexes. The method combines a short (2 ns) all-atom molecular dynamics simulation with explicit solvent and solution theory in the energy representation (ER). We showed that this method successfully selected structures similar to the native complex structure (near-native decoys) as the lowest binding free energy structures. In our current work, we applied this method (evERdock) to 100 or 300 model structures of four protein-protein complexes. The crystal structures and the near-native decoys showed the lowest binding free energy of all the examined structures, indicating that evERdock can successfully evaluate decoys. Several decoys that show low interface root-mean-square distance but relatively high binding free energy were also identified. Analysis of the fraction of native contacts, hydrogen bonds, and salt bridges at the protein-protein interface indicated that these decoys were insufficiently optimized at the interface. After optimizing the interactions around the interface by including interfacial water molecules, the binding free energies of these decoys were improved. We also investigated the effect of solute entropy on binding free energy and found that consideration of the entropy term does not necessarily improve the evaluations of decoys using the normal model analysis for entropy calculation.

Potentials of mean force for protein structure prediction vindicated, formalized and generalized.

Directory of Open Access Journals (Sweden)

Thomas Hamelryck

Full Text Available Understanding protein structure is of crucial importance in science, medicine and biotechnology. For about two decades, knowledge-based potentials based on pairwise distances--so-called "potentials of mean force" (PMFs--have been center stage in the prediction and design of protein structure and the simulation of protein folding. However, the validity, scope and limitations of these potentials are still vigorously debated and disputed, and the optimal choice of the reference state--a necessary component of these potentials--is an unsolved problem. PMFs are loosely justified by analogy to the reversible work theorem in statistical physics, or by a statistical argument based on a likelihood function. Both justifications are insightful but leave many questions unanswered. Here, we show for the first time that PMFs can be seen as approximations to quantities that do have a rigorous probabilistic justification: they naturally arise when probability distributions over different features of proteins need to be combined. We call these quantities "reference ratio distributions" deriving from the application of the "reference ratio method." This new view is not only of theoretical relevance but leads to many insights that are of direct practical use: the reference state is uniquely defined and does not require external physical insights; the approach can be generalized beyond pairwise distances to arbitrary features of protein structure; and it becomes clear for which purposes the use of these quantities is justified. We illustrate these insights with two applications, involving the radius of gyration and hydrogen bonding. In the latter case, we also show how the reference ratio method can be iteratively applied to sculpt an energy funnel. Our results considerably increase the understanding and scope of energy functions derived from known biomolecular structures.

The Protein Data Bank in Europe (PDBe): bringing structure to biology.

Science.gov (United States)

Velankar, Sameer; Kleywegt, Gerard J

2011-04-01

The Protein Data Bank in Europe (PDBe) is the European partner in the Worldwide PDB and as such handles depositions of X-ray, NMR and EM data and structure models. PDBe also provides advanced bioinformatics services based on data from the PDB and related resources. Some of the challenges facing the PDB and its guardians are discussed, as well as some of the areas on which PDBe activities will focus in the future (advanced services, ligands, integration, validation and experimental data). Finally, some recent developments at PDBe are described.

Extending the validity of the Feeding Practices and Structure Questionnaire

OpenAIRE

Jansen, Elena; Mallan, Kimberley M.; Daniels, Lynne A.

2015-01-01

Background Feeding practices are commonly examined as potentially modifiable determinants of children?s eating behaviours and weight status. Although a variety of questionnaires exist to assess different feeding aspects, many lack thorough reliability and validity testing. The Feeding Practices and Structure Questionnaire (FPSQ) is a tool designed to measure early feeding practices related to non-responsive feeding and structure of the meal environment. Face validity, factorial validity, inte...

Integral membrane protein structure determination using pseudocontact shifts

Energy Technology Data Exchange (ETDEWEB)

Crick, Duncan J.; Wang, Jue X. [University of Cambridge, Department of Biochemistry (United Kingdom); Graham, Bim; Swarbrick, James D. [Monash University, Monash Institute of Pharmaceutical Sciences (Australia); Mott, Helen R.; Nietlispach, Daniel, E-mail: dn206@cam.ac.uk [University of Cambridge, Department of Biochemistry (United Kingdom)

2015-04-15

Obtaining enough experimental restraints can be a limiting factor in the NMR structure determination of larger proteins. This is particularly the case for large assemblies such as membrane proteins that have been solubilized in a membrane-mimicking environment. Whilst in such cases extensive deuteration strategies are regularly utilised with the aim to improve the spectral quality, these schemes often limit the number of NOEs obtainable, making complementary strategies highly beneficial for successful structure elucidation. Recently, lanthanide-induced pseudocontact shifts (PCSs) have been established as a structural tool for globular proteins. Here, we demonstrate that a PCS-based approach can be successfully applied for the structure determination of integral membrane proteins. Using the 7TM α-helical microbial receptor pSRII, we show that PCS-derived restraints from lanthanide binding tags attached to four different positions of the protein facilitate the backbone structure determination when combined with a limited set of NOEs. In contrast, the same set of NOEs fails to determine the correct 3D fold. The latter situation is frequently encountered in polytopical α-helical membrane proteins and a PCS approach is thus suitable even for this particularly challenging class of membrane proteins. The ease of measuring PCSs makes this an attractive route for structure determination of large membrane proteins in general.

Sampling Realistic Protein Conformations Using Local Structural Bias

DEFF Research Database (Denmark)

Hamelryck, Thomas Wim; Kent, John T.; Krogh, A.

2006-01-01

The prediction of protein structure from sequence remains a major unsolved problem in biology. The most successful protein structure prediction methods make use of a divide-and-conquer strategy to attack the problem: a conformational sampling method generates plausible candidate structures, which...... are subsequently accepted or rejected using an energy function. Conceptually, this often corresponds to separating local structural bias from the long-range interactions that stabilize the compact, native state. However, sampling protein conformations that are compatible with the local structural bias encoded...... in a given protein sequence is a long-standing open problem, especially in continuous space. We describe an elegant and mathematically rigorous method to do this, and show that it readily generates native-like protein conformations simply by enforcing compactness. Our results have far-reaching implications...

A novel Multi-Agent Ada-Boost algorithm for predicting protein structural class with the information of protein secondary structure.

Science.gov (United States)

Fan, Ming; Zheng, Bin; Li, Lihua

2015-10-01

Knowledge of the structural class of a given protein is important for understanding its folding patterns. Although a lot of efforts have been made, it still remains a challenging problem for prediction of protein structural class solely from protein sequences. The feature extraction and classification of proteins are the main problems in prediction. In this research, we extended our earlier work regarding these two aspects. In protein feature extraction, we proposed a scheme by calculating the word frequency and word position from sequences of amino acid, reduced amino acid, and secondary structure. For an accurate classification of the structural class of protein, we developed a novel Multi-Agent Ada-Boost (MA-Ada) method by integrating the features of Multi-Agent system into Ada-Boost algorithm. Extensive experiments were taken to test and compare the proposed method using four benchmark datasets in low homology. The results showed classification accuracies of 88.5%, 96.0%, 88.4%, and 85.5%, respectively, which are much better compared with the existing methods. The source code and dataset are available on request.

Accurate protein structure modeling using sparse NMR data and homologous structure information.

Science.gov (United States)

Thompson, James M; Sgourakis, Nikolaos G; Liu, Gaohua; Rossi, Paolo; Tang, Yuefeng; Mills, Jeffrey L; Szyperski, Thomas; Montelione, Gaetano T; Baker, David

2012-06-19

While information from homologous structures plays a central role in X-ray structure determination by molecular replacement, such information is rarely used in NMR structure determination because it can be incorrect, both locally and globally, when evolutionary relationships are inferred incorrectly or there has been considerable evolutionary structural divergence. Here we describe a method that allows robust modeling of protein structures of up to 225 residues by combining (1)H(N), (13)C, and (15)N backbone and (13)Cβ chemical shift data, distance restraints derived from homologous structures, and a physically realistic all-atom energy function. Accurate models are distinguished from inaccurate models generated using incorrect sequence alignments by requiring that (i) the all-atom energies of models generated using the restraints are lower than models generated in unrestrained calculations and (ii) the low-energy structures converge to within 2.0 Å backbone rmsd over 75% of the protein. Benchmark calculations on known structures and blind targets show that the method can accurately model protein structures, even with very remote homology information, to a backbone rmsd of 1.2-1.9 Å relative to the conventional determined NMR ensembles and of 0.9-1.6 Å relative to X-ray structures for well-defined regions of the protein structures. This approach facilitates the accurate modeling of protein structures using backbone chemical shift data without need for side-chain resonance assignments and extensive analysis of NOESY cross-peak assignments.

Interleukin-11 binds specific EF-hand proteins via their conserved structural motifs.

Science.gov (United States)

Kazakov, Alexei S; Sokolov, Andrei S; Vologzhannikova, Alisa A; Permyakova, Maria E; Khorn, Polina A; Ismailov, Ramis G; Denessiouk, Konstantin A; Denesyuk, Alexander I; Rastrygina, Victoria A; Baksheeva, Viktoriia E; Zernii, Evgeni Yu; Zinchenko, Dmitry V; Glazatov, Vladimir V; Uversky, Vladimir N; Mirzabekov, Tajib A; Permyakov, Eugene A; Permyakov, Sergei E

2017-01-01

Interleukin-11 (IL-11) is a hematopoietic cytokine engaged in numerous biological processes and validated as a target for treatment of various cancers. IL-11 contains intrinsically disordered regions that might recognize multiple targets. Recently we found that aside from IL-11RA and gp130 receptors, IL-11 interacts with calcium sensor protein S100P. Strict calcium dependence of this interaction suggests a possibility of IL-11 interaction with other calcium sensor proteins. Here we probed specificity of IL-11 to calcium-binding proteins of various types: calcium sensors of the EF-hand family (calmodulin, S100B and neuronal calcium sensors: recoverin, NCS-1, GCAP-1, GCAP-2), calcium buffers of the EF-hand family (S100G, oncomodulin), and a non-EF-hand calcium buffer (α-lactalbumin). A specific subset of the calcium sensor proteins (calmodulin, S100B, NCS-1, GCAP-1/2) exhibits metal-dependent binding of IL-11 with dissociation constants of 1-19 μM. These proteins share several amino acid residues belonging to conservative structural motifs of the EF-hand proteins, 'black' and 'gray' clusters. Replacements of the respective S100P residues by alanine drastically decrease its affinity to IL-11, suggesting their involvement into the association process. Secondary structure and accessibility of the hinge region of the EF-hand proteins studied are predicted to control specificity and selectivity of their binding to IL-11. The IL-11 interaction with the EF-hand proteins is expected to occur under numerous pathological conditions, accompanied by disintegration of plasma membrane and efflux of cellular components into the extracellular milieu.

Exploring the universe of protein structures beyond the Protein Data Bank.

Directory of Open Access Journals (Sweden)

Pilar Cossio

Full Text Available It is currently believed that the atlas of existing protein structures is faithfully represented in the Protein Data Bank. However, whether this atlas covers the full universe of all possible protein structures is still a highly debated issue. By using a sophisticated numerical approach, we performed an exhaustive exploration of the conformational space of a 60 amino acid polypeptide chain described with an accurate all-atom interaction potential. We generated a database of around 30,000 compact folds with at least of secondary structure corresponding to local minima of the potential energy. This ensemble plausibly represents the universe of protein folds of similar length; indeed, all the known folds are represented in the set with good accuracy. However, we discover that the known folds form a rather small subset, which cannot be reproduced by choosing random structures in the database. Rather, natural and possible folds differ by the contact order, on average significantly smaller in the former. This suggests the presence of an evolutionary bias, possibly related to kinetic accessibility, towards structures with shorter loops between contacting residues. Beside their conceptual relevance, the new structures open a range of practical applications such as the development of accurate structure prediction strategies, the optimization of force fields, and the identification and design of novel folds.

Simultaneous determination of protein structure and dynamics

DEFF Research Database (Denmark)

Lindorff-Larsen, Kresten; Best, Robert B.; DePristo, M. A.

2005-01-01

at the atomic level about the structural and dynamical features of proteins-with the ability of molecular dynamics simulations to explore a wide range of protein conformations. We illustrate the method for human ubiquitin in solution and find that there is considerable conformational heterogeneity throughout......We present a protocol for the experimental determination of ensembles of protein conformations that represent simultaneously the native structure and its associated dynamics. The procedure combines the strengths of nuclear magnetic resonance spectroscopy-for obtaining experimental information...... the protein structure. The interior atoms of the protein are tightly packed in each individual conformation that contributes to the ensemble but their overall behaviour can be described as having a significant degree of liquid-like character. The protocol is completely general and should lead to significant...

Compare local pocket and global protein structure models by small structure patterns

KAUST Repository

Cui, Xuefeng

2015-09-09

Researchers proposed several criteria to assess the quality of predicted protein structures because it is one of the essential tasks in the Critical Assessment of Techniques for Protein Structure Prediction (CASP) competitions. Popular criteria include root mean squared deviation (RMSD), MaxSub score, TM-score, GDT-TS and GDT-HA scores. All these criteria require calculation of rigid transformations to superimpose the the predicted protein structure to the native protein structure. Yet, how to obtain the rigid transformations is unknown or with high time complexity, and, hence, heuristic algorithms were proposed. In this work, we carefully design various small structure patterns, including the ones specifically tuned for local pockets. Such structure patterns are biologically meaningful, and address the issue of relying on a sufficient number of backbone residue fragments for existing methods. We sample the rigid transformations from these small structure patterns; and the optimal superpositions yield by these small structures are refined and reported. As a result, among 11; 669 pairs of predicted and native local protein pocket models from the CASP10 dataset, the GDT-TS scores calculated by our method are significantly higher than those calculated by LGA. Moreover, our program is computationally much more efficient. Source codes and executables are publicly available at http://www.cbrc.kaust.edu.sa/prosta/

Predicting adverse drug reaction profiles by integrating protein interaction networks with drug structures.

Science.gov (United States)

Huang, Liang-Chin; Wu, Xiaogang; Chen, Jake Y

2013-01-01

The prediction of adverse drug reactions (ADRs) has become increasingly important, due to the rising concern on serious ADRs that can cause drugs to fail to reach or stay in the market. We proposed a framework for predicting ADR profiles by integrating protein-protein interaction (PPI) networks with drug structures. We compared ADR prediction performances over 18 ADR categories through four feature groups-only drug targets, drug targets with PPI networks, drug structures, and drug targets with PPI networks plus drug structures. The results showed that the integration of PPI networks and drug structures can significantly improve the ADR prediction performance. The median AUC values for the four groups were 0.59, 0.61, 0.65, and 0.70. We used the protein features in the best two models, "Cardiac disorders" (median-AUC: 0.82) and "Psychiatric disorders" (median-AUC: 0.76), to build ADR-specific PPI networks with literature supports. For validation, we examined 30 drugs withdrawn from the U.S. market to see if our approach can predict their ADR profiles and explain why they were withdrawn. Except for three drugs having ADRs in the categories we did not predict, 25 out of 27 withdrawn drugs (92.6%) having severe ADRs were successfully predicted by our approach. © 2012 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Hidden Structural Codes in Protein Intrinsic Disorder.

Science.gov (United States)

Borkosky, Silvia S; Camporeale, Gabriela; Chemes, Lucía B; Risso, Marikena; Noval, María Gabriela; Sánchez, Ignacio E; Alonso, Leonardo G; de Prat Gay, Gonzalo

2017-10-17

Intrinsic disorder is a major structural category in biology, accounting for more than 30% of coding regions across the domains of life, yet consists of conformational ensembles in equilibrium, a major challenge in protein chemistry. Anciently evolved papillomavirus genomes constitute an unparalleled case for sequence to structure-function correlation in cases in which there are no folded structures. E7, the major transforming oncoprotein of human papillomaviruses, is a paradigmatic example among the intrinsically disordered proteins. Analysis of a large number of sequences of the same viral protein allowed for the identification of a handful of residues with absolute conservation, scattered along the sequence of its N-terminal intrinsically disordered domain, which intriguingly are mostly leucine residues. Mutation of these led to a pronounced increase in both α-helix and β-sheet structural content, reflected by drastic effects on equilibrium propensities and oligomerization kinetics, and uncovers the existence of local structural elements that oppose canonical folding. These folding relays suggest the existence of yet undefined hidden structural codes behind intrinsic disorder in this model protein. Thus, evolution pinpoints conformational hot spots that could have not been identified by direct experimental methods for analyzing or perturbing the equilibrium of an intrinsically disordered protein ensemble.

K-nearest uphill clustering in the protein structure space

KAUST Repository

Cui, Xuefeng

2016-08-26

The protein structure classification problem, which is to assign a protein structure to a cluster of similar proteins, is one of the most fundamental problems in the construction and application of the protein structure space. Early manually curated protein structure classifications (e.g., SCOP and CATH) are very successful, but recently suffer the slow updating problem because of the increased throughput of newly solved protein structures. Thus, fully automatic methods to cluster proteins in the protein structure space have been designed and developed. In this study, we observed that the SCOP superfamilies are highly consistent with clustering trees representing hierarchical clustering procedures, but the tree cutting is very challenging and becomes the bottleneck of clustering accuracy. To overcome this challenge, we proposed a novel density-based K-nearest uphill clustering method that effectively eliminates noisy pairwise protein structure similarities and identifies density peaks as cluster centers. Specifically, the density peaks are identified based on K-nearest uphills (i.e., proteins with higher densities) and K-nearest neighbors. To our knowledge, this is the first attempt to apply and develop density-based clustering methods in the protein structure space. Our results show that our density-based clustering method outperforms the state-of-the-art clustering methods previously applied to the problem. Moreover, we observed that computational methods and human experts could produce highly similar clusters at high precision values, while computational methods also suggest to split some large superfamilies into smaller clusters. © 2016 Elsevier B.V.

Structural Mass Spectrometry of Proteins Using Hydroxyl Radical Based Protein Footprinting

OpenAIRE

Wang, Liwen; Chance, Mark R.

2011-01-01

Structural MS is a rapidly growing field with many applications in basic research and pharmaceutical drug development. In this feature article the overall technology is described and several examples of how hydroxyl radical based footprinting MS can be used to map interfaces, evaluate protein structure, and identify ligand dependent conformational changes in proteins are described.

Extracting knowledge from protein structure geometry

DEFF Research Database (Denmark)

Røgen, Peter; Koehl, Patrice

2013-01-01

potential from geometric knowledge extracted from native and misfolded conformers of protein structures. This new potential, Metric Protein Potential (MPP), has two main features that are key to its success. Firstly, it is composite in that it includes local and nonlocal geometric information on proteins...

Relationship between Molecular Structure Characteristics of Feed Proteins and Protein Digestibility and Solubility

Directory of Open Access Journals (Sweden)

Mingmei Bai

2016-08-01

Full Text Available The nutritional value of feed proteins and their utilization by livestock are related not only to the chemical composition but also to the structure of feed proteins, but few studies thus far have investigated the relationship between the structure of feed proteins and their solubility as well as digestibility in monogastric animals. To address this question we analyzed soybean meal, fish meal, corn distiller’s dried grains with solubles, corn gluten meal, and feather meal by Fourier transform infrared (FTIR spectroscopy to determine the protein molecular spectral band characteristics for amides I and II as well as α-helices and β-sheets and their ratios. Protein solubility and in vitro digestibility were measured with the Kjeldahl method using 0.2% KOH solution and the pepsin-pancreatin two-step enzymatic method, respectively. We found that all measured spectral band intensities (height and area of feed proteins were correlated with their the in vitro digestibility and solubility (p≤0.003; moreover, the relatively quantitative amounts of α-helices, random coils, and α-helix to β-sheet ratio in protein secondary structures were positively correlated with protein in vitro digestibility and solubility (p≤0.004. On the other hand, the percentage of β-sheet structures was negatively correlated with protein in vitro digestibility (p<0.001 and solubility (p = 0.002. These results demonstrate that the molecular structure characteristics of feed proteins are closely related to their in vitro digestibility at 28 h and solubility. Furthermore, the α-helix-to-β-sheet ratio can be used to predict the nutritional value of feed proteins.

Crystal structure analysis, overexpression and refolding behaviour of a DING protein with single mutation

International Nuclear Information System (INIS)

Gai, Zuoqi; Nakamura, Akiyoshi; Tanaka, Yoshikazu; Hirano, Nagisa; Tanaka, Isao; Yao, Min

2013-01-01

Crystals of a member of the DING protein family (HPBP) were obtained accidentally, and the structure was determined at 1.35 Å resolution. For further analysis, a system for preparation of HPBP was constructed and the structure of a prepared sample was confirmed by X-ray crystal structure analysis at 1.03 Å resolution. After crystallization of a certain protein–RNA complex, well diffracting crystals were obtained. However, the asymmetric unit of the crystal was too small to locate any components. Mass spectrometry and X-ray crystal structure analysis showed that it was a member of the DING protein family (HPBP). Surprisingly, the structure of HPBP reported previously was also determined accidentally as a contaminant, suggesting that HPBP has a strong tendency to crystallize. Furthermore, DING proteins were reported to relate in disease. These observations suggest that DING has potential for application in a wide range of research fields. To enable further analyses, a system for preparation of HPBP was constructed. As HPBP was expressed in insoluble form in Escherichia coli, it was unfolded chemically and refolded. Finally, a very high yield preparation method was constructed, in which 43 mg of HPBP was obtained from 1 L of culture. Furthermore, to evaluate the validity of refolding, its crystal structure was determined at 1.03 Å resolution. The determined structure was identical to the native structure, in which two disulfide bonds were recovered correctly and a phosphate ion was captured. Based on these results, it was concluded that the refolded HPBP recovers its structure correctly

Crystal structure analysis, overexpression and refolding behaviour of a DING protein with single mutation

Energy Technology Data Exchange (ETDEWEB)

Gai, Zuoqi; Nakamura, Akiyoshi [Hokkaido University, Sapporo 060-0810 (Japan); Tanaka, Yoshikazu, E-mail: tanaka@sci.hokudai.ac.jp [Hokkaido University, Sapporo 060-0810 (Japan); Hokkaido University, Sapporo 060-0810 (Japan); Hirano, Nagisa [Hokkaido University, Sapporo 060-0810 (Japan); Tanaka, Isao; Yao, Min [Hokkaido University, Sapporo 060-0810 (Japan); Hokkaido University, Sapporo 060-0810 (Japan)

2013-11-01

Crystals of a member of the DING protein family (HPBP) were obtained accidentally, and the structure was determined at 1.35 Å resolution. For further analysis, a system for preparation of HPBP was constructed and the structure of a prepared sample was confirmed by X-ray crystal structure analysis at 1.03 Å resolution. After crystallization of a certain protein–RNA complex, well diffracting crystals were obtained. However, the asymmetric unit of the crystal was too small to locate any components. Mass spectrometry and X-ray crystal structure analysis showed that it was a member of the DING protein family (HPBP). Surprisingly, the structure of HPBP reported previously was also determined accidentally as a contaminant, suggesting that HPBP has a strong tendency to crystallize. Furthermore, DING proteins were reported to relate in disease. These observations suggest that DING has potential for application in a wide range of research fields. To enable further analyses, a system for preparation of HPBP was constructed. As HPBP was expressed in insoluble form in Escherichia coli, it was unfolded chemically and refolded. Finally, a very high yield preparation method was constructed, in which 43 mg of HPBP was obtained from 1 L of culture. Furthermore, to evaluate the validity of refolding, its crystal structure was determined at 1.03 Å resolution. The determined structure was identical to the native structure, in which two disulfide bonds were recovered correctly and a phosphate ion was captured. Based on these results, it was concluded that the refolded HPBP recovers its structure correctly.

Relation between native ensembles and experimental structures of proteins

DEFF Research Database (Denmark)

Best, R. B.; Lindorff-Larsen, Kresten; DePristo, M. A.

2006-01-01

Different experimental structures of the same protein or of proteins with high sequence similarity contain many small variations. Here we construct ensembles of "high-sequence similarity Protein Data Bank" (HSP) structures and consider the extent to which such ensembles represent the structural...... Data Bank ensembles; moreover, we show that the effects of uncertainties in structure determination are insufficient to explain the results. These results highlight the importance of accounting for native-state protein dynamics in making comparisons with ensemble-averaged experimental data and suggest...... heterogeneity of the native state in solution. We find that different NMR measurements probing structure and dynamics of given proteins in solution, including order parameters, scalar couplings, and residual dipolar couplings, are remarkably well reproduced by their respective high-sequence similarity Protein...

A protein relational database and protein family knowledge bases to facilitate structure-based design analyses.

Science.gov (United States)

Mobilio, Dominick; Walker, Gary; Brooijmans, Natasja; Nilakantan, Ramaswamy; Denny, R Aldrin; Dejoannis, Jason; Feyfant, Eric; Kowticwar, Rupesh K; Mankala, Jyoti; Palli, Satish; Punyamantula, Sairam; Tatipally, Maneesh; John, Reji K; Humblet, Christine

2010-08-01

The Protein Data Bank is the most comprehensive source of experimental macromolecular structures. It can, however, be difficult at times to locate relevant structures with the Protein Data Bank search interface. This is particularly true when searching for complexes containing specific interactions between protein and ligand atoms. Moreover, searching within a family of proteins can be tedious. For example, one cannot search for some conserved residue as residue numbers vary across structures. We describe herein three databases, Protein Relational Database, Kinase Knowledge Base, and Matrix Metalloproteinase Knowledge Base, containing protein structures from the Protein Data Bank. In Protein Relational Database, atom-atom distances between protein and ligand have been precalculated allowing for millisecond retrieval based on atom identity and distance constraints. Ring centroids, centroid-centroid and centroid-atom distances and angles have also been included permitting queries for pi-stacking interactions and other structural motifs involving rings. Other geometric features can be searched through the inclusion of residue pair and triplet distances. In Kinase Knowledge Base and Matrix Metalloproteinase Knowledge Base, the catalytic domains have been aligned into common residue numbering schemes. Thus, by searching across Protein Relational Database and Kinase Knowledge Base, one can easily retrieve structures wherein, for example, a ligand of interest is making contact with the gatekeeper residue.

Structure of human Rad51 protein filament from molecular modeling and site-specific linear dichroism spectroscopy

KAUST Repository

Reymer, A.

2009-07-08

To get mechanistic insight into the DNA strand-exchange reaction of homologous recombination, we solved a filament structure of a human Rad51 protein, combining molecular modeling with experimental data. We build our structure on reported structures for central and N-terminal parts of pure (uncomplexed) Rad51 protein by aid of linear dichroism spectroscopy, providing angular orientations of substituted tyrosine residues of Rad51-dsDNA filaments in solution. The structure, validated by comparison with an electron microscopy density map and results from mutation analysis, is proposed to represent an active solution structure of the nucleo-protein complex. An inhomogeneously stretched double-stranded DNA fitted into the filament emphasizes the strategic positioning of 2 putative DNA-binding loops in a way that allows us speculate about their possibly distinct roles in nucleo-protein filament assembly and DNA strand-exchange reaction. The model suggests that the extension of a single-stranded DNA molecule upon binding of Rad51 is ensured by intercalation of Tyr-232 of the L1 loop, which might act as a docking tool, aligning protein monomers along the DNA strand upon filament assembly. Arg-235, also sitting on L1, is in the right position to make electrostatic contact with the phosphate backbone of the other DNA strand. The L2 loop position and its more ordered compact conformation makes us propose that this loop has another role, as a binding site for an incoming double-stranded DNA. Our filament structure and spectroscopic approach open the possibility of analyzing details along the multistep path of the strand-exchange reaction.

Sequential search leads to faster, more efficient fragment-based de novo protein structure prediction.

Science.gov (United States)

de Oliveira, Saulo H P; Law, Eleanor C; Shi, Jiye; Deane, Charlotte M

2018-04-01

Most current de novo structure prediction methods randomly sample protein conformations and thus require large amounts of computational resource. Here, we consider a sequential sampling strategy, building on ideas from recent experimental work which shows that many proteins fold cotranslationally. We have investigated whether a pseudo-greedy search approach, which begins sequentially from one of the termini, can improve the performance and accuracy of de novo protein structure prediction. We observed that our sequential approach converges when fewer than 20 000 decoys have been produced, fewer than commonly expected. Using our software, SAINT2, we also compared the run time and quality of models produced in a sequential fashion against a standard, non-sequential approach. Sequential prediction produces an individual decoy 1.5-2.5 times faster than non-sequential prediction. When considering the quality of the best model, sequential prediction led to a better model being produced for 31 out of 41 soluble protein validation cases and for 18 out of 24 transmembrane protein cases. Correct models (TM-Score > 0.5) were produced for 29 of these cases by the sequential mode and for only 22 by the non-sequential mode. Our comparison reveals that a sequential search strategy can be used to drastically reduce computational time of de novo protein structure prediction and improve accuracy. Data are available for download from: http://opig.stats.ox.ac.uk/resources. SAINT2 is available for download from: https://github.com/sauloho/SAINT2. saulo.deoliveira@dtc.ox.ac.uk. Supplementary data are available at Bioinformatics online.

DNA mimic proteins: functions, structures, and bioinformatic analysis.

Science.gov (United States)

Wang, Hao-Ching; Ho, Chun-Han; Hsu, Kai-Cheng; Yang, Jinn-Moon; Wang, Andrew H-J

2014-05-13

DNA mimic proteins have DNA-like negative surface charge distributions, and they function by occupying the DNA binding sites of DNA binding proteins to prevent these sites from being accessed by DNA. DNA mimic proteins control the activities of a variety of DNA binding proteins and are involved in a wide range of cellular mechanisms such as chromatin assembly, DNA repair, transcription regulation, and gene recombination. However, the sequences and structures of DNA mimic proteins are diverse, making them difficult to predict by bioinformatic search. To date, only a few DNA mimic proteins have been reported. These DNA mimics were not found by searching for functional motifs in their sequences but were revealed only by structural analysis of their charge distribution. This review highlights the biological roles and structures of 16 reported DNA mimic proteins. We also discuss approaches that might be used to discover new DNA mimic proteins.

Compare local pocket and global protein structure models by small structure patterns

KAUST Repository

Cui, Xuefeng; Kuwahara, Hiroyuki; Li, Shuai Cheng; Gao, Xin

2015-01-01

Researchers proposed several criteria to assess the quality of predicted protein structures because it is one of the essential tasks in the Critical Assessment of Techniques for Protein Structure Prediction (CASP) competitions. Popular criteria

Structural refinement and prediction of potential CCR2 antagonists through validated multi-QSAR modeling studies.

Science.gov (United States)

Amin, Sk Abdul; Adhikari, Nilanjan; Baidya, Sandip Kumar; Gayen, Shovanlal; Jha, Tarun

2018-01-03

Chemokines trigger numerous inflammatory responses and modulate the immune system. The interaction between monocyte chemoattractant protein-1 and chemokine receptor 2 (CCR2) may be the cause of atherosclerosis, obesity, and insulin resistance. However, CCR2 is also implicated in other inflammatory diseases such as rheumatoid arthritis, multiple sclerosis, asthma, and neuropathic pain. Therefore, there is a paramount importance of designing potent and selective CCR2 antagonists despite a number of drug candidates failed in clinical trials. In this article, 83 CCR2 antagonists by Jhonson and Jhonson Pharmaceuticals have been considered for robust validated multi-QSAR modeling studies to get an idea about the structural and pharmacophoric requirements for designing more potent CCR2 antagonists. All these QSAR models were validated and statistically reliable. Observations resulted from different modeling studies correlated and validated results of other ones. Finally, depending on these QSAR observations, some new molecules were proposed that may exhibit higher activity against CCR2.

Plant-derived phenolics inhibit the accrual of structurally characterised protein and lipid oxidative modifications.

Directory of Open Access Journals (Sweden)

Arantza Soler-Cantero

Full Text Available Epidemiological data suggest that plant-derived phenolics beneficial effects include an inhibition of LDL oxidation. After applying a screening method based on 2,4-dinitrophenyl hydrazine-protein carbonyl reaction to 21 different plant-derived phenolic acids, we selected the most antioxidant ones. Their effect was assessed in 5 different oxidation systems, as well as in other model proteins. Mass-spectrometry was then used, evidencing a heterogeneous effect on the accumulation of the structurally characterized protein carbonyl glutamic and aminoadipic semialdehydes as well as for malondialdehyde-lysine in LDL apoprotein. After TOF based lipidomics, we identified the most abundant differential lipids in Cu(++-incubated LDL as 1-palmitoyllysophosphatidylcholine and 1-stearoyl-sn-glycero-3-phosphocholine. Most of selected phenolic compounds prevented the accumulation of those phospholipids and the cellular impairment induced by oxidized LDL. Finally, to validate these effects in vivo, we evaluated the effect of the intake of a phenolic-enriched extract in plasma protein and lipid modifications in a well-established model of atherosclerosis (diet-induced hypercholesterolemia in hamsters. This showed that a dietary supplement with a phenolic-enriched extract diminished plasma protein oxidative and lipid damage. Globally, these data show structural basis of antioxidant properties of plant-derived phenolic acids in protein oxidation that may be relevant for the health-promoting effects of its dietary intake.

Chemical and protein structural basis for biological crosstalk between PPAR α and COX enzymes

Science.gov (United States)

Cleves, Ann E.; Jain, Ajay N.

2015-02-01

We have previously validated a probabilistic framework that combined computational approaches for predicting the biological activities of small molecule drugs. Molecule comparison methods included molecular structural similarity metrics and similarity computed from lexical analysis of text in drug package inserts. Here we present an analysis of novel drug/target predictions, focusing on those that were not obvious based on known pharmacological crosstalk. Considering those cases where the predicted target was an enzyme with known 3D structure allowed incorporation of information from molecular docking and protein binding pocket similarity in addition to ligand-based comparisons. Taken together, the combination of orthogonal information sources led to investigation of a surprising predicted relationship between a transcription factor and an enzyme, specifically, PPAR α and the cyclooxygenase enzymes. These predictions were confirmed by direct biochemical experiments which validate the approach and show for the first time that PPAR α agonists are cyclooxygenase inhibitors.

Solution structure and dynamics of melanoma inhibitory activity protein

International Nuclear Information System (INIS)

Lougheed, Julie C.; Domaille, Peter J.; Handel, Tracy M.

2002-01-01

Melanoma inhibitory activity (MIA) is a small secreted protein that is implicated in cartilage cell maintenance and melanoma metastasis. It is representative of a recently discovered family of proteins that contain a Src Homologous 3 (SH3) subdomain. While SH3 domains are normally found in intracellular proteins and mediate protein-protein interactions via recognition of polyproline helices, MIA is single-domain extracellular protein, and it probably binds to a different class of ligands.Here we report the assignments, solution structure, and dynamics of human MIA determined by heteronuclear NMR methods. The structures were calculated in a semi-automated manner without manual assignment of NOE crosspeaks, and have a backbone rmsd of 0.38 A over the ordered regions of the protein. The structure consists of an SH3-like subdomain with N- and C-terminal extensions of approximately 20 amino acids each that together form a novel fold. The rmsd between the solution structure and our recently reported crystal structure is 0.86 A over the ordered regions of the backbone, and the main differences are localized to the most dynamic regions of the protein. The similarity between the NMR and crystal structures supports the use of automated NOE assignments and ambiguous restraints to accelerate the calculation of NMR structures

PONDEROSA-C/S: client-server based software package for automated protein 3D structure determination.

Science.gov (United States)

Lee, Woonghee; Stark, Jaime L; Markley, John L

2014-11-01

Peak-picking Of Noe Data Enabled by Restriction Of Shift Assignments-Client Server (PONDEROSA-C/S) builds on the original PONDEROSA software (Lee et al. in Bioinformatics 27:1727-1728. doi: 10.1093/bioinformatics/btr200, 2011) and includes improved features for structure calculation and refinement. PONDEROSA-C/S consists of three programs: Ponderosa Server, Ponderosa Client, and Ponderosa Analyzer. PONDEROSA-C/S takes as input the protein sequence, a list of assigned chemical shifts, and nuclear Overhauser data sets ((13)C- and/or (15)N-NOESY). The output is a set of assigned NOEs and 3D structural models for the protein. Ponderosa Analyzer supports the visualization, validation, and refinement of the results from Ponderosa Server. These tools enable semi-automated NMR-based structure determination of proteins in a rapid and robust fashion. We present examples showing the use of PONDEROSA-C/S in solving structures of four proteins: two that enable comparison with the original PONDEROSA package, and two from the Critical Assessment of automated Structure Determination by NMR (Rosato et al. in Nat Methods 6:625-626. doi: 10.1038/nmeth0909-625 , 2009) competition. The software package can be downloaded freely in binary format from http://pine.nmrfam.wisc.edu/download_packages.html. Registered users of the National Magnetic Resonance Facility at Madison can submit jobs to the PONDEROSA-C/S server at http://ponderosa.nmrfam.wisc.edu, where instructions, tutorials, and instructions can be found. Structures are normally returned within 1-2 days.

Feature Extraction for Structural Dynamics Model Validation

Energy Technology Data Exchange (ETDEWEB)

Farrar, Charles [Los Alamos National Laboratory; Nishio, Mayuko [Yokohama University; Hemez, Francois [Los Alamos National Laboratory; Stull, Chris [Los Alamos National Laboratory; Park, Gyuhae [Chonnam Univesity; Cornwell, Phil [Rose-Hulman Institute of Technology; Figueiredo, Eloi [Universidade Lusófona; Luscher, D. J. [Los Alamos National Laboratory; Worden, Keith [University of Sheffield

2016-01-13

As structural dynamics becomes increasingly non-modal, stochastic and nonlinear, finite element model-updating technology must adopt the broader notions of model validation and uncertainty quantification. For example, particular re-sampling procedures must be implemented to propagate uncertainty through a forward calculation, and non-modal features must be defined to analyze nonlinear data sets. The latter topic is the focus of this report, but first, some more general comments regarding the concept of model validation will be discussed.

Improved protein surface comparison and application to low-resolution protein structure data

Directory of Open Access Journals (Sweden)

Kihara Daisuke

2010-12-01

Full Text Available Abstract Background Recent advancements of experimental techniques for determining protein tertiary structures raise significant challenges for protein bioinformatics. With the number of known structures of unknown function expanding at a rapid pace, an urgent task is to provide reliable clues to their biological function on a large scale. Conventional approaches for structure comparison are not suitable for a real-time database search due to their slow speed. Moreover, a new challenge has arisen from recent techniques such as electron microscopy (EM, which provide low-resolution structure data. Previously, we have introduced a method for protein surface shape representation using the 3D Zernike descriptors (3DZDs. The 3DZD enables fast structure database searches, taking advantage of its rotation invariance and compact representation. The search results of protein surface represented with the 3DZD has showngood agreement with the existing structure classifications, but some discrepancies were also observed. Results The three new surface representations of backbone atoms, originally devised all-atom-surface representation, and the combination of all-atom surface with the backbone representation are examined. All representations are encoded with the 3DZD. Also, we have investigated the applicability of the 3DZD for searching protein EM density maps of varying resolutions. The surface representations are evaluated on structure retrieval using two existing classifications, SCOP and the CE-based classification. Conclusions Overall, the 3DZDs representing backbone atoms show better retrieval performance than the original all-atom surface representation. The performance further improved when the two representations are combined. Moreover, we observed that the 3DZD is also powerful in comparing low-resolution structures obtained by electron microscopy.

Improved protein surface comparison and application to low-resolution protein structure data.

Science.gov (United States)

Sael, Lee; Kihara, Daisuke

2010-12-14

Recent advancements of experimental techniques for determining protein tertiary structures raise significant challenges for protein bioinformatics. With the number of known structures of unknown function expanding at a rapid pace, an urgent task is to provide reliable clues to their biological function on a large scale. Conventional approaches for structure comparison are not suitable for a real-time database search due to their slow speed. Moreover, a new challenge has arisen from recent techniques such as electron microscopy (EM), which provide low-resolution structure data. Previously, we have introduced a method for protein surface shape representation using the 3D Zernike descriptors (3DZDs). The 3DZD enables fast structure database searches, taking advantage of its rotation invariance and compact representation. The search results of protein surface represented with the 3DZD has showngood agreement with the existing structure classifications, but some discrepancies were also observed. The three new surface representations of backbone atoms, originally devised all-atom-surface representation, and the combination of all-atom surface with the backbone representation are examined. All representations are encoded with the 3DZD. Also, we have investigated the applicability of the 3DZD for searching protein EM density maps of varying resolutions. The surface representations are evaluated on structure retrieval using two existing classifications, SCOP and the CE-based classification. Overall, the 3DZDs representing backbone atoms show better retrieval performance than the original all-atom surface representation. The performance further improved when the two representations are combined. Moreover, we observed that the 3DZD is also powerful in comparing low-resolution structures obtained by electron microscopy.

Topological properties of complex networks in protein structures

Science.gov (United States)

Kim, Kyungsik; Jung, Jae-Won; Min, Seungsik

2014-03-01

We study topological properties of networks in structural classification of proteins. We model the native-state protein structure as a network made of its constituent amino-acids and their interactions. We treat four structural classes of proteins composed predominantly of α helices and β sheets and consider several proteins from each of these classes whose sizes range from amino acids of the Protein Data Bank. Particularly, we simulate and analyze the network metrics such as the mean degree, the probability distribution of degree, the clustering coefficient, the characteristic path length, the local efficiency, and the cost. This work was supported by the KMAR and DP under Grant WISE project (153-3100-3133-302-350).

Studying Membrane Protein Structure and Function Using Nanodiscs

DEFF Research Database (Denmark)

Huda, Pie

The structure and dynamic of membrane proteins can provide valuable information about general functions, diseases and effects of various drugs. Studying membrane proteins are a challenge as an amphiphilic environment is necessary to stabilise the protein in a functionally and structurally relevant...... form. This is most typically achieved through the use of detergent based reconstitution systems. However, time and again such systems fail to provide a suitable environment causing aggregation and inactivation. Nanodiscs are self-assembled lipoproteins containing two membrane scaffold proteins...... and a lipid bilayer in defined nanometer size, which can act as a stabiliser for membrane proteins. This enables both functional and structural investigation of membrane proteins in a detergent free environment which is closer to the native situation. Understanding the self-assembly of nanodiscs is important...

3D bioprinting of structural proteins.

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Włodarczyk-Biegun, Małgorzata K; Del Campo, Aránzazu

2017-07-01

3D bioprinting is a booming method to obtain scaffolds of different materials with predesigned and customized morphologies and geometries. In this review we focus on the experimental strategies and recent achievements in the bioprinting of major structural proteins (collagen, silk, fibrin), as a particularly interesting technology to reconstruct the biochemical and biophysical composition and hierarchical morphology of natural scaffolds. The flexibility in molecular design offered by structural proteins, combined with the flexibility in mixing, deposition, and mechanical processing inherent to bioprinting technologies, enables the fabrication of highly functional scaffolds and tissue mimics with a degree of complexity and organization which has only just started to be explored. Here we describe the printing parameters and physical (mechanical) properties of bioinks based on structural proteins, including the biological function of the printed scaffolds. We describe applied printing techniques and cross-linking methods, highlighting the modifications implemented to improve scaffold properties. The used cell types, cell viability, and possible construct applications are also reported. We envision that the application of printing technologies to structural proteins will enable unprecedented control over their supramolecular organization, conferring printed scaffolds biological properties and functions close to natural systems. Copyright © 2017 Elsevier Ltd. All rights reserved.

Protein NMR Structures Refined with Rosetta Have Higher Accuracy Relative to Corresponding X-ray Crystal Structures

Science.gov (United States)

2014-01-01

We have found that refinement of protein NMR structures using Rosetta with experimental NMR restraints yields more accurate protein NMR structures than those that have been deposited in the PDB using standard refinement protocols. Using 40 pairs of NMR and X-ray crystal structures determined by the Northeast Structural Genomics Consortium, for proteins ranging in size from 5–22 kDa, restrained Rosetta refined structures fit better to the raw experimental data, are in better agreement with their X-ray counterparts, and have better phasing power compared to conventionally determined NMR structures. For 37 proteins for which NMR ensembles were available and which had similar structures in solution and in the crystal, all of the restrained Rosetta refined NMR structures were sufficiently accurate to be used for solving the corresponding X-ray crystal structures by molecular replacement. The protocol for restrained refinement of protein NMR structures was also compared with restrained CS-Rosetta calculations. For proteins smaller than 10 kDa, restrained CS-Rosetta, starting from extended conformations, provides slightly more accurate structures, while for proteins in the size range of 10–25 kDa the less CPU intensive restrained Rosetta refinement protocols provided equally or more accurate structures. The restrained Rosetta protocols described here can improve the accuracy of protein NMR structures and should find broad and general for studies of protein structure and function. PMID:24392845

Prediction of protein structural classes by Chou's pseudo amino acid composition: approached using continuous wavelet transform and principal component analysis.

Science.gov (United States)

Li, Zhan-Chao; Zhou, Xi-Bin; Dai, Zong; Zou, Xiao-Yong

2009-07-01

A prior knowledge of protein structural classes can provide useful information about its overall structure, so it is very important for quick and accurate determination of protein structural class with computation method in protein science. One of the key for computation method is accurate protein sample representation. Here, based on the concept of Chou's pseudo-amino acid composition (AAC, Chou, Proteins: structure, function, and genetics, 43:246-255, 2001), a novel method of feature extraction that combined continuous wavelet transform (CWT) with principal component analysis (PCA) was introduced for the prediction of protein structural classes. Firstly, the digital signal was obtained by mapping each amino acid according to various physicochemical properties. Secondly, CWT was utilized to extract new feature vector based on wavelet power spectrum (WPS), which contains more abundant information of sequence order in frequency domain and time domain, and PCA was then used to reorganize the feature vector to decrease information redundancy and computational complexity. Finally, a pseudo-amino acid composition feature vector was further formed to represent primary sequence by coupling AAC vector with a set of new feature vector of WPS in an orthogonal space by PCA. As a showcase, the rigorous jackknife cross-validation test was performed on the working datasets. The results indicated that prediction quality has been improved, and the current approach of protein representation may serve as a useful complementary vehicle in classifying other attributes of proteins, such as enzyme family class, subcellular localization, membrane protein types and protein secondary structure, etc.

ProteinSplit: splitting of multi-domain proteins using prediction of ordered and disordered regions in protein sequences for virtual structural genomics

International Nuclear Information System (INIS)

Wyrwicz, Lucjan S; Koczyk, Grzegorz; Rychlewski, Leszek; Plewczynski, Dariusz

2007-01-01

The annotation of protein folds within newly sequenced genomes is the main target for semi-automated protein structure prediction (virtual structural genomics). A large number of automated methods have been developed recently with very good results in the case of single-domain proteins. Unfortunately, most of these automated methods often fail to properly predict the distant homology between a given multi-domain protein query and structural templates. Therefore a multi-domain protein should be split into domains in order to overcome this limitation. ProteinSplit is designed to identify protein domain boundaries using a novel algorithm that predicts disordered regions in protein sequences. The software utilizes various sequence characteristics to assess the local propensity of a protein to be disordered or ordered in terms of local structure stability. These disordered parts of a protein are likely to create interdomain spacers. Because of its speed and portability, the method was successfully applied to several genome-wide fold annotation experiments. The user can run an automated analysis of sets of proteins or perform semi-automated multiple user projects (saving the results on the server). Additionally the sequences of predicted domains can be sent to the Bioinfo.PL Protein Structure Prediction Meta-Server for further protein three-dimensional structure and function prediction. The program is freely accessible as a web service at http://lucjan.bioinfo.pl/proteinsplit together with detailed benchmark results on the critical assessment of a fully automated structure prediction (CAFASP) set of sequences. The source code of the local version of protein domain boundary prediction is available upon request from the authors

A hidden markov model derived structural alphabet for proteins.

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Camproux, A C; Gautier, R; Tufféry, P

2004-06-04

Understanding and predicting protein structures depends on the complexity and the accuracy of the models used to represent them. We have set up a hidden Markov model that discretizes protein backbone conformation as series of overlapping fragments (states) of four residues length. This approach learns simultaneously the geometry of the states and their connections. We obtain, using a statistical criterion, an optimal systematic decomposition of the conformational variability of the protein peptidic chain in 27 states with strong connection logic. This result is stable over different protein sets. Our model fits well the previous knowledge related to protein architecture organisation and seems able to grab some subtle details of protein organisation, such as helix sub-level organisation schemes. Taking into account the dependence between the states results in a description of local protein structure of low complexity. On an average, the model makes use of only 8.3 states among 27 to describe each position of a protein structure. Although we use short fragments, the learning process on entire protein conformations captures the logic of the assembly on a larger scale. Using such a model, the structure of proteins can be reconstructed with an average accuracy close to 1.1A root-mean-square deviation and for a complexity of only 3. Finally, we also observe that sequence specificity increases with the number of states of the structural alphabet. Such models can constitute a very relevant approach to the analysis of protein architecture in particular for protein structure prediction.

3D complex: a structural classification of protein complexes.

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Emmanuel D Levy

2006-11-01

Full Text Available Most of the proteins in a cell assemble into complexes to carry out their function. It is therefore crucial to understand the physicochemical properties as well as the evolution of interactions between proteins. The Protein Data Bank represents an important source of information for such studies, because more than half of the structures are homo- or heteromeric protein complexes. Here we propose the first hierarchical classification of whole protein complexes of known 3-D structure, based on representing their fundamental structural features as a graph. This classification provides the first overview of all the complexes in the Protein Data Bank and allows nonredundant sets to be derived at different levels of detail. This reveals that between one-half and two-thirds of known structures are multimeric, depending on the level of redundancy accepted. We also analyse the structures in terms of the topological arrangement of their subunits and find that they form a small number of arrangements compared with all theoretically possible ones. This is because most complexes contain four subunits or less, and the large majority are homomeric. In addition, there is a strong tendency for symmetry in complexes, even for heteromeric complexes. Finally, through comparison of Biological Units in the Protein Data Bank with the Protein Quaternary Structure database, we identified many possible errors in quaternary structure assignments. Our classification, available as a database and Web server at http://www.3Dcomplex.org, will be a starting point for future work aimed at understanding the structure and evolution of protein complexes.

Identification of similar regions of protein structures using integrated sequence and structure analysis tools

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Heiland Randy

2006-03-01

Full Text Available Abstract Background Understanding protein function from its structure is a challenging problem. Sequence based approaches for finding homology have broad use for annotation of both structure and function. 3D structural information of protein domains and their interactions provide a complementary view to structure function relationships to sequence information. We have developed a web site http://www.sblest.org/ and an API of web services that enables users to submit protein structures and identify statistically significant neighbors and the underlying structural environments that make that match using a suite of sequence and structure analysis tools. To do this, we have integrated S-BLEST, PSI-BLAST and HMMer based superfamily predictions to give a unique integrated view to prediction of SCOP superfamilies, EC number, and GO term, as well as identification of the protein structural environments that are associated with that prediction. Additionally, we have extended UCSF Chimera and PyMOL to support our web services, so that users can characterize their own proteins of interest. Results Users are able to submit their own queries or use a structure already in the PDB. Currently the databases that a user can query include the popular structural datasets ASTRAL 40 v1.69, ASTRAL 95 v1.69, CLUSTER50, CLUSTER70 and CLUSTER90 and PDBSELECT25. The results can be downloaded directly from the site and include function prediction, analysis of the most conserved environments and automated annotation of query proteins. These results reflect both the hits found with PSI-BLAST, HMMer and with S-BLEST. We have evaluated how well annotation transfer can be performed on SCOP ID's, Gene Ontology (GO ID's and EC Numbers. The method is very efficient and totally automated, generally taking around fifteen minutes for a 400 residue protein. Conclusion With structural genomics initiatives determining structures with little, if any, functional characterization

Extending the validity of the Feeding Practices and Structure Questionnaire.

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Jansen, Elena; Mallan, Kimberley M; Daniels, Lynne A

2015-06-30

Feeding practices are commonly examined as potentially modifiable determinants of children's eating behaviours and weight status. Although a variety of questionnaires exist to assess different feeding aspects, many lack thorough reliability and validity testing. The Feeding Practices and Structure Questionnaire (FPSQ) is a tool designed to measure early feeding practices related to non-responsive feeding and structure of the meal environment. Face validity, factorial validity, internal reliability and cross-sectional correlations with children's eating behaviours have been established in mothers with 2-year-old children. The aim of the present study was to further extend the validity of the FPSQ by examining factorial, construct and predictive validity, and stability. Participants were from the NOURISH randomised controlled trial which evaluated an intervention with first-time mothers designed to promote protective feeding practices. Maternal feeding practices (FP) and child eating behaviours were assessed when children were aged 2 years and 3.7 years (n = 388). Confirmatory Factor analysis, group differences, predictive relationships, and stability were tested. The original 9-factor structure was confirmed when children were aged 3.7 ± 0.3 years. Cronbach's alpha was above the recommended 0.70 cut-off for all factors except Structured Meal Timing, Over Restriction and Distrust in Appetite which were 0.58, 0.67 and 0.66 respectively. Allocated group differences reflected behaviour consistent with intervention content and all feeding practices were stable across both time points (range of r = 0.45-0.70). There was some evidence for the predictive validity of factors with 2 FP showing expected relationships, 2 FP showing expected and unexpected relationships and 5 FP showing no relationship. Reliability and validity was demonstrated for most subscales of the FPSQ. Future validation is warranted with culturally diverse samples and with fathers and

Deprotonated imidodiphosphate in AMPPNP-containing protein structures

International Nuclear Information System (INIS)

Dauter, Miroslawa; Dauter, Zbigniew

2011-01-01

In certain AMPPNP-containing protein structures, the nitrogen bridging the two terminal phosphate groups can be deprotonated. Many different proteins utilize the chemical energy provided by the cofactor adenosine triphosphate (ATP) for their proper function. A number of structures in the Protein Data Bank (PDB) contain adenosine 5′-(β,γ-imido)triphosphate (AMPPNP), a nonhydrolysable analog of ATP in which the bridging O atom between the two terminal phosphate groups is substituted by the imido function. Under mild conditions imides do not have acidic properties and thus the imide nitrogen should be protonated. However, an analysis of protein structures containing AMPPNP reveals that the imide group is deprotonated in certain complexes if the negative charges of the phosphate moieties in AMPPNP are in part neutralized by coordinating divalent metals or a guanidinium group of an arginine

Fragger: a protein fragment picker for structural queries.

Science.gov (United States)

Berenger, Francois; Simoncini, David; Voet, Arnout; Shrestha, Rojan; Zhang, Kam Y J

2017-01-01

Protein modeling and design activities often require querying the Protein Data Bank (PDB) with a structural fragment, possibly containing gaps. For some applications, it is preferable to work on a specific subset of the PDB or with unpublished structures. These requirements, along with specific user needs, motivated the creation of a new software to manage and query 3D protein fragments. Fragger is a protein fragment picker that allows protein fragment databases to be created and queried. All fragment lengths are supported and any set of PDB files can be used to create a database. Fragger can efficiently search a fragment database with a query fragment and a distance threshold. Matching fragments are ranked by distance to the query. The query fragment can have structural gaps and the allowed amino acid sequences matching a query can be constrained via a regular expression of one-letter amino acid codes. Fragger also incorporates a tool to compute the backbone RMSD of one versus many fragments in high throughput. Fragger should be useful for protein design, loop grafting and related structural bioinformatics tasks.

Dengue Virus Non-structural Protein 1 Modulates Infectious Particle Production via Interaction with the Structural Proteins.

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Pietro Scaturro

Full Text Available Non-structural protein 1 (NS1 is one of the most enigmatic proteins of the Dengue virus (DENV, playing distinct functions in immune evasion, pathogenesis and viral replication. The recently reported crystal structure of DENV NS1 revealed its peculiar three-dimensional fold; however, detailed information on NS1 function at different steps of the viral replication cycle is still missing. By using the recently reported crystal structure, as well as amino acid sequence conservation, as a guide for a comprehensive site-directed mutagenesis study, we discovered that in addition to being essential for RNA replication, DENV NS1 is also critically required for the production of infectious virus particles. Taking advantage of a trans-complementation approach based on fully functional epitope-tagged NS1 variants, we identified previously unreported interactions between NS1 and the structural proteins Envelope (E and precursor Membrane (prM. Interestingly, coimmunoprecipitation revealed an additional association with capsid, arguing that NS1 interacts via the structural glycoproteins with DENV particles. Results obtained with mutations residing either in the NS1 Wing domain or in the β-ladder domain suggest that NS1 might have two distinct functions in the assembly of DENV particles. By using a trans-complementation approach with a C-terminally KDEL-tagged ER-resident NS1, we demonstrate that the secretion of NS1 is dispensable for both RNA replication and infectious particle production. In conclusion, our results provide an extensive genetic map of NS1 determinants essential for viral RNA replication and identify a novel role of NS1 in virion production that is mediated via interaction with the structural proteins. These studies extend the list of NS1 functions and argue for a central role in coordinating replication and assembly/release of infectious DENV particles.

Prediction of protein-protein interactions in dengue virus coat proteins guided by low resolution cryoEM structures

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Srinivasan Narayanaswamy

2010-06-01

Full Text Available Abstract Background Dengue virus along with the other members of the flaviviridae family has reemerged as deadly human pathogens. Understanding the mechanistic details of these infections can be highly rewarding in developing effective antivirals. During maturation of the virus inside the host cell, the coat proteins E and M undergo conformational changes, altering the morphology of the viral coat. However, due to low resolution nature of the available 3-D structures of viral assemblies, the atomic details of these changes are still elusive. Results In the present analysis, starting from Cα positions of low resolution cryo electron microscopic structures the residue level details of protein-protein interaction interfaces of dengue virus coat proteins have been predicted. By comparing the preexisting structures of virus in different phases of life cycle, the changes taking place in these predicted protein-protein interaction interfaces were followed as a function of maturation process of the virus. Besides changing the current notion about the presence of only homodimers in the mature viral coat, the present analysis indicated presence of a proline-rich motif at the protein-protein interaction interface of the coat protein. Investigating the conservation status of these seemingly functionally crucial residues across other members of flaviviridae family enabled dissecting common mechanisms used for infections by these viruses. Conclusions Thus, using computational approach the present analysis has provided better insights into the preexisting low resolution structures of virus assemblies, the findings of which can be made use of in designing effective antivirals against these deadly human pathogens.

De novo protein structure determination using sparse NMR data

International Nuclear Information System (INIS)

Bowers, Peter M.; Strauss, Charlie E.M.; Baker, David

2000-01-01

We describe a method for generating moderate to high-resolution protein structures using limited NMR data combined with the ab initio protein structure prediction method Rosetta. Peptide fragments are selected from proteins of known structure based on sequence similarity and consistency with chemical shift and NOE data. Models are built from these fragments by minimizing an energy function that favors hydrophobic burial, strand pairing, and satisfaction of NOE constraints. Models generated using this procedure with ∼1 NOE constraint per residue are in some cases closer to the corresponding X-ray structures than the published NMR solution structures. The method requires only the sparse constraints available during initial stages of NMR structure determination, and thus holds promise for increasing the speed with which protein solution structures can be determined

Beyond BLASTing: Tertiary and Quaternary Structure Analysis Helps Identify Major Vault Proteins

Science.gov (United States)

Daly, Toni K.; Sutherland-Smith, Andrew J.; Penny, David

2013-01-01

We examine the advantages of going beyond sequence similarity and use both protein three-dimensional (3D) structure prediction and then quaternary structure (docking) of inferred 3D structures to help evaluate whether comparable sequences can fold into homologous structures with sufficient lateral associations for quaternary structure formation. Our test case is the major vault protein (MVP) that oligomerizes in multiple copies to form barrel-like vault particles and is relatively widespread among eukaryotes. We used the iterative threading assembly refinement server (I-TASSER) to predict whether putative MVP sequences identified by BLASTp and PSI Basic Local Alignment Search Tool are structurally similar to the experimentally determined rodent MVP tertiary structures. Then two identical predicted quaternary structures from I-TASSER are analyzed by RosettaDock to test whether a pair-wise association occurs, and hence whether the oligomeric vault complex is likely to form for a given MVP sequence. Positive controls for the method are the experimentally determined rat (Rattus norvegicus) vault X-ray crystal structure and the purple sea urchin (Strongylocentrotus purpuratus) MVP sequence that forms experimentally observed vaults. These and two kinetoplast MVP structural homologs were predicted with high confidence value, and RosettaDock predicted that these MVP sequences would dock laterally and therefore could form oligomeric vaults. As the negative control, I-TASSER did not predict an MVP-like structure from a randomized rat MVP sequence, even when constrained to the rat MVP crystal structure (PDB:2ZUO), thus further validating the method. The protocol identified six putative homologous MVP sequences in the heterobolosean Naegleria gruberi within the excavate kingdom. Two of these sequences are predicted to be structurally similar to rat MVP, despite being in excess of 300 residues shorter. The method can be used generally to help test predictions of homology via

Structural studies of human glioma pathogenesis-related protein 1

Energy Technology Data Exchange (ETDEWEB)

Asojo, Oluwatoyin A., E-mail: oasojo@unmc.edu [College of Medicine, Nebraska Medical Center, Omaha, NE 68198-6495 (United States); Koski, Raymond A.; Bonafé, Nathalie [L2 Diagnostics LLC, 300 George Street, New Haven, CT 06511 (United States); College of Medicine, Nebraska Medical Center, Omaha, NE 68198-6495 (United States)

2011-10-01

Structural analysis of a truncated soluble domain of human glioma pathogenesis-related protein 1, a membrane protein implicated in the proliferation of aggressive brain cancer, is presented. Human glioma pathogenesis-related protein 1 (GLIPR1) is a membrane protein that is highly upregulated in brain cancers but is barely detectable in normal brain tissue. GLIPR1 is composed of a signal peptide that directs its secretion, a conserved cysteine-rich CAP (cysteine-rich secretory proteins, antigen 5 and pathogenesis-related 1 proteins) domain and a transmembrane domain. GLIPR1 is currently being investigated as a candidate for prostate cancer gene therapy and for glioblastoma targeted therapy. Crystal structures of a truncated soluble domain of the human GLIPR1 protein (sGLIPR1) solved by molecular replacement using a truncated polyalanine search model of the CAP domain of stecrisp, a snake-venom cysteine-rich secretory protein (CRISP), are presented. The correct molecular-replacement solution could only be obtained by removing all loops from the search model. The native structure was refined to 1.85 Å resolution and that of a Zn{sup 2+} complex was refined to 2.2 Å resolution. The latter structure revealed that the putative binding cavity coordinates Zn{sup 2+} similarly to snake-venom CRISPs, which are involved in Zn{sup 2+}-dependent mechanisms of inflammatory modulation. Both sGLIPR1 structures have extensive flexible loop/turn regions and unique charge distributions that were not observed in any of the previously reported CAP protein structures. A model is also proposed for the structure of full-length membrane-bound GLIPR1.

Constraint Logic Programming approach to protein structure prediction

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Fogolari Federico

2004-11-01

Full Text Available Abstract Background The protein structure prediction problem is one of the most challenging problems in biological sciences. Many approaches have been proposed using database information and/or simplified protein models. The protein structure prediction problem can be cast in the form of an optimization problem. Notwithstanding its importance, the problem has very seldom been tackled by Constraint Logic Programming, a declarative programming paradigm suitable for solving combinatorial optimization problems. Results Constraint Logic Programming techniques have been applied to the protein structure prediction problem on the face-centered cube lattice model. Molecular dynamics techniques, endowed with the notion of constraint, have been also exploited. Even using a very simplified model, Constraint Logic Programming on the face-centered cube lattice model allowed us to obtain acceptable results for a few small proteins. As a test implementation their (known secondary structure and the presence of disulfide bridges are used as constraints. Simplified structures obtained in this way have been converted to all atom models with plausible structure. Results have been compared with a similar approach using a well-established technique as molecular dynamics. Conclusions The results obtained on small proteins show that Constraint Logic Programming techniques can be employed for studying protein simplified models, which can be converted into realistic all atom models. The advantage of Constraint Logic Programming over other, much more explored, methodologies, resides in the rapid software prototyping, in the easy way of encoding heuristics, and in exploiting all the advances made in this research area, e.g. in constraint propagation and its use for pruning the huge search space.

Constraint Logic Programming approach to protein structure prediction.

Science.gov (United States)

Dal Palù, Alessandro; Dovier, Agostino; Fogolari, Federico

2004-11-30

The protein structure prediction problem is one of the most challenging problems in biological sciences. Many approaches have been proposed using database information and/or simplified protein models. The protein structure prediction problem can be cast in the form of an optimization problem. Notwithstanding its importance, the problem has very seldom been tackled by Constraint Logic Programming, a declarative programming paradigm suitable for solving combinatorial optimization problems. Constraint Logic Programming techniques have been applied to the protein structure prediction problem on the face-centered cube lattice model. Molecular dynamics techniques, endowed with the notion of constraint, have been also exploited. Even using a very simplified model, Constraint Logic Programming on the face-centered cube lattice model allowed us to obtain acceptable results for a few small proteins. As a test implementation their (known) secondary structure and the presence of disulfide bridges are used as constraints. Simplified structures obtained in this way have been converted to all atom models with plausible structure. Results have been compared with a similar approach using a well-established technique as molecular dynamics. The results obtained on small proteins show that Constraint Logic Programming techniques can be employed for studying protein simplified models, which can be converted into realistic all atom models. The advantage of Constraint Logic Programming over other, much more explored, methodologies, resides in the rapid software prototyping, in the easy way of encoding heuristics, and in exploiting all the advances made in this research area, e.g. in constraint propagation and its use for pruning the huge search space.

PSPP: a protein structure prediction pipeline for computing clusters.

Directory of Open Access Journals (Sweden)

Michael S Lee

2009-07-01

Full Text Available Protein structures are critical for understanding the mechanisms of biological systems and, subsequently, for drug and vaccine design. Unfortunately, protein sequence data exceed structural data by a factor of more than 200 to 1. This gap can be partially filled by using computational protein structure prediction. While structure prediction Web servers are a notable option, they often restrict the number of sequence queries and/or provide a limited set of prediction methodologies. Therefore, we present a standalone protein structure prediction software package suitable for high-throughput structural genomic applications that performs all three classes of prediction methodologies: comparative modeling, fold recognition, and ab initio. This software can be deployed on a user's own high-performance computing cluster.The pipeline consists of a Perl core that integrates more than 20 individual software packages and databases, most of which are freely available from other research laboratories. The query protein sequences are first divided into domains either by domain boundary recognition or Bayesian statistics. The structures of the individual domains are then predicted using template-based modeling or ab initio modeling. The predicted models are scored with a statistical potential and an all-atom force field. The top-scoring ab initio models are annotated by structural comparison against the Structural Classification of Proteins (SCOP fold database. Furthermore, secondary structure, solvent accessibility, transmembrane helices, and structural disorder are predicted. The results are generated in text, tab-delimited, and hypertext markup language (HTML formats. So far, the pipeline has been used to study viral and bacterial proteomes.The standalone pipeline that we introduce here, unlike protein structure prediction Web servers, allows users to devote their own computing assets to process a potentially unlimited number of queries as well as perform

ProSelection: A Novel Algorithm to Select Proper Protein Structure Subsets for in Silico Target Identification and Drug Discovery Research.

Science.gov (United States)

Wang, Nanyi; Wang, Lirong; Xie, Xiang-Qun

2017-11-27

Molecular docking is widely applied to computer-aided drug design and has become relatively mature in the recent decades. Application of docking in modeling varies from single lead compound optimization to large-scale virtual screening. The performance of molecular docking is highly dependent on the protein structures selected. It is especially challenging for large-scale target prediction research when multiple structures are available for a single target. Therefore, we have established ProSelection, a docking preferred-protein selection algorithm, in order to generate the proper structure subset(s). By the ProSelection algorithm, protein structures of "weak selectors" are filtered out whereas structures of "strong selectors" are kept. Specifically, the structure which has a good statistical performance of distinguishing active ligands from inactive ligands is defined as a strong selector. In this study, 249 protein structures of 14 autophagy-related targets are investigated. Surflex-dock was used as the docking engine to distinguish active and inactive compounds against these protein structures. Both t test and Mann-Whitney U test were used to distinguish the strong from the weak selectors based on the normality of the docking score distribution. The suggested docking score threshold for active ligands (SDA) was generated for each strong selector structure according to the receiver operating characteristic (ROC) curve. The performance of ProSelection was further validated by predicting the potential off-targets of 43 U.S. Federal Drug Administration approved small molecule antineoplastic drugs. Overall, ProSelection will accelerate the computational work in protein structure selection and could be a useful tool for molecular docking, target prediction, and protein-chemical database establishment research.

Tertiary alphabet for the observable protein structural universe.

Science.gov (United States)

Mackenzie, Craig O; Zhou, Jianfu; Grigoryan, Gevorg

2016-11-22

Here, we systematically decompose the known protein structural universe into its basic elements, which we dub tertiary structural motifs (TERMs). A TERM is a compact backbone fragment that captures the secondary, tertiary, and quaternary environments around a given residue, comprising one or more disjoint segments (three on average). We seek the set of universal TERMs that capture all structure in the Protein Data Bank (PDB), finding remarkable degeneracy. Only ∼600 TERMs are sufficient to describe 50% of the PDB at sub-Angstrom resolution. However, more rare geometries also exist, and the overall structural coverage grows logarithmically with the number of TERMs. We go on to show that universal TERMs provide an effective mapping between sequence and structure. We demonstrate that TERM-based statistics alone are sufficient to recapitulate close-to-native sequences given either NMR or X-ray backbones. Furthermore, sequence variability predicted from TERM data agrees closely with evolutionary variation. Finally, locations of TERMs in protein chains can be predicted from sequence alone based on sequence signatures emergent from TERM instances in the PDB. For multisegment motifs, this method identifies spatially adjacent fragments that are not contiguous in sequence-a major bottleneck in structure prediction. Although all TERMs recur in diverse proteins, some appear specialized for certain functions, such as interface formation, metal coordination, or even water binding. Structural biology has benefited greatly from previously observed degeneracies in structure. The decomposition of the known structural universe into a finite set of compact TERMs offers exciting opportunities toward better understanding, design, and prediction of protein structure.

MEGADOCK-Web: an integrated database of high-throughput structure-based protein-protein interaction predictions.

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Hayashi, Takanori; Matsuzaki, Yuri; Yanagisawa, Keisuke; Ohue, Masahito; Akiyama, Yutaka

2018-05-08

Protein-protein interactions (PPIs) play several roles in living cells, and computational PPI prediction is a major focus of many researchers. The three-dimensional (3D) structure and binding surface are important for the design of PPI inhibitors. Therefore, rigid body protein-protein docking calculations for two protein structures are expected to allow elucidation of PPIs different from known complexes in terms of 3D structures because known PPI information is not explicitly required. We have developed rapid PPI prediction software based on protein-protein docking, called MEGADOCK. In order to fully utilize the benefits of computational PPI predictions, it is necessary to construct a comprehensive database to gather prediction results and their predicted 3D complex structures and to make them easily accessible. Although several databases exist that provide predicted PPIs, the previous databases do not contain a sufficient number of entries for the purpose of discovering novel PPIs. In this study, we constructed an integrated database of MEGADOCK PPI predictions, named MEGADOCK-Web. MEGADOCK-Web provides more than 10 times the number of PPI predictions than previous databases and enables users to conduct PPI predictions that cannot be found in conventional PPI prediction databases. In MEGADOCK-Web, there are 7528 protein chains and 28,331,628 predicted PPIs from all possible combinations of those proteins. Each protein structure is annotated with PDB ID, chain ID, UniProt AC, related KEGG pathway IDs, and known PPI pairs. Additionally, MEGADOCK-Web provides four powerful functions: 1) searching precalculated PPI predictions, 2) providing annotations for each predicted protein pair with an experimentally known PPI, 3) visualizing candidates that may interact with the query protein on biochemical pathways, and 4) visualizing predicted complex structures through a 3D molecular viewer. MEGADOCK-Web provides a huge amount of comprehensive PPI predictions based on

Improved protein structure reconstruction using secondary structures, contacts at higher distance thresholds, and non-contacts.

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Adhikari, Badri; Cheng, Jianlin

2017-08-29

Residue-residue contacts are key features for accurate de novo protein structure prediction. For the optimal utilization of these predicted contacts in folding proteins accurately, it is important to study the challenges of reconstructing protein structures using true contacts. Because contact-guided protein modeling approach is valuable for predicting the folds of proteins that do not have structural templates, it is necessary for reconstruction studies to focus on hard-to-predict protein structures. Using a data set consisting of 496 structural domains released in recent CASP experiments and a dataset of 150 representative protein structures, in this work, we discuss three techniques to improve the reconstruction accuracy using true contacts - adding secondary structures, increasing contact distance thresholds, and adding non-contacts. We find that reconstruction using secondary structures and contacts can deliver accuracy higher than using full contact maps. Similarly, we demonstrate that non-contacts can improve reconstruction accuracy not only when the used non-contacts are true but also when they are predicted. On the dataset consisting of 150 proteins, we find that by simply using low ranked predicted contacts as non-contacts and adding them as additional restraints, can increase the reconstruction accuracy by 5% when the reconstructed models are evaluated using TM-score. Our findings suggest that secondary structures are invaluable companions of contacts for accurate reconstruction. Confirming some earlier findings, we also find that larger distance thresholds are useful for folding many protein structures which cannot be folded using the standard definition of contacts. Our findings also suggest that for more accurate reconstruction using predicted contacts it is useful to predict contacts at higher distance thresholds (beyond 8 Å) and predict non-contacts.

Fibrous Protein Structures: Hierarchy, History and Heroes.

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Squire, John M; Parry, David A D

2017-01-01

During the 1930s and 1940s the technique of X-ray diffraction was applied widely by William Astbury and his colleagues to a number of naturally-occurring fibrous materials. On the basis of the diffraction patterns obtained, he observed that the structure of each of the fibres was dominated by one of a small number of different types of molecular conformation. One group of fibres, known as the k-m-e-f group of proteins (keratin - myosin - epidermin - fibrinogen), gave rise to diffraction characteristics that became known as the α-pattern. Others, such as those from a number of silks, gave rise to a different pattern - the β-pattern, while connective tissues yielded a third unique set of diffraction characteristics. At the time of Astbury's work, the structures of these materials were unknown, though the spacings of the main X-ray reflections gave an idea of the axial repeats and the lateral packing distances. In a breakthrough in the early 1950s, the basic structures of all of these fibrous proteins were determined. It was found that the long protein chains, composed of strings of amino acids, could be folded up in a systematic manner to generate a limited number of structures that were consistent with the X-ray data. The most important of these were known as the α-helix, the β-sheet, and the collagen triple helix. These studies provided information about the basic building blocks of all proteins, both fibrous and globular. They did not, however, provide detailed information about how these molecules packed together in three-dimensions to generate the fibres found in vivo. A number of possible packing arrangements were subsequently deduced from the X-ray diffraction and other data, but it is only in the last few years, through the continued improvements of electron microscopy, that the packing details within some fibrous proteins can now be seen directly. Here we outline briefly some of the milestones in fibrous protein structure determination, the role of the

MetaGO: Predicting Gene Ontology of Non-homologous Proteins Through Low-Resolution Protein Structure Prediction and Protein-Protein Network Mapping.

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Zhang, Chengxin; Zheng, Wei; Freddolino, Peter L; Zhang, Yang

2018-03-10

Homology-based transferal remains the major approach to computational protein function annotations, but it becomes increasingly unreliable when the sequence identity between query and template decreases below 30%. We propose a novel pipeline, MetaGO, to deduce Gene Ontology attributes of proteins by combining sequence homology-based annotation with low-resolution structure prediction and comparison, and partner's homology-based protein-protein network mapping. The pipeline was tested on a large-scale set of 1000 non-redundant proteins from the CAFA3 experiment. Under the stringent benchmark conditions where templates with >30% sequence identity to the query are excluded, MetaGO achieves average F-measures of 0.487, 0.408, and 0.598, for Molecular Function, Biological Process, and Cellular Component, respectively, which are significantly higher than those achieved by other state-of-the-art function annotations methods. Detailed data analysis shows that the major advantage of the MetaGO lies in the new functional homolog detections from partner's homology-based network mapping and structure-based local and global structure alignments, the confidence scores of which can be optimally combined through logistic regression. These data demonstrate the power of using a hybrid model incorporating protein structure and interaction networks to deduce new functional insights beyond traditional sequence homology-based referrals, especially for proteins that lack homologous function templates. The MetaGO pipeline is available at http://zhanglab.ccmb.med.umich.edu/MetaGO/. Copyright © 2018. Published by Elsevier Ltd.

Structural study of surfactant-dependent interaction with protein

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Mehan, Sumit; Aswal, Vinod K., E-mail: vkaswal@barc.gov.in [Solid State Physics Division, Bhabha Atomic Research Centre, Mumbai 400 085 (India); Kohlbrecher, Joachim [Laboratory for Neutron Scattering, Paul Scherrer Institut, CH-5232 PSI Villigen (Switzerland)

2015-06-24

Small-angle neutron scattering (SANS) has been used to study the complex structure of anionic BSA protein with three different (cationic DTAB, anionic SDS and non-ionic C12E10) surfactants. These systems form very different surfactant-dependent complexes. We show that the structure of protein-surfactant complex is initiated by the site-specific electrostatic interaction between the components, followed by the hydrophobic interaction at high surfactant concentrations. It is also found that hydrophobic interaction is preferred over the electrostatic interaction in deciding the resultant structure of protein-surfactant complexes.

Structural Elements Regulating AAA+ Protein Quality Control Machines.

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Chang, Chiung-Wen; Lee, Sukyeong; Tsai, Francis T F

2017-01-01

Members of the ATPases Associated with various cellular Activities (AAA+) superfamily participate in essential and diverse cellular pathways in all kingdoms of life by harnessing the energy of ATP binding and hydrolysis to drive their biological functions. Although most AAA+ proteins share a ring-shaped architecture, AAA+ proteins have evolved distinct structural elements that are fine-tuned to their specific functions. A central question in the field is how ATP binding and hydrolysis are coupled to substrate translocation through the central channel of ring-forming AAA+ proteins. In this mini-review, we will discuss structural elements present in AAA+ proteins involved in protein quality control, drawing similarities to their known role in substrate interaction by AAA+ proteins involved in DNA translocation. Elements to be discussed include the pore loop-1, the Inter-Subunit Signaling (ISS) motif, and the Pre-Sensor I insert (PS-I) motif. Lastly, we will summarize our current understanding on the inter-relationship of those structural elements and propose a model how ATP binding and hydrolysis might be coupled to polypeptide translocation in protein quality control machines.

Structure of synaptophysin: a hexameric MARVEL-domain channel protein.

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Arthur, Christopher P; Stowell, Michael H B

2007-06-01

Synaptophysin I (SypI) is an archetypal member of the MARVEL-domain family of integral membrane proteins and one of the first synaptic vesicle proteins to be identified and cloned. Most all MARVEL-domain proteins are involved in membrane apposition and vesicle-trafficking events, but their precise role in these processes is unclear. We have purified mammalian SypI and determined its three-dimensional (3D) structure by using electron microscopy and single-particle 3D reconstruction. The hexameric structure resembles an open basket with a large pore and tenuous interactions within the cytosolic domain. The structure suggests a model for Synaptophysin's role in fusion and recycling that is regulated by known interactions with the SNARE machinery. This 3D structure of a MARVEL-domain protein provides a structural foundation for understanding the role of these important proteins in a variety of biological processes.

The structure of pyogenecin immunity protein, a novel bacteriocin-like immunity protein from streptococcus pyogenes.

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Chang, C.; Coggill, P.; Bateman, A.; Finn, R.; Cymborowski, M.; Otwinowski, Z.; Minor, W.; Volkart, L.; Joachimiak, A.; Wellcome Trust Sanger Inst.; Univ. of Virginia; UT Southwestern Medical Center

2009-12-17

Many Gram-positive lactic acid bacteria (LAB) produce anti-bacterial peptides and small proteins called bacteriocins, which enable them to compete against other bacteria in the environment. These peptides fall structurally into three different classes, I, II, III, with class IIa being pediocin-like single entities and class IIb being two-peptide bacteriocins. Self-protective cognate immunity proteins are usually co-transcribed with these toxins. Several examples of cognates for IIa have already been solved structurally. Streptococcus pyogenes, closely related to LAB, is one of the most common human pathogens, so knowledge of how it competes against other LAB species is likely to prove invaluable. We have solved the crystal structure of the gene-product of locus Spy-2152 from S. pyogenes, (PDB: 2fu2), and found it to comprise an anti-parallel four-helix bundle that is structurally similar to other bacteriocin immunity proteins. Sequence analyses indicate this protein to be a possible immunity protein protective against class IIa or IIb bacteriocins. However, given that S. pyogenes appears to lack any IIa pediocin-like proteins but does possess class IIb bacteriocins, we suggest this protein confers immunity to IIb-like peptides. Combined structural, genomic and proteomic analyses have allowed the identification and in silico characterization of a new putative immunity protein from S. pyogenes, possibly the first structure of an immunity protein protective against potential class IIb two-peptide bacteriocins. We have named the two pairs of putative bacteriocins found in S. pyogenes pyogenecin 1, 2, 3 and 4.

The contact activation proteins: a structure/function overview

NARCIS (Netherlands)

Meijers, J. C.; McMullen, B. A.; Bouma, B. N.

1992-01-01

In recent years, extensive knowledge has been obtained on the structure/function relationships of blood coagulation proteins. In this overview, we present recent developments on the structure/function relationships of the contact activation proteins: factor XII, high molecular weight kininogen,

Blind Test of Physics-Based Prediction of Protein Structures

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Shell, M. Scott; Ozkan, S. Banu; Voelz, Vincent; Wu, Guohong Albert; Dill, Ken A.

2009-01-01

We report here a multiprotein blind test of a computer method to predict native protein structures based solely on an all-atom physics-based force field. We use the AMBER 96 potential function with an implicit (GB/SA) model of solvation, combined with replica-exchange molecular-dynamics simulations. Coarse conformational sampling is performed using the zipping and assembly method (ZAM), an approach that is designed to mimic the putative physical routes of protein folding. ZAM was applied to the folding of six proteins, from 76 to 112 monomers in length, in CASP7, a community-wide blind test of protein structure prediction. Because these predictions have about the same level of accuracy as typical bioinformatics methods, and do not utilize information from databases of known native structures, this work opens up the possibility of predicting the structures of membrane proteins, synthetic peptides, or other foldable polymers, for which there is little prior knowledge of native structures. This approach may also be useful for predicting physical protein folding routes, non-native conformations, and other physical properties from amino acid sequences. PMID:19186130

Structural model for the interaction of a designed Ankyrin Repeat Protein with the human epidermal growth factor receptor 2.

Directory of Open Access Journals (Sweden)

V Chandana Epa

Full Text Available Designed Ankyrin Repeat Proteins are a class of novel binding proteins that can be selected and evolved to bind to targets with high affinity and specificity. We are interested in the DARPin H10-2-G3, which has been evolved to bind with very high affinity to the human epidermal growth factor receptor 2 (HER2. HER2 is found to be over-expressed in 30% of breast cancers, and is the target for the FDA-approved therapeutic monoclonal antibodies trastuzumab and pertuzumab and small molecule tyrosine kinase inhibitors. Here, we use computational macromolecular docking, coupled with several interface metrics such as shape complementarity, interaction energy, and electrostatic complementarity, to model the structure of the complex between the DARPin H10-2-G3 and HER2. We analyzed the interface between the two proteins and then validated the structural model by showing that selected HER2 point mutations at the putative interface with H10-2-G3 reduce the affinity of binding up to 100-fold without affecting the binding of trastuzumab. Comparisons made with a subsequently solved X-ray crystal structure of the complex yielded a backbone atom root mean square deviation of 0.84-1.14 Ångstroms. The study presented here demonstrates the capability of the computational techniques of structural bioinformatics in generating useful structural models of protein-protein interactions.

Structural Analysis of PTM Hotspots (SAPH-ire)--A Quantitative Informatics Method Enabling the Discovery of Novel Regulatory Elements in Protein Families.

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Dewhurst, Henry M; Choudhury, Shilpa; Torres, Matthew P

2015-08-01

Predicting the biological function potential of post-translational modifications (PTMs) is becoming increasingly important in light of the exponential increase in available PTM data from high-throughput proteomics. We developed structural analysis of PTM hotspots (SAPH-ire)--a quantitative PTM ranking method that integrates experimental PTM observations, sequence conservation, protein structure, and interaction data to allow rank order comparisons within or between protein families. Here, we applied SAPH-ire to the study of PTMs in diverse G protein families, a conserved and ubiquitous class of proteins essential for maintenance of intracellular structure (tubulins) and signal transduction (large and small Ras-like G proteins). A total of 1728 experimentally verified PTMs from eight unique G protein families were clustered into 451 unique hotspots, 51 of which have a known and cited biological function or response. Using customized software, the hotspots were analyzed in the context of 598 unique protein structures. By comparing distributions of hotspots with known versus unknown function, we show that SAPH-ire analysis is predictive for PTM biological function. Notably, SAPH-ire revealed high-ranking hotspots for which a functional impact has not yet been determined, including phosphorylation hotspots in the N-terminal tails of G protein gamma subunits--conserved protein structures never before reported as regulators of G protein coupled receptor signaling. To validate this prediction we used the yeast model system for G protein coupled receptor signaling, revealing that gamma subunit-N-terminal tail phosphorylation is activated in response to G protein coupled receptor stimulation and regulates protein stability in vivo. These results demonstrate the utility of integrating protein structural and sequence features into PTM prioritization schemes that can improve the analysis and functional power of modification-specific proteomics data. © 2015 by The American

Implementation of a Parallel Protein Structure Alignment Service on Cloud

Directory of Open Access Journals (Sweden)

Che-Lun Hung

2013-01-01

Full Text Available Protein structure alignment has become an important strategy by which to identify evolutionary relationships between protein sequences. Several alignment tools are currently available for online comparison of protein structures. In this paper, we propose a parallel protein structure alignment service based on the Hadoop distribution framework. This service includes a protein structure alignment algorithm, a refinement algorithm, and a MapReduce programming model. The refinement algorithm refines the result of alignment. To process vast numbers of protein structures in parallel, the alignment and refinement algorithms are implemented using MapReduce. We analyzed and compared the structure alignments produced by different methods using a dataset randomly selected from the PDB database. The experimental results verify that the proposed algorithm refines the resulting alignments more accurately than existing algorithms. Meanwhile, the computational performance of the proposed service is proportional to the number of processors used in our cloud platform.

Accurate protein structure annotation through competitive diffusion of enzymatic functions over a network of local evolutionary similarities.

Directory of Open Access Journals (Sweden)

Eric Venner

Full Text Available High-throughput Structural Genomics yields many new protein structures without known molecular function. This study aims to uncover these missing annotations by globally comparing select functional residues across the structural proteome. First, Evolutionary Trace Annotation, or ETA, identifies which proteins have local evolutionary and structural features in common; next, these proteins are linked together into a proteomic network of ETA similarities; then, starting from proteins with known functions, competing functional labels diffuse link-by-link over the entire network. Every node is thus assigned a likelihood z-score for every function, and the most significant one at each node wins and defines its annotation. In high-throughput controls, this competitive diffusion process recovered enzyme activity annotations with 99% and 97% accuracy at half-coverage for the third and fourth Enzyme Commission (EC levels, respectively. This corresponds to false positive rates 4-fold lower than nearest-neighbor and 5-fold lower than sequence-based annotations. In practice, experimental validation of the predicted carboxylesterase activity in a protein from Staphylococcus aureus illustrated the effectiveness of this approach in the context of an increasingly drug-resistant microbe. This study further links molecular function to a small number of evolutionarily important residues recognizable by Evolutionary Tracing and it points to the specificity and sensitivity of functional annotation by competitive global network diffusion. A web server is at http://mammoth.bcm.tmc.edu/networks.

Automatic rebuilding and optimization of crystallographic structures in the Protein Data Bank.

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Joosten, Robbie P; Joosten, Krista; Cohen, Serge X; Vriend, Gert; Perrakis, Anastassis

2011-12-15

Macromolecular crystal structures in the Protein Data Bank (PDB) are a key source of structural insight into biological processes. These structures, some >30 years old, were constructed with methods of their era. With PDB_REDO, we aim to automatically optimize these structures to better fit their corresponding experimental data, passing the benefits of new methods in crystallography on to a wide base of non-crystallographer structure users. We developed new algorithms to allow automatic rebuilding and remodeling of main chain peptide bonds and side chains in crystallographic electron density maps, and incorporated these and further enhancements in the PDB_REDO procedure. Applying the updated PDB_REDO to the oldest, but also to some of the newest models in the PDB, corrects existing modeling errors and brings these models to a higher quality, as judged by standard validation methods. The PDB_REDO database and links to all software are available at http://www.cmbi.ru.nl/pdb_redo. r.joosten@nki.nl; a.perrakis@nki.nl Supplementary data are available at Bioinformatics online.

STRUCTURAL FEATURES OF PLANT CHITINASES AND CHITIN-BINDING PROTEINS

NARCIS (Netherlands)

BEINTEMA, JJ

1994-01-01

Structural features of plant chitinases and chitin-binding proteins are discussed. Many of these proteins consist of multiple domains,of which the chitin-binding hevein domain is a predominant one. X-ray and NMR structures of representatives of the major classes of these proteins are available now,

Rapid and reliable protein structure determination via chemical shift threading.

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Hafsa, Noor E; Berjanskii, Mark V; Arndt, David; Wishart, David S

2018-01-01

Protein structure determination using nuclear magnetic resonance (NMR) spectroscopy can be both time-consuming and labor intensive. Here we demonstrate how chemical shift threading can permit rapid, robust, and accurate protein structure determination using only chemical shift data. Threading is a relatively old bioinformatics technique that uses a combination of sequence information and predicted (or experimentally acquired) low-resolution structural data to generate high-resolution 3D protein structures. The key motivations behind using NMR chemical shifts for protein threading lie in the fact that they are easy to measure, they are available prior to 3D structure determination, and they contain vital structural information. The method we have developed uses not only sequence and chemical shift similarity but also chemical shift-derived secondary structure, shift-derived super-secondary structure, and shift-derived accessible surface area to generate a high quality protein structure regardless of the sequence similarity (or lack thereof) to a known structure already in the PDB. The method (called E-Thrifty) was found to be very fast (often chemical shift refinement, these results suggest that protein structure determination, using only NMR chemical shifts, is becoming increasingly practical and reliable. E-Thrifty is available as a web server at http://ethrifty.ca .

Structure-based inference of molecular functions of proteins of unknown function from Berkeley Structural Genomics Center

Energy Technology Data Exchange (ETDEWEB)

Kim, Sung-Hou; Shin, Dong Hae; Hou, Jingtong; Chandonia, John-Marc; Das, Debanu; Choi, In-Geol; Kim, Rosalind; Kim, Sung-Hou

2007-09-02

Advances in sequence genomics have resulted in an accumulation of a huge number of protein sequences derived from genome sequences. However, the functions of a large portion of them cannot be inferred based on the current methods of sequence homology detection to proteins of known functions. Three-dimensional structure can have an important impact in providing inference of molecular function (physical and chemical function) of a protein of unknown function. Structural genomics centers worldwide have been determining many 3-D structures of the proteins of unknown functions, and possible molecular functions of them have been inferred based on their structures. Combined with bioinformatics and enzymatic assay tools, the successful acceleration of the process of protein structure determination through high throughput pipelines enables the rapid functional annotation of a large fraction of hypothetical proteins. We present a brief summary of the process we used at the Berkeley Structural Genomics Center to infer molecular functions of proteins of unknown function.

MolTalk--a programming library for protein structures and structure analysis.

Science.gov (United States)

Diemand, Alexander V; Scheib, Holger

2004-04-19

Two of the mostly unsolved but increasingly urgent problems for modern biologists are a) to quickly and easily analyse protein structures and b) to comprehensively mine the wealth of information, which is distributed along with the 3D co-ordinates by the Protein Data Bank (PDB). Tools which address this issue need to be highly flexible and powerful but at the same time must be freely available and easy to learn. We present MolTalk, an elaborate programming language, which consists of the programming library libmoltalk implemented in Objective-C and the Smalltalk-based interpreter MolTalk. MolTalk combines the advantages of an easy to learn and programmable procedural scripting with the flexibility and power of a full programming language. An overview of currently available applications of MolTalk is given and with PDBChainSaw one such application is described in more detail. PDBChainSaw is a MolTalk-based parser and information extraction utility of PDB files. Weekly updates of the PDB are synchronised with PDBChainSaw and are available for free download from the MolTalk project page http://www.moltalk.org following the link to PDBChainSaw. For each chain in a protein structure, PDBChainSaw extracts the sequence from its co-ordinates and provides additional information from the PDB-file header section, such as scientific organism, compound name, and EC code. MolTalk provides a rich set of methods to analyse and even modify experimentally determined or modelled protein structures. These methods vary in complexity and are thus suitable for beginners and advanced programmers alike. We envision MolTalk to be most valuable in the following applications:1) To analyse protein structures repetitively in large-scale, i.e. to benchmark protein structure prediction methods or to evaluate structural models. The quality of the resulting 3D-models can be assessed by e.g. calculating a Ramachandran-Sasisekharan plot.2) To quickly retrieve information for (a limited number of

Predicting nucleic acid binding interfaces from structural models of proteins.

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Dror, Iris; Shazman, Shula; Mukherjee, Srayanta; Zhang, Yang; Glaser, Fabian; Mandel-Gutfreund, Yael

2012-02-01

The function of DNA- and RNA-binding proteins can be inferred from the characterization and accurate prediction of their binding interfaces. However, the main pitfall of various structure-based methods for predicting nucleic acid binding function is that they are all limited to a relatively small number of proteins for which high-resolution three-dimensional structures are available. In this study, we developed a pipeline for extracting functional electrostatic patches from surfaces of protein structural models, obtained using the I-TASSER protein structure predictor. The largest positive patches are extracted from the protein surface using the patchfinder algorithm. We show that functional electrostatic patches extracted from an ensemble of structural models highly overlap the patches extracted from high-resolution structures. Furthermore, by testing our pipeline on a set of 55 known nucleic acid binding proteins for which I-TASSER produces high-quality models, we show that the method accurately identifies the nucleic acids binding interface on structural models of proteins. Employing a combined patch approach we show that patches extracted from an ensemble of models better predicts the real nucleic acid binding interfaces compared with patches extracted from independent models. Overall, these results suggest that combining information from a collection of low-resolution structural models could be a valuable approach for functional annotation. We suggest that our method will be further applicable for predicting other functional surfaces of proteins with unknown structure. Copyright © 2011 Wiley Periodicals, Inc.

Design, synthesis, and validation of a β-turn mimetic library targeting protein-protein and peptide-receptor interactions.

Science.gov (United States)

Whitby, Landon R; Ando, Yoshio; Setola, Vincent; Vogt, Peter K; Roth, Bryan L; Boger, Dale L

2011-07-06

The design and synthesis of a β-turn mimetic library as a key component of a small-molecule library targeting the major recognition motifs involved in protein-protein interactions is described. Analysis of a geometric characterization of 10,245 β-turns in the protein data bank (PDB) suggested that trans-pyrrolidine-3,4-dicarboxamide could serve as an effective and synthetically accessible library template. This was confirmed by initially screening select compounds against a series of peptide-activated GPCRs that recognize a β-turn structure in their endogenous ligands. This validation study was highlighted by identification of both nonbasic and basic small molecules with high affinities (K(i) = 390 and 23 nM, respectively) for the κ-opioid receptor (KOR). Consistent with the screening capabilities of collaborators and following the design validation, the complete library was assembled as 210 mixtures of 20 compounds, providing a total of 4200 compounds designed to mimic all possible permutations of 3 of the 4 residues in a naturally occurring β-turn. Unique to the design and because of the C(2) symmetry of the template, a typical 20 × 20 × 20-mix (8000 compounds prepared as 400 mixtures of 20 compounds) needed to represent 20 variations in the side chains of three amino acid residues reduces to a 210 × 20-mix, thereby simplifying the library synthesis and subsequent screening. The library was prepared using a solution-phase synthetic protocol with liquid-liquid or liquid-solid extractions for purification and conducted on a scale that insures its long-term availability for screening campaigns. Screening the library against the human opioid receptors (KOR, MOR, and DOR) identified not only the activity of library members expected to mimic the opioid receptor peptide ligands but also additional side-chain combinations that provided enhanced receptor binding selectivities (>100-fold) and affinities (as low as K(i) = 80 nM for KOR). A key insight to emerge from

Worldwide Protein Data Bank biocuration supporting open access to high-quality 3D structural biology data

Science.gov (United States)

Westbrook, John D; Feng, Zukang; Persikova, Irina; Sala, Raul; Sen, Sanchayita; Berrisford, John M; Swaminathan, G Jawahar; Oldfield, Thomas J; Gutmanas, Aleksandras; Igarashi, Reiko; Armstrong, David R; Baskaran, Kumaran; Chen, Li; Chen, Minyu; Clark, Alice R; Di Costanzo, Luigi; Dimitropoulos, Dimitris; Gao, Guanghua; Ghosh, Sutapa; Gore, Swanand; Guranovic, Vladimir; Hendrickx, Pieter M S; Hudson, Brian P; Ikegawa, Yasuyo; Kengaku, Yumiko; Lawson, Catherine L; Liang, Yuhe; Mak, Lora; Mukhopadhyay, Abhik; Narayanan, Buvaneswari; Nishiyama, Kayoko; Patwardhan, Ardan; Sahni, Gaurav; Sanz-García, Eduardo; Sato, Junko; Sekharan, Monica R; Shao, Chenghua; Smart, Oliver S; Tan, Lihua; van Ginkel, Glen; Yang, Huanwang; Zhuravleva, Marina A; Markley, John L; Nakamura, Haruki; Kurisu, Genji; Kleywegt, Gerard J; Velankar, Sameer; Berman, Helen M; Burley, Stephen K

2018-01-01

Abstract The Protein Data Bank (PDB) is the single global repository for experimentally determined 3D structures of biological macromolecules and their complexes with ligands. The worldwide PDB (wwPDB) is the international collaboration that manages the PDB archive according to the FAIR principles: Findability, Accessibility, Interoperability and Reusability. The wwPDB recently developed OneDep, a unified tool for deposition, validation and biocuration of structures of biological macromolecules. All data deposited to the PDB undergo critical review by wwPDB Biocurators. This article outlines the importance of biocuration for structural biology data deposited to the PDB and describes wwPDB biocuration processes and the role of expert Biocurators in sustaining a high-quality archive. Structural data submitted to the PDB are examined for self-consistency, standardized using controlled vocabularies, cross-referenced with other biological data resources and validated for scientific/technical accuracy. We illustrate how biocuration is integral to PDB data archiving, as it facilitates accurate, consistent and comprehensive representation of biological structure data, allowing efficient and effective usage by research scientists, educators, students and the curious public worldwide. Database URL: https://www.wwpdb.org/ PMID:29688351

Using linear algebra for protein structural comparison and classification.

Science.gov (United States)

Gomide, Janaína; Melo-Minardi, Raquel; Dos Santos, Marcos Augusto; Neshich, Goran; Meira, Wagner; Lopes, Júlio César; Santoro, Marcelo

2009-07-01

In this article, we describe a novel methodology to extract semantic characteristics from protein structures using linear algebra in order to compose structural signature vectors which may be used efficiently to compare and classify protein structures into fold families. These signatures are built from the pattern of hydrophobic intrachain interactions using Singular Value Decomposition (SVD) and Latent Semantic Indexing (LSI) techniques. Considering proteins as documents and contacts as terms, we have built a retrieval system which is able to find conserved contacts in samples of myoglobin fold family and to retrieve these proteins among proteins of varied folds with precision of up to 80%. The classifier is a web tool available at our laboratory website. Users can search for similar chains from a specific PDB, view and compare their contact maps and browse their structures using a JMol plug-in.

Using linear algebra for protein structural comparison and classification

Directory of Open Access Journals (Sweden)

Janaína Gomide

2009-01-01

Full Text Available In this article, we describe a novel methodology to extract semantic characteristics from protein structures using linear algebra in order to compose structural signature vectors which may be used efficiently to compare and classify protein structures into fold families. These signatures are built from the pattern of hydrophobic intrachain interactions using Singular Value Decomposition (SVD and Latent Semantic Indexing (LSI techniques. Considering proteins as documents and contacts as terms, we have built a retrieval system which is able to find conserved contacts in samples of myoglobin fold family and to retrieve these proteins among proteins of varied folds with precision of up to 80%. The classifier is a web tool available at our laboratory website. Users can search for similar chains from a specific PDB, view and compare their contact maps and browse their structures using a JMol plug-in.

Protein 3D structure computed from evolutionary sequence variation.

Directory of Open Access Journals (Sweden)

Debora S Marks

Full Text Available The evolutionary trajectory of a protein through sequence space is constrained by its function. Collections of sequence homologs record the outcomes of millions of evolutionary experiments in which the protein evolves according to these constraints. Deciphering the evolutionary record held in these sequences and exploiting it for predictive and engineering purposes presents a formidable challenge. The potential benefit of solving this challenge is amplified by the advent of inexpensive high-throughput genomic sequencing.In this paper we ask whether we can infer evolutionary constraints from a set of sequence homologs of a protein. The challenge is to distinguish true co-evolution couplings from the noisy set of observed correlations. We address this challenge using a maximum entropy model of the protein sequence, constrained by the statistics of the multiple sequence alignment, to infer residue pair couplings. Surprisingly, we find that the strength of these inferred couplings is an excellent predictor of residue-residue proximity in folded structures. Indeed, the top-scoring residue couplings are sufficiently accurate and well-distributed to define the 3D protein fold with remarkable accuracy.We quantify this observation by computing, from sequence alone, all-atom 3D structures of fifteen test proteins from different fold classes, ranging in size from 50 to 260 residues, including a G-protein coupled receptor. These blinded inferences are de novo, i.e., they do not use homology modeling or sequence-similar fragments from known structures. The co-evolution signals provide sufficient information to determine accurate 3D protein structure to 2.7-4.8 Å C(α-RMSD error relative to the observed structure, over at least two-thirds of the protein (method called EVfold, details at http://EVfold.org. This discovery provides insight into essential interactions constraining protein evolution and will facilitate a comprehensive survey of the universe of

Ion pairs in non-redundant protein structures

Indian Academy of Sciences (India)

Ion pairs contribute to several functions including the activity of catalytic triads, fusion of viral membranes, stability in thermophilic proteins and solvent–protein interactions. Furthermore, they have the ability to affect the stability of protein structures and are also a part of the forces that act to hold monomers together.

Distance matrix-based approach to protein structure prediction.

Science.gov (United States)

Kloczkowski, Andrzej; Jernigan, Robert L; Wu, Zhijun; Song, Guang; Yang, Lei; Kolinski, Andrzej; Pokarowski, Piotr

2009-03-01

Much structural information is encoded in the internal distances; a distance matrix-based approach can be used to predict protein structure and dynamics, and for structural refinement. Our approach is based on the square distance matrix D = [r(ij)(2)] containing all square distances between residues in proteins. This distance matrix contains more information than the contact matrix C, that has elements of either 0 or 1 depending on whether the distance r (ij) is greater or less than a cutoff value r (cutoff). We have performed spectral decomposition of the distance matrices D = sigma lambda(k)V(k)V(kT), in terms of eigenvalues lambda kappa and the corresponding eigenvectors v kappa and found that it contains at most five nonzero terms. A dominant eigenvector is proportional to r (2)--the square distance of points from the center of mass, with the next three being the principal components of the system of points. By predicting r (2) from the sequence we can approximate a distance matrix of a protein with an expected RMSD value of about 7.3 A, and by combining it with the prediction of the first principal component we can improve this approximation to 4.0 A. We can also explain the role of hydrophobic interactions for the protein structure, because r is highly correlated with the hydrophobic profile of the sequence. Moreover, r is highly correlated with several sequence profiles which are useful in protein structure prediction, such as contact number, the residue-wise contact order (RWCO) or mean square fluctuations (i.e. crystallographic temperature factors). We have also shown that the next three components are related to spatial directionality of the secondary structure elements, and they may be also predicted from the sequence, improving overall structure prediction. We have also shown that the large number of available HIV-1 protease structures provides a remarkable sampling of conformations, which can be viewed as direct structural information about the

Validation of the manufacturing process used to produce long-acting recombinant factor IX Fc fusion protein.

Science.gov (United States)

McCue, J; Osborne, D; Dumont, J; Peters, R; Mei, B; Pierce, G F; Kobayashi, K; Euwart, D

2014-07-01

Recombinant factor IX Fc (rFIXFc) fusion protein is the first of a new class of bioengineered long-acting factors approved for the treatment and prevention of bleeding episodes in haemophilia B. The aim of this work was to describe the manufacturing process for rFIXFc, to assess product quality and to evaluate the capacity of the process to remove impurities and viruses. This manufacturing process utilized a transferable and scalable platform approach established for therapeutic antibody manufacturing and adapted for production of the rFIXFc molecule. rFIXFc was produced using a process free of human- and animal-derived raw materials and a host cell line derived from human embryonic kidney (HEK) 293H cells. The process employed multi-step purification and viral clearance processing, including use of a protein A affinity capture chromatography step, which binds to the Fc portion of the rFIXFc molecule with high affinity and specificity, and a 15 nm pore size virus removal nanofilter. Process validation studies were performed to evaluate identity, purity, activity and safety. The manufacturing process produced rFIXFc with consistent product quality and high purity. Impurity clearance validation studies demonstrated robust and reproducible removal of process-related impurities and adventitious viruses. The rFIXFc manufacturing process produces a highly pure product, free of non-human glycan structures. Validation studies demonstrate that this product is produced with consistent quality and purity. In addition, the scalability and transferability of this process are key attributes to ensure consistent and continuous supply of rFIXFc. © 2014 The Authors. Haemophilia Published by John Wiley & Sons Ltd.

Host Proteins Determine MRSA Biofilm Structure and Integrity

DEFF Research Database (Denmark)

Dreier, Cindy; Nielsen, Astrid; Jørgensen, Nis Pedersen

Human extracellular matrix (hECM) proteins aids the initial attachment and initiation of an infection, by specific binding to bacterial cell surface proteins. However, the importance of hECM proteins in structure, integrity and antibiotic resilience of a biofilm is unknown. This study aims...... to determine how specific hECM proteins affect S. aureus USA300 JE2 biofilms. Biofilms were grown in the presence of synovial fluid from rheumatoid arteritis patients to mimic in vivo conditions, where bacteria incorporate hECM proteins into the biofilm matrix. Difference in biofilm structure, with and without...... addition of hECM to growth media, was visualized by confocal laser scanning microscopy. Two enzymatic degradation experiments were used to study biofilm matrix composition and importance of hECM proteins: enzymatic removal of specific hECM proteins from growth media, before biofilm formation, and enzymatic...

Integrating protein structures and precomputed genealogies in the Magnum database: Examples with cellular retinoid binding proteins

Directory of Open Access Journals (Sweden)

Bradley Michael E

2006-02-01

Full Text Available Abstract Background When accurate models for the divergent evolution of protein sequences are integrated with complementary biological information, such as folded protein structures, analyses of the combined data often lead to new hypotheses about molecular physiology. This represents an excellent example of how bioinformatics can be used to guide experimental research. However, progress in this direction has been slowed by the lack of a publicly available resource suitable for general use. Results The precomputed Magnum database offers a solution to this problem for ca. 1,800 full-length protein families with at least one crystal structure. The Magnum deliverables include 1 multiple sequence alignments, 2 mapping of alignment sites to crystal structure sites, 3 phylogenetic trees, 4 inferred ancestral sequences at internal tree nodes, and 5 amino acid replacements along tree branches. Comprehensive evaluations revealed that the automated procedures used to construct Magnum produced accurate models of how proteins divergently evolve, or genealogies, and correctly integrated these with the structural data. To demonstrate Magnum's capabilities, we asked for amino acid replacements requiring three nucleotide substitutions, located at internal protein structure sites, and occurring on short phylogenetic tree branches. In the cellular retinoid binding protein family a site that potentially modulates ligand binding affinity was discovered. Recruitment of cellular retinol binding protein to function as a lens crystallin in the diurnal gecko afforded another opportunity to showcase the predictive value of a browsable database containing branch replacement patterns integrated with protein structures. Conclusion We integrated two areas of protein science, evolution and structure, on a large scale and created a precomputed database, known as Magnum, which is the first freely available resource of its kind. Magnum provides evolutionary and structural

Structural elucidation of transmembrane domain zero (TMD0) of EcdL: A multidrug resistance-associated protein (MRP) family of ATP-binding cassette transporter protein revealed by atomistic simulation.

Science.gov (United States)

Bera, Krishnendu; Rani, Priyanka; Kishor, Gaurav; Agarwal, Shikha; Kumar, Antresh; Singh, Durg Vijay

2017-09-20

ATP-Binding cassette (ABC) transporters play an extensive role in the translocation of diverse sets of biologically important molecules across membrane. EchnocandinB (antifungal) and EcdL protein of Aspergillus rugulosus are encoded by the same cluster of genes. Co-expression of EcdL and echinocandinB reflects tightly linked biological functions. EcdL belongs to Multidrug Resistance associated Protein (MRP) subfamily of ABC transporters with an extra transmembrane domain zero (TMD0). Complete structure of MRP subfamily comprising of TMD0 domain, at atomic resolution is not known. We hypothesized that the transportation of echonocandinB is mediated via EcdL protein. Henceforth, it is pertinent to know the topological arrangement of TMD0, with other domains of protein and its possible role in transportation of echinocandinB. Absence of effective template for TMD0 domain lead us to model by I-TASSER, further structure has been refined by multiple template modelling using homologous templates of remaining domains (TMD1, NBD1, TMD2, NBD2). The modelled structure has been validated for packing, folding and stereochemical properties. MD simulation for 0.1 μs has been carried out in the biphasic environment for refinement of modelled protein. Non-redundant structures have been excavated by clustering of MD trajectory. The structural alignment of modelled structure has shown Z-score -37.9; 31.6, 31.5 with RMSD; 2.4, 4.2, 4.8 with ABC transporters; PDB ID 4F4C, 4M1 M, 4M2T, respectively, reflecting the correctness of structure. EchinocandinB has been docked to the modelled as well as to the clustered structures, which reveals interaction of echinocandinB with TMD0 and other TM helices in the translocation path build of TMDs.

PCI-SS: MISO dynamic nonlinear protein secondary structure prediction

Directory of Open Access Journals (Sweden)

Aboul-Magd Mohammed O

2009-07-01

Full Text Available Abstract Background Since the function of a protein is largely dictated by its three dimensional configuration, determining a protein's structure is of fundamental importance to biology. Here we report on a novel approach to determining the one dimensional secondary structure of proteins (distinguishing α-helices, β-strands, and non-regular structures from primary sequence data which makes use of Parallel Cascade Identification (PCI, a powerful technique from the field of nonlinear system identification. Results Using PSI-BLAST divergent evolutionary profiles as input data, dynamic nonlinear systems are built through a black-box approach to model the process of protein folding. Genetic algorithms (GAs are applied in order to optimize the architectural parameters of the PCI models. The three-state prediction problem is broken down into a combination of three binary sub-problems and protein structure classifiers are built using 2 layers of PCI classifiers. Careful construction of the optimization, training, and test datasets ensures that no homology exists between any training and testing data. A detailed comparison between PCI and 9 contemporary methods is provided over a set of 125 new protein chains guaranteed to be dissimilar to all training data. Unlike other secondary structure prediction methods, here a web service is developed to provide both human- and machine-readable interfaces to PCI-based protein secondary structure prediction. This server, called PCI-SS, is available at http://bioinf.sce.carleton.ca/PCISS. In addition to a dynamic PHP-generated web interface for humans, a Simple Object Access Protocol (SOAP interface is added to permit invocation of the PCI-SS service remotely. This machine-readable interface facilitates incorporation of PCI-SS into multi-faceted systems biology analysis pipelines requiring protein secondary structure information, and greatly simplifies high-throughput analyses. XML is used to represent the input

Discrete Haar transform and protein structure.

Science.gov (United States)

Morosetti, S

1997-12-01

The discrete Haar transform of the sequence of the backbone dihedral angles (phi and psi) was performed over a set of X-ray protein structures of high resolution from the Brookhaven Protein Data Bank. Afterwards, the new dihedral angles were calculated by the inverse transform, using a growing number of Haar functions, from the lower to the higher degree. New structures were obtained using these dihedral angles, with standard values for bond lengths and angles, and with omega = 0 degree. The reconstructed structures were compared with the experimental ones, and analyzed by visual inspection and statistical analysis. When half of the Haar coefficients were used, all the reconstructed structures were not yet collapsed to a tertiary folding, but they showed yet realized most of the secondary motifs. These results indicate a substantial separation of structural information in the space of Haar transform, with the secondary structural information mainly present in the Haar coefficients of lower degrees, and the tertiary one present in the higher degree coefficients. Because of this separation, the representation of the folded structures in the space of Haar transform seems a promising candidate to encompass the problem of premature convergence in genetic algorithms.

Tuning structure of oppositely charged nanoparticle and protein complexes

Energy Technology Data Exchange (ETDEWEB)

Kumar, Sugam, E-mail: sugam@barc.gov.in; Aswal, V. K., E-mail: sugam@barc.gov.in [Solid State Physics Division, Bhabha Atomic Research Centre, Mumbai-400085 (India); Callow, P. [Institut Laue Langevin, DS/LSS, 6 rue Jules Horowitz, 38042 Grenoble Cedex 9 (France)

2014-04-24

Small-angle neutron scattering (SANS) has been used to probe the structures of anionic silica nanoparticles (LS30) and cationic lyszyme protein (M.W. 14.7kD, I.P. ∼ 11.4) by tuning their interaction through the pH variation. The protein adsorption on nanoparticles is found to be increasing with pH and determined by the electrostatic attraction between two components as well as repulsion between protein molecules. We show the strong electrostatic attraction between nanoparticles and protein molecules leads to protein-mediated aggregation of nanoparticles which are characterized by fractal structures. At pH 5, the protein adsorption gives rise to nanoparticle aggregation having surface fractal morphology with close packing of nanoparticles. The surface fractals transform to open structures of mass fractal morphology at higher pH (7 and 9) on approaching isoelectric point (I.P.)

Comparative evaluation of six ELISAs for the detection of antibodies to the non-structural proteins of foot-and-mouth disease virus

DEFF Research Database (Denmark)

Brocchi, E.; Bergmann, I.E.; Dekker, A.

2006-01-01

To validate the use of serology in substantiating freedom from infection after foot-and-mouth disease (FMD) outbreaks have been controlled by measures that include vaccination, 3551 sera were tested with six assays that detect antibodies to the non-structural proteins of FMD virus. The sera came...

Relationship between Molecular Structure Characteristics of Feed Proteins and Protein In vitro Digestibility and Solubility.

Science.gov (United States)

Bai, Mingmei; Qin, Guixin; Sun, Zewei; Long, Guohui

2016-08-01

The nutritional value of feed proteins and their utilization by livestock are related not only to the chemical composition but also to the structure of feed proteins, but few studies thus far have investigated the relationship between the structure of feed proteins and their solubility as well as digestibility in monogastric animals. To address this question we analyzed soybean meal, fish meal, corn distiller's dried grains with solubles, corn gluten meal, and feather meal by Fourier transform infrared (FTIR) spectroscopy to determine the protein molecular spectral band characteristics for amides I and II as well as α-helices and β-sheets and their ratios. Protein solubility and in vitro digestibility were measured with the Kjeldahl method using 0.2% KOH solution and the pepsin-pancreatin two-step enzymatic method, respectively. We found that all measured spectral band intensities (height and area) of feed proteins were correlated with their the in vitro digestibility and solubility (p≤0.003); moreover, the relatively quantitative amounts of α-helices, random coils, and α-helix to β-sheet ratio in protein secondary structures were positively correlated with protein in vitro digestibility and solubility (p≤0.004). On the other hand, the percentage of β-sheet structures was negatively correlated with protein in vitro digestibility (pdigestibility at 28 h and solubility. Furthermore, the α-helix-to-β-sheet ratio can be used to predict the nutritional value of feed proteins.

Structure modeling of all identified G protein-coupled receptors in the human genome.

Science.gov (United States)

Zhang, Yang; Devries, Mark E; Skolnick, Jeffrey

2006-02-01

G protein-coupled receptors (GPCRs), encoded by about 5% of human genes, comprise the largest family of integral membrane proteins and act as cell surface receptors responsible for the transduction of endogenous signal into a cellular response. Although tertiary structural information is crucial for function annotation and drug design, there are few experimentally determined GPCR structures. To address this issue, we employ the recently developed threading assembly refinement (TASSER) method to generate structure predictions for all 907 putative GPCRs in the human genome. Unlike traditional homology modeling approaches, TASSER modeling does not require solved homologous template structures; moreover, it often refines the structures closer to native. These features are essential for the comprehensive modeling of all human GPCRs when close homologous templates are absent. Based on a benchmarked confidence score, approximately 820 predicted models should have the correct folds. The majority of GPCR models share the characteristic seven-transmembrane helix topology, but 45 ORFs are predicted to have different structures. This is due to GPCR fragments that are predominantly from extracellular or intracellular domains as well as database annotation errors. Our preliminary validation includes the automated modeling of bovine rhodopsin, the only solved GPCR in the Protein Data Bank. With homologous templates excluded, the final model built by TASSER has a global C(alpha) root-mean-squared deviation from native of 4.6 angstroms, with a root-mean-squared deviation in the transmembrane helix region of 2.1 angstroms. Models of several representative GPCRs are compared with mutagenesis and affinity labeling data, and consistent agreement is demonstrated. Structure clustering of the predicted models shows that GPCRs with similar structures tend to belong to a similar functional class even when their sequences are diverse. These results demonstrate the usefulness and robustness

Structure modeling of all identified G protein-coupled receptors in the human genome.

Directory of Open Access Journals (Sweden)

Yang Zhang

2006-02-01

Full Text Available G protein-coupled receptors (GPCRs, encoded by about 5% of human genes, comprise the largest family of integral membrane proteins and act as cell surface receptors responsible for the transduction of endogenous signal into a cellular response. Although tertiary structural information is crucial for function annotation and drug design, there are few experimentally determined GPCR structures. To address this issue, we employ the recently developed threading assembly refinement (TASSER method to generate structure predictions for all 907 putative GPCRs in the human genome. Unlike traditional homology modeling approaches, TASSER modeling does not require solved homologous template structures; moreover, it often refines the structures closer to native. These features are essential for the comprehensive modeling of all human GPCRs when close homologous templates are absent. Based on a benchmarked confidence score, approximately 820 predicted models should have the correct folds. The majority of GPCR models share the characteristic seven-transmembrane helix topology, but 45 ORFs are predicted to have different structures. This is due to GPCR fragments that are predominantly from extracellular or intracellular domains as well as database annotation errors. Our preliminary validation includes the automated modeling of bovine rhodopsin, the only solved GPCR in the Protein Data Bank. With homologous templates excluded, the final model built by TASSER has a global C(alpha root-mean-squared deviation from native of 4.6 angstroms, with a root-mean-squared deviation in the transmembrane helix region of 2.1 angstroms. Models of several representative GPCRs are compared with mutagenesis and affinity labeling data, and consistent agreement is demonstrated. Structure clustering of the predicted models shows that GPCRs with similar structures tend to belong to a similar functional class even when their sequences are diverse. These results demonstrate the usefulness

Structural Analysis of PTM Hotspots (SAPH-ire) – A Quantitative Informatics Method Enabling the Discovery of Novel Regulatory Elements in Protein Families*

Science.gov (United States)

Dewhurst, Henry M.; Choudhury, Shilpa; Torres, Matthew P.

2015-01-01

Predicting the biological function potential of post-translational modifications (PTMs) is becoming increasingly important in light of the exponential increase in available PTM data from high-throughput proteomics. We developed structural analysis of PTM hotspots (SAPH-ire)—a quantitative PTM ranking method that integrates experimental PTM observations, sequence conservation, protein structure, and interaction data to allow rank order comparisons within or between protein families. Here, we applied SAPH-ire to the study of PTMs in diverse G protein families, a conserved and ubiquitous class of proteins essential for maintenance of intracellular structure (tubulins) and signal transduction (large and small Ras-like G proteins). A total of 1728 experimentally verified PTMs from eight unique G protein families were clustered into 451 unique hotspots, 51 of which have a known and cited biological function or response. Using customized software, the hotspots were analyzed in the context of 598 unique protein structures. By comparing distributions of hotspots with known versus unknown function, we show that SAPH-ire analysis is predictive for PTM biological function. Notably, SAPH-ire revealed high-ranking hotspots for which a functional impact has not yet been determined, including phosphorylation hotspots in the N-terminal tails of G protein gamma subunits—conserved protein structures never before reported as regulators of G protein coupled receptor signaling. To validate this prediction we used the yeast model system for G protein coupled receptor signaling, revealing that gamma subunit–N-terminal tail phosphorylation is activated in response to G protein coupled receptor stimulation and regulates protein stability in vivo. These results demonstrate the utility of integrating protein structural and sequence features into PTM prioritization schemes that can improve the analysis and functional power of modification-specific proteomics data. PMID:26070665

Principal components analysis of protein structure ensembles calculated using NMR data

International Nuclear Information System (INIS)

Howe, Peter W.A.

2001-01-01

One important problem when calculating structures of biomolecules from NMR data is distinguishing converged structures from outlier structures. This paper describes how Principal Components Analysis (PCA) has the potential to classify calculated structures automatically, according to correlated structural variation across the population. PCA analysis has the additional advantage that it highlights regions of proteins which are varying across the population. To apply PCA, protein structures have to be reduced in complexity and this paper describes two different representations of protein structures which achieve this. The calculated structures of a 28 amino acid peptide are used to demonstrate the methods. The two different representations of protein structure are shown to give equivalent results, and correct results are obtained even though the ensemble of structures used as an example contains two different protein conformations. The PCA analysis also correctly identifies the structural differences between the two conformations

A generative, probabilistic model of local protein structure

DEFF Research Database (Denmark)

Boomsma, Wouter; Mardia, Kanti V.; Taylor, Charles C.

2008-01-01

Despite significant progress in recent years, protein structure prediction maintains its status as one of the prime unsolved problems in computational biology. One of the key remaining challenges is an efficient probabilistic exploration of the structural space that correctly reflects the relative...... conformational stabilities. Here, we present a fully probabilistic, continuous model of local protein structure in atomic detail. The generative model makes efficient conformational sampling possible and provides a framework for the rigorous analysis of local sequence-structure correlations in the native state...

3DProIN: Protein-Protein Interaction Networks and Structure Visualization.

Science.gov (United States)

Li, Hui; Liu, Chunmei

2014-06-14

3DProIN is a computational tool to visualize protein-protein interaction networks in both two dimensional (2D) and three dimensional (3D) view. It models protein-protein interactions in a graph and explores the biologically relevant features of the tertiary structures of each protein in the network. Properties such as color, shape and name of each node (protein) of the network can be edited in either 2D or 3D views. 3DProIN is implemented using 3D Java and C programming languages. The internet crawl technique is also used to parse dynamically grasped protein interactions from protein data bank (PDB). It is a java applet component that is embedded in the web page and it can be used on different platforms including Linux, Mac and Window using web browsers such as Firefox, Internet Explorer, Chrome and Safari. It also was converted into a mac app and submitted to the App store as a free app. Mac users can also download the app from our website. 3DProIN is available for academic research at http://bicompute.appspot.com.

Structure modification and functionality of whey proteins: quantitative structure-activity relationship approach.

Science.gov (United States)

Nakai, S; Li-Chan, E

1985-10-01

According to the original idea of quantitative structure-activity relationship, electric, hydrophobic, and structural parameters should be taken into consideration for elucidating functionality. Changes in these parameters are reflected in the property of protein solubility upon modification of whey proteins by heating. Although solubility is itself a functional property, it has been utilized to explain other functionalities of proteins. However, better correlations were obtained when hydrophobic parameters of the proteins were used in conjunction with solubility. Various treatments reported in the literature were applied to whey protein concentrate in an attempt to obtain whipping and gelling properties similar to those of egg white. Mapping simplex optimization was used to search for the best results. Improvement in whipping properties by pepsin hydrolysis may have been due to higher protein solubility, and good gelling properties resulting from polyphosphate treatment may have been due to an increase in exposable hydrophobicity. However, the results of angel food cake making were still unsatisfactory.

Computational Prediction of Atomic Structures of Helical Membrane Proteins Aided by EM Maps

Science.gov (United States)

Kovacs, Julio A.; Yeager, Mark; Abagyan, Ruben

2007-01-01

Integral membrane proteins pose a major challenge for protein-structure prediction because only ≈100 high-resolution structures are available currently, thereby impeding the development of rules or empirical potentials to predict the packing of transmembrane α-helices. However, when an intermediate-resolution electron microscopy (EM) map is available, it can be used to provide restraints which, in combination with a suitable computational protocol, make structure prediction feasible. In this work we present such a protocol, which proceeds in three stages: 1), generation of an ensemble of α-helices by flexible fitting into each of the density rods in the low-resolution EM map, spanning a range of rotational angles around the main helical axes and translational shifts along the density rods; 2), fast optimization of side chains and scoring of the resulting conformations; and 3), refinement of the lowest-scoring conformations with internal coordinate mechanics, by optimizing the van der Waals, electrostatics, hydrogen bonding, torsional, and solvation energy contributions. In addition, our method implements a penalty term through a so-called tethering map, derived from the EM map, which restrains the positions of the α-helices. The protocol was validated on three test cases: GpA, KcsA, and MscL. PMID:17496035

Exploring protein dynamics space: the dynasome as the missing link between protein structure and function.

Directory of Open Access Journals (Sweden)

Ulf Hensen

Full Text Available Proteins are usually described and classified according to amino acid sequence, structure or function. Here, we develop a minimally biased scheme to compare and classify proteins according to their internal mobility patterns. This approach is based on the notion that proteins not only fold into recurring structural motifs but might also be carrying out only a limited set of recurring mobility motifs. The complete set of these patterns, which we tentatively call the dynasome, spans a multi-dimensional space with axes, the dynasome descriptors, characterizing different aspects of protein dynamics. The unique dynamic fingerprint of each protein is represented as a vector in the dynasome space. The difference between any two vectors, consequently, gives a reliable measure of the difference between the corresponding protein dynamics. We characterize the properties of the dynasome by comparing the dynamics fingerprints obtained from molecular dynamics simulations of 112 proteins but our approach is, in principle, not restricted to any specific source of data of protein dynamics. We conclude that: 1. the dynasome consists of a continuum of proteins, rather than well separated classes. 2. For the majority of proteins we observe strong correlations between structure and dynamics. 3. Proteins with similar function carry out similar dynamics, which suggests a new method to improve protein function annotation based on protein dynamics.

Chaperonin Structure - The Large Multi-Subunit Protein Complex

Directory of Open Access Journals (Sweden)

Irena Roterman

2009-03-01

Full Text Available The multi sub-unit protein structure representing the chaperonins group is analyzed with respect to its hydrophobicity distribution. The proteins of this group assist protein folding supported by ATP. The specific axial symmetry GroEL structure (two rings of seven units stacked back to back - 524 aa each and the GroES (single ring of seven units - 97 aa each polypeptide chains are analyzed using the hydrophobicity distribution expressed as excess/deficiency all over the molecule to search for structure-to-function relationships. The empirically observed distribution of hydrophobic residues is confronted with the theoretical one representing the idealized hydrophobic core with hydrophilic residues exposure on the surface. The observed discrepancy between these two distributions seems to be aim-oriented, determining the structure-to-function relation. The hydrophobic force field structure generated by the chaperonin capsule is presented. Its possible influence on substrate folding is suggested.

Optimal neural networks for protein-structure prediction

International Nuclear Information System (INIS)

Head-Gordon, T.; Stillinger, F.H.

1993-01-01

The successful application of neural-network algorithms for prediction of protein structure is stymied by three problem areas: the sparsity of the database of known protein structures, poorly devised network architectures which make the input-output mapping opaque, and a global optimization problem in the multiple-minima space of the network variables. We present a simplified polypeptide model residing in two dimensions with only two amino-acid types, A and B, which allows the determination of the global energy structure for all possible sequences of pentamer, hexamer, and heptamer lengths. This model simplicity allows us to compile a complete structural database and to devise neural networks that reproduce the tertiary structure of all sequences with absolute accuracy and with the smallest number of network variables. These optimal networks reveal that the three problem areas are convoluted, but that thoughtful network designs can actually deconvolute these detrimental traits to provide network algorithms that genuinely impact on the ability of the network to generalize or learn the desired mappings. Furthermore, the two-dimensional polypeptide model shows sufficient chemical complexity so that transfer of neural-network technology to more realistic three-dimensional proteins is evident

Crystal structure of Homo sapiens protein LOC79017

Energy Technology Data Exchange (ETDEWEB)

Bae, Euiyoung; Bingman, Craig A.; Aceti, David J.; Phillips, Jr., George N. (UW)

2010-02-08

LOC79017 (MW 21.0 kDa, residues 1-188) was annotated as a hypothetical protein encoded by Homo sapiens chromosome 7 open reading frame 24. It was selected as a target by the Center for Eukaryotic Structural Genomics (CESG) because it did not share more than 30% sequence identity with any protein for which the three-dimensional structure is known. The biological function of the protein has not been established yet. Parts of LOC79017 were identified as members of uncharacterized Pfam families (residues 1-95 as PB006073 and residues 104-180 as PB031696). BLAST searches revealed homologues of LOC79017 in many eukaryotes, but none of them have been functionally characterized. Here, we report the crystal structure of H. sapiens protein LOC79017 (UniGene code Hs.530024, UniProt code O75223, CESG target number go.35223).

Protein structure prediction using bee colony optimization metaheuristic

DEFF Research Database (Denmark)

Fonseca, Rasmus; Paluszewski, Martin; Winter, Pawel

2010-01-01

of the proteins structure, an energy potential and some optimization algorithm that ¿nds the structure with minimal energy. Bee Colony Optimization (BCO) is a relatively new approach to solving opti- mization problems based on the foraging behaviour of bees. Several variants of BCO have been suggested......Predicting the native structure of proteins is one of the most challenging problems in molecular biology. The goal is to determine the three-dimensional struc- ture from the one-dimensional amino acid sequence. De novo prediction algorithms seek to do this by developing a representation...... our BCO method to generate good solutions to the protein structure prediction problem. The results show that BCO generally ¿nds better solutions than simulated annealing which so far has been the metaheuristic of choice for this problem....

Nonlinear deterministic structures and the randomness of protein sequences

CERN Document Server

Huang Yan Zhao

2003-01-01

To clarify the randomness of protein sequences, we make a detailed analysis of a set of typical protein sequences representing each structural classes by using nonlinear prediction method. No deterministic structures are found in these protein sequences and this implies that they behave as random sequences. We also give an explanation to the controversial results obtained in previous investigations.

Integrated Structural Biology for α-Helical Membrane Protein Structure Determination.

Science.gov (United States)

Xia, Yan; Fischer, Axel W; Teixeira, Pedro; Weiner, Brian; Meiler, Jens

2018-04-03

While great progress has been made, only 10% of the nearly 1,000 integral, α-helical, multi-span membrane protein families are represented by at least one experimentally determined structure in the PDB. Previously, we developed the algorithm BCL::MP-Fold, which samples the large conformational space of membrane proteins de novo by assembling predicted secondary structure elements guided by knowledge-based potentials. Here, we present a case study of rhodopsin fold determination by integrating sparse and/or low-resolution restraints from multiple experimental techniques including electron microscopy, electron paramagnetic resonance spectroscopy, and nuclear magnetic resonance spectroscopy. Simultaneous incorporation of orthogonal experimental restraints not only significantly improved the sampling accuracy but also allowed identification of the correct fold, which is demonstrated by a protein size-normalized transmembrane root-mean-square deviation as low as 1.2 Å. The protocol developed in this case study can be used for the determination of unknown membrane protein folds when limited experimental restraints are available. Copyright © 2018 Elsevier Ltd. All rights reserved.

Fast protein tertiary structure retrieval based on global surface shape similarity.

Science.gov (United States)

Sael, Lee; Li, Bin; La, David; Fang, Yi; Ramani, Karthik; Rustamov, Raif; Kihara, Daisuke

2008-09-01

Characterization and identification of similar tertiary structure of proteins provides rich information for investigating function and evolution. The importance of structure similarity searches is increasing as structure databases continue to expand, partly due to the structural genomics projects. A crucial drawback of conventional protein structure comparison methods, which compare structures by their main-chain orientation or the spatial arrangement of secondary structure, is that a database search is too slow to be done in real-time. Here we introduce a global surface shape representation by three-dimensional (3D) Zernike descriptors, which represent a protein structure compactly as a series expansion of 3D functions. With this simplified representation, the search speed against a few thousand structures takes less than a minute. To investigate the agreement between surface representation defined by 3D Zernike descriptor and conventional main-chain based representation, a benchmark was performed against a protein classification generated by the combinatorial extension algorithm. Despite the different representation, 3D Zernike descriptor retrieved proteins of the same conformation defined by combinatorial extension in 89.6% of the cases within the top five closest structures. The real-time protein structure search by 3D Zernike descriptor will open up new possibility of large-scale global and local protein surface shape comparison. 2008 Wiley-Liss, Inc.

Bayesian comparison of protein structures using partial Procrustes distance.

Science.gov (United States)

Ejlali, Nasim; Faghihi, Mohammad Reza; Sadeghi, Mehdi

2017-09-26

An important topic in bioinformatics is the protein structure alignment. Some statistical methods have been proposed for this problem, but most of them align two protein structures based on the global geometric information without considering the effect of neighbourhood in the structures. In this paper, we provide a Bayesian model to align protein structures, by considering the effect of both local and global geometric information of protein structures. Local geometric information is incorporated to the model through the partial Procrustes distance of small substructures. These substructures are composed of β-carbon atoms from the side chains. Parameters are estimated using a Markov chain Monte Carlo (MCMC) approach. We evaluate the performance of our model through some simulation studies. Furthermore, we apply our model to a real dataset and assess the accuracy and convergence rate. Results show that our model is much more efficient than previous approaches.

Structural analysis of recombinant human protein QM

International Nuclear Information System (INIS)

Gualberto, D.C.H.; Fernandes, J.L.; Silva, F.S.; Saraiva, K.W.; Affonso, R.; Pereira, L.M.; Silva, I.D.C.G.

2012-01-01

Full text: The ribosomal protein QM belongs to a family of ribosomal proteins, which is highly conserved from yeast to humans. The presence of the QM protein is necessary for joining the 60S and 40S subunits in a late step of the initiation of mRNA translation. Although the exact extra-ribosomal functions of QM are not yet fully understood, it has been identified as a putative tumor suppressor. This protein was reported to interact with the transcription factor c-Jun and thereby prevent c-Jun actives genes of the cellular growth. In this study, the human QM protein was expressed in bacterial system, in the soluble form and this structure was analyzed by Circular Dichroism and Fluorescence. The results of Circular Dichroism showed that this protein has less alpha helix than beta sheet, as described in the literature. QM protein does not contain a leucine zipper region; however the ion zinc is necessary for binding of QM to c-Jun. Then we analyzed the relationship between the removal of zinc ions and folding of protein. Preliminary results obtained by the technique Fluorescence showed a gradual increase in fluorescence with the addition of increasing concentration of EDTA. This suggests that the zinc is important in the tertiary structure of the protein. More studies are being made for better understand these results. (author)

Utilizing knowledge base of amino acids structural neighborhoods to predict protein-protein interaction sites.

Science.gov (United States)

Jelínek, Jan; Škoda, Petr; Hoksza, David

2017-12-06

Protein-protein interactions (PPI) play a key role in an investigation of various biochemical processes, and their identification is thus of great importance. Although computational prediction of which amino acids take part in a PPI has been an active field of research for some time, the quality of in-silico methods is still far from perfect. We have developed a novel prediction method called INSPiRE which benefits from a knowledge base built from data available in Protein Data Bank. All proteins involved in PPIs were converted into labeled graphs with nodes corresponding to amino acids and edges to pairs of neighboring amino acids. A structural neighborhood of each node was then encoded into a bit string and stored in the knowledge base. When predicting PPIs, INSPiRE labels amino acids of unknown proteins as interface or non-interface based on how often their structural neighborhood appears as interface or non-interface in the knowledge base. We evaluated INSPiRE's behavior with respect to different types and sizes of the structural neighborhood. Furthermore, we examined the suitability of several different features for labeling the nodes. Our evaluations showed that INSPiRE clearly outperforms existing methods with respect to Matthews correlation coefficient. In this paper we introduce a new knowledge-based method for identification of protein-protein interaction sites called INSPiRE. Its knowledge base utilizes structural patterns of known interaction sites in the Protein Data Bank which are then used for PPI prediction. Extensive experiments on several well-established datasets show that INSPiRE significantly surpasses existing PPI approaches.

Protein structure estimation from NMR data by matrix completion.

Science.gov (United States)

Li, Zhicheng; Li, Yang; Lei, Qiang; Zhao, Qing

2017-09-01

Knowledge of protein structures is very important to understand their corresponding physical and chemical properties. Nuclear Magnetic Resonance (NMR) spectroscopy is one of the main methods to measure protein structure. In this paper, we propose a two-stage approach to calculate the structure of a protein from a highly incomplete distance matrix, where most data are obtained from NMR. We first randomly "guess" a small part of unobservable distances by utilizing the triangle inequality, which is crucial for the second stage. Then we use matrix completion to calculate the protein structure from the obtained incomplete distance matrix. We apply the accelerated proximal gradient algorithm to solve the corresponding optimization problem. Furthermore, the recovery error of our method is analyzed, and its efficiency is demonstrated by several practical examples.

NMR approaches in structure-based lead discovery: recent developments and new frontiers for targeting multi-protein complexes.

Science.gov (United States)

Dias, David M; Ciulli, Alessio

2014-01-01

Nuclear magnetic resonance (NMR) spectroscopy is a pivotal method for structure-based and fragment-based lead discovery because it is one of the most robust techniques to provide information on protein structure, dynamics and interaction at an atomic level in solution. Nowadays, in most ligand screening cascades, NMR-based methods are applied to identify and structurally validate small molecule binding. These can be high-throughput and are often used synergistically with other biophysical assays. Here, we describe current state-of-the-art in the portfolio of available NMR-based experiments that are used to aid early-stage lead discovery. We then focus on multi-protein complexes as targets and how NMR spectroscopy allows studying of interactions within the high molecular weight assemblies that make up a vast fraction of the yet untargeted proteome. Finally, we give our perspective on how currently available methods could build an improved strategy for drug discovery against such challenging targets. Copyright © 2014 The Authors. Published by Elsevier Ltd.. All rights reserved.

Mining protein loops using a structural alphabet and statistical exceptionality

Directory of Open Access Journals (Sweden)

Martin Juliette

2010-02-01

Full Text Available Abstract Background Protein loops encompass 50% of protein residues in available three-dimensional structures. These regions are often involved in protein functions, e.g. binding site, catalytic pocket... However, the description of protein loops with conventional tools is an uneasy task. Regular secondary structures, helices and strands, have been widely studied whereas loops, because they are highly variable in terms of sequence and structure, are difficult to analyze. Due to data sparsity, long loops have rarely been systematically studied. Results We developed a simple and accurate method that allows the description and analysis of the structures of short and long loops using structural motifs without restriction on loop length. This method is based on the structural alphabet HMM-SA. HMM-SA allows the simplification of a three-dimensional protein structure into a one-dimensional string of states, where each state is a four-residue prototype fragment, called structural letter. The difficult task of the structural grouping of huge data sets is thus easily accomplished by handling structural letter strings as in conventional protein sequence analysis. We systematically extracted all seven-residue fragments in a bank of 93000 protein loops and grouped them according to the structural-letter sequence, named structural word. This approach permits a systematic analysis of loops of all sizes since we consider the structural motifs of seven residues rather than complete loops. We focused the analysis on highly recurrent words of loops (observed more than 30 times. Our study reveals that 73% of loop-lengths are covered by only 3310 highly recurrent structural words out of 28274 observed words. These structural words have low structural variability (mean RMSd of 0.85 Å. As expected, half of these motifs display a flanking-region preference but interestingly, two thirds are shared by short (less than 12 residues and long loops. Moreover, half of

Mining protein loops using a structural alphabet and statistical exceptionality.

Science.gov (United States)

Regad, Leslie; Martin, Juliette; Nuel, Gregory; Camproux, Anne-Claude

2010-02-04

Protein loops encompass 50% of protein residues in available three-dimensional structures. These regions are often involved in protein functions, e.g. binding site, catalytic pocket... However, the description of protein loops with conventional tools is an uneasy task. Regular secondary structures, helices and strands, have been widely studied whereas loops, because they are highly variable in terms of sequence and structure, are difficult to analyze. Due to data sparsity, long loops have rarely been systematically studied. We developed a simple and accurate method that allows the description and analysis of the structures of short and long loops using structural motifs without restriction on loop length. This method is based on the structural alphabet HMM-SA. HMM-SA allows the simplification of a three-dimensional protein structure into a one-dimensional string of states, where each state is a four-residue prototype fragment, called structural letter. The difficult task of the structural grouping of huge data sets is thus easily accomplished by handling structural letter strings as in conventional protein sequence analysis. We systematically extracted all seven-residue fragments in a bank of 93000 protein loops and grouped them according to the structural-letter sequence, named structural word. This approach permits a systematic analysis of loops of all sizes since we consider the structural motifs of seven residues rather than complete loops. We focused the analysis on highly recurrent words of loops (observed more than 30 times). Our study reveals that 73% of loop-lengths are covered by only 3310 highly recurrent structural words out of 28274 observed words). These structural words have low structural variability (mean RMSd of 0.85 A). As expected, half of these motifs display a flanking-region preference but interestingly, two thirds are shared by short (less than 12 residues) and long loops. Moreover, half of recurrent motifs exhibit a significant level of

Combining NMR and small angle X-ray and neutron scattering in the structural analysis of a ternary protein-RNA complex

International Nuclear Information System (INIS)

Hennig, Janosch; Wang, Iren; Sonntag, Miriam; Gabel, Frank; Sattler, Michael

2013-01-01

Many processes in the regulation of gene expression and signaling involve the formation of protein complexes involving multi-domain proteins. Individual domains that mediate protein-protein and protein-nucleic acid interactions are typically connected by flexible linkers, which contribute to conformational dynamics and enable the formation of complexes with distinct binding partners. Solution techniques are therefore required for structural analysis and to characterize potential conformational dynamics. Nuclear magnetic resonance spectroscopy (NMR) provides such information but often only sparse data are obtained with increasing molecular weight of the complexes. It is therefore beneficial to combine NMR data with additional structural restraints from complementary solution techniques. Small angle X-ray/neutron scattering (SAXS/SANS) data can be efficiently combined with NMR-derived information, either for validation or by providing additional restraints for structural analysis. Here, we show that the combination of SAXS and SANS data can help to refine structural models obtained from data-driven docking using HADDOCK based on sparse NMR data. The approach is demonstrated with the ternary protein-protein-RNA complex involving two RNA recognition motif (RRM) domains of Sex-lethal, the N-terminal cold shock domain of Upstream-to-N-Ras, and msl-2 mRNA. Based on chemical shift perturbations we have mapped protein-protein and protein-RNA interfaces and complemented this NMR-derived information with SAXS data, as well as SANS measurements on subunit-selectively deuterated samples of the ternary complex. Our results show that, while the use of SAXS data is beneficial, the additional combination with contrast variation in SANS data resolves remaining ambiguities and improves the docking based on chemical shift perturbations of the ternary protein-RNA complex.

Combining NMR and small angle X-ray and neutron scattering in the structural analysis of a ternary protein-RNA complex

Energy Technology Data Exchange (ETDEWEB)

Hennig, Janosch; Wang, Iren; Sonntag, Miriam [Institute of Structural Biology, Helmholtz Zentrum Muenchen (Germany); Gabel, Frank [Extremophiles and Large Molecular Assemblies Group (ELMA), Institut de Biologie Structurale (IBS) CEA-CNRS-UJF (France); Sattler, Michael, E-mail: sattler@helmholtz-muenchen.de [Institute of Structural Biology, Helmholtz Zentrum Muenchen (Germany)

2013-05-15

Many processes in the regulation of gene expression and signaling involve the formation of protein complexes involving multi-domain proteins. Individual domains that mediate protein-protein and protein-nucleic acid interactions are typically connected by flexible linkers, which contribute to conformational dynamics and enable the formation of complexes with distinct binding partners. Solution techniques are therefore required for structural analysis and to characterize potential conformational dynamics. Nuclear magnetic resonance spectroscopy (NMR) provides such information but often only sparse data are obtained with increasing molecular weight of the complexes. It is therefore beneficial to combine NMR data with additional structural restraints from complementary solution techniques. Small angle X-ray/neutron scattering (SAXS/SANS) data can be efficiently combined with NMR-derived information, either for validation or by providing additional restraints for structural analysis. Here, we show that the combination of SAXS and SANS data can help to refine structural models obtained from data-driven docking using HADDOCK based on sparse NMR data. The approach is demonstrated with the ternary protein-protein-RNA complex involving two RNA recognition motif (RRM) domains of Sex-lethal, the N-terminal cold shock domain of Upstream-to-N-Ras, and msl-2 mRNA. Based on chemical shift perturbations we have mapped protein-protein and protein-RNA interfaces and complemented this NMR-derived information with SAXS data, as well as SANS measurements on subunit-selectively deuterated samples of the ternary complex. Our results show that, while the use of SAXS data is beneficial, the additional combination with contrast variation in SANS data resolves remaining ambiguities and improves the docking based on chemical shift perturbations of the ternary protein-RNA complex.

HDAPD: a web tool for searching the disease-associated protein structures

Science.gov (United States)

2010-01-01

Background The protein structures of the disease-associated proteins are important for proceeding with the structure-based drug design to against a particular disease. Up until now, proteins structures are usually searched through a PDB id or some sequence information. However, in the HDAPD database presented here the protein structure of a disease-associated protein can be directly searched through the associated disease name keyed in. Description The search in HDAPD can be easily initiated by keying some key words of a disease, protein name, protein type, or PDB id. The protein sequence can be presented in FASTA format and directly copied for a BLAST search. HDAPD is also interfaced with Jmol so that users can observe and operate a protein structure with Jmol. The gene ontological data such as cellular components, molecular functions, and biological processes are provided once a hyperlink to Gene Ontology (GO) is clicked. Further, HDAPD provides a link to the KEGG map such that where the protein is placed and its relationship with other proteins in a metabolic pathway can be found from the map. The latest literatures namely titles, journals, authors, and abstracts searched from PubMed for the protein are also presented as a length controllable list. Conclusions Since the HDAPD data content can be routinely updated through a PHP-MySQL web page built, the new database presented is useful for searching the structures for some disease-associated proteins that may play important roles in the disease developing process for performing the structure-based drug design to against the diseases. PMID:20158919

Combining neural networks for protein secondary structure prediction

DEFF Research Database (Denmark)

Riis, Søren Kamaric

1995-01-01

In this paper structured neural networks are applied to the problem of predicting the secondary structure of proteins. A hierarchical approach is used where specialized neural networks are designed for each structural class and then combined using another neural network. The submodels are designed...... by using a priori knowledge of the mapping between protein building blocks and the secondary structure and by using weight sharing. Since none of the individual networks have more than 600 adjustable weights over-fitting is avoided. When ensembles of specialized experts are combined the performance...

Determination of structural fluctuations of proteins from structure-based calculations of residual dipolar couplings

International Nuclear Information System (INIS)

Montalvao, Rinaldo W.; De Simone, Alfonso; Vendruscolo, Michele

2012-01-01

Residual dipolar couplings (RDCs) have the potential of providing detailed information about the conformational fluctuations of proteins. It is very challenging, however, to extract such information because of the complex relationship between RDCs and protein structures. A promising approach to decode this relationship involves structure-based calculations of the alignment tensors of protein conformations. By implementing this strategy to generate structural restraints in molecular dynamics simulations we show that it is possible to extract effectively the information provided by RDCs about the conformational fluctuations in the native states of proteins. The approach that we present can be used in a wide range of alignment media, including Pf1, charged bicelles and gels. The accuracy of the method is demonstrated by the analysis of the Q factors for RDCs not used as restraints in the calculations, which are significantly lower than those corresponding to existing high-resolution structures and structural ensembles, hence showing that we capture effectively the contributions to RDCs from conformational fluctuations.

Protein Structure Determination Using Chemical Shifts

DEFF Research Database (Denmark)

Christensen, Anders Steen

is determined using only chemical shifts recorded and assigned through automated processes. The CARMSD to the experimental X-ray for this structure is 1.1. Å. Additionally, the method is combined with very sparse NOE-restraints and evolutionary distance restraints and tested on several protein structures >100...

CATHEDRAL: a fast and effective algorithm to predict folds and domain boundaries from multidomain protein structures.

Directory of Open Access Journals (Sweden)

Oliver C Redfern

2007-11-01

Full Text Available We present CATHEDRAL, an iterative protocol for determining the location of previously observed protein folds in novel multidomain protein structures. CATHEDRAL builds on the features of a fast secondary-structure-based method (using graph theory to locate known folds within a multidomain context and a residue-based, double-dynamic programming algorithm, which is used to align members of the target fold groups against the query protein structure to identify the closest relative and assign domain boundaries. To increase the fidelity of the assignments, a support vector machine is used to provide an optimal scoring scheme. Once a domain is verified, it is excised, and the search protocol is repeated in an iterative fashion until all recognisable domains have been identified. We have performed an initial benchmark of CATHEDRAL against other publicly available structure comparison methods using a consensus dataset of domains derived from the CATH and SCOP domain classifications. CATHEDRAL shows superior performance in fold recognition and alignment accuracy when compared with many equivalent methods. If a novel multidomain structure contains a known fold, CATHEDRAL will locate it in 90% of cases, with <1% false positives. For nearly 80% of assigned domains in a manually validated test set, the boundaries were correctly delineated within a tolerance of ten residues. For the remaining cases, previously classified domains were very remotely related to the query chain so that embellishments to the core of the fold caused significant differences in domain sizes and manual refinement of the boundaries was necessary. To put this performance in context, a well-established sequence method based on hidden Markov models was only able to detect 65% of domains, with 33% of the subsequent boundaries assigned within ten residues. Since, on average, 50% of newly determined protein structures contain more than one domain unit, and typically 90% or more of these

An Algebro-Topological Description of Protein Domain Structure

Science.gov (United States)

Penner, Robert Clark; Knudsen, Michael; Wiuf, Carsten; Andersen, Jørgen Ellegaard

2011-01-01

The space of possible protein structures appears vast and continuous, and the relationship between primary, secondary and tertiary structure levels is complex. Protein structure comparison and classification is therefore a difficult but important task since structure is a determinant for molecular interaction and function. We introduce a novel mathematical abstraction based on geometric topology to describe protein domain structure. Using the locations of the backbone atoms and the hydrogen bonds, we build a combinatorial object – a so-called fatgraph. The description is discrete yet gives rise to a 2-dimensional mathematical surface. Thus, each protein domain corresponds to a particular mathematical surface with characteristic topological invariants, such as the genus (number of holes) and the number of boundary components. Both invariants are global fatgraph features reflecting the interconnectivity of the domain by hydrogen bonds. We introduce the notion of robust variables, that is variables that are robust towards minor changes in the structure/fatgraph, and show that the genus and the number of boundary components are robust. Further, we invesigate the distribution of different fatgraph variables and show how only four variables are capable of distinguishing different folds. We use local (secondary) and global (tertiary) fatgraph features to describe domain structures and illustrate that they are useful for classification of domains in CATH. In addition, we combine our method with two other methods thereby using primary, secondary, and tertiary structure information, and show that we can identify a large percentage of new and unclassified structures in CATH. PMID:21629687

Nucleotide sequence of Phaseolus vulgaris L. alcohol dehydrogenase encoding cDNA and three-dimensional structure prediction of the deduced protein.

Science.gov (United States)

Amelia, Kassim; Khor, Chin Yin; Shah, Farida Habib; Bhore, Subhash J

2015-01-01

Common beans (Phaseolus vulgaris L.) are widely consumed as a source of proteins and natural products. However, its yield needs to be increased. In line with the agenda of Phaseomics (an international consortium), work of expressed sequence tags (ESTs) generation from bean pods was initiated. Altogether, 5972 ESTs have been isolated. Alcohol dehydrogenase (AD) encoding gene cDNA was a noticeable transcript among the generated ESTs. This AD is an important enzyme; therefore, to understand more about it this study was undertaken. The objective of this study was to elucidate P. vulgaris L. AD (PvAD) gene cDNA sequence and to predict the three-dimensional (3D) structure of deduced protein. positive and negative strands of the PvAD cDNA clone were sequenced using M13 forward and M13 reverse primers to elucidate the nucleotide sequence. Deduced PvAD cDNA and protein sequence was analyzed for their basic features using online bioinformatics tools. Sequence comparison was carried out using bl2seq program, and tree-view program was used to construct a phylogenetic tree. The secondary structures and 3D structure of PvAD protein were predicted by using the PHYRE automatic fold recognition server. The sequencing results analysis showed that PvAD cDNA is 1294 bp in length. It's open reading frame encodes for a protein that contains 371 amino acids. Deduced protein sequence analysis showed the presence of putative substrate binding, catalytic Zn binding, and NAD binding sites. Results indicate that the predicted 3D structure of PvAD protein is analogous to the experimentally determined crystal structure of s-nitrosoglutathione reductase from an Arabidopsis species. The 1294 bp long PvAD cDNA encodes for 371 amino acid long protein that contains conserved domains required for biological functions of AD. The predicted deduced PvAD protein's 3D structure reflects the analogy with the crystal structure of Arabidopsis thaliana s-nitrosoglutathione reductase. Further study is required

Protein Structure Classification and Loop Modeling Using Multiple Ramachandran Distributions

KAUST Repository

Najibi, Seyed Morteza; Maadooliat, Mehdi; Zhou, Lan; Huang, Jianhua Z.; Gao, Xin

2017-01-01

Recently, the study of protein structures using angular representations has attracted much attention among structural biologists. The main challenge is how to efficiently model the continuous conformational space of the protein structures based on the differences and similarities between different Ramachandran plots. Despite the presence of statistical methods for modeling angular data of proteins, there is still a substantial need for more sophisticated and faster statistical tools to model the large-scale circular datasets. To address this need, we have developed a nonparametric method for collective estimation of multiple bivariate density functions for a collection of populations of protein backbone angles. The proposed method takes into account the circular nature of the angular data using trigonometric spline which is more efficient compared to existing methods. This collective density estimation approach is widely applicable when there is a need to estimate multiple density functions from different populations with common features. Moreover, the coefficients of adaptive basis expansion for the fitted densities provide a low-dimensional representation that is useful for visualization, clustering, and classification of the densities. The proposed method provides a novel and unique perspective to two important and challenging problems in protein structure research: structure-based protein classification and angular-sampling-based protein loop structure prediction.

Protein Structure Classification and Loop Modeling Using Multiple Ramachandran Distributions

KAUST Repository

Najibi, Seyed Morteza

2017-02-08

Recently, the study of protein structures using angular representations has attracted much attention among structural biologists. The main challenge is how to efficiently model the continuous conformational space of the protein structures based on the differences and similarities between different Ramachandran plots. Despite the presence of statistical methods for modeling angular data of proteins, there is still a substantial need for more sophisticated and faster statistical tools to model the large-scale circular datasets. To address this need, we have developed a nonparametric method for collective estimation of multiple bivariate density functions for a collection of populations of protein backbone angles. The proposed method takes into account the circular nature of the angular data using trigonometric spline which is more efficient compared to existing methods. This collective density estimation approach is widely applicable when there is a need to estimate multiple density functions from different populations with common features. Moreover, the coefficients of adaptive basis expansion for the fitted densities provide a low-dimensional representation that is useful for visualization, clustering, and classification of the densities. The proposed method provides a novel and unique perspective to two important and challenging problems in protein structure research: structure-based protein classification and angular-sampling-based protein loop structure prediction.

Density functional study of molecular interactions in secondary structures of proteins.

Science.gov (United States)

Takano, Yu; Kusaka, Ayumi; Nakamura, Haruki

2016-01-01

Proteins play diverse and vital roles in biology, which are dominated by their three-dimensional structures. The three-dimensional structure of a protein determines its functions and chemical properties. Protein secondary structures, including α-helices and β-sheets, are key components of the protein architecture. Molecular interactions, in particular hydrogen bonds, play significant roles in the formation of protein secondary structures. Precise and quantitative estimations of these interactions are required to understand the principles underlying the formation of three-dimensional protein structures. In the present study, we have investigated the molecular interactions in α-helices and β-sheets, using ab initio wave function-based methods, the Hartree-Fock method (HF) and the second-order Møller-Plesset perturbation theory (MP2), density functional theory, and molecular mechanics. The characteristic interactions essential for forming the secondary structures are discussed quantitatively.

Structure and Calcium Binding Properties of a Neuronal Calcium-Myristoyl Switch Protein, Visinin-Like Protein 3.

Science.gov (United States)

Li, Congmin; Lim, Sunghyuk; Braunewell, Karl H; Ames, James B

2016-01-01

Visinin-like protein 3 (VILIP-3) belongs to a family of Ca2+-myristoyl switch proteins that regulate signal transduction in the brain and retina. Here we analyze Ca2+ binding, characterize Ca2+-induced conformational changes, and determine the NMR structure of myristoylated VILIP-3. Three Ca2+ bind cooperatively to VILIP-3 at EF2, EF3 and EF4 (KD = 0.52 μM and Hill slope of 1.8). NMR assignments, mutagenesis and structural analysis indicate that the covalently attached myristoyl group is solvent exposed in Ca2+-bound VILIP-3, whereas Ca2+-free VILIP-3 contains a sequestered myristoyl group that interacts with protein residues (E26, Y64, V68), which are distinct from myristate contacts seen in other Ca2+-myristoyl switch proteins. The myristoyl group in VILIP-3 forms an unusual L-shaped structure that places the C14 methyl group inside a shallow protein groove, in contrast to the much deeper myristoyl binding pockets observed for recoverin, NCS-1 and GCAP1. Thus, the myristoylated VILIP-3 protein structure determined in this study is quite different from those of other known myristoyl switch proteins (recoverin, NCS-1, and GCAP1). We propose that myristoylation serves to fine tune the three-dimensional structures of neuronal calcium sensor proteins as a means of generating functional diversity.

Modeling complexes of modeled proteins.

Science.gov (United States)

Anishchenko, Ivan; Kundrotas, Petras J; Vakser, Ilya A

2017-03-01

Structural characterization of proteins is essential for understanding life processes at the molecular level. However, only a fraction of known proteins have experimentally determined structures. This fraction is even smaller for protein-protein complexes. Thus, structural modeling of protein-protein interactions (docking) primarily has to rely on modeled structures of the individual proteins, which typically are less accurate than the experimentally determined ones. Such "double" modeling is the Grand Challenge of structural reconstruction of the interactome. Yet it remains so far largely untested in a systematic way. We present a comprehensive validation of template-based and free docking on a set of 165 complexes, where each protein model has six levels of structural accuracy, from 1 to 6 Å C α RMSD. Many template-based docking predictions fall into acceptable quality category, according to the CAPRI criteria, even for highly inaccurate proteins (5-6 Å RMSD), although the number of such models (and, consequently, the docking success rate) drops significantly for models with RMSD > 4 Å. The results show that the existing docking methodologies can be successfully applied to protein models with a broad range of structural accuracy, and the template-based docking is much less sensitive to inaccuracies of protein models than the free docking. Proteins 2017; 85:470-478. © 2016 Wiley Periodicals, Inc. © 2016 Wiley Periodicals, Inc.

Lipid nanotechnologies for structural studies of membrane-associated proteins.

Science.gov (United States)

Stoilova-McPhie, Svetla; Grushin, Kirill; Dalm, Daniela; Miller, Jaimy

2014-11-01

We present a methodology of lipid nanotubes (LNT) and nanodisks technologies optimized in our laboratory for structural studies of membrane-associated proteins at close to physiological conditions. The application of these lipid nanotechnologies for structure determination by cryo-electron microscopy (cryo-EM) is fundamental for understanding and modulating their function. The LNTs in our studies are single bilayer galactosylceramide based nanotubes of ∼20 nm inner diameter and a few microns in length, that self-assemble in aqueous solutions. The lipid nanodisks (NDs) are self-assembled discoid lipid bilayers of ∼10 nm diameter, which are stabilized in aqueous solutions by a belt of amphipathic helical scaffold proteins. By combining LNT and ND technologies, we can examine structurally how the membrane curvature and lipid composition modulates the function of the membrane-associated proteins. As proof of principle, we have engineered these lipid nanotechnologies to mimic the activated platelet's phosphtaidylserine rich membrane and have successfully assembled functional membrane-bound coagulation factor VIII in vitro for structure determination by cryo-EM. The macromolecular organization of the proteins bound to ND and LNT are further defined by fitting the known atomic structures within the calculated three-dimensional maps. The combination of LNT and ND technologies offers a means to control the design and assembly of a wide range of functional membrane-associated proteins and complexes for structural studies by cryo-EM. The presented results confirm the suitability of the developed methodology for studying the functional structure of membrane-associated proteins, such as the coagulation factors, at a close to physiological environment. © 2014 Wiley Periodicals, Inc.

Effects of NMR spectral resolution on protein structure calculation.

Directory of Open Access Journals (Sweden)

Suhas Tikole

Full Text Available Adequate digital resolution and signal sensitivity are two critical factors for protein structure determinations by solution NMR spectroscopy. The prime objective for obtaining high digital resolution is to resolve peak overlap, especially in NOESY spectra with thousands of signals where the signal analysis needs to be performed on a large scale. Achieving maximum digital resolution is usually limited by the practically available measurement time. We developed a method utilizing non-uniform sampling for balancing digital resolution and signal sensitivity, and performed a large-scale analysis of the effect of the digital resolution on the accuracy of the resulting protein structures. Structure calculations were performed as a function of digital resolution for about 400 proteins with molecular sizes ranging between 5 and 33 kDa. The structural accuracy was assessed by atomic coordinate RMSD values from the reference structures of the proteins. In addition, we monitored also the number of assigned NOESY cross peaks, the average signal sensitivity, and the chemical shift spectral overlap. We show that high resolution is equally important for proteins of every molecular size. The chemical shift spectral overlap depends strongly on the corresponding spectral digital resolution. Thus, knowing the extent of overlap can be a predictor of the resulting structural accuracy. Our results show that for every molecular size a minimal digital resolution, corresponding to the natural linewidth, needs to be achieved for obtaining the highest accuracy possible for the given protein size using state-of-the-art automated NOESY assignment and structure calculation methods.

Chemical cross-linking and mass spectrometry for protein structural modeling

NARCIS (Netherlands)

Back, Jaap Willem; de Jong, Luitzen; Muijsers, Anton O.; de Koster, Chris G.

2003-01-01

The growth of gene and protein sequence information is currently so rapid that three-dimensional structural information is lacking for the overwhelming majority of known proteins. In this review, efforts towards rapid and sensitive methods for protein structural characterization are described,

Analyzing the simplicial decomposition of spatial protein structures

Directory of Open Access Journals (Sweden)

Szabadka Zoltán

2008-02-01

Full Text Available Abstract Background The fast growing Protein Data Bank contains the three-dimensional description of more than 45000 protein- and nucleic-acid structures today. The large majority of the data in the PDB are measured by X-ray crystallography by thousands of researchers in millions of work-hours. Unfortunately, lots of structural errors, bad labels, missing atoms, falsely identified chains and groups make dificult the automated processing of this treasury of structural biological data. Results After we performed a rigorous re-structuring of the whole PDB on graph-theoretical basis, we created the RS-PDB (Rich-Structure PDB database. Using this cleaned and repaired database, we defined simplicial complexes on the heavy-atoms of the PDB, and analyzed the tetrahedra for geometric properties. Conclusion We have found surprisingly characteristic differences between simplices with atomic vertices of different types, and between the atomic neighborhoods – described also by simplices – of different ligand atoms in proteins.

A Structural Perspective on the Modulation of Protein-Protein Interactions with Small Molecules.

Science.gov (United States)

Demirel, Habibe Cansu; Dogan, Tunca; Tuncbag, Nurcan

2018-05-31

Protein-protein interactions (PPIs) are the key components in many cellular processes including signaling pathways, enzymatic reactions and epigenetic regulation. Abnormal interactions of some proteins may be pathogenic and cause various disorders including cancer and neurodegenerative diseases. Although inhibiting PPIs with small molecules is a challenging task, it gained an increasing interest because of its strong potential for drug discovery and design. The knowledge of the interface as well as the structural and chemical characteristics of the PPIs and their roles in the cellular pathways are necessary for a rational design of small molecules to modulate PPIs. In this study, we review the recent progress in the field and detail the physicochemical properties of PPIs including binding hot spots with a focus on structural methods. Then, we review recent approaches for structural prediction of PPIs. Finally, we revisit the concept of targeting PPIs in a systems biology perspective and we refer to the non-structural approaches, usually employed when the structural information is not present. Copyright© Bentham Science Publishers; For any queries, please email at epub@benthamscience.org.

Sequential Release of Proteins from Structured Multishell Microcapsules.

Science.gov (United States)

Shimanovich, Ulyana; Michaels, Thomas C T; De Genst, Erwin; Matak-Vinkovic, Dijana; Dobson, Christopher M; Knowles, Tuomas P J

2017-10-09

In nature, a wide range of functional materials is based on proteins. Increasing attention is also turning to the use of proteins as artificial biomaterials in the form of films, gels, particles, and fibrils that offer great potential for applications in areas ranging from molecular medicine to materials science. To date, however, most such applications have been limited to single component materials despite the fact that their natural analogues are composed of multiple types of proteins with a variety of functionalities that are coassembled in a highly organized manner on the micrometer scale, a process that is currently challenging to achieve in the laboratory. Here, we demonstrate the fabrication of multicomponent protein microcapsules where the different components are positioned in a controlled manner. We use molecular self-assembly to generate multicomponent structures on the nanometer scale and droplet microfluidics to bring together the different components on the micrometer scale. Using this approach, we synthesize a wide range of multiprotein microcapsules containing three well-characterized proteins: glucagon, insulin, and lysozyme. The localization of each protein component in multishell microcapsules has been detected by labeling protein molecules with different fluorophores, and the final three-dimensional microcapsule structure has been resolved by using confocal microscopy together with image analysis techniques. In addition, we show that these structures can be used to tailor the release of such functional proteins in a sequential manner. Moreover, our observations demonstrate that the protein release mechanism from multishell capsules is driven by the kinetic control of mass transport of the cargo and by the dissolution of the shells. The ability to generate artificial materials that incorporate a variety of different proteins with distinct functionalities increases the breadth of the potential applications of artificial protein-based materials

EVA: continuous automatic evaluation of protein structure prediction servers.

Science.gov (United States)

Eyrich, V A; Martí-Renom, M A; Przybylski, D; Madhusudhan, M S; Fiser, A; Pazos, F; Valencia, A; Sali, A; Rost, B

2001-12-01

Evaluation of protein structure prediction methods is difficult and time-consuming. Here, we describe EVA, a web server for assessing protein structure prediction methods, in an automated, continuous and large-scale fashion. Currently, EVA evaluates the performance of a variety of prediction methods available through the internet. Every week, the sequences of the latest experimentally determined protein structures are sent to prediction servers, results are collected, performance is evaluated, and a summary is published on the web. EVA has so far collected data for more than 3000 protein chains. These results may provide valuable insight to both developers and users of prediction methods. http://cubic.bioc.columbia.edu/eva. eva@cubic.bioc.columbia.edu

G-LoSA for Prediction of Protein-Ligand Binding Sites and Structures.

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Lee, Hui Sun; Im, Wonpil

2017-01-01

Recent advances in high-throughput structure determination and computational protein structure prediction have significantly enriched the universe of protein structure. However, there is still a large gap between the number of available protein structures and that of proteins with annotated function in high accuracy. Computational structure-based protein function prediction has emerged to reduce this knowledge gap. The identification of a ligand binding site and its structure is critical to the determination of a protein's molecular function. We present a computational methodology for predicting small molecule ligand binding site and ligand structure using G-LoSA, our protein local structure alignment and similarity measurement tool. All the computational procedures described here can be easily implemented using G-LoSA Toolkit, a package of standalone software programs and preprocessed PDB structure libraries. G-LoSA and G-LoSA Toolkit are freely available to academic users at http://compbio.lehigh.edu/GLoSA . We also illustrate a case study to show the potential of our template-based approach harnessing G-LoSA for protein function prediction.

Overcoming barriers to membrane protein structure determination

NARCIS (Netherlands)

Bill, Roslyn M.; Henderson, Peter J. F.; Iwata, So; Kunji, Edmund R. S.; Michel, Hartmut; Neutze, Richard; Newstead, Simon; Poolman, Bert; Tate, Christopher G.; Vogel, Horst

After decades of slow progress, the pace of research on membrane protein structures is beginning to quicken thanks to various improvements in technology, including protein engineering and microfocus X-ray diffraction. Here we review these developments and, where possible, highlight generic new

De novo protein structure generation from incomplete chemical shift assignments

Energy Technology Data Exchange (ETDEWEB)

Shen Yang [National Institutes of Health, Laboratory of Chemical Physics, National Institute of Diabetes and Digestive and Kidney Diseases (United States); Vernon, Robert; Baker, David [University of Washington, Department of Biochemistry and Howard Hughes Medical Institute (United States); Bax, Ad [National Institutes of Health, Laboratory of Chemical Physics, National Institute of Diabetes and Digestive and Kidney Diseases (United States)], E-mail: bax@nih.gov

2009-02-15

NMR chemical shifts provide important local structural information for proteins. Consistent structure generation from NMR chemical shift data has recently become feasible for proteins with sizes of up to 130 residues, and such structures are of a quality comparable to those obtained with the standard NMR protocol. This study investigates the influence of the completeness of chemical shift assignments on structures generated from chemical shifts. The Chemical-Shift-Rosetta (CS-Rosetta) protocol was used for de novo protein structure generation with various degrees of completeness of the chemical shift assignment, simulated by omission of entries in the experimental chemical shift data previously used for the initial demonstration of the CS-Rosetta approach. In addition, a new CS-Rosetta protocol is described that improves robustness of the method for proteins with missing or erroneous NMR chemical shift input data. This strategy, which uses traditional Rosetta for pre-filtering of the fragment selection process, is demonstrated for two paramagnetic proteins and also for two proteins with solid-state NMR chemical shift assignments.

The Selective Mutism Questionnaire: Measurement Structure and Validity

Science.gov (United States)

Letamendi, Andrea M.; Chavira, Denise A.; Hitchcock, Carla A.; Roesch, Scott C.; Shipon-Blum, Elisa; Stein, Murray B.; Roesch, Scott C.

2010-01-01

Objective To evaluate the factor structure, reliability, and validity of the 17-item Selective Mutism Questionnaire. Method Diagnostic interviews were administered via telephone to 102 parents of children identified with selective mutism (SM) and 43 parents of children without SM from varying U.S. geographic regions. Children were between the ages of 3 and 11 inclusive and comprised 58% girls and 42% boys. SM diagnoses were determined using the Anxiety Disorders Interview Schedule for Children - Parent Version (ADIS-C/P); SM severity was assessed using the 17-item Selective Mutism Questionnaire (SMQ); and behavioral and affective symptoms were assessed using the Child Behavior Checklist (CBCL). An exploratory factor analysis (EFA) was conducted to investigate the dimensionality of the SMQ and a modified parallel analysis procedure was used to confirm EFA results. Internal consistency, construct validity, and incremental validity were also examined. Results The EFA yielded a 13-item solution consisting of three factors: a) Social Situations Outside of School, b) School Situations, and c) Home and Family Situations. Internal consistency of SMQ factors and total scale ranged from moderate to high. Convergent and incremental validity were also well supported. Conclusions Measure structure findings are consistent with the 3-factor solution found in a previous psychometric evaluation of the SMQ. Results also suggest that the SMQ provides useful and unique information in the prediction of SM phenomenon beyond other child anxiety measures. PMID:18698268

MolTalk – a programming library for protein structures and structure analysis

Science.gov (United States)

Diemand, Alexander V; Scheib, Holger

2004-01-01

Background Two of the mostly unsolved but increasingly urgent problems for modern biologists are a) to quickly and easily analyse protein structures and b) to comprehensively mine the wealth of information, which is distributed along with the 3D co-ordinates by the Protein Data Bank (PDB). Tools which address this issue need to be highly flexible and powerful but at the same time must be freely available and easy to learn. Results We present MolTalk, an elaborate programming language, which consists of the programming library libmoltalk implemented in Objective-C and the Smalltalk-based interpreter MolTalk. MolTalk combines the advantages of an easy to learn and programmable procedural scripting with the flexibility and power of a full programming language. An overview of currently available applications of MolTalk is given and with PDBChainSaw one such application is described in more detail. PDBChainSaw is a MolTalk-based parser and information extraction utility of PDB files. Weekly updates of the PDB are synchronised with PDBChainSaw and are available for free download from the MolTalk project page following the link to PDBChainSaw. For each chain in a protein structure, PDBChainSaw extracts the sequence from its co-ordinates and provides additional information from the PDB-file header section, such as scientific organism, compound name, and EC code. Conclusion MolTalk provides a rich set of methods to analyse and even modify experimentally determined or modelled protein structures. These methods vary in complexity and are thus suitable for beginners and advanced programmers alike. We envision MolTalk to be most valuable in the following applications: 1) To analyse protein structures repetitively in large-scale, i.e. to benchmark protein structure prediction methods or to evaluate structural models. The quality of the resulting 3D-models can be assessed by e.g. calculating a Ramachandran-Sasisekharan plot. 2) To quickly retrieve information for (a limited

MolTalk – a programming library for protein structures and structure analysis

Directory of Open Access Journals (Sweden)

Diemand Alexander V

2004-04-01

Full Text Available Abstract Background Two of the mostly unsolved but increasingly urgent problems for modern biologists are a to quickly and easily analyse protein structures and b to comprehensively mine the wealth of information, which is distributed along with the 3D co-ordinates by the Protein Data Bank (PDB. Tools which address this issue need to be highly flexible and powerful but at the same time must be freely available and easy to learn. Results We present MolTalk, an elaborate programming language, which consists of the programming library libmoltalk implemented in Objective-C and the Smalltalk-based interpreter MolTalk. MolTalk combines the advantages of an easy to learn and programmable procedural scripting with the flexibility and power of a full programming language. An overview of currently available applications of MolTalk is given and with PDBChainSaw one such application is described in more detail. PDBChainSaw is a MolTalk-based parser and information extraction utility of PDB files. Weekly updates of the PDB are synchronised with PDBChainSaw and are available for free download from the MolTalk project page http://www.moltalk.org following the link to PDBChainSaw. For each chain in a protein structure, PDBChainSaw extracts the sequence from its co-ordinates and provides additional information from the PDB-file header section, such as scientific organism, compound name, and EC code. Conclusion MolTalk provides a rich set of methods to analyse and even modify experimentally determined or modelled protein structures. These methods vary in complexity and are thus suitable for beginners and advanced programmers alike. We envision MolTalk to be most valuable in the following applications: 1 To analyse protein structures repetitively in large-scale, i.e. to benchmark protein structure prediction methods or to evaluate structural models. The quality of the resulting 3D-models can be assessed by e.g. calculating a Ramachandran-Sasisekharan plot. 2 To

Soliton concepts and protein structure

Science.gov (United States)

Krokhotin, Andrei; Niemi, Antti J.; Peng, Xubiao

2012-03-01

Structural classification shows that the number of different protein folds is surprisingly small. It also appears that proteins are built in a modular fashion from a relatively small number of components. Here we propose that the modular building blocks are made of the dark soliton solution of a generalized discrete nonlinear Schrödinger equation. We find that practically all protein loops can be obtained simply by scaling the size and by joining together a number of copies of the soliton, one after another. The soliton has only two loop-specific parameters, and we compute their statistical distribution in the Protein Data Bank (PDB). We explicitly construct a collection of 200 sets of parameters, each determining a soliton profile that describes a different short loop. The ensuing profiles cover practically all those proteins in PDB that have a resolution which is better than 2.0 Å, with a precision such that the average root-mean-square distance between the loop and its soliton is less than the experimental B-factor fluctuation distance. We also present two examples that describe how the loop library can be employed both to model and to analyze folded proteins.

NMR structure of the protein NP-247299.1: comparison with the crystal structure

International Nuclear Information System (INIS)

Jaudzems, Kristaps; Geralt, Michael; Serrano, Pedro; Mohanty, Biswaranjan; Horst, Reto; Pedrini, Bill; Elsliger, Marc-André; Wilson, Ian A.; Wüthrich, Kurt

2010-01-01

Comparison of the NMR and crystal structures of a protein determined using largely automated methods has enabled the interpretation of local differences in the highly similar structures. These differences are found in segments of higher B values in the crystal and correlate with dynamic processes on the NMR chemical shift timescale observed in solution. The NMR structure of the protein NP-247299.1 in solution at 313 K has been determined and is compared with the X-ray crystal structure, which was also solved in the Joint Center for Structural Genomics (JCSG) at 100 K and at 1.7 Å resolution. Both structures were obtained using the current largely automated crystallographic and solution NMR methods used by the JCSG. This paper assesses the accuracy and precision of the results from these recently established automated approaches, aiming for quantitative statements about the location of structure variations that may arise from either one of the methods used or from the different environments in solution and in the crystal. To evaluate the possible impact of the different software used for the crystallographic and the NMR structure determinations and analysis, the concept is introduced of reference structures, which are computed using the NMR software with input of upper-limit distance constraints derived from the molecular models representing the results of the two structure determinations. The use of this new approach is explored to quantify global differences that arise from the different methods of structure determination and analysis versus those that represent interesting local variations or dynamics. The near-identity of the protein core in the NMR and crystal structures thus provided a basis for the identification of complementary information from the two different methods. It was thus observed that locally increased crystallographic B values correlate with dynamic structural polymorphisms in solution, including that the solution state of the protein involves

Structural entanglements in protein complexes

Science.gov (United States)

Zhao, Yani; Chwastyk, Mateusz; Cieplak, Marek

2017-06-01

We consider multi-chain protein native structures and propose a criterion that determines whether two chains in the system are entangled or not. The criterion is based on the behavior observed by pulling at both termini of each chain simultaneously in the two chains. We have identified about 900 entangled systems in the Protein Data Bank and provided a more detailed analysis for several of them. We argue that entanglement enhances the thermodynamic stability of the system but it may have other functions: burying the hydrophobic residues at the interface and increasing the DNA or RNA binding area. We also study the folding and stretching properties of the knotted dimeric proteins MJ0366, YibK, and bacteriophytochrome. These proteins have been studied theoretically in their monomeric versions so far. The dimers are seen to separate on stretching through the tensile mechanism and the characteristic unraveling force depends on the pulling direction.

Yellow fluorescent protein phiYFPv (Phialidium): structure and structure-based mutagenesis

Energy Technology Data Exchange (ETDEWEB)

Pletneva, Nadya V.; Pletnev, Vladimir Z., E-mail: vzpletnev@gmail.com; Souslova, Ekaterina; Chudakov, Dmitry M. [Russian Academy of Sciences, Moscow (Russian Federation); Lukyanov, Sergey [Russian Academy of Sciences, Moscow (Russian Federation); Nizhny Novgorod State Medical Academy, Nizhny Novgorod (Russian Federation); Martynov, Vladimir I.; Arhipova, Svetlena; Artemyev, Igor [Russian Academy of Sciences, Moscow (Russian Federation); Wlodawer, Alexander [National Cancer Institute, Frederick, MD 21702 (United States); Dauter, Zbigniew [National Cancer Institute, Argonne, IL 60439 (United States); Pletnev, Sergei [National Cancer Institute, Argonne, IL 60439 (United States); SAIC-Frederick, 9700 South Cass Avenue, Argonne, IL 60439 (United States); Russian Academy of Sciences, Moscow (Russian Federation)

2013-06-01

The yellow fluorescent protein phiYFPv with improved folding has been developed from the spectrally identical wild-type phiYFP found in the marine jellyfish Phialidium. The yellow fluorescent protein phiYFPv (λ{sub em}{sup max} ≃ 537 nm) with improved folding has been developed from the spectrally identical wild-type phiYFP found in the marine jellyfish Phialidium. The latter fluorescent protein is one of only two known cases of naturally occurring proteins that exhibit emission spectra in the yellow–orange range (535–555 nm). Here, the crystal structure of phiYFPv has been determined at 2.05 Å resolution. The ‘yellow’ chromophore formed from the sequence triad Thr65-Tyr66-Gly67 adopts the bicyclic structure typical of fluorophores emitting in the green spectral range. It was demonstrated that perfect antiparallel π-stacking of chromophore Tyr66 and the proximal Tyr203, as well as Val205, facing the chromophore phenolic ring are chiefly responsible for the observed yellow emission of phiYFPv at 537 nm. Structure-based site-directed mutagenesis has been used to identify the key functional residues in the chromophore environment. The obtained results have been utilized to improve the properties of phiYFPv and its homologous monomeric biomarker tagYFP.

Structure-sequence based analysis for identification of conserved regions in proteins

Science.gov (United States)

Zemla, Adam T; Zhou, Carol E; Lam, Marisa W; Smith, Jason R; Pardes, Elizabeth

2013-05-28

Disclosed are computational methods, and associated hardware and software products for scoring conservation in a protein structure based on a computationally identified family or cluster of protein structures. A method of computationally identifying a family or cluster of protein structures in also disclosed herein.

Can Natural Proteins Designed with ‘Inverted’ Peptide Sequences Adopt Native-Like Protein Folds?

Science.gov (United States)

Sridhar, Settu; Guruprasad, Kunchur

2014-01-01

We have carried out a systematic computational analysis on a representative dataset of proteins of known three-dimensional structure, in order to evaluate whether it would possible to ‘swap’ certain short peptide sequences in naturally occurring proteins with their corresponding ‘inverted’ peptides and generate ‘artificial’ proteins that are predicted to retain native-like protein fold. The analysis of 3,967 representative proteins from the Protein Data Bank revealed 102,677 unique identical inverted peptide sequence pairs that vary in sequence length between 5–12 and 18 amino acid residues. Our analysis illustrates with examples that such ‘artificial’ proteins may be generated by identifying peptides with ‘similar structural environment’ and by using comparative protein modeling and validation studies. Our analysis suggests that natural proteins may be tolerant to accommodating such peptides. PMID:25210740

Protein Secondary Structure Prediction Using Deep Convolutional Neural Fields.

Science.gov (United States)

Wang, Sheng; Peng, Jian; Ma, Jianzhu; Xu, Jinbo

2016-01-11

Protein secondary structure (SS) prediction is important for studying protein structure and function. When only the sequence (profile) information is used as input feature, currently the best predictors can obtain ~80% Q3 accuracy, which has not been improved in the past decade. Here we present DeepCNF (Deep Convolutional Neural Fields) for protein SS prediction. DeepCNF is a Deep Learning extension of Conditional Neural Fields (CNF), which is an integration of Conditional Random Fields (CRF) and shallow neural networks. DeepCNF can model not only complex sequence-structure relationship by a deep hierarchical architecture, but also interdependency between adjacent SS labels, so it is much more powerful than CNF. Experimental results show that DeepCNF can obtain ~84% Q3 accuracy, ~85% SOV score, and ~72% Q8 accuracy, respectively, on the CASP and CAMEO test proteins, greatly outperforming currently popular predictors. As a general framework, DeepCNF can be used to predict other protein structure properties such as contact number, disorder regions, and solvent accessibility.

G-protein-coupled receptor structures were not built in a day.

Science.gov (United States)

Blois, Tracy M; Bowie, James U

2009-07-01

Among the most exciting recent developments in structural biology is the structure determination of G-protein-coupled receptors (GPCRs), which comprise the largest class of membrane proteins in mammalian cells and have enormous importance for disease and drug development. The GPCR structures are perhaps the most visible examples of a nascent revolution in membrane protein structure determination. Like other major milestones in science, however, such as the sequencing of the human genome, these achievements were built on a hidden foundation of technological developments. Here, we describe some of the methods that are fueling the membrane protein structure revolution and have enabled the determination of the current GPCR structures, along with new techniques that may lead to future structures.

Structure and assembly of scalable porous protein cages

Science.gov (United States)

Sasaki, Eita; Böhringer, Daniel; van de Waterbeemd, Michiel; Leibundgut, Marc; Zschoche, Reinhard; Heck, Albert J. R.; Ban, Nenad; Hilvert, Donald

2017-03-01

Proteins that self-assemble into regular shell-like polyhedra are useful, both in nature and in the laboratory, as molecular containers. Here we describe cryo-electron microscopy (EM) structures of two versatile encapsulation systems that exploit engineered electrostatic interactions for cargo loading. We show that increasing the number of negative charges on the lumenal surface of lumazine synthase, a protein that naturally assembles into a ~1-MDa dodecahedron composed of 12 pentamers, induces stepwise expansion of the native protein shell, giving rise to thermostable ~3-MDa and ~6-MDa assemblies containing 180 and 360 subunits, respectively. Remarkably, these expanded particles assume unprecedented tetrahedrally and icosahedrally symmetric structures constructed entirely from pentameric units. Large keyhole-shaped pores in the shell, not present in the wild-type capsid, enable diffusion-limited encapsulation of complementarily charged guests. The structures of these supercharged assemblies demonstrate how programmed electrostatic effects can be effectively harnessed to tailor the architecture and properties of protein cages.

Structural Basis for the Interaction of the Golgi-Associated Retrograde Protein (GARP) Complex with the t-SNARE Syntaxin 6

Science.gov (United States)

Abascal-Palacios, Guillermo; Schindler, Christina; Rojas, Adriana L; Bonifacino, Juan S.; Hierro, Aitor

2016-01-01

Summary The Golgi-Associated Retrograde Protein (GARP) is a tethering complex involved in the fusion of endosome-derived transport vesicles to the trans-Golgi network through interaction with components of the Syntaxin 6/Syntaxin 16/Vti1a/VAMP4 SNARE complex. The mechanisms by which GARP and other tethering factors engage the SNARE fusion machinery are poorly understood. Herein we report the structural basis for the interaction of the human Ang2 subunit of GARP with Syntaxin 6 and the closely related Syntaxin 10. The crystal structure of Syntaxin 6 Habc domain in complex with a peptide from the N terminus of Ang2 shows a novel binding mode in which a di-tyrosine motif of Ang2 interacts with a highly conserved groove in Syntaxin 6. Structure-based mutational analyses validate the crystal structure and support the phylogenetic conservation of this interaction. The same binding determinants are found in other tethering proteins and syntaxins, suggesting a general interaction mechanism. PMID:23932592

Ab initio protein structure assembly using continuous structure fragments and optimized knowledge-based force field.

Science.gov (United States)

Xu, Dong; Zhang, Yang

2012-07-01

Ab initio protein folding is one of the major unsolved problems in computational biology owing to the difficulties in force field design and conformational search. We developed a novel program, QUARK, for template-free protein structure prediction. Query sequences are first broken into fragments of 1-20 residues where multiple fragment structures are retrieved at each position from unrelated experimental structures. Full-length structure models are then assembled from fragments using replica-exchange Monte Carlo simulations, which are guided by a composite knowledge-based force field. A number of novel energy terms and Monte Carlo movements are introduced and the particular contributions to enhancing the efficiency of both force field and search engine are analyzed in detail. QUARK prediction procedure is depicted and tested on the structure modeling of 145 nonhomologous proteins. Although no global templates are used and all fragments from experimental structures with template modeling score >0.5 are excluded, QUARK can successfully construct 3D models of correct folds in one-third cases of short proteins up to 100 residues. In the ninth community-wide Critical Assessment of protein Structure Prediction experiment, QUARK server outperformed the second and third best servers by 18 and 47% based on the cumulative Z-score of global distance test-total scores in the FM category. Although ab initio protein folding remains a significant challenge, these data demonstrate new progress toward the solution of the most important problem in the field. Copyright © 2012 Wiley Periodicals, Inc.

VoroMQA: Assessment of protein structure quality using interatomic contact areas.

Science.gov (United States)

Olechnovič, Kliment; Venclovas, Česlovas

2017-06-01

In the absence of experimentally determined protein structure many biological questions can be addressed using computational structural models. However, the utility of protein structural models depends on their quality. Therefore, the estimation of the quality of predicted structures is an important problem. One of the approaches to this problem is the use of knowledge-based statistical potentials. Such methods typically rely on the statistics of distances and angles of residue-residue or atom-atom interactions collected from experimentally determined structures. Here, we present VoroMQA (Voronoi tessellation-based Model Quality Assessment), a new method for the estimation of protein structure quality. Our method combines the idea of statistical potentials with the use of interatomic contact areas instead of distances. Contact areas, derived using Voronoi tessellation of protein structure, are used to describe and seamlessly integrate both explicit interactions between protein atoms and implicit interactions of protein atoms with solvent. VoroMQA produces scores at atomic, residue, and global levels, all in the fixed range from 0 to 1. The method was tested on the CASP data and compared to several other single-model quality assessment methods. VoroMQA showed strong performance in the recognition of the native structure and in the structural model selection tests, thus demonstrating the efficacy of interatomic contact areas in estimating protein structure quality. The software implementation of VoroMQA is freely available as a standalone application and as a web server at http://bioinformatics.lt/software/voromqa. Proteins 2017; 85:1131-1145. © 2017 Wiley Periodicals, Inc. © 2017 Wiley Periodicals, Inc.

Phylogenetic continuum indicates "galaxies" in the protein universe: preliminary results on the natural group structures of proteins.

Science.gov (United States)

Ladunga, I

1992-04-01

The markedly nonuniform, even systematic distribution of sequences in the protein "universe" has been analyzed by methods of protein taxonomy. Mapping of the natural hierarchical system of proteins has revealed some dense cores, i.e., well-defined clusterings of proteins that seem to be natural structural groupings, possibly seeds for a future protein taxonomy. The aim was not to force proteins into more or less man-made categories by discriminant analysis, but to find structurally similar groups, possibly of common evolutionary origin. Single-valued distance measures between pairs of superfamilies from the Protein Identification Resource were defined by two chi 2-like methods on tripeptide frequencies and the variable-length subsequence identity method derived from dot-matrix comparisons. Distance matrices were processed by several methods of cluster analysis to detect phylogenetic continuum between highly divergent proteins. Only well-defined clusters characterized by relatively unique structural, intracellular environmental, organismal, and functional attribute states were selected as major protein groups, including subsets of viral and Escherichia coli proteins, hormones, inhibitors, plant, ribosomal, serum and structural proteins, amino acid synthases, and clusters dominated by certain oxidoreductases and apolar and DNA-associated enzymes. The limited repertoire of functional patterns due to small genome size, the high rate of recombination, specific features of the bacterial membranes, or of the virus cycle canalize certain proteins of viruses and Gram-negative bacteria, respectively, to organismal groups.

Structural basis of protein oxidation resistance: a lysozyme study.

Directory of Open Access Journals (Sweden)

Marion Girod

Full Text Available Accumulation of oxidative damage in proteins correlates with aging since it can cause irreversible and progressive degeneration of almost all cellular functions. Apparently, native protein structures have evolved intrinsic resistance to oxidation since perfectly folded proteins are, by large most robust. Here we explore the structural basis of protein resistance to radiation-induced oxidation using chicken egg white lysozyme in the native and misfolded form. We study the differential resistance to oxidative damage of six different parts of native and misfolded lysozyme by a targeted tandem/mass spectrometry approach of its tryptic fragments. The decay of the amount of each lysozyme fragment with increasing radiation dose is found to be a two steps process, characterized by a double exponential evolution of their amounts: the first one can be largely attributed to oxidation of specific amino acids, while the second one corresponds to further degradation of the protein. By correlating these results to the structural parameters computed from molecular dynamics (MD simulations, we find the protein parts with increased root-mean-square deviation (RMSD to be more susceptible to modifications. In addition, involvement of amino acid side-chains in hydrogen bonds has a protective effect against oxidation Increased exposure to solvent of individual amino acid side chains correlates with high susceptibility to oxidative and other modifications like side chain fragmentation. Generally, while none of the structural parameters alone can account for the fate of peptides during radiation, together they provide an insight into the relationship between protein structure and susceptibility to oxidation.

Protein structure based prediction of catalytic residues.

Science.gov (United States)

Fajardo, J Eduardo; Fiser, Andras

2013-02-22

Worldwide structural genomics projects continue to release new protein structures at an unprecedented pace, so far nearly 6000, but only about 60% of these proteins have any sort of functional annotation. We explored a range of features that can be used for the prediction of functional residues given a known three-dimensional structure. These features include various centrality measures of nodes in graphs of interacting residues: closeness, betweenness and page-rank centrality. We also analyzed the distance of functional amino acids to the general center of mass (GCM) of the structure, relative solvent accessibility (RSA), and the use of relative entropy as a measure of sequence conservation. From the selected features, neural networks were trained to identify catalytic residues. We found that using distance to the GCM together with amino acid type provide a good discriminant function, when combined independently with sequence conservation. Using an independent test set of 29 annotated protein structures, the method returned 411 of the initial 9262 residues as the most likely to be involved in function. The output 411 residues contain 70 of the annotated 111 catalytic residues. This represents an approximately 14-fold enrichment of catalytic residues on the entire input set (corresponding to a sensitivity of 63% and a precision of 17%), a performance competitive with that of other state-of-the-art methods. We found that several of the graph based measures utilize the same underlying feature of protein structures, which can be simply and more effectively captured with the distance to GCM definition. This also has the added the advantage of simplicity and easy implementation. Meanwhile sequence conservation remains by far the most influential feature in identifying functional residues. We also found that due the rapid changes in size and composition of sequence databases, conservation calculations must be recalibrated for specific reference databases.

Crystal structure of human protein kinase CK2

DEFF Research Database (Denmark)

Niefind, K; Guerra, B; Ermakowa, I

2001-01-01

The crystal structure of a fully active form of human protein kinase CK2 (casein kinase 2) consisting of two C-terminally truncated catalytic and two regulatory subunits has been determined at 3.1 A resolution. In the CK2 complex the regulatory subunits form a stable dimer linking the two catalyt...... as a docking partner for various protein kinases. Furthermore it shows an inter-domain mobility in the catalytic subunit known to be functionally important in protein kinases and detected here for the first time directly within one crystal structure.......The crystal structure of a fully active form of human protein kinase CK2 (casein kinase 2) consisting of two C-terminally truncated catalytic and two regulatory subunits has been determined at 3.1 A resolution. In the CK2 complex the regulatory subunits form a stable dimer linking the two catalytic...... subunits, which make no direct contact with one another. Each catalytic subunit interacts with both regulatory chains, predominantly via an extended C-terminal tail of the regulatory subunit. The CK2 structure is consistent with its constitutive activity and with a flexible role of the regulatory subunit...

Insulin as a model to teach three-dimensional structure of proteins

Directory of Open Access Journals (Sweden)

João Batista Teixeira da Rocha

2018-02-01

Proteins are the most ubiquitous macromolecules found in the living cells and have innumerous physiological functions. Therefore, it is fundamental to build a solid knowledge about the proteins three dimensional structure to better understand the living state. The hierarchical structure of proteins is usually studied in the undergraduate discipline of Biochemistry. Here we described pedagogical interventions designed to increase the preservice teacher chemistry students’ knowledge about protein structure. The activities were made using alternative and cheap materials to encourage the application of these simple methodologies by the future teachers in the secondary school. From the primary structure of insulin chains, students had to construct a three-dimensional structure of insulin. After the activities, the students highlighted an improvement of their previous knowledge about proteins structure. The construction of a tridimensional model together with other activities seems to be an efficient way to promote the learning about the structure of proteins to undergraduate students. The methodology used was inexpensiveness and simple and it can be used both in the university and in the high-school.

Systematic comparison of crystal and NMR protein structures deposited in the protein data bank.

Science.gov (United States)

Sikic, Kresimir; Tomic, Sanja; Carugo, Oliviero

2010-09-03

Nearly all the macromolecular three-dimensional structures deposited in Protein Data Bank were determined by either crystallographic (X-ray) or Nuclear Magnetic Resonance (NMR) spectroscopic methods. This paper reports a systematic comparison of the crystallographic and NMR results deposited in the files of the Protein Data Bank, in order to find out to which extent these information can be aggregated in bioinformatics. A non-redundant data set containing 109 NMR - X-ray structure pairs of nearly identical proteins was derived from the Protein Data Bank. A series of comparisons were performed by focusing the attention towards both global features and local details. It was observed that: (1) the RMDS values between NMR and crystal structures range from about 1.5 Å to about 2.5 Å; (2) the correlation between conformational deviations and residue type reveals that hydrophobic amino acids are more similar in crystal and NMR structures than hydrophilic amino acids; (3) the correlation between solvent accessibility of the residues and their conformational variability in solid state and in solution is relatively modest (correlation coefficient = 0.462); (4) beta strands on average match better between NMR and crystal structures than helices and loops; (5) conformational differences between loops are independent of crystal packing interactions in the solid state; (6) very seldom, side chains buried in the protein interior are observed to adopt different orientations in the solid state and in solution.

A computational tool to predict the evolutionarily conserved protein-protein interaction hot-spot residues from the structure of the unbound protein.

Science.gov (United States)

Agrawal, Neeraj J; Helk, Bernhard; Trout, Bernhardt L

2014-01-21

Identifying hot-spot residues - residues that are critical to protein-protein binding - can help to elucidate a protein's function and assist in designing therapeutic molecules to target those residues. We present a novel computational tool, termed spatial-interaction-map (SIM), to predict the hot-spot residues of an evolutionarily conserved protein-protein interaction from the structure of an unbound protein alone. SIM can predict the protein hot-spot residues with an accuracy of 36-57%. Thus, the SIM tool can be used to predict the yet unknown hot-spot residues for many proteins for which the structure of the protein-protein complexes are not available, thereby providing a clue to their functions and an opportunity to design therapeutic molecules to target these proteins. Copyright © 2013 Federation of European Biochemical Societies. Published by Elsevier B.V. All rights reserved.

Heterochiral Knottin Protein: Folding and Solution Structure.

Science.gov (United States)

Mong, Surin K; Cochran, Frank V; Yu, Hongtao; Graziano, Zachary; Lin, Yu-Shan; Cochran, Jennifer R; Pentelute, Bradley L

2017-10-31

Homochirality is a general feature of biological macromolecules, and Nature includes few examples of heterochiral proteins. Herein, we report on the design, chemical synthesis, and structural characterization of heterochiral proteins possessing loops of amino acids of chirality opposite to that of the rest of a protein scaffold. Using the protein Ecballium elaterium trypsin inhibitor II, we discover that selective β-alanine substitution favors the efficient folding of our heterochiral constructs. Solution nuclear magnetic resonance spectroscopy of one such heterochiral protein reveals a homogeneous global fold. Additionally, steered molecular dynamics simulation indicate β-alanine reduces the free energy required to fold the protein. We also find these heterochiral proteins to be more resistant to proteolysis than homochiral l-proteins. This work informs the design of heterochiral protein architectures containing stretches of both d- and l-amino acids.

Structural features that predict real-value fluctuations of globular proteins.

Science.gov (United States)

Jamroz, Michal; Kolinski, Andrzej; Kihara, Daisuke

2012-05-01

It is crucial to consider dynamics for understanding the biological function of proteins. We used a large number of molecular dynamics (MD) trajectories of nonhomologous proteins as references and examined static structural features of proteins that are most relevant to fluctuations. We examined correlation of individual structural features with fluctuations and further investigated effective combinations of features for predicting the real value of residue fluctuations using the support vector regression (SVR). It was found that some structural features have higher correlation than crystallographic B-factors with fluctuations observed in MD trajectories. Moreover, SVR that uses combinations of static structural features showed accurate prediction of fluctuations with an average Pearson's correlation coefficient of 0.669 and a root mean square error of 1.04 Å. This correlation coefficient is higher than the one observed in predictions by the Gaussian network model (GNM). An advantage of the developed method over the GNMs is that the former predicts the real value of fluctuation. The results help improve our understanding of relationships between protein structure and fluctuation. Furthermore, the developed method provides a convienient practial way to predict fluctuations of proteins using easily computed static structural features of proteins. Copyright © 2012 Wiley Periodicals, Inc.

Human cancer protein-protein interaction network: a structural perspective.

Directory of Open Access Journals (Sweden)

Gozde Kar

2009-12-01

Full Text Available Protein-protein interaction networks provide a global picture of cellular function and biological processes. Some proteins act as hub proteins, highly connected to others, whereas some others have few interactions. The dysfunction of some interactions causes many diseases, including cancer. Proteins interact through their interfaces. Therefore, studying the interface properties of cancer-related proteins will help explain their role in the interaction networks. Similar or overlapping binding sites should be used repeatedly in single interface hub proteins, making them promiscuous. Alternatively, multi-interface hub proteins make use of several distinct binding sites to bind to different partners. We propose a methodology to integrate protein interfaces into cancer interaction networks (ciSPIN, cancer structural protein interface network. The interactions in the human protein interaction network are replaced by interfaces, coming from either known or predicted complexes. We provide a detailed analysis of cancer related human protein-protein interfaces and the topological properties of the cancer network. The results reveal that cancer-related proteins have smaller, more planar, more charged and less hydrophobic binding sites than non-cancer proteins, which may indicate low affinity and high specificity of the cancer-related interactions. We also classified the genes in ciSPIN according to phenotypes. Within phenotypes, for breast cancer, colorectal cancer and leukemia, interface properties were found to be discriminating from non-cancer interfaces with an accuracy of 71%, 67%, 61%, respectively. In addition, cancer-related proteins tend to interact with their partners through distinct interfaces, corresponding mostly to multi-interface hubs, which comprise 56% of cancer-related proteins, and constituting the nodes with higher essentiality in the network (76%. We illustrate the interface related affinity properties of two cancer-related hub

BioJava-ModFinder: identification of protein modifications in 3D structures from the Protein Data Bank.

Science.gov (United States)

Gao, Jianjiong; Prlic, Andreas; Bi, Chunxiao; Bluhm, Wolfgang F; Dimitropoulos, Dimitris; Xu, Dong; Bourne, Philip E; Rose, Peter W

2017-07-01

We developed a new software tool, BioJava-ModFinder, for identifying protein modifications observed in 3D structures archived in the Protein Data Bank (PDB). Information on more than 400 types of protein modifications were collected and curated from annotations in PDB, RESID, and PSI-MOD. We divided these modifications into three categories: modified residues, attachment modifications, and cross-links. We have developed a systematic method to identify these modifications in 3D protein structures. We have integrated this package with the RCSB PDB web application and added protein modification annotations to the sequence diagram and structure display. By scanning all 3D structures in the PDB using BioJava-ModFinder, we identified more than 30 000 structures with protein modifications, which can be searched, browsed, and visualized on the RCSB PDB website. BioJava-ModFinder is available as open source (LGPL license) at ( https://github.com/biojava/biojava/tree/master/biojava-modfinder ). The RCSB PDB can be accessed at http://www.rcsb.org . pwrose@ucsd.edu. © The Author 2017. Published by Oxford University Press.

Development and Validation of Protein Microarray Technology for Simultaneous Inflammatory Mediator Detection in Human Sera

Directory of Open Access Journals (Sweden)

Senthooran Selvarajah

2014-01-01

Full Text Available Biomarkers, including cytokines, can help in the diagnosis, prognosis, and prediction of treatment response across a wide range of disease settings. Consequently, the recent emergence of protein microarray technology, which is able to quantify a range of inflammatory mediators in a large number of samples simultaneously, has become highly desirable. However, the cost of commercial systems remains somewhat prohibitive. Here we show the development, validation, and implementation of an in-house microarray platform which enables the simultaneous quantitative analysis of multiple protein biomarkers. The accuracy and precision of the in-house microarray system were investigated according to the Food and Drug Administration (FDA guidelines for pharmacokinetic assay validation. The assay fell within these limits for all but the very low-abundant cytokines, such as interleukin- (IL- 10. Additionally, there were no significant differences between cytokine detection using our microarray system and the “gold standard” ELISA format. Crucially, future biomarker detection need not be limited to the 16 cytokines shown here but could be expanded as required. In conclusion, we detail a bespoke protein microarray system, utilizing well-validated ELISA reagents, that allows accurate, precise, and reproducible multiplexed biomarker quantification, comparable with commercial ELISA, and allowing customization beyond that of similar commercial microarrays.

Structure of the ordered hydration of amino acids in proteins: analysis of crystal structures

Energy Technology Data Exchange (ETDEWEB)

Biedermannová, Lada, E-mail: lada.biedermannova@ibt.cas.cz; Schneider, Bohdan [Institute of Biotechnology CAS, Videnska 1083, 142 20 Prague (Czech Republic)

2015-10-27

The hydration of protein crystal structures was studied at the level of individual amino acids. The dependence of the number of water molecules and their preferred spatial localization on various parameters, such as solvent accessibility, secondary structure and side-chain conformation, was determined. Crystallography provides unique information about the arrangement of water molecules near protein surfaces. Using a nonredundant set of 2818 protein crystal structures with a resolution of better than 1.8 Å, the extent and structure of the hydration shell of all 20 standard amino-acid residues were analyzed as function of the residue conformation, secondary structure and solvent accessibility. The results show how hydration depends on the amino-acid conformation and the environment in which it occurs. After conformational clustering of individual residues, the density distribution of water molecules was compiled and the preferred hydration sites were determined as maxima in the pseudo-electron-density representation of water distributions. Many hydration sites interact with both main-chain and side-chain amino-acid atoms, and several occurrences of hydration sites with less canonical contacts, such as carbon–donor hydrogen bonds, OH–π interactions and off-plane interactions with aromatic heteroatoms, are also reported. Information about the location and relative importance of the empirically determined preferred hydration sites in proteins has applications in improving the current methods of hydration-site prediction in molecular replacement, ab initio protein structure prediction and the set-up of molecular-dynamics simulations.

Structure and Dynamic Properties of Membrane Proteins using NMR

DEFF Research Database (Denmark)

Rösner, Heike; Kragelund, Birthe

2012-01-01

conformational changes. Their structural and functional decoding is challenging and has imposed demanding experimental development. Solution nuclear magnetic resonance (NMR) spectroscopy is one of the techniques providing the capacity to make a significant difference in the deciphering of the membrane protein...... structure-function paradigm. The method has evolved dramatically during the last decade resulting in a plethora of new experiments leading to a significant increase in the scientific repertoire for studying membrane proteins. Besides solving the three-dimensional structures using state-of-the-art approaches......-populated states, this review seeks to introduce the vast possibilities solution NMR can offer to the study of membrane protein structure-function analyses with special focus on applicability. © 2012 American Physiological Society. Compr Physiol 2:1491-1539, 2012....

Thermal green protein, an extremely stable, nonaggregating fluorescent protein created by structure-guided surface engineering.

Science.gov (United States)

Close, Devin W; Paul, Craig Don; Langan, Patricia S; Wilce, Matthew C J; Traore, Daouda A K; Halfmann, Randal; Rocha, Reginaldo C; Waldo, Geoffery S; Payne, Riley J; Rucker, Joseph B; Prescott, Mark; Bradbury, Andrew R M

2015-07-01

In this article, we describe the engineering and X-ray crystal structure of Thermal Green Protein (TGP), an extremely stable, highly soluble, non-aggregating green fluorescent protein. TGP is a soluble variant of the fluorescent protein eCGP123, which despite being highly stable, has proven to be aggregation-prone. The X-ray crystal structure of eCGP123, also determined within the context of this paper, was used to carry out rational surface engineering to improve its solubility, leading to TGP. The approach involved simultaneously eliminating crystal lattice contacts while increasing the overall negative charge of the protein. Despite intentional disruption of lattice contacts and introduction of high entropy glutamate side chains, TGP crystallized readily in a number of different conditions and the X-ray crystal structure of TGP was determined to 1.9 Å resolution. The structural reasons for the enhanced stability of TGP and eCGP123 are discussed. We demonstrate the utility of using TGP as a fusion partner in various assays and significantly, in amyloid assays in which the standard fluorescent protein, EGFP, is undesirable because of aberrant oligomerization. © 2014 Wiley Periodicals, Inc.

Validity and factor structure of the bodybuilding dependence scale

OpenAIRE

Smith, D; Hale, B

2004-01-01

Objectives: To investigate the factor structure, validity, and reliability of the bodybuilding dependence scale and to investigate differences in bodybuilding dependence between men and women and competitive and non-competitive bodybuilders.

Structure of haze forming proteins in white wines: Vitis vinifera thaumatin-like proteins.

Science.gov (United States)

Marangon, Matteo; Van Sluyter, Steven C; Waters, Elizabeth J; Menz, Robert I

2014-01-01

Grape thaumatin-like proteins (TLPs) play roles in plant-pathogen interactions and can cause protein haze in white wine unless removed prior to bottling. Different isoforms of TLPs have different hazing potential and aggregation behavior. Here we present the elucidation of the molecular structures of three grape TLPs that display different hazing potential. The three TLPs have very similar structures despite belonging to two different classes (F2/4JRU is a thaumatin-like protein while I/4L5H and H2/4MBT are VVTL1), and having different unfolding temperatures (56 vs. 62°C), with protein F2/4JRU being heat unstable and forming haze, while I/4L5H does not. These differences in properties are attributable to the conformation of a single loop and the amino acid composition of its flanking regions.

Development and Validation of a Multiplexed Protein Quantitation Assay for the Determination of Three Recombinant Proteins in Soybean Tissues by Liquid Chromatography with Tandem Mass Spectrometry.

Science.gov (United States)

Hill, Ryan C; Oman, Trent J; Shan, Guomin; Schafer, Barry; Eble, Julie; Chen, Cynthia

2015-08-26

Currently, traditional immunochemistry technologies such as enzyme-linked immunosorbent assays (ELISA) are the predominant analytical tool used to measure levels of recombinant proteins expressed in genetically engineered (GE) plants. Recent advances in agricultural biotechnology have created a need to develop methods capable of selectively detecting and quantifying multiple proteins in complex matrices because of increasing numbers of transgenic proteins being coexpressed or "stacked" to achieve tolerance to multiple herbicides or to provide multiple modes of action for insect control. A multiplexing analytical method utilizing liquid chromatography with tandem mass spectrometry (LC-MS/MS) has been developed and validated to quantify three herbicide-tolerant proteins in soybean tissues: aryloxyalkanoate dioxygenase (AAD-12), 5-enol-pyruvylshikimate-3-phosphate synthase (2mEPSPS), and phosphinothricin acetyltransferase (PAT). Results from the validation showed high recovery and precision over multiple analysts and laboratories. Results from this method were comparable to those obtained with ELISA with respect to protein quantitation, and the described method was demonstrated to be suitable for multiplex quantitation of transgenic proteins in GE crops.

Structural Conservation of the Myoviridae Phage Tail Sheath Protein Fold

Energy Technology Data Exchange (ETDEWEB)

Aksyuk, Anastasia A.; Kurochkina, Lidia P.; Fokine, Andrei; Forouhar, Farhad; Mesyanzhinov, Vadim V.; Tong, Liang; Rossmann, Michael G. (SOIBC); (Purdue); (Columbia)

2012-02-21

Bacteriophage phiKZ is a giant phage that infects Pseudomonas aeruginosa, a human pathogen. The phiKZ virion consists of a 1450 {angstrom} diameter icosahedral head and a 2000 {angstrom}-long contractile tail. The structure of the whole virus was previously reported, showing that its tail organization in the extended state is similar to the well-studied Myovirus bacteriophage T4 tail. The crystal structure of a tail sheath protein fragment of phiKZ was determined to 2.4 {angstrom} resolution. Furthermore, crystal structures of two prophage tail sheath proteins were determined to 1.9 and 3.3 {angstrom} resolution. Despite low sequence identity between these proteins, all of these structures have a similar fold. The crystal structure of the phiKZ tail sheath protein has been fitted into cryo-electron-microscopy reconstructions of the extended tail sheath and of a polysheath. The structural rearrangement of the phiKZ tail sheath contraction was found to be similar to that of phage T4.

Constraining cyclic peptides to mimic protein structure motifs

DEFF Research Database (Denmark)

Hill, Timothy A.; Shepherd, Nicholas E.; Diness, Frederik

2014-01-01

peptides can have protein-like biological activities and potencies, enabling their uses as biological probes and leads to therapeutics, diagnostics and vaccines. This Review highlights examples of cyclic peptides that mimic three-dimensional structures of strand, turn or helical segments of peptides...... and proteins, and identifies some additional restraints incorporated into natural product cyclic peptides and synthetic macrocyclic pepti-domimetics that refine peptide structure and confer biological properties....

Structure of PIN-domain protein PH0500 from Pyrococcus horikoshii

International Nuclear Information System (INIS)

Jeyakanthan, Jeyaraman; Inagaki, Eiji; Kuroishi, Chizu; Tahirov, Tahir H.

2005-01-01

The structure of P. horikoshii OT3 protein PH0500 was determined by the multiple anomalous dispersion method and refined in two crystal forms. The protein is a dimer and has a PIN-domain fold. The Pyrococcus horikoshii OT3 protein PH0500 is highly conserved within the Pyrococcus genus of hyperthermophilic archaea and shows low amino-acid sequence similarity with a family of PIN-domain proteins. The protein has been expressed, purified and crystallized in two crystal forms: PH0500-I and PH0500-II. The structure was determined at 2.0 Å by the multiple anomalous dispersion method using a selenomethionyl derivative of crystal form PH0500-I (PH0500-I-Se). The structure of PH0500-I has been refined at 1.75 Å resolution to an R factor of 20.9% and the structure of PH0500-II has been refined at 2.0 Å resolution to an R factor of 23.4%. In both crystal forms as well as in solution the molecule appears to be a dimer. Searches of the databases for protein-fold similarities confirmed that the PH0500 protein is a PIN-domain protein with possible exonuclease activity and involvement in DNA or RNA editing

Crystal structure of an orthomyxovirus matrix protein reveals mechanisms for self-polymerization and membrane association.

Science.gov (United States)

Zhang, Wenting; Zheng, Wenjie; Toh, Yukimatsu; Betancourt-Solis, Miguel A; Tu, Jiagang; Fan, Yanlin; Vakharia, Vikram N; Liu, Jun; McNew, James A; Jin, Meilin; Tao, Yizhi J

2017-08-08

Many enveloped viruses encode a matrix protein. In the influenza A virus, the matrix protein M1 polymerizes into a rigid protein layer underneath the viral envelope to help enforce the shape and structural integrity of intact viruses. The influenza virus M1 is also known to mediate virus budding as well as the nuclear export of the viral nucleocapsids and their subsequent packaging into nascent viral particles. Despite extensive studies on the influenza A virus M1 (FLUA-M1), only crystal structures of its N-terminal domain are available. Here we report the crystal structure of the full-length M1 from another orthomyxovirus that infects fish, the infectious salmon anemia virus (ISAV). The structure of ISAV-M1 assumes the shape of an elbow, with its N domain closely resembling that of the FLUA-M1. The C domain, which is connected to the N domain through a flexible linker, is made of four α-helices packed as a tight bundle. In the crystal, ISAV-M1 monomers form infinite 2D arrays with a network of interactions involving both the N and C domains. Results from liposome flotation assays indicated that ISAV-M1 binds membrane via electrostatic interactions that are primarily mediated by a positively charged surface loop from the N domain. Cryoelectron tomography reconstruction of intact ISA virions identified a matrix protein layer adjacent to the inner leaflet of the viral membrane. The physical dimensions of the virion-associated matrix layer are consistent with the 2D ISAV-M1 crystal lattice, suggesting that the crystal lattice is a valid model for studying M1-M1, M1-membrane, and M1-RNP interactions in the virion.