Simplified Swarm Optimization-Based Function Module Detection in Protein–Protein Interaction Networks

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Xianghan Zheng

2017-04-01

Full Text Available Proteomics research has become one of the most important topics in the field of life science and natural science. At present, research on protein–protein interaction networks (PPIN mainly focuses on detecting protein complexes or function modules. However, existing approaches are either ineffective or incomplete. In this paper, we investigate detection mechanisms of functional modules in PPIN, including open database, existing detection algorithms, and recent solutions. After that, we describe the proposed approach based on the simplified swarm optimization (SSO algorithm and the knowledge of Gene Ontology (GO. The proposed solution implements the SSO algorithm for clustering proteins with similar function, and imports biological gene ontology knowledge for further identifying function complexes and improving detection accuracy. Furthermore, we use four different categories of species datasets for experiment: fruitfly, mouse, scere, and human. The testing and analysis result show that the proposed solution is feasible, efficient, and could achieve a higher accuracy of prediction than existing approaches.

Structure-based functional annotation of putative conserved proteins having lyase activity from Haemophilus influenzae.

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Shahbaaz, Mohd; Ahmad, Faizan; Imtaiyaz Hassan, Md

2015-06-01

Haemophilus influenzae is a small pleomorphic Gram-negative bacteria which causes several chronic diseases, including bacteremia, meningitis, cellulitis, epiglottitis, septic arthritis, pneumonia, and empyema. Here we extensively analyzed the sequenced genome of H. influenzae strain Rd KW20 using protein family databases, protein structure prediction, pathways and genome context methods to assign a precise function to proteins whose functions are unknown. These proteins are termed as hypothetical proteins (HPs), for which no experimental information is available. Function prediction of these proteins would surely be supportive to precisely understand the biochemical pathways and mechanism of pathogenesis of Haemophilus influenzae. During the extensive analysis of H. influenzae genome, we found the presence of eight HPs showing lyase activity. Subsequently, we modeled and analyzed three-dimensional structure of all these HPs to determine their functions more precisely. We found these HPs possess cystathionine-β-synthase, cyclase, carboxymuconolactone decarboxylase, pseudouridine synthase A and C, D-tagatose-1,6-bisphosphate aldolase and aminodeoxychorismate lyase-like features, indicating their corresponding functions in the H. influenzae. Lyases are actively involved in the regulation of biosynthesis of various hormones, metabolic pathways, signal transduction, and DNA repair. Lyases are also considered as a key player for various biological processes. These enzymes are critically essential for the survival and pathogenesis of H. influenzae and, therefore, these enzymes may be considered as a potential target for structure-based rational drug design. Our structure-function relationship analysis will be useful to search and design potential lead molecules based on the structure of these lyases, for drug design and discovery.

Incorporating functional inter-relationships into protein function prediction algorithms

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Kumar Vipin

2009-05-01

Full Text Available Abstract Background Functional classification schemes (e.g. the Gene Ontology that serve as the basis for annotation efforts in several organisms are often the source of gold standard information for computational efforts at supervised protein function prediction. While successful function prediction algorithms have been developed, few previous efforts have utilized more than the protein-to-functional class label information provided by such knowledge bases. For instance, the Gene Ontology not only captures protein annotations to a set of functional classes, but it also arranges these classes in a DAG-based hierarchy that captures rich inter-relationships between different classes. These inter-relationships present both opportunities, such as the potential for additional training examples for small classes from larger related classes, and challenges, such as a harder to learn distinction between similar GO terms, for standard classification-based approaches. Results We propose a method to enhance the performance of classification-based protein function prediction algorithms by addressing the issue of using these interrelationships between functional classes constituting functional classification schemes. Using a standard measure for evaluating the semantic similarity between nodes in an ontology, we quantify and incorporate these inter-relationships into the k-nearest neighbor classifier. We present experiments on several large genomic data sets, each of which is used for the modeling and prediction of over hundred classes from the GO Biological Process ontology. The results show that this incorporation produces more accurate predictions for a large number of the functional classes considered, and also that the classes benefitted most by this approach are those containing the fewest members. In addition, we show how our proposed framework can be used for integrating information from the entire GO hierarchy for improving the accuracy of

ProLanGO: Protein Function Prediction Using Neural Machine Translation Based on a Recurrent Neural Network.

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Cao, Renzhi; Freitas, Colton; Chan, Leong; Sun, Miao; Jiang, Haiqing; Chen, Zhangxin

2017-10-17

With the development of next generation sequencing techniques, it is fast and cheap to determine protein sequences but relatively slow and expensive to extract useful information from protein sequences because of limitations of traditional biological experimental techniques. Protein function prediction has been a long standing challenge to fill the gap between the huge amount of protein sequences and the known function. In this paper, we propose a novel method to convert the protein function problem into a language translation problem by the new proposed protein sequence language "ProLan" to the protein function language "GOLan", and build a neural machine translation model based on recurrent neural networks to translate "ProLan" language to "GOLan" language. We blindly tested our method by attending the latest third Critical Assessment of Function Annotation (CAFA 3) in 2016, and also evaluate the performance of our methods on selected proteins whose function was released after CAFA competition. The good performance on the training and testing datasets demonstrates that our new proposed method is a promising direction for protein function prediction. In summary, we first time propose a method which converts the protein function prediction problem to a language translation problem and applies a neural machine translation model for protein function prediction.

Canola/rapeseed protein-functionality and nutrition

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Wanasundara Janitha P.D.

2016-07-01

Full Text Available Protein rich meal is a valuable co-product of canola/rapeseed oil extraction. Seed storage proteins that include cruciferin (11S and napin (2S dominate the protein complement of canola while oleosins, lipid transfer proteins and other minor proteins of non-storage nature are also found. Although oil-free canola meal contains 36–40% protein on a dry weight basis, non-protein components including fibre, polymeric phenolics, phytates and sinapine, etc. of the seed coat and cellular components make protein less suitable for food use. Separation of canola protein from non-protein components is a technical challenge but necessary to obtain full nutritional and functional potential of protein. Process conditions of raw material and protein preparation are critical of nutritional and functional value of the final protein product. The storage proteins of canola can satisfy many nutritional and functional requirements for food applications. Protein macromolecules of canola also provide functionalities required in applications beyond edible uses; there exists substantial potential as a source of plant protein and a renewable biopolymer. Available information at present is mostly based on the protein products that can be obtained as mixtures of storage protein types and other chemical constituents of the seed; therefore, full potential of canola storage proteins is yet to be revealed.

Mining protein function from text using term-based support vector machines

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Rice, Simon B; Nenadic, Goran; Stapley, Benjamin J

2005-01-01

Background Text mining has spurred huge interest in the domain of biology. The goal of the BioCreAtIvE exercise was to evaluate the performance of current text mining systems. We participated in Task 2, which addressed assigning Gene Ontology terms to human proteins and selecting relevant evidence from full-text documents. We approached it as a modified form of the document classification task. We used a supervised machine-learning approach (based on support vector machines) to assign protein function and select passages that support the assignments. As classification features, we used a protein's co-occurring terms that were automatically extracted from documents. Results The results evaluated by curators were modest, and quite variable for different problems: in many cases we have relatively good assignment of GO terms to proteins, but the selected supporting text was typically non-relevant (precision spanning from 3% to 50%). The method appears to work best when a substantial set of relevant documents is obtained, while it works poorly on single documents and/or short passages. The initial results suggest that our approach can also mine annotations from text even when an explicit statement relating a protein to a GO term is absent. Conclusion A machine learning approach to mining protein function predictions from text can yield good performance only if sufficient training data is available, and significant amount of supporting data is used for prediction. The most promising results are for combined document retrieval and GO term assignment, which calls for the integration of methods developed in BioCreAtIvE Task 1 and Task 2. PMID:15960835

Text mining improves prediction of protein functional sites.

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Karin M Verspoor

Full Text Available We present an approach that integrates protein structure analysis and text mining for protein functional site prediction, called LEAP-FS (Literature Enhanced Automated Prediction of Functional Sites. The structure analysis was carried out using Dynamics Perturbation Analysis (DPA, which predicts functional sites at control points where interactions greatly perturb protein vibrations. The text mining extracts mentions of residues in the literature, and predicts that residues mentioned are functionally important. We assessed the significance of each of these methods by analyzing their performance in finding known functional sites (specifically, small-molecule binding sites and catalytic sites in about 100,000 publicly available protein structures. The DPA predictions recapitulated many of the functional site annotations and preferentially recovered binding sites annotated as biologically relevant vs. those annotated as potentially spurious. The text-based predictions were also substantially supported by the functional site annotations: compared to other residues, residues mentioned in text were roughly six times more likely to be found in a functional site. The overlap of predictions with annotations improved when the text-based and structure-based methods agreed. Our analysis also yielded new high-quality predictions of many functional site residues that were not catalogued in the curated data sources we inspected. We conclude that both DPA and text mining independently provide valuable high-throughput protein functional site predictions, and that integrating the two methods using LEAP-FS further improves the quality of these predictions.

Text Mining Improves Prediction of Protein Functional Sites

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Cohn, Judith D.; Ravikumar, Komandur E.

2012-01-01

We present an approach that integrates protein structure analysis and text mining for protein functional site prediction, called LEAP-FS (Literature Enhanced Automated Prediction of Functional Sites). The structure analysis was carried out using Dynamics Perturbation Analysis (DPA), which predicts functional sites at control points where interactions greatly perturb protein vibrations. The text mining extracts mentions of residues in the literature, and predicts that residues mentioned are functionally important. We assessed the significance of each of these methods by analyzing their performance in finding known functional sites (specifically, small-molecule binding sites and catalytic sites) in about 100,000 publicly available protein structures. The DPA predictions recapitulated many of the functional site annotations and preferentially recovered binding sites annotated as biologically relevant vs. those annotated as potentially spurious. The text-based predictions were also substantially supported by the functional site annotations: compared to other residues, residues mentioned in text were roughly six times more likely to be found in a functional site. The overlap of predictions with annotations improved when the text-based and structure-based methods agreed. Our analysis also yielded new high-quality predictions of many functional site residues that were not catalogued in the curated data sources we inspected. We conclude that both DPA and text mining independently provide valuable high-throughput protein functional site predictions, and that integrating the two methods using LEAP-FS further improves the quality of these predictions. PMID:22393388

Nutritional and functional properties of whey proteins concentrate and isolate

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Zoran Herceg

2006-12-01

Full Text Available Whey protein fractions represent 18 - 20 % of total milk nitrogen content. Nutritional value in addition to diverse physico - chemical and functional properties make whey proteins highly suitable for application in foodstuffs. In the most cases, whey proteins are used because of their functional properties. Whey proteins possess favourable functional characteristics such as gelling, water binding, emulsification and foaming ability. Due to application of new process techniques (membrane fractionation techniques, it is possible to produce various whey - protein based products. The most important products based on the whey proteins are whey protein concentrates (WPC and whey protein isolates (WPI. The aim of this paper was to give comprehensive review of nutritional and functional properties of the most common used whey proteins (whey protein concentrate - WPC and whey protein isolate - WPI in the food industry.

Cell array-based intracellular localization screening reveals novel functional features of human chromosome 21 proteins

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Kahlem Pascal

2006-06-01

Full Text Available Abstract Background Trisomy of human chromosome 21 (Chr21 results in Down's syndrome, a complex developmental and neurodegenerative disease. Molecular analysis of Down's syndrome, however, poses a particular challenge, because the aneuploid region of Chr21 contains many genes of unknown function. Subcellular localization of human Chr21 proteins may contribute to further understanding of the functions and regulatory mechanisms of the genes that code for these proteins. Following this idea, we used a transfected-cell array technique to perform a rapid and cost-effective analysis of the intracellular distribution of Chr 21 proteins. Results We chose 89 genes that were distributed over the majority of 21q, ranging from RBM11 (14.5 Mb to MCM3AP (46.6 Mb, with part of them expressed aberrantly in the Down's syndrome mouse model. Open reading frames of these genes were cloned into a mammalian expression vector with an amino-terminal His6 tag. All of the constructs were arrayed on glass slides and reverse transfected into HEK293T cells for protein expression. Co-localization detection using a set of organelle markers was carried out for each Chr21 protein. Here, we report the subcellular localization properties of 52 proteins. For 34 of these proteins, their localization is described for the first time. Furthermore, the alteration in cell morphology and growth as a result of protein over-expression for claudin-8 and claudin-14 genes has been characterized. Conclusion The cell array-based protein expression and detection approach is a cost-effective platform for large-scale functional analyses, including protein subcellular localization and cell phenotype screening. The results from this study reveal novel functional features of human Chr21 proteins, which should contribute to further understanding of the molecular pathology of Down's syndrome.

On the analysis of protein-protein interactions via knowledge-based potentials for the prediction of protein-protein docking

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Feliu, Elisenda; Aloy, Patrick; Oliva, Baldo

2011-01-01

Development of effective methods to screen binary interactions obtained by rigid-body protein-protein docking is key for structure prediction of complexes and for elucidating physicochemical principles of protein-protein binding. We have derived empirical knowledge-based potential functions for s...... and with independence of the partner. This information is encoded at the residue level and could be easily incorporated in the initial grid scoring for Fast Fourier Transform rigid-body docking methods.......Development of effective methods to screen binary interactions obtained by rigid-body protein-protein docking is key for structure prediction of complexes and for elucidating physicochemical principles of protein-protein binding. We have derived empirical knowledge-based potential functions...... for selecting rigid-body docking poses. These potentials include the energetic component that provides the residues with a particular secondary structure and surface accessibility. These scoring functions have been tested on a state-of-art benchmark dataset and on a decoy dataset of permanent interactions. Our...

Topology-function conservation in protein-protein interaction networks.

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Davis, Darren; Yaveroğlu, Ömer Nebil; Malod-Dognin, Noël; Stojmirovic, Aleksandar; Pržulj, Nataša

2015-05-15

Proteins underlay the functioning of a cell and the wiring of proteins in protein-protein interaction network (PIN) relates to their biological functions. Proteins with similar wiring in the PIN (topology around them) have been shown to have similar functions. This property has been successfully exploited for predicting protein functions. Topological similarity is also used to guide network alignment algorithms that find similarly wired proteins between PINs of different species; these similarities are used to transfer annotation across PINs, e.g. from model organisms to human. To refine these functional predictions and annotation transfers, we need to gain insight into the variability of the topology-function relationships. For example, a function may be significantly associated with specific topologies, while another function may be weakly associated with several different topologies. Also, the topology-function relationships may differ between different species. To improve our understanding of topology-function relationships and of their conservation among species, we develop a statistical framework that is built upon canonical correlation analysis. Using the graphlet degrees to represent the wiring around proteins in PINs and gene ontology (GO) annotations to describe their functions, our framework: (i) characterizes statistically significant topology-function relationships in a given species, and (ii) uncovers the functions that have conserved topology in PINs of different species, which we term topologically orthologous functions. We apply our framework to PINs of yeast and human, identifying seven biological process and two cellular component GO terms to be topologically orthologous for the two organisms. © The Author 2015. Published by Oxford University Press.

Avaliação funcional de bases proteicas desidratadas de anchoita (Engraulis anchoita Functional evaluation of two dehydrated anchovy (Engraulis anchoita Protein bases

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Liziane Garcia-Torchelsen

2011-12-01

Full Text Available Considerou-se neste trabalho a avaliação funcional de bases proteicas desidratadas de anchoita (Engraulis anchoita foi considerada neste trabalho. A polpa do pescado foi separada mecanicamente e submetida à lavagem com dois solventes, água e ácido fosfórico. A secagem em camada delgada das bases proteicas foi conduzida em temperaturas de 40, 60 e 70°C e espessuras de amostra de 5mm. O produto foi avaliado considerando a determinação de proteínas solúveis, composição centesimal e propriedades funcionais, expressas pela solubilidade protéica, capacidade de retenção de água, capacidade de retenção de gordura e capacidade emulsificante. Os resultados indicaram que a obtenção da base proteica de anchoita usando ácido fosfórico como solvente de lavagem apresentou melhores características, se consideradas as operações de extração de proteínas solúveis, secagem e propriedades funcionais do produto final. Com relação à secagem, verificou-se que esta operação origina um produto com melhores características funcionais quando são empregadas temperaturas de 40 e 60°C.The functional evaluation of two dehydrated anchovy (Engraulis anchoita protein bases was considered in this work. The fish meat was mechanically separated and subjected to washing with two solvents, water and phosphoric acid, to obtain the protein bases. Thin layer drying of the protein bases was carried out at temperatures of 40, 60 and 70 °C, with a sample thickness of 5mm. The products were evaluated considering the determinations of the soluble proteins, proximate composition and the functional properties such as protein solubility, water holding capacity, fat holding capacity and emulsifying capacity. The results indicated that obtaining the anchovy protein base using phosphoric acid as the washing solvent resulted in better characteristics, when considering the operations of extracting and drying the soluble proteins and the functional properties of

Nanochemistry of protein-based delivery agents

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Rajendran, Subin; Udenigwe, Chibuike; Yada, Rickey

2016-07-01

The past decade has seen an increased interest in the conversion of food proteins into functional biomaterials, including their use for loading and delivery of physiologically active compounds such as nutraceuticals and pharmaceuticals. Proteins possess a competitive advantage over other platforms for the development of nanodelivery systems since they are biocompatible, amphipathic, and widely available. Proteins also have unique molecular structures and diverse functional groups that can be selectively modified to alter encapsulation and release properties. A number of physical and chemical methods have been used for preparing protein nanoformulations, each based on different underlying protein chemistry. This review focuses on the chemistry of the reorganization and/or modification of proteins into functional nanostructures for delivery, from the perspective of their preparation, functionality, stability and physiological behavior.

Functionality of alternative protein in gluten-free product development.

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Deora, Navneet Singh; Deswal, Aastha; Mishra, Hari Niwas

2015-07-01

Celiac disease is an immune-mediated disease triggered in genetically susceptible individuals by ingested gluten from wheat, rye, barley, and other closely related cereal grains. The current treatment for celiac disease is life-long adherence to a strict gluten-exclusion diet. The replacement of gluten presents a significant technological challenge, as it is an essential structure-building protein, which is necessary for formulating high-quality baked goods. A major limitation in the production of gluten-free products is the lack of protein functionality in non-wheat cereals. Additionally, commercial gluten-free mixes usually contain only carbohydrates, which may significantly limit the amount of protein in the diet. In the recent past, various approaches are attempted to incorporate protein-based ingredients and to modify the functional properties for gluten-free product development. This review aims to the highlight functionality of the alternative protein-based ingredients, which can be utilized for gluten-free product development both functionally as well as nutritionally. © The Author(s) 2014.

Scoring protein relationships in functional interaction networks predicted from sequence data.

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Gaston K Mazandu

Full Text Available UNLABELLED: The abundance of diverse biological data from various sources constitutes a rich source of knowledge, which has the power to advance our understanding of organisms. This requires computational methods in order to integrate and exploit these data effectively and elucidate local and genome wide functional connections between protein pairs, thus enabling functional inferences for uncharacterized proteins. These biological data are primarily in the form of sequences, which determine functions, although functional properties of a protein can often be predicted from just the domains it contains. Thus, protein sequences and domains can be used to predict protein pair-wise functional relationships, and thus contribute to the function prediction process of uncharacterized proteins in order to ensure that knowledge is gained from sequencing efforts. In this work, we introduce information-theoretic based approaches to score protein-protein functional interaction pairs predicted from protein sequence similarity and conserved protein signature matches. The proposed schemes are effective for data-driven scoring of connections between protein pairs. We applied these schemes to the Mycobacterium tuberculosis proteome to produce a homology-based functional network of the organism with a high confidence and coverage. We use the network for predicting functions of uncharacterised proteins. AVAILABILITY: Protein pair-wise functional relationship scores for Mycobacterium tuberculosis strain CDC1551 sequence data and python scripts to compute these scores are available at http://web.cbio.uct.ac.za/~gmazandu/scoringschemes.

Studying Membrane Protein Structure and Function Using Nanodiscs

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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...

Roles for text mining in protein function prediction.

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Verspoor, Karin M

2014-01-01

The Human Genome Project has provided science with a hugely valuable resource: the blueprints for life; the specification of all of the genes that make up a human. While the genes have all been identified and deciphered, it is proteins that are the workhorses of the human body: they are essential to virtually all cell functions and are the primary mechanism through which biological function is carried out. Hence in order to fully understand what happens at a molecular level in biological organisms, and eventually to enable development of treatments for diseases where some aspect of a biological system goes awry, we must understand the functions of proteins. However, experimental characterization of protein function cannot scale to the vast amount of DNA sequence data now available. Computational protein function prediction has therefore emerged as a problem at the forefront of modern biology (Radivojac et al., Nat Methods 10(13):221-227, 2013).Within the varied approaches to computational protein function prediction that have been explored, there are several that make use of biomedical literature mining. These methods take advantage of information in the published literature to associate specific proteins with specific protein functions. In this chapter, we introduce two main strategies for doing this: association of function terms, represented as Gene Ontology terms (Ashburner et al., Nat Genet 25(1):25-29, 2000), to proteins based on information in published articles, and a paradigm called LEAP-FS (Literature-Enhanced Automated Prediction of Functional Sites) in which literature mining is used to validate the predictions of an orthogonal computational protein function prediction method.

Nanochemistry of protein-based delivery agents

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Subin R.C.K. Rajendran

2016-07-01

Full Text Available The past decade has seen an increased interest in the conversion of food proteins into functional biomaterials, including their use for loading and delivery of physiologically active compounds such as nutraceuticals and pharmaceuticals. Proteins possess a competitive advantage over other platforms for the development of nanodelivery systems since they are biocompatible, amphipathic, and widely available. Proteins also have unique molecular structures and diverse functional groups that can be selectively modified to alter encapsulation and release properties. A number of physical and chemical methods have been used for preparing protein nanoformulations, each based on different underlying protein chemistry. This review focuses on the chemistry of the reorganization and/or modification of proteins into functional nanostructures for delivery, from the perspective of their preparation, functionality, stability and physiological behavior.

Protein-Based Drug-Delivery Materials

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Dave Jao

2017-05-01

Full Text Available There is a pressing need for long-term, controlled drug release for sustained treatment of chronic or persistent medical conditions and diseases. Guided drug delivery is difficult because therapeutic compounds need to survive numerous transport barriers and binding targets throughout the body. Nanoscale protein-based polymers are increasingly used for drug and vaccine delivery to cross these biological barriers and through blood circulation to their molecular site of action. Protein-based polymers compared to synthetic polymers have the advantages of good biocompatibility, biodegradability, environmental sustainability, cost effectiveness and availability. This review addresses the sources of protein-based polymers, compares the similarity and differences, and highlights characteristic properties and functionality of these protein materials for sustained and controlled drug release. Targeted drug delivery using highly functional multicomponent protein composites to guide active drugs to the site of interest will also be discussed. A systematical elucidation of drug-delivery efficiency in the case of molecular weight, particle size, shape, morphology, and porosity of materials will then be demonstrated to achieve increased drug absorption. Finally, several important biomedical applications of protein-based materials with drug-delivery function—including bone healing, antibiotic release, wound healing, and corneal regeneration, as well as diabetes, neuroinflammation and cancer treatments—are summarized at the end of this review.

SitesIdentify: a protein functional site prediction tool

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Doig Andrew J

2009-11-01

Full Text Available Abstract Background The rate of protein structures being deposited in the Protein Data Bank surpasses the capacity to experimentally characterise them and therefore computational methods to analyse these structures have become increasingly important. Identifying the region of the protein most likely to be involved in function is useful in order to gain information about its potential role. There are many available approaches to predict functional site, but many are not made available via a publicly-accessible application. Results Here we present a functional site prediction tool (SitesIdentify, based on combining sequence conservation information with geometry-based cleft identification, that is freely available via a web-server. We have shown that SitesIdentify compares favourably to other functional site prediction tools in a comparison of seven methods on a non-redundant set of 237 enzymes with annotated active sites. Conclusion SitesIdentify is able to produce comparable accuracy in predicting functional sites to its closest available counterpart, but in addition achieves improved accuracy for proteins with few characterised homologues. SitesIdentify is available via a webserver at http://www.manchester.ac.uk/bioinformatics/sitesidentify/

Recognition of functional sites in protein structures.

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Shulman-Peleg, Alexandra; Nussinov, Ruth; Wolfson, Haim J

2004-06-04

Recognition of regions on the surface of one protein, that are similar to a binding site of another is crucial for the prediction of molecular interactions and for functional classifications. We first describe a novel method, SiteEngine, that assumes no sequence or fold similarities and is able to recognize proteins that have similar binding sites and may perform similar functions. We achieve high efficiency and speed by introducing a low-resolution surface representation via chemically important surface points, by hashing triangles of physico-chemical properties and by application of hierarchical scoring schemes for a thorough exploration of global and local similarities. We proceed to rigorously apply this method to functional site recognition in three possible ways: first, we search a given functional site on a large set of complete protein structures. Second, a potential functional site on a protein of interest is compared with known binding sites, to recognize similar features. Third, a complete protein structure is searched for the presence of an a priori unknown functional site, similar to known sites. Our method is robust and efficient enough to allow computationally demanding applications such as the first and the third. From the biological standpoint, the first application may identify secondary binding sites of drugs that may lead to side-effects. The third application finds new potential sites on the protein that may provide targets for drug design. Each of the three applications may aid in assigning a function and in classification of binding patterns. We highlight the advantages and disadvantages of each type of search, provide examples of large-scale searches of the entire Protein Data Base and make functional predictions.

Random heteropolymers preserve protein function in foreign environments

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Panganiban, Brian; Qiao, Baofu; Jiang, Tao; DelRe, Christopher; Obadia, Mona M.; Nguyen, Trung Dac; Smith, Anton A. A.; Hall, Aaron; Sit, Izaac; Crosby, Marquise G.; Dennis, Patrick B.; Drockenmuller, Eric; Olvera de la Cruz, Monica; Xu, Ting

2018-03-01

The successful incorporation of active proteins into synthetic polymers could lead to a new class of materials with functions found only in living systems. However, proteins rarely function under the conditions suitable for polymer processing. On the basis of an analysis of trends in protein sequences and characteristic chemical patterns on protein surfaces, we designed four-monomer random heteropolymers to mimic intrinsically disordered proteins for protein solubilization and stabilization in non-native environments. The heteropolymers, with optimized composition and statistical monomer distribution, enable cell-free synthesis of membrane proteins with proper protein folding for transport and enzyme-containing plastics for toxin bioremediation. Controlling the statistical monomer distribution in a heteropolymer, rather than the specific monomer sequence, affords a new strategy to interface with biological systems for protein-based biomaterials.

Quantitative protein localization signatures reveal an association between spatial and functional divergences of proteins.

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Loo, Lit-Hsin; Laksameethanasan, Danai; Tung, Yi-Ling

2014-03-01

Protein subcellular localization is a major determinant of protein function. However, this important protein feature is often described in terms of discrete and qualitative categories of subcellular compartments, and therefore it has limited applications in quantitative protein function analyses. Here, we present Protein Localization Analysis and Search Tools (PLAST), an automated analysis framework for constructing and comparing quantitative signatures of protein subcellular localization patterns based on microscopy images. PLAST produces human-interpretable protein localization maps that quantitatively describe the similarities in the localization patterns of proteins and major subcellular compartments, without requiring manual assignment or supervised learning of these compartments. Using the budding yeast Saccharomyces cerevisiae as a model system, we show that PLAST is more accurate than existing, qualitative protein localization annotations in identifying known co-localized proteins. Furthermore, we demonstrate that PLAST can reveal protein localization-function relationships that are not obvious from these annotations. First, we identified proteins that have similar localization patterns and participate in closely-related biological processes, but do not necessarily form stable complexes with each other or localize at the same organelles. Second, we found an association between spatial and functional divergences of proteins during evolution. Surprisingly, as proteins with common ancestors evolve, they tend to develop more diverged subcellular localization patterns, but still occupy similar numbers of compartments. This suggests that divergence of protein localization might be more frequently due to the development of more specific localization patterns over ancestral compartments than the occupation of new compartments. PLAST enables systematic and quantitative analyses of protein localization-function relationships, and will be useful to elucidate protein

Functional aspects of protein flexibility

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Teilum, Kaare; Olsen, Johan G; Kragelund, Birthe B

2009-01-01

this into an intuitive perception of protein function is challenging. Flexibility is of overwhelming importance for protein function, and the changes in protein structure during interactions with binding partners can be dramatic. The present review addresses protein flexibility, focusing on protein-ligand interactions...

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

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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.

A proteomics strategy to elucidate functional protein-protein interactions applied to EGF signaling

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Blagoev, B.; Kratchmarova, I.; Ong, S.E.

2003-01-01

Mass spectrometry-based proteomics can reveal protein-protein interactions on a large scale, but it has been difficult to separate background binding from functionally important interactions and still preserve weak binders. To investigate the epidermal growth factor receptor (EGFR) pathway, we em...

Combining modularity, conservation, and interactions of proteins significantly increases precision and coverage of protein function prediction

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Sers Christine T

2010-12-01

Full Text Available Abstract Background While the number of newly sequenced genomes and genes is constantly increasing, elucidation of their function still is a laborious and time-consuming task. This has led to the development of a wide range of methods for predicting protein functions in silico. We report on a new method that predicts function based on a combination of information about protein interactions, orthology, and the conservation of protein networks in different species. Results We show that aggregation of these independent sources of evidence leads to a drastic increase in number and quality of predictions when compared to baselines and other methods reported in the literature. For instance, our method generates more than 12,000 novel protein functions for human with an estimated precision of ~76%, among which are 7,500 new functional annotations for 1,973 human proteins that previously had zero or only one function annotated. We also verified our predictions on a set of genes that play an important role in colorectal cancer (MLH1, PMS2, EPHB4 and could confirm more than 73% of them based on evidence in the literature. Conclusions The combination of different methods into a single, comprehensive prediction method infers thousands of protein functions for every species included in the analysis at varying, yet always high levels of precision and very good coverage.

Predicting Protein Function via Semantic Integration of Multiple Networks.

Science.gov (United States)

Yu, Guoxian; Fu, Guangyuan; Wang, Jun; Zhu, Hailong

2016-01-01

Determining the biological functions of proteins is one of the key challenges in the post-genomic era. The rapidly accumulated large volumes of proteomic and genomic data drives to develop computational models for automatically predicting protein function in large scale. Recent approaches focus on integrating multiple heterogeneous data sources and they often get better results than methods that use single data source alone. In this paper, we investigate how to integrate multiple biological data sources with the biological knowledge, i.e., Gene Ontology (GO), for protein function prediction. We propose a method, called SimNet, to Semantically integrate multiple functional association Networks derived from heterogenous data sources. SimNet firstly utilizes GO annotations of proteins to capture the semantic similarity between proteins and introduces a semantic kernel based on the similarity. Next, SimNet constructs a composite network, obtained as a weighted summation of individual networks, and aligns the network with the kernel to get the weights assigned to individual networks. Then, it applies a network-based classifier on the composite network to predict protein function. Experiment results on heterogenous proteomic data sources of Yeast, Human, Mouse, and Fly show that, SimNet not only achieves better (or comparable) results than other related competitive approaches, but also takes much less time. The Matlab codes of SimNet are available at https://sites.google.com/site/guoxian85/simnet.

New insights into potential functions for the protein 4.1superfamily of proteins in kidney epithelium

Energy Technology Data Exchange (ETDEWEB)

Calinisan, Venice; Gravem, Dana; Chen, Ray Ping-Hsu; Brittin,Sachi; Mohandas, Narla; Lecomte, Marie-Christine; Gascard, Philippe

2005-06-17

Members of the protein 4.1 family of adapter proteins are expressed in a broad panel of tissues including various epithelia where they likely play an important role in maintenance of cell architecture and polarity and in control of cell proliferation. We have recently characterized the structure and distribution of three members of the protein 4.1 family, 4.1B, 4.1R and 4.1N, in mouse kidney. We describe here binding partners for renal 4.1 proteins, identified through the screening of a rat kidney yeast two-hybrid system cDNA library. The identification of putative protein 4.1-based complexes enables us to envision potential functions for 4.1 proteins in kidney: organization of signaling complexes, response to osmotic stress, protein trafficking, and control of cell proliferation. We discuss the relevance of these protein 4.1-based interactions in kidney physio-pathology in the context of their previously identified functions in other cells and tissues. Specifically, we will focus on renal 4.1 protein interactions with beta amyloid precursor protein (beta-APP), 14-3-3 proteins, and the cell swelling-activated chloride channel pICln. We also discuss the functional relevance of another member of the protein 4.1 superfamily, ezrin, in kidney physiopathology.

Unveiling network-based functional features through integration of gene expression into protein networks.

Science.gov (United States)

Jalili, Mahdi; Gebhardt, Tom; Wolkenhauer, Olaf; Salehzadeh-Yazdi, Ali

2018-06-01

Decoding health and disease phenotypes is one of the fundamental objectives in biomedicine. Whereas high-throughput omics approaches are available, it is evident that any single omics approach might not be adequate to capture the complexity of phenotypes. Therefore, integrated multi-omics approaches have been used to unravel genotype-phenotype relationships such as global regulatory mechanisms and complex metabolic networks in different eukaryotic organisms. Some of the progress and challenges associated with integrated omics studies have been reviewed previously in comprehensive studies. In this work, we highlight and review the progress, challenges and advantages associated with emerging approaches, integrating gene expression and protein-protein interaction networks to unravel network-based functional features. This includes identifying disease related genes, gene prioritization, clustering protein interactions, developing the modules, extract active subnetworks and static protein complexes or dynamic/temporal protein complexes. We also discuss how these approaches contribute to our understanding of the biology of complex traits and diseases. This article is part of a Special Issue entitled: Cardiac adaptations to obesity, diabetes and insulin resistance, edited by Professors Jan F.C. Glatz, Jason R.B. Dyck and Christine Des Rosiers. Copyright © 2018 Elsevier B.V. All rights reserved.

Integration of gel-based and gel-free proteomic data for functional analysis of proteins through Soybean Proteome Database

KAUST Repository

Komatsu, Setsuko

2017-05-10

The Soybean Proteome Database (SPD) stores data on soybean proteins obtained with gel-based and gel-free proteomic techniques. The database was constructed to provide information on proteins for functional analyses. The majority of the data is focused on soybean (Glycine max ‘Enrei’). The growth and yield of soybean are strongly affected by environmental stresses such as flooding. The database was originally constructed using data on soybean proteins separated by two-dimensional polyacrylamide gel electrophoresis, which is a gel-based proteomic technique. Since 2015, the database has been expanded to incorporate data obtained by label-free mass spectrometry-based quantitative proteomics, which is a gel-free proteomic technique. Here, the portions of the database consisting of gel-free proteomic data are described. The gel-free proteomic database contains 39,212 proteins identified in 63 sample sets, such as temporal and organ-specific samples of soybean plants grown under flooding stress or non-stressed conditions. In addition, data on organellar proteins identified in mitochondria, nuclei, and endoplasmic reticulum are stored. Furthermore, the database integrates multiple omics data such as genomics, transcriptomics, metabolomics, and proteomics. The SPD database is accessible at http://proteome.dc.affrc.go.jp/Soybean/. Biological significanceThe Soybean Proteome Database stores data obtained from both gel-based and gel-free proteomic techniques. The gel-free proteomic database comprises 39,212 proteins identified in 63 sample sets, such as different organs of soybean plants grown under flooding stress or non-stressed conditions in a time-dependent manner. In addition, organellar proteins identified in mitochondria, nuclei, and endoplasmic reticulum are stored in the gel-free proteomics database. A total of 44,704 proteins, including 5490 proteins identified using a gel-based proteomic technique, are stored in the SPD. It accounts for approximately 80% of all

Integration of gel-based and gel-free proteomic data for functional analysis of proteins through Soybean Proteome Database.

Science.gov (United States)

Komatsu, Setsuko; Wang, Xin; Yin, Xiaojian; Nanjo, Yohei; Ohyanagi, Hajime; Sakata, Katsumi

2017-06-23

The Soybean Proteome Database (SPD) stores data on soybean proteins obtained with gel-based and gel-free proteomic techniques. The database was constructed to provide information on proteins for functional analyses. The majority of the data is focused on soybean (Glycine max 'Enrei'). The growth and yield of soybean are strongly affected by environmental stresses such as flooding. The database was originally constructed using data on soybean proteins separated by two-dimensional polyacrylamide gel electrophoresis, which is a gel-based proteomic technique. Since 2015, the database has been expanded to incorporate data obtained by label-free mass spectrometry-based quantitative proteomics, which is a gel-free proteomic technique. Here, the portions of the database consisting of gel-free proteomic data are described. The gel-free proteomic database contains 39,212 proteins identified in 63 sample sets, such as temporal and organ-specific samples of soybean plants grown under flooding stress or non-stressed conditions. In addition, data on organellar proteins identified in mitochondria, nuclei, and endoplasmic reticulum are stored. Furthermore, the database integrates multiple omics data such as genomics, transcriptomics, metabolomics, and proteomics. The SPD database is accessible at http://proteome.dc.affrc.go.jp/Soybean/. The Soybean Proteome Database stores data obtained from both gel-based and gel-free proteomic techniques. The gel-free proteomic database comprises 39,212 proteins identified in 63 sample sets, such as different organs of soybean plants grown under flooding stress or non-stressed conditions in a time-dependent manner. In addition, organellar proteins identified in mitochondria, nuclei, and endoplasmic reticulum are stored in the gel-free proteomics database. A total of 44,704 proteins, including 5490 proteins identified using a gel-based proteomic technique, are stored in the SPD. It accounts for approximately 80% of all predicted proteins from

Integration of gel-based and gel-free proteomic data for functional analysis of proteins through Soybean Proteome Database

KAUST Repository

Komatsu, Setsuko; Wang, Xin; Yin, Xiaojian; Nanjo, Yohei; Ohyanagi, Hajime; Sakata, Katsumi

2017-01-01

The Soybean Proteome Database (SPD) stores data on soybean proteins obtained with gel-based and gel-free proteomic techniques. The database was constructed to provide information on proteins for functional analyses. The majority of the data is focused on soybean (Glycine max ‘Enrei’). The growth and yield of soybean are strongly affected by environmental stresses such as flooding. The database was originally constructed using data on soybean proteins separated by two-dimensional polyacrylamide gel electrophoresis, which is a gel-based proteomic technique. Since 2015, the database has been expanded to incorporate data obtained by label-free mass spectrometry-based quantitative proteomics, which is a gel-free proteomic technique. Here, the portions of the database consisting of gel-free proteomic data are described. The gel-free proteomic database contains 39,212 proteins identified in 63 sample sets, such as temporal and organ-specific samples of soybean plants grown under flooding stress or non-stressed conditions. In addition, data on organellar proteins identified in mitochondria, nuclei, and endoplasmic reticulum are stored. Furthermore, the database integrates multiple omics data such as genomics, transcriptomics, metabolomics, and proteomics. The SPD database is accessible at http://proteome.dc.affrc.go.jp/Soybean/. Biological significanceThe Soybean Proteome Database stores data obtained from both gel-based and gel-free proteomic techniques. The gel-free proteomic database comprises 39,212 proteins identified in 63 sample sets, such as different organs of soybean plants grown under flooding stress or non-stressed conditions in a time-dependent manner. In addition, organellar proteins identified in mitochondria, nuclei, and endoplasmic reticulum are stored in the gel-free proteomics database. A total of 44,704 proteins, including 5490 proteins identified using a gel-based proteomic technique, are stored in the SPD. It accounts for approximately 80% of all

Automatic annotation of protein motif function with Gene Ontology terms

Directory of Open Access Journals (Sweden)

Gopalakrishnan Vanathi

2004-09-01

Full Text Available Abstract Background Conserved protein sequence motifs are short stretches of amino acid sequence patterns that potentially encode the function of proteins. Several sequence pattern searching algorithms and programs exist foridentifying candidate protein motifs at the whole genome level. However, amuch needed and importanttask is to determine the functions of the newly identified protein motifs. The Gene Ontology (GO project is an endeavor to annotate the function of genes or protein sequences with terms from a dynamic, controlled vocabulary and these annotations serve well as a knowledge base. Results This paperpresents methods to mine the GO knowledge base and use the association between the GO terms assigned to a sequence and the motifs matched by the same sequence as evidence for predicting the functions of novel protein motifs automatically. The task of assigning GO terms to protein motifsis viewed as both a binary classification and information retrieval problem, where PROSITE motifs are used as samples for mode training and functional prediction. The mutual information of a motif and aGO term association isfound to be a very useful feature. We take advantageof the known motifs to train a logistic regression classifier, which allows us to combine mutual information with other frequency-based features and obtain a probability of correctassociation. The trained logistic regression model has intuitively meaningful and logically plausible parameter values, and performs very well empirically according to our evaluation criteria. Conclusions In this research, different methods for automatic annotation of protein motifs have been investigated. Empirical result demonstrated that the methods have a great potential for detecting and augmenting information about thefunctions of newly discovered candidate protein motifs.

Prediction of heterodimeric protein complexes from weighted protein-protein interaction networks using novel features and kernel functions.

Directory of Open Access Journals (Sweden)

Peiying Ruan

Full Text Available Since many proteins express their functional activity by interacting with other proteins and forming protein complexes, it is very useful to identify sets of proteins that form complexes. For that purpose, many prediction methods for protein complexes from protein-protein interactions have been developed such as MCL, MCODE, RNSC, PCP, RRW, and NWE. These methods have dealt with only complexes with size of more than three because the methods often are based on some density of subgraphs. However, heterodimeric protein complexes that consist of two distinct proteins occupy a large part according to several comprehensive databases of known complexes. In this paper, we propose several feature space mappings from protein-protein interaction data, in which each interaction is weighted based on reliability. Furthermore, we make use of prior knowledge on protein domains to develop feature space mappings, domain composition kernel and its combination kernel with our proposed features. We perform ten-fold cross-validation computational experiments. These results suggest that our proposed kernel considerably outperforms the naive Bayes-based method, which is the best existing method for predicting heterodimeric protein complexes.

Architectures and Functional Coverage of Protein-Protein Interfaces

Science.gov (United States)

Tuncbag, Nurcan; Gursoy, Attila; Guney, Emre; Nussinov, Ruth; Keskin, Ozlem

2008-01-01

The diverse range of cellular functions is performed by a limited number of protein folds existing in nature. One may similarly expect that cellular functional diversity would be covered by a limited number of protein-protein interface architectures. Here, we present 8205 interface clusters, each representing unique interface architecture. This dataset of protein-protein interfaces is analyzed and compared with older datasets. We observe that the number of both biological and crystal interfaces increase significantly compared to the number of PDB entries. Further, we find that the number of distinct interface architectures grows at a much faster rate than the number of folds and is yet to level off. We further analyze the growth trend of the functional coverage by constructing functional interaction networks from interfaces. The functional coverage is also found to steadily increase. Interestingly, we also observe that despite the diversity of interface architectures, some are more favorable and frequently used, and of particular interest, those are the ones which are also preferred in single chains. PMID:18620705

Proteins of unknown function in the Protein Data Bank (PDB): an inventory of true uncharacterized proteins and computational tools for their analysis.

Science.gov (United States)

Nadzirin, Nurul; Firdaus-Raih, Mohd

2012-10-08

Proteins of uncharacterized functions form a large part of many of the currently available biological databases and this situation exists even in the Protein Data Bank (PDB). Our analysis of recent PDB data revealed that only 42.53% of PDB entries (1084 coordinate files) that were categorized under "unknown function" are true examples of proteins of unknown function at this point in time. The remainder 1465 entries also annotated as such appear to be able to have their annotations re-assessed, based on the availability of direct functional characterization experiments for the protein itself, or for homologous sequences or structures thus enabling computational function inference.

A three-way approach for protein function classification.

Directory of Open Access Journals (Sweden)

Hafeez Ur Rehman

Full Text Available The knowledge of protein functions plays an essential role in understanding biological cells and has a significant impact on human life in areas such as personalized medicine, better crops and improved therapeutic interventions. Due to expense and inherent difficulty of biological experiments, intelligent methods are generally relied upon for automatic assignment of functions to proteins. The technological advancements in the field of biology are improving our understanding of biological processes and are regularly resulting in new features and characteristics that better describe the role of proteins. It is inevitable to neglect and overlook these anticipated features in designing more effective classification techniques. A key issue in this context, that is not being sufficiently addressed, is how to build effective classification models and approaches for protein function prediction by incorporating and taking advantage from the ever evolving biological information. In this article, we propose a three-way decision making approach which provides provisions for seeking and incorporating future information. We considered probabilistic rough sets based models such as Game-Theoretic Rough Sets (GTRS and Information-Theoretic Rough Sets (ITRS for inducing three-way decisions. An architecture of protein functions classification with probabilistic rough sets based three-way decisions is proposed and explained. Experiments are carried out on Saccharomyces cerevisiae species dataset obtained from Uniprot database with the corresponding functional classes extracted from the Gene Ontology (GO database. The results indicate that as the level of biological information increases, the number of deferred cases are reduced while maintaining similar level of accuracy.

Synthesis and characterization of recombinant abductin-based proteins.

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Su, Renay S-C; Renner, Julie N; Liu, Julie C

2013-12-09

Recombinant proteins are promising tools for tissue engineering and drug delivery applications. Protein-based biomaterials have several advantages over natural and synthetic polymers, including precise control over amino acid composition and molecular weight, modular swapping of functional domains, and tunable mechanical and physical properties. In this work, we describe recombinant proteins based on abductin, an elastomeric protein that is found in the inner hinge of bivalves and functions as a coil spring to keep shells open. We illustrate, for the first time, the design, cloning, expression, and purification of a recombinant protein based on consensus abductin sequences derived from Argopecten irradians . The molecular weight of the protein was confirmed by mass spectrometry, and the protein was 94% pure. Circular dichroism studies showed that the dominant structures of abductin-based proteins were polyproline II helix structures in aqueous solution and type II β-turns in trifluoroethanol. Dynamic light scattering studies illustrated that the abductin-based proteins exhibit reversible upper critical solution temperature behavior and irreversible aggregation behavior at high temperatures. A LIVE/DEAD assay revealed that human umbilical vein endothelial cells had a viability of 98 ± 4% after being cultured for two days on the abductin-based protein. Initial cell spreading on the abductin-based protein was similar to that on bovine serum albumin. These studies thus demonstrate the potential of abductin-based proteins in tissue engineering and drug delivery applications due to the cytocompatibility and its response to temperature.

Functional equivalency inferred from "authoritative sources" in networks of homologous proteins.

Science.gov (United States)

Natarajan, Shreedhar; Jakobsson, Eric

2009-06-12

A one-on-one mapping of protein functionality across different species is a critical component of comparative analysis. This paper presents a heuristic algorithm for discovering the Most Likely Functional Counterparts (MoLFunCs) of a protein, based on simple concepts from network theory. A key feature of our algorithm is utilization of the user's knowledge to assign high confidence to selected functional identification. We show use of the algorithm to retrieve functional equivalents for 7 membrane proteins, from an exploration of almost 40 genomes form multiple online resources. We verify the functional equivalency of our dataset through a series of tests that include sequence, structure and function comparisons. Comparison is made to the OMA methodology, which also identifies one-on-one mapping between proteins from different species. Based on that comparison, we believe that incorporation of user's knowledge as a key aspect of the technique adds value to purely statistical formal methods.

Proteins of Unknown Function in the Protein Data Bank (PDB: An Inventory of True Uncharacterized Proteins and Computational Tools for Their Analysis

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Nurul Nadzirin

2012-10-01

Full Text Available Proteins of uncharacterized functions form a large part of many of the currently available biological databases and this situation exists even in the Protein Data Bank (PDB. Our analysis of recent PDB data revealed that only 42.53% of PDB entries (1084 coordinate files that were categorized under “unknown function” are true examples of proteins of unknown function at this point in time. The remainder 1465 entries also annotated as such appear to be able to have their annotations re-assessed, based on the availability of direct functional characterization experiments for the protein itself, or for homologous sequences or structures thus enabling computational function inference.

Chaos game representation of functional protein sequences, and simulation and multifractal analysis of induced measures

International Nuclear Information System (INIS)

Zu-Guo, Yu; Qian-Jun, Xiao; Long, Shi; Jun-Wu, Yu; Anh, Vo

2010-01-01

Investigating the biological function of proteins is a key aspect of protein studies. Bioinformatic methods become important for studying the biological function of proteins. In this paper, we first give the chaos game representation (CGR) of randomly-linked functional protein sequences, then propose the use of the recurrent iterated function systems (RIFS) in fractal theory to simulate the measure based on their chaos game representations. This method helps to extract some features of functional protein sequences, and furthermore the biological functions of these proteins. Then multifractal analysis of the measures based on the CGRs of randomly-linked functional protein sequences are performed. We find that the CGRs have clear fractal patterns. The numerical results show that the RIFS can simulate the measure based on the CGR very well. The relative standard error and the estimated probability matrix in the RIFS do not depend on the order to link the functional protein sequences. The estimated probability matrices in the RIFS with different biological functions are evidently different. Hence the estimated probability matrices in the RIFS can be used to characterise the difference among linked functional protein sequences with different biological functions. From the values of the D q curves, one sees that these functional protein sequences are not completely random. The D q of all linked functional proteins studied are multifractal-like and sufficiently smooth for the C q (analogous to specific heat) curves to be meaningful. Furthermore, the D q curves of the measure μ based on their CGRs for different orders to link the functional protein sequences are almost identical if q ≥ 0. Finally, the C q curves of all linked functional proteins resemble a classical phase transition at a critical point. (cross-disciplinary physics and related areas of science and technology)

Phytochemicals perturb membranes and promiscuously alter protein function.

Science.gov (United States)

Ingólfsson, Helgi I; Thakur, Pratima; Herold, Karl F; Hobart, E Ashley; Ramsey, Nicole B; Periole, Xavier; de Jong, Djurre H; Zwama, Martijn; Yilmaz, Duygu; Hall, Katherine; Maretzky, Thorsten; Hemmings, Hugh C; Blobel, Carl; Marrink, Siewert J; Koçer, Armağan; Sack, Jon T; Andersen, Olaf S

2014-08-15

A wide variety of phytochemicals are consumed for their perceived health benefits. Many of these phytochemicals have been found to alter numerous cell functions, but the mechanisms underlying their biological activity tend to be poorly understood. Phenolic phytochemicals are particularly promiscuous modifiers of membrane protein function, suggesting that some of their actions may be due to a common, membrane bilayer-mediated mechanism. To test whether bilayer perturbation may underlie this diversity of actions, we examined five bioactive phenols reported to have medicinal value: capsaicin from chili peppers, curcumin from turmeric, EGCG from green tea, genistein from soybeans, and resveratrol from grapes. We find that each of these widely consumed phytochemicals alters lipid bilayer properties and the function of diverse membrane proteins. Molecular dynamics simulations show that these phytochemicals modify bilayer properties by localizing to the bilayer/solution interface. Bilayer-modifying propensity was verified using a gramicidin-based assay, and indiscriminate modulation of membrane protein function was demonstrated using four proteins: membrane-anchored metalloproteases, mechanosensitive ion channels, and voltage-dependent potassium and sodium channels. Each protein exhibited similar responses to multiple phytochemicals, consistent with a common, bilayer-mediated mechanism. Our results suggest that many effects of amphiphilic phytochemicals are due to cell membrane perturbations, rather than specific protein binding.

Simulation of Protein and Peptide-Based Biomaterials

National Research Council Canada - National Science Library

Daggett, Valerie

2002-01-01

The overall goal of the proposed research is to pursue realistic molecular modeling studies of the stability, dynamics, structure, function, and folding of proteins and protein-based biomaterials in solution...

Origins of Protein Functions in Cells

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Seelig, Burchard; Pohorille, Andrzej

2011-01-01

In modern organisms proteins perform a majority of cellular functions, such as chemical catalysis, energy transduction and transport of material across cell walls. Although great strides have been made towards understanding protein evolution, a meaningful extrapolation from contemporary proteins to their earliest ancestors is virtually impossible. In an alternative approach, the origin of water-soluble proteins was probed through the synthesis and in vitro evolution of very large libraries of random amino acid sequences. In combination with computer modeling and simulations, these experiments allow us to address a number of fundamental questions about the origins of proteins. Can functionality emerge from random sequences of proteins? How did the initial repertoire of functional proteins diversify to facilitate new functions? Did this diversification proceed primarily through drawing novel functionalities from random sequences or through evolution of already existing proto-enzymes? Did protein evolution start from a pool of proteins defined by a frozen accident and other collections of proteins could start a different evolutionary pathway? Although we do not have definitive answers to these questions yet, important clues have been uncovered. In one example (Keefe and Szostak, 2001), novel ATP binding proteins were identified that appear to be unrelated in both sequence and structure to any known ATP binding proteins. One of these proteins was subsequently redesigned computationally to bind GTP through introducing several mutations that introduce targeted structural changes to the protein, improve its binding to guanine and prevent water from accessing the active center. This study facilitates further investigations of individual evolutionary steps that lead to a change of function in primordial proteins. In a second study (Seelig and Szostak, 2007), novel enzymes were generated that can join two pieces of RNA in a reaction for which no natural enzymes are known

Experimental parameterization of an energy function for the simulation of unfolded proteins

DEFF Research Database (Denmark)

Norgaard, A.B.; Ferkinghoff-Borg, Jesper; Lindorff-Larsen, K.

2008-01-01

The determination of conformational preferences in unfolded and disordered proteins is an important challenge in structural biology. We here describe an algorithm to optimize energy functions for the simulation of unfolded proteins. The procedure is based on the maximum likelihood principle and e...... and can be applied to a range of experimental data and energy functions including the force fields used in molecular dynamics simulations.......The determination of conformational preferences in unfolded and disordered proteins is an important challenge in structural biology. We here describe an algorithm to optimize energy functions for the simulation of unfolded proteins. The procedure is based on the maximum likelihood principle...

Feline coronavirus: Insights into viral pathogenesis based on the spike protein structure and function.

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Jaimes, Javier A; Whittaker, Gary R

2018-04-01

Feline coronavirus (FCoV) is an etiological agent that causes a benign enteric illness and the fatal systemic disease feline infectious peritonitis (FIP). The FCoV spike (S) protein is considered the viral regulator for binding and entry to the cell. This protein is also involved in FCoV tropism and virulence, as well as in the switch from enteric disease to FIP. This regulation is carried out by spike's major functions: receptor binding and virus-cell membrane fusion. In this review, we address important aspects in FCoV genetics, replication and pathogenesis, focusing on the role of S. To better understand this, FCoV S protein models were constructed, based on the human coronavirus NL63 (HCoV-NL63) S structure. We describe the specific structural characteristics of the FCoV S, in comparison with other coronavirus spikes. We also revise the biochemical events needed for FCoV S activation and its relation to the structural features of the protein. Copyright © 2018 Elsevier Inc. All rights reserved.

One-step synthesis of DNA functionalized cadmium-free quantum dots and its application in FRET-based protein sensing

Energy Technology Data Exchange (ETDEWEB)

Zhang, Cuiling, E-mail: clzhang@chem.ecnu.edu.cn [Department of Chemistry, School of Chemistry and Molecular Engineering, East China Normal University, Shanghai 200241 (China); Ding, Caiping [Department of Chemistry, School of Chemistry and Molecular Engineering, East China Normal University, Shanghai 200241 (China); Zhou, Guohua [School of Chemistry and Chemical Engineering, Lingnan Normal University, Zhanjiang, 524048 (China); Xue, Qin [Department of Chemistry, School of Chemistry and Molecular Engineering, East China Normal University, Shanghai 200241 (China); Xian, Yuezhong, E-mail: yzxian@chem.ecnu.edu.cn [Department of Chemistry, School of Chemistry and Molecular Engineering, East China Normal University, Shanghai 200241 (China)

2017-03-08

DNA functionalized quantum dots (QDs) are promising nanoprobes for the fluorescence resonance energy transfer (FRET)-based biosensing. Herein, cadmium-free DNA functionalized Mn-doped ZnS (DNA-ZnS:Mn{sup 2+}) QDs were successfully synthesized by one-step route. As-synthesized QDs show excellent photo-stability with the help of PAA and DNA. Then, we constructed a novel FRET model based on the QDs and WS{sub 2} nanosheets as the energy donor-acceptor pairs, which was successfully applied for the protein detection through the terminal protection of small molecule-linked DNA assay. This work not only explores the potential bioapplication of the DNA-ZnS:Mn{sup 2+} QDs, but also provides a platform for the investigation of small molecule-protein interaction. - Highlights: • The stable and cadmium-free DNA functionalized ZnS:Mn{sup 2+} QDs were successfully synthesized through a facile one-step route. • We constructed a novel FRET system based on one-step synthesized DNA-ZnS:Mn{sup 2+} QDs (donor) and WS{sub 2} nanosheets (acceptor). • The FRET-based strategy was applied for the detection of streptavidin and folate receptor by combining TPSMLD and Exo III.

Prediction of human protein function from post-translational modifications and localization features

DEFF Research Database (Denmark)

Jensen, Lars Juhl; Gupta, Ramneek; Blom, Nikolaj

2002-01-01

a number of functional attributes that are more directly related to the linear sequence of amino acids, and hence easier to predict, than protein structure. These attributes include features associated with post-translational modifications and protein sorting, but also much simpler aspects......We have developed an entirely sequence-based method that identifies and integrates relevant features that can be used to assign proteins of unknown function to functional classes, and enzyme categories for enzymes. We show that strategies for the elucidation of protein function may benefit from...

Wiki-pi: a web-server of annotated human protein-protein interactions to aid in discovery of protein function.

Directory of Open Access Journals (Sweden)

Naoki Orii

Full Text Available Protein-protein interactions (PPIs are the basis of biological functions. Knowledge of the interactions of a protein can help understand its molecular function and its association with different biological processes and pathways. Several publicly available databases provide comprehensive information about individual proteins, such as their sequence, structure, and function. There also exist databases that are built exclusively to provide PPIs by curating them from published literature. The information provided in these web resources is protein-centric, and not PPI-centric. The PPIs are typically provided as lists of interactions of a given gene with links to interacting partners; they do not present a comprehensive view of the nature of both the proteins involved in the interactions. A web database that allows search and retrieval based on biomedical characteristics of PPIs is lacking, and is needed. We present Wiki-Pi (read Wiki-π, a web-based interface to a database of human PPIs, which allows users to retrieve interactions by their biomedical attributes such as their association to diseases, pathways, drugs and biological functions. Each retrieved PPI is shown with annotations of both of the participant proteins side-by-side, creating a basis to hypothesize the biological function facilitated by the interaction. Conceptually, it is a search engine for PPIs analogous to PubMed for scientific literature. Its usefulness in generating novel scientific hypotheses is demonstrated through the study of IGSF21, a little-known gene that was recently identified to be associated with diabetic retinopathy. Using Wiki-Pi, we infer that its association to diabetic retinopathy may be mediated through its interactions with the genes HSPB1, KRAS, TMSB4X and DGKD, and that it may be involved in cellular response to external stimuli, cytoskeletal organization and regulation of molecular activity. The website also provides a wiki-like capability allowing users

Protein-protein docking using region-based 3D Zernike descriptors.

Science.gov (United States)

Venkatraman, Vishwesh; Yang, Yifeng D; Sael, Lee; Kihara, Daisuke

2009-12-09

Protein-protein interactions are a pivotal component of many biological processes and mediate a variety of functions. Knowing the tertiary structure of a protein complex is therefore essential for understanding the interaction mechanism. However, experimental techniques to solve the structure of the complex are often found to be difficult. To this end, computational protein-protein docking approaches can provide a useful alternative to address this issue. Prediction of docking conformations relies on methods that effectively capture shape features of the participating proteins while giving due consideration to conformational changes that may occur. We present a novel protein docking algorithm based on the use of 3D Zernike descriptors as regional features of molecular shape. The key motivation of using these descriptors is their invariance to transformation, in addition to a compact representation of local surface shape characteristics. Docking decoys are generated using geometric hashing, which are then ranked by a scoring function that incorporates a buried surface area and a novel geometric complementarity term based on normals associated with the 3D Zernike shape description. Our docking algorithm was tested on both bound and unbound cases in the ZDOCK benchmark 2.0 dataset. In 74% of the bound docking predictions, our method was able to find a near-native solution (interface C-alphaRMSD 3D Zernike descriptors are adept in capturing shape complementarity at the protein-protein interface and useful for protein docking prediction. Rigorous benchmark studies show that our docking approach has a superior performance compared to existing methods.

Functional assignment to JEV proteins using SVM.

Science.gov (United States)

Sahoo, Ganesh Chandra; Dikhit, Manas Ranjan; Das, Pradeep

2008-01-01

Identification of different protein functions facilitates a mechanistic understanding of Japanese encephalitis virus (JEV) infection and opens novel means for drug development. Support vector machines (SVM), useful for predicting the functional class of distantly related proteins, is employed to ascribe a possible functional class to Japanese encephalitis virus protein. Our study from SVMProt and available JE virus sequences suggests that structural and nonstructural proteins of JEV genome possibly belong to diverse protein functions, are expected to occur in the life cycle of JE virus. Protein functions common to both structural and non-structural proteins are iron-binding, metal-binding, lipid-binding, copper-binding, transmembrane, outer membrane, channels/Pores - Pore-forming toxins (proteins and peptides) group of proteins. Non-structural proteins perform functions like actin binding, zinc-binding, calcium-binding, hydrolases, Carbon-Oxygen Lyases, P-type ATPase, proteins belonging to major facilitator family (MFS), secreting main terminal branch (MTB) family, phosphotransfer-driven group translocators and ATP-binding cassette (ABC) family group of proteins. Whereas structural proteins besides belonging to same structural group of proteins (capsid, structural, envelope), they also perform functions like nuclear receptor, antibiotic resistance, RNA-binding, DNA-binding, magnesium-binding, isomerase (intra-molecular), oxidoreductase and participate in type II (general) secretory pathway (IISP).

Collective estimation of multiple bivariate density functions with application to angular-sampling-based protein loop modeling

KAUST Repository

Maadooliat, Mehdi

2015-10-21

This paper develops a method for simultaneous estimation of density functions for a collection of populations of protein backbone angle pairs using a data-driven, shared basis that is constructed by bivariate spline functions defined on a triangulation of the bivariate domain. The circular nature of angular data is taken into account by imposing appropriate smoothness constraints across boundaries of the triangles. Maximum penalized likelihood is used to fit the model and an alternating blockwise Newton-type algorithm is developed for computation. A simulation study shows that the collective estimation approach is statistically more efficient than estimating the densities individually. The proposed method was used to estimate neighbor-dependent distributions of protein backbone dihedral angles (i.e., Ramachandran distributions). The estimated distributions were applied to protein loop modeling, one of the most challenging open problems in protein structure prediction, by feeding them into an angular-sampling-based loop structure prediction framework. Our estimated distributions compared favorably to the Ramachandran distributions estimated by fitting a hierarchical Dirichlet process model; and in particular, our distributions showed significant improvements on the hard cases where existing methods do not work well.

Collective estimation of multiple bivariate density functions with application to angular-sampling-based protein loop modeling

KAUST Repository

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

2015-01-01

This paper develops a method for simultaneous estimation of density functions for a collection of populations of protein backbone angle pairs using a data-driven, shared basis that is constructed by bivariate spline functions defined on a triangulation of the bivariate domain. The circular nature of angular data is taken into account by imposing appropriate smoothness constraints across boundaries of the triangles. Maximum penalized likelihood is used to fit the model and an alternating blockwise Newton-type algorithm is developed for computation. A simulation study shows that the collective estimation approach is statistically more efficient than estimating the densities individually. The proposed method was used to estimate neighbor-dependent distributions of protein backbone dihedral angles (i.e., Ramachandran distributions). The estimated distributions were applied to protein loop modeling, one of the most challenging open problems in protein structure prediction, by feeding them into an angular-sampling-based loop structure prediction framework. Our estimated distributions compared favorably to the Ramachandran distributions estimated by fitting a hierarchical Dirichlet process model; and in particular, our distributions showed significant improvements on the hard cases where existing methods do not work well.

Protein-protein interaction site prediction in Homo sapiens and E. coli using an interaction-affinity based membership function in fuzzy SVM.

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Sriwastava, Brijesh Kumar; Basu, Subhadip; Maulik, Ujjwal

2015-10-01

Protein-protein interaction (PPI) site prediction aids to ascertain the interface residues that participate in interaction processes. Fuzzy support vector machine (F-SVM) is proposed as an effective method to solve this problem, and we have shown that the performance of the classical SVM can be enhanced with the help of an interaction-affinity based fuzzy membership function. The performances of both SVM and F-SVM on the PPI databases of the Homo sapiens and E. coli organisms are evaluated and estimated the statistical significance of the developed method over classical SVM and other fuzzy membership-based SVM methods available in the literature. Our membership function uses the residue-level interaction affinity scores for each pair of positive and negative sequence fragments. The average AUC scores in the 10-fold cross-validation experiments are measured as 79.94% and 80.48% for the Homo sapiens and E. coli organisms respectively. On the independent test datasets, AUC scores are obtained as 76.59% and 80.17% respectively for the two organisms. In almost all cases, the developed F-SVM method improves the performances obtained by the corresponding classical SVM and the other classifiers, available in the literature.

Biases in the experimental annotations of protein function and their effect on our understanding of protein function space.

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Alexandra M Schnoes

Full Text Available The ongoing functional annotation of proteins relies upon the work of curators to capture experimental findings from scientific literature and apply them to protein sequence and structure data. However, with the increasing use of high-throughput experimental assays, a small number of experimental studies dominate the functional protein annotations collected in databases. Here, we investigate just how prevalent is the "few articles - many proteins" phenomenon. We examine the experimentally validated annotation of proteins provided by several groups in the GO Consortium, and show that the distribution of proteins per published study is exponential, with 0.14% of articles providing the source of annotations for 25% of the proteins in the UniProt-GOA compilation. Since each of the dominant articles describes the use of an assay that can find only one function or a small group of functions, this leads to substantial biases in what we know about the function of many proteins. Mass-spectrometry, microscopy and RNAi experiments dominate high throughput experiments. Consequently, the functional information derived from these experiments is mostly of the subcellular location of proteins, and of the participation of proteins in embryonic developmental pathways. For some organisms, the information provided by different studies overlap by a large amount. We also show that the information provided by high throughput experiments is less specific than those provided by low throughput experiments. Given the experimental techniques available, certain biases in protein function annotation due to high-throughput experiments are unavoidable. Knowing that these biases exist and understanding their characteristics and extent is important for database curators, developers of function annotation programs, and anyone who uses protein function annotation data to plan experiments.

Biases in the Experimental Annotations of Protein Function and Their Effect on Our Understanding of Protein Function Space

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Schnoes, Alexandra M.; Ream, David C.; Thorman, Alexander W.; Babbitt, Patricia C.; Friedberg, Iddo

2013-01-01

The ongoing functional annotation of proteins relies upon the work of curators to capture experimental findings from scientific literature and apply them to protein sequence and structure data. However, with the increasing use of high-throughput experimental assays, a small number of experimental studies dominate the functional protein annotations collected in databases. Here, we investigate just how prevalent is the “few articles - many proteins” phenomenon. We examine the experimentally validated annotation of proteins provided by several groups in the GO Consortium, and show that the distribution of proteins per published study is exponential, with 0.14% of articles providing the source of annotations for 25% of the proteins in the UniProt-GOA compilation. Since each of the dominant articles describes the use of an assay that can find only one function or a small group of functions, this leads to substantial biases in what we know about the function of many proteins. Mass-spectrometry, microscopy and RNAi experiments dominate high throughput experiments. Consequently, the functional information derived from these experiments is mostly of the subcellular location of proteins, and of the participation of proteins in embryonic developmental pathways. For some organisms, the information provided by different studies overlap by a large amount. We also show that the information provided by high throughput experiments is less specific than those provided by low throughput experiments. Given the experimental techniques available, certain biases in protein function annotation due to high-throughput experiments are unavoidable. Knowing that these biases exist and understanding their characteristics and extent is important for database curators, developers of function annotation programs, and anyone who uses protein function annotation data to plan experiments. PMID:23737737

AVID: An integrative framework for discovering functional relationships among proteins

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Keating Amy E

2005-06-01

Full Text Available Abstract Background Determining the functions of uncharacterized proteins is one of the most pressing problems in the post-genomic era. Large scale protein-protein interaction assays, global mRNA expression analyses and systematic protein localization studies provide experimental information that can be used for this purpose. The data from such experiments contain many false positives and false negatives, but can be processed using computational methods to provide reliable information about protein-protein relationships and protein function. An outstanding and important goal is to predict detailed functional annotation for all uncharacterized proteins that is reliable enough to effectively guide experiments. Results We present AVID, a computational method that uses a multi-stage learning framework to integrate experimental results with sequence information, generating networks reflecting functional similarities among proteins. We illustrate use of the networks by making predictions of detailed Gene Ontology (GO annotations in three categories: molecular function, biological process, and cellular component. Applied to the yeast Saccharomyces cerevisiae, AVID provides 37,451 pair-wise functional linkages between 4,191 proteins. These relationships are ~65–78% accurate, as assessed by cross-validation testing. Assignments of highly detailed functional descriptors to proteins, based on the networks, are estimated to be ~67% accurate for GO categories describing molecular function and cellular component and ~52% accurate for terms describing biological process. The predictions cover 1,490 proteins with no previous annotation in GO and also assign more detailed functions to many proteins annotated only with less descriptive terms. Predictions made by AVID are largely distinct from those made by other methods. Out of 37,451 predicted pair-wise relationships, the greatest number shared in common with another method is 3,413. Conclusion AVID provides

Functionalized linear poly(amidoamine)s are efficient vectors for intracellular protein delivery

NARCIS (Netherlands)

Coué, G.M.J.P.C.; Engbersen, Johannes F.J.

2011-01-01

An effective intracellular protein delivery system was developed based on functionalized linear poly(amidoamine)s (PAAs) that form self-assembled cationic nanocomplexes with oppositely charged proteins. Three differently functionalized PAAs were synthesized, two of these having repetitive disulfide

Growing functional modules from a seed protein via integration of protein interaction and gene expression data

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Dimitrakopoulou Konstantina

2007-10-01

Full Text Available Abstract Background Nowadays modern biology aims at unravelling the strands of complex biological structures such as the protein-protein interaction (PPI networks. A key concept in the organization of PPI networks is the existence of dense subnetworks (functional modules in them. In recent approaches clustering algorithms were applied at these networks and the resulting subnetworks were evaluated by estimating the coverage of well-established protein complexes they contained. However, most of these algorithms elaborate on an unweighted graph structure which in turn fails to elevate those interactions that would contribute to the construction of biologically more valid and coherent functional modules. Results In the current study, we present a method that corroborates the integration of protein interaction and microarray data via the discovery of biologically valid functional modules. Initially the gene expression information is overlaid as weights onto the PPI network and the enriched PPI graph allows us to exploit its topological aspects, while simultaneously highlights enhanced functional association in specific pairs of proteins. Then we present an algorithm that unveils the functional modules of the weighted graph by expanding a kernel protein set, which originates from a given 'seed' protein used as starting-point. Conclusion The integrated data and the concept of our approach provide reliable functional modules. We give proofs based on yeast data that our method manages to give accurate results in terms both of structural coherency, as well as functional consistency.

Protein-protein docking using region-based 3D Zernike descriptors

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Sael Lee

2009-12-01

Full Text Available Abstract Background Protein-protein interactions are a pivotal component of many biological processes and mediate a variety of functions. Knowing the tertiary structure of a protein complex is therefore essential for understanding the interaction mechanism. However, experimental techniques to solve the structure of the complex are often found to be difficult. To this end, computational protein-protein docking approaches can provide a useful alternative to address this issue. Prediction of docking conformations relies on methods that effectively capture shape features of the participating proteins while giving due consideration to conformational changes that may occur. Results We present a novel protein docking algorithm based on the use of 3D Zernike descriptors as regional features of molecular shape. The key motivation of using these descriptors is their invariance to transformation, in addition to a compact representation of local surface shape characteristics. Docking decoys are generated using geometric hashing, which are then ranked by a scoring function that incorporates a buried surface area and a novel geometric complementarity term based on normals associated with the 3D Zernike shape description. Our docking algorithm was tested on both bound and unbound cases in the ZDOCK benchmark 2.0 dataset. In 74% of the bound docking predictions, our method was able to find a near-native solution (interface C-αRMSD ≤ 2.5 Å within the top 1000 ranks. For unbound docking, among the 60 complexes for which our algorithm returned at least one hit, 60% of the cases were ranked within the top 2000. Comparison with existing shape-based docking algorithms shows that our method has a better performance than the others in unbound docking while remaining competitive for bound docking cases. Conclusion We show for the first time that the 3D Zernike descriptors are adept in capturing shape complementarity at the protein-protein interface and useful for

MM-ISMSA: An Ultrafast and Accurate Scoring Function for Protein-Protein Docking.

Science.gov (United States)

Klett, Javier; Núñez-Salgado, Alfonso; Dos Santos, Helena G; Cortés-Cabrera, Álvaro; Perona, Almudena; Gil-Redondo, Rubén; Abia, David; Gago, Federico; Morreale, Antonio

2012-09-11

An ultrafast and accurate scoring function for protein-protein docking is presented. It includes (1) a molecular mechanics (MM) part based on a 12-6 Lennard-Jones potential; (2) an electrostatic component based on an implicit solvent model (ISM) with individual desolvation penalties for each partner in the protein-protein complex plus a hydrogen bonding term; and (3) a surface area (SA) contribution to account for the loss of water contacts upon protein-protein complex formation. The accuracy and performance of the scoring function, termed MM-ISMSA, have been assessed by (1) comparing the total binding energies, the electrostatic term, and its components (charge-charge and individual desolvation energies), as well as the per residue contributions, to results obtained with well-established methods such as APBSA or MM-PB(GB)SA for a set of 1242 decoy protein-protein complexes and (2) testing its ability to recognize the docking solution closest to the experimental structure as that providing the most favorable total binding energy. For this purpose, a test set consisting of 15 protein-protein complexes with known 3D structure mixed with 10 decoys for each complex was used. The correlation between the values afforded by MM-ISMSA and those from the other methods is quite remarkable (r(2) ∼ 0.9), and only 0.2-5.0 s (depending on the number of residues) are spent on a single calculation including an all vs all pairwise energy decomposition. On the other hand, MM-ISMSA correctly identifies the best docking solution as that closest to the experimental structure in 80% of the cases. Finally, MM-ISMSA can process molecular dynamics trajectories and reports the results as averaged values with their standard deviations. MM-ISMSA has been implemented as a plugin to the widely used molecular graphics program PyMOL, although it can also be executed in command-line mode. MM-ISMSA is distributed free of charge to nonprofit organizations.

Intuitive Density Functional Theory-Based Energy Decomposition Analysis for Protein-Ligand Interactions.

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Phipps, M J S; Fox, T; Tautermann, C S; Skylaris, C-K

2017-04-11

First-principles quantum mechanical calculations with methods such as density functional theory (DFT) allow the accurate calculation of interaction energies between molecules. These interaction energies can be dissected into chemically relevant components such as electrostatics, polarization, and charge transfer using energy decomposition analysis (EDA) approaches. Typically EDA has been used to study interactions between small molecules; however, it has great potential to be applied to large biomolecular assemblies such as protein-protein and protein-ligand interactions. We present an application of EDA calculations to the study of ligands that bind to the thrombin protein, using the ONETEP program for linear-scaling DFT calculations. Our approach goes beyond simply providing the components of the interaction energy; we are also able to provide visual representations of the changes in density that happen as a result of polarization and charge transfer, thus pinpointing the functional groups between the ligand and protein that participate in each kind of interaction. We also demonstrate with this approach that we can focus on studying parts (fragments) of ligands. The method is relatively insensitive to the protocol that is used to prepare the structures, and the results obtained are therefore robust. This is an application to a real protein drug target of a whole new capability where accurate DFT calculations can produce both energetic and visual descriptors of interactions. These descriptors can be used to provide insights for tailoring interactions, as needed for example in drug design.

A discriminatory function for prediction of protein-DNA interactions based on alpha shape modeling.

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Zhou, Weiqiang; Yan, Hong

2010-10-15

Protein-DNA interaction has significant importance in many biological processes. However, the underlying principle of the molecular recognition process is still largely unknown. As more high-resolution 3D structures of protein-DNA complex are becoming available, the surface characteristics of the complex become an important research topic. In our work, we apply an alpha shape model to represent the surface structure of the protein-DNA complex and developed an interface-atom curvature-dependent conditional probability discriminatory function for the prediction of protein-DNA interaction. The interface-atom curvature-dependent formalism captures atomic interaction details better than the atomic distance-based method. The proposed method provides good performance in discriminating the native structures from the docking decoy sets, and outperforms the distance-dependent formalism in terms of the z-score. Computer experiment results show that the curvature-dependent formalism with the optimal parameters can achieve a native z-score of -8.17 in discriminating the native structure from the highest surface-complementarity scored decoy set and a native z-score of -7.38 in discriminating the native structure from the lowest RMSD decoy set. The interface-atom curvature-dependent formalism can also be used to predict apo version of DNA-binding proteins. These results suggest that the interface-atom curvature-dependent formalism has a good prediction capability for protein-DNA interactions. The code and data sets are available for download on http://www.hy8.com/bioinformatics.htm kenandzhou@hotmail.com.

Integration of relational and hierarchical network information for protein function prediction

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Jiang Xiaoyu

2008-08-01

Full Text Available Abstract Background In the current climate of high-throughput computational biology, the inference of a protein's function from related measurements, such as protein-protein interaction relations, has become a canonical task. Most existing technologies pursue this task as a classification problem, on a term-by-term basis, for each term in a database, such as the Gene Ontology (GO database, a popular rigorous vocabulary for biological functions. However, ontology structures are essentially hierarchies, with certain top to bottom annotation rules which protein function predictions should in principle follow. Currently, the most common approach to imposing these hierarchical constraints on network-based classifiers is through the use of transitive closure to predictions. Results We propose a probabilistic framework to integrate information in relational data, in the form of a protein-protein interaction network, and a hierarchically structured database of terms, in the form of the GO database, for the purpose of protein function prediction. At the heart of our framework is a factorization of local neighborhood information in the protein-protein interaction network across successive ancestral terms in the GO hierarchy. We introduce a classifier within this framework, with computationally efficient implementation, that produces GO-term predictions that naturally obey a hierarchical 'true-path' consistency from root to leaves, without the need for further post-processing. Conclusion A cross-validation study, using data from the yeast Saccharomyces cerevisiae, shows our method offers substantial improvements over both standard 'guilt-by-association' (i.e., Nearest-Neighbor and more refined Markov random field methods, whether in their original form or when post-processed to artificially impose 'true-path' consistency. Further analysis of the results indicates that these improvements are associated with increased predictive capabilities (i.e., increased

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.

Analysis of hepatocellular carcinoma and metastatic hepatic carcinoma via functional modules in a protein-protein interaction network

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Jun Pan

2014-01-01

Full Text Available Introduction: This study aims to identify protein clusters with potential functional relevance in the pathogenesis of hepatocellular carcinoma (HCC and metastatic hepatic carcinoma using network analysis. Materials and Methods: We used human protein interaction data to build a protein-protein interaction network with Cytoscape and then derived functional clusters using MCODE. Combining the gene expression profiles, we calculated the functional scores for the clusters and selected statistically significant clusters. Meanwhile, Gene Ontology was used to assess the functionality of these clusters. Finally, a support vector machine was trained on the gold standard data sets. Results: The differentially expressed genes of HCC were mainly involved in metabolic and signaling processes. We acquired 13 significant modules from the gene expression profiles. The area under the curve value based on the differentially expressed modules were 98.31%, which outweighed the classification with DEGs. Conclusions: Differentially expressed modules are valuable to screen biomarkers combined with functional modules.

Design of sweet protein based sweeteners: hints from structure-function relationships.

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Rega, Michele Fortunato; Di Monaco, Rossella; Leone, Serena; Donnarumma, Federica; Spadaccini, Roberta; Cavella, Silvana; Picone, Delia

2015-04-15

Sweet proteins represent a class of natural molecules, which are extremely interesting regarding their potential use as safe low-calories sweeteners for individuals who need to control sugar intake, such as obese or diabetic subjects. Punctual mutations of amino acid residues of MNEI, a single chain derivative of the natural sweet protein monellin, allow the modulation of its taste. In this study we present a structural and functional comparison between MNEI and a sweeter mutant Y65R, containing an extra positive charge on the protein surface, in conditions mimicking those of typical beverages. Y65R exhibits superior sweetness in all the experimental conditions tested, has a better solubility at mild acidic pH and preserves a significant thermal stability in a wide range of pH conditions, although slightly lower than MNEI. Our findings confirm the advantages of structure-guided protein engineering to design improved low-calorie sweeteners and excipients for food and pharmaceutical preparations. Copyright © 2014 Elsevier Ltd. All rights reserved.

Integrative Identification of Arabidopsis Mitochondrial Proteome and Its Function Exploitation through Protein Interaction Network

Science.gov (United States)

Cui, Jian; Liu, Jinghua; Li, Yuhua; Shi, Tieliu

2011-01-01

Mitochondria are major players on the production of energy, and host several key reactions involved in basic metabolism and biosynthesis of essential molecules. Currently, the majority of nucleus-encoded mitochondrial proteins are unknown even for model plant Arabidopsis. We reported a computational framework for predicting Arabidopsis mitochondrial proteins based on a probabilistic model, called Naive Bayesian Network, which integrates disparate genomic data generated from eight bioinformatics tools, multiple orthologous mappings, protein domain properties and co-expression patterns using 1,027 microarray profiles. Through this approach, we predicted 2,311 candidate mitochondrial proteins with 84.67% accuracy and 2.53% FPR performances. Together with those experimental confirmed proteins, 2,585 mitochondria proteins (named CoreMitoP) were identified, we explored those proteins with unknown functions based on protein-protein interaction network (PIN) and annotated novel functions for 26.65% CoreMitoP proteins. Moreover, we found newly predicted mitochondrial proteins embedded in particular subnetworks of the PIN, mainly functioning in response to diverse environmental stresses, like salt, draught, cold, and wound etc. Candidate mitochondrial proteins involved in those physiological acitivites provide useful targets for further investigation. Assigned functions also provide comprehensive information for Arabidopsis mitochondrial proteome. PMID:21297957

Structuring detergents for extracting and stabilizing functional membrane proteins.

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Rima Matar-Merheb

Full Text Available BACKGROUND: Membrane proteins are privileged pharmaceutical targets for which the development of structure-based drug design is challenging. One underlying reason is the fact that detergents do not stabilize membrane domains as efficiently as natural lipids in membranes, often leading to a partial to complete loss of activity/stability during protein extraction and purification and preventing crystallization in an active conformation. METHODOLOGY/PRINCIPAL FINDINGS: Anionic calix[4]arene based detergents (C4Cn, n=1-12 were designed to structure the membrane domains through hydrophobic interactions and a network of salt bridges with the basic residues found at the cytosol-membrane interface of membrane proteins. These compounds behave as surfactants, forming micelles of 5-24 nm, with the critical micellar concentration (CMC being as expected sensitive to pH ranging from 0.05 to 1.5 mM. Both by 1H NMR titration and Surface Tension titration experiments, the interaction of these molecules with the basic amino acids was confirmed. They extract membrane proteins from different origins behaving as mild detergents, leading to partial extraction in some cases. They also retain protein functionality, as shown for BmrA (Bacillus multidrug resistance ATP protein, a membrane multidrug-transporting ATPase, which is particularly sensitive to detergent extraction. These new detergents allow BmrA to bind daunorubicin with a Kd of 12 µM, a value similar to that observed after purification using dodecyl maltoside (DDM. They preserve the ATPase activity of BmrA (which resets the protein to its initial state after drug efflux much more efficiently than SDS (sodium dodecyl sulphate, FC12 (Foscholine 12 or DDM. They also maintain in a functional state the C4Cn-extracted protein upon detergent exchange with FC12. Finally, they promote 3D-crystallization of the membrane protein. CONCLUSION/SIGNIFICANCE: These compounds seem promising to extract in a functional state

Structure and function of homodomain-leucine zipper (HD-Zip) proteins.

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Elhiti, Mohamed; Stasolla, Claudio

2009-02-01

Homeodomain-leucine zipper (HD-Zip) proteins are transcription factors unique to plants and are encoded by more than 25 genes in Arabidopsis thaliana. Based on sequence analyses these proteins have been classified into four distinct groups: HD-Zip I-IV. HD-Zip proteins are characterized by the presence of two functional domains; a homeodomain (HD) responsible for DNA binding and a leucine zipper domain (Zip) located immediately C-terminal to the homeodomain and involved in protein-protein interaction. Despite sequence similarities HD-ZIP proteins participate in a variety of processes during plant growth and development. HD-Zip I proteins are generally involved in responses related to abiotic stress, abscisic acid (ABA), blue light, de-etiolation and embryogenesis. HD-Zip II proteins participate in light response, shade avoidance and auxin signalling. Members of the third group (HD-Zip III) control embryogenesis, leaf polarity, lateral organ initiation and meristem function. HD-Zip IV proteins play significant roles during anthocyanin accumulation, differentiation of epidermal cells, trichome formation and root development.

Discovering functional interdependence relationship in PPI networks for protein complex identification.

Science.gov (United States)

Lam, Winnie W M; Chan, Keith C C

2012-04-01

Protein molecules interact with each other in protein complexes to perform many vital functions, and different computational techniques have been developed to identify protein complexes in protein-protein interaction (PPI) networks. These techniques are developed to search for subgraphs of high connectivity in PPI networks under the assumption that the proteins in a protein complex are highly interconnected. While these techniques have been shown to be quite effective, it is also possible that the matching rate between the protein complexes they discover and those that are previously determined experimentally be relatively low and the "false-alarm" rate can be relatively high. This is especially the case when the assumption of proteins in protein complexes being more highly interconnected be relatively invalid. To increase the matching rate and reduce the false-alarm rate, we have developed a technique that can work effectively without having to make this assumption. The name of the technique called protein complex identification by discovering functional interdependence (PCIFI) searches for protein complexes in PPI networks by taking into consideration both the functional interdependence relationship between protein molecules and the network topology of the network. The PCIFI works in several steps. The first step is to construct a multiple-function protein network graph by labeling each vertex with one or more of the molecular functions it performs. The second step is to filter out protein interactions between protein pairs that are not functionally interdependent of each other in the statistical sense. The third step is to make use of an information-theoretic measure to determine the strength of the functional interdependence between all remaining interacting protein pairs. Finally, the last step is to try to form protein complexes based on the measure of the strength of functional interdependence and the connectivity between proteins. For performance evaluation

Bioengineered protein-based nanocage for drug delivery.

Science.gov (United States)

Lee, Eun Jung; Lee, Na Kyeong; Kim, In-San

2016-11-15

Nature, in its wonders, presents and assembles the most intricate and delicate protein structures and this remarkable phenomenon occurs in all kingdom and phyla of life. Of these proteins, cage-like multimeric proteins provide spatial control to biological processes and also compartmentalizes compounds that may be toxic or unstable and avoids their contact with the environment. Protein-based nanocages are of particular interest because of their potential applicability as drug delivery carriers and their perfect and complex symmetry and ideal physical properties, which have stimulated researchers to engineer, modify or mimic these qualities. This article reviews various existing types of protein-based nanocages that are used for therapeutic purposes, and outlines their drug-loading mechanisms and bioengineering strategies via genetic and chemical functionalization. Through a critical evaluation of recent advances in protein nanocage-based drug delivery in vitro and in vivo, an outlook for de novo and in silico nanocage design, and also protein-based nanocage preclinical and future clinical applications will be presented. Copyright © 2016 Elsevier B.V. All rights reserved.

Experimental-confirmation and functional-annotation of predicted proteins in the chicken genome

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McCarthy Fiona M

2007-11-01

Full Text Available Abstract Background The chicken genome was sequenced because of its phylogenetic position as a non-mammalian vertebrate, its use as a biomedical model especially to study embryology and development, its role as a source of human disease organisms and its importance as the major source of animal derived food protein. However, genomic sequence data is, in itself, of limited value; generally it is not equivalent to understanding biological function. The benefit of having a genome sequence is that it provides a basis for functional genomics. However, the sequence data currently available is poorly structurally and functionally annotated and many genes do not have standard nomenclature assigned. Results We analysed eight chicken tissues and improved the chicken genome structural annotation by providing experimental support for the in vivo expression of 7,809 computationally predicted proteins, including 30 chicken proteins that were only electronically predicted or hypothetical translations in human. To improve functional annotation (based on Gene Ontology, we mapped these identified proteins to their human and mouse orthologs and used this orthology to transfer Gene Ontology (GO functional annotations to the chicken proteins. The 8,213 orthology-based GO annotations that we produced represent an 8% increase in currently available chicken GO annotations. Orthologous chicken products were also assigned standardized nomenclature based on current chicken nomenclature guidelines. Conclusion We demonstrate the utility of high-throughput expression proteomics for rapid experimental structural annotation of a newly sequenced eukaryote genome. These experimentally-supported predicted proteins were further annotated by assigning the proteins with standardized nomenclature and functional annotation. This method is widely applicable to a diverse range of species. Moreover, information from one genome can be used to improve the annotation of other genomes and

Inferring the Functions of Proteins from the Interrelationships between Functional Categories.

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Taha, Kamal

2018-01-01

This study proposes a new method to determine the functions of an unannotated protein. The proteins and amino acid residues mentioned in biomedical texts associated with an unannotated protein can be considered as characteristics terms for , which are highly predictive of the potential functions of . Similarly, proteins and amino acid residues mentioned in biomedical texts associated with proteins annotated with a functional category can be considered as characteristics terms of . We introduce in this paper an information extraction system called IFP_IFC that predicts the functions of an unannotated protein by representing and each functional category by a vector of weights. Each weight reflects the degree of association between a characteristic term and (or a characteristic term and ). First, IFP_IFC constructs a network, whose nodes represent the different functional categories, and its edges the interrelationships between the nodes. Then, it determines the functions of by employing random walks with restarts on the mentioned network. The walker is the vector of . Finally, is assigned to the functional categories of the nodes in the network that are visited most by the walker. We evaluated the quality of IFP_IFC by comparing it experimentally with two other systems. Results showed marked improvement.

Efficient identification of critical residues based only on protein structure by network analysis.

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Michael P Cusack

2007-05-01

Full Text Available Despite the increasing number of published protein structures, and the fact that each protein's function relies on its three-dimensional structure, there is limited access to automatic programs used for the identification of critical residues from the protein structure, compared with those based on protein sequence. Here we present a new algorithm based on network analysis applied exclusively on protein structures to identify critical residues. Our results show that this method identifies critical residues for protein function with high reliability and improves automatic sequence-based approaches and previous network-based approaches. The reliability of the method depends on the conformational diversity screened for the protein of interest. We have designed a web site to give access to this software at http://bis.ifc.unam.mx/jamming/. In summary, a new method is presented that relates critical residues for protein function with the most traversed residues in networks derived from protein structures. A unique feature of the method is the inclusion of the conformational diversity of proteins in the prediction, thus reproducing a basic feature of the structure/function relationship of proteins.

Designing protein-based biomaterials for medical applications.

Science.gov (United States)

Gagner, Jennifer E; Kim, Wookhyun; Chaikof, Elliot L

2014-04-01

Biomaterials produced by nature have been honed through billions of years, evolving exquisitely precise structure-function relationships that scientists strive to emulate. Advances in genetic engineering have facilitated extensive investigations to determine how changes in even a single peptide within a protein sequence can produce biomaterials with unique thermal, mechanical and biological properties. Elastin, a naturally occurring protein polymer, serves as a model protein to determine the relationship between specific structural elements and desirable material characteristics. The modular, repetitive nature of the protein facilitates the formation of well-defined secondary structures with the ability to self-assemble into complex three-dimensional architectures on a variety of length scales. Furthermore, many opportunities exist to incorporate other protein-based motifs and inorganic materials into recombinant protein-based materials, extending the range and usefulness of these materials in potential biomedical applications. Elastin-like polypeptides (ELPs) can be assembled into 3-D architectures with precise control over payload encapsulation, mechanical and thermal properties, as well as unique functionalization opportunities through both genetic and enzymatic means. An overview of current protein-based materials, their properties and uses in biomedicine will be provided, with a focus on the advantages of ELPs. Applications of these biomaterials as imaging and therapeutic delivery agents will be discussed. Finally, broader implications and future directions of these materials as diagnostic and therapeutic systems will be explored. Copyright © 2013 Elsevier Ltd. All rights reserved.

Semantic integration to identify overlapping functional modules in protein interaction networks

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Ramanathan Murali

2007-07-01

Full Text Available Abstract Background The systematic analysis of protein-protein interactions can enable a better understanding of cellular organization, processes and functions. Functional modules can be identified from the protein interaction networks derived from experimental data sets. However, these analyses are challenging because of the presence of unreliable interactions and the complex connectivity of the network. The integration of protein-protein interactions with the data from other sources can be leveraged for improving the effectiveness of functional module detection algorithms. Results We have developed novel metrics, called semantic similarity and semantic interactivity, which use Gene Ontology (GO annotations to measure the reliability of protein-protein interactions. The protein interaction networks can be converted into a weighted graph representation by assigning the reliability values to each interaction as a weight. We presented a flow-based modularization algorithm to efficiently identify overlapping modules in the weighted interaction networks. The experimental results show that the semantic similarity and semantic interactivity of interacting pairs were positively correlated with functional co-occurrence. The effectiveness of the algorithm for identifying modules was evaluated using functional categories from the MIPS database. We demonstrated that our algorithm had higher accuracy compared to other competing approaches. Conclusion The integration of protein interaction networks with GO annotation data and the capability of detecting overlapping modules substantially improve the accuracy of module identification.

Protein-Protein Interactions Prediction Based on Iterative Clique Extension with Gene Ontology Filtering

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Lei Yang

2014-01-01

Full Text Available Cliques (maximal complete subnets in protein-protein interaction (PPI network are an important resource used to analyze protein complexes and functional modules. Clique-based methods of predicting PPI complement the data defection from biological experiments. However, clique-based predicting methods only depend on the topology of network. The false-positive and false-negative interactions in a network usually interfere with prediction. Therefore, we propose a method combining clique-based method of prediction and gene ontology (GO annotations to overcome the shortcoming and improve the accuracy of predictions. According to different GO correcting rules, we generate two predicted interaction sets which guarantee the quality and quantity of predicted protein interactions. The proposed method is applied to the PPI network from the Database of Interacting Proteins (DIP and most of the predicted interactions are verified by another biological database, BioGRID. The predicted protein interactions are appended to the original protein network, which leads to clique extension and shows the significance of biological meaning.

Hierarchical partitioning of metazoan protein conservation profiles provides new functional insights.

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Jonathan Witztum

Full Text Available The availability of many complete, annotated proteomes enables the systematic study of the relationships between protein conservation and functionality. We explore this question based solely on the presence or absence of protein homologues (a.k.a. conservation profiles. We study 18 metazoans, from two distinct points of view: the human's and the fly's. Using the GOrilla gene ontology (GO analysis tool, we explore functional enrichment of the "universal proteins", those with homologues in all 17 other species, and of the "non-universal proteins". A large number of GO terms are strongly enriched in both human and fly universal proteins. Most of these functions are known to be essential. A smaller number of GO terms, exhibiting markedly different properties, are enriched in both human and fly non-universal proteins. We further explore the non-universal proteins, whose conservation profiles are consistent with the "tree of life" (TOL consistent, as well as the TOL inconsistent proteins. Finally, we applied Quantum Clustering to the conservation profiles of the TOL consistent proteins. Each cluster is strongly associated with one or a small number of specific monophyletic clades in the tree of life. The proteins in many of these clusters exhibit strong functional enrichment associated with the "life style" of the related clades. Most previous approaches for studying function and conservation are "bottom up", studying protein families one by one, and separately assessing the conservation of each. By way of contrast, our approach is "top down". We globally partition the set of all proteins hierarchically, as described above, and then identify protein families enriched within different subdivisions. While supporting previous findings, our approach also provides a tool for discovering novel relations between protein conservation profiles, functionality, and evolutionary history as represented by the tree of life.

Automatic discovery of cross-family sequence features associated with protein function

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Krings Andrea

2006-01-01

Full Text Available Abstract Background Methods for predicting protein function directly from amino acid sequences are useful tools in the study of uncharacterised protein families and in comparative genomics. Until now, this problem has been approached using machine learning techniques that attempt to predict membership, or otherwise, to predefined functional categories or subcellular locations. A potential drawback of this approach is that the human-designated functional classes may not accurately reflect the underlying biology, and consequently important sequence-to-function relationships may be missed. Results We show that a self-supervised data mining approach is able to find relationships between sequence features and functional annotations. No preconceived ideas about functional categories are required, and the training data is simply a set of protein sequences and their UniProt/Swiss-Prot annotations. The main technical aspect of the approach is the co-evolution of amino acid-based regular expressions and keyword-based logical expressions with genetic programming. Our experiments on a strictly non-redundant set of eukaryotic proteins reveal that the strongest and most easily detected sequence-to-function relationships are concerned with targeting to various cellular compartments, which is an area already well studied both experimentally and computationally. Of more interest are a number of broad functional roles which can also be correlated with sequence features. These include inhibition, biosynthesis, transcription and defence against bacteria. Despite substantial overlaps between these functions and their corresponding cellular compartments, we find clear differences in the sequence motifs used to predict some of these functions. For example, the presence of polyglutamine repeats appears to be linked more strongly to the "transcription" function than to the general "nuclear" function/location. Conclusion We have developed a novel and useful approach for

Protein Functionalized Nanodiamond Arrays

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Liu YL

2010-01-01

Full Text Available Abstract Various nanoscale elements are currently being explored for bio-applications, such as in bio-images, bio-detection, and bio-sensors. Among them, nanodiamonds possess remarkable features such as low bio-cytotoxicity, good optical property in fluorescent and Raman spectra, and good photostability for bio-applications. In this work, we devise techniques to position functionalized nanodiamonds on self-assembled monolayer (SAMs arrays adsorbed on silicon and ITO substrates surface using electron beam lithography techniques. The nanodiamond arrays were functionalized with lysozyme to target a certain biomolecule or protein specifically. The optical properties of the nanodiamond-protein complex arrays were characterized by a high throughput confocal microscope. The synthesized nanodiamond-lysozyme complex arrays were found to still retain their functionality in interacting with E. coli.

Protein single-model quality assessment by feature-based probability density functions.

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Cao, Renzhi; Cheng, Jianlin

2016-04-04

Protein quality assessment (QA) has played an important role in protein structure prediction. We developed a novel single-model quality assessment method-Qprob. Qprob calculates the absolute error for each protein feature value against the true quality scores (i.e. GDT-TS scores) of protein structural models, and uses them to estimate its probability density distribution for quality assessment. Qprob has been blindly tested on the 11th Critical Assessment of Techniques for Protein Structure Prediction (CASP11) as MULTICOM-NOVEL server. The official CASP result shows that Qprob ranks as one of the top single-model QA methods. In addition, Qprob makes contributions to our protein tertiary structure predictor MULTICOM, which is officially ranked 3rd out of 143 predictors. The good performance shows that Qprob is good at assessing the quality of models of hard targets. These results demonstrate that this new probability density distribution based method is effective for protein single-model quality assessment and is useful for protein structure prediction. The webserver of Qprob is available at: http://calla.rnet.missouri.edu/qprob/. The software is now freely available in the web server of Qprob.

A new protein-protein interaction sensor based on tripartite split-GFP association.

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Cabantous, Stéphanie; Nguyen, Hau B; Pedelacq, Jean-Denis; Koraïchi, Faten; Chaudhary, Anu; Ganguly, Kumkum; Lockard, Meghan A; Favre, Gilles; Terwilliger, Thomas C; Waldo, Geoffrey S

2013-10-04

Monitoring protein-protein interactions in living cells is key to unraveling their roles in numerous cellular processes and various diseases. Previously described split-GFP based sensors suffer from poor folding and/or self-assembly background fluorescence. Here, we have engineered a micro-tagging system to monitor protein-protein interactions in vivo and in vitro. The assay is based on tripartite association between two twenty amino-acids long GFP tags, GFP10 and GFP11, fused to interacting protein partners, and the complementary GFP1-9 detector. When proteins interact, GFP10 and GFP11 self-associate with GFP1-9 to reconstitute a functional GFP. Using coiled-coils and FRB/FKBP12 model systems we characterize the sensor in vitro and in Escherichia coli. We extend the studies to mammalian cells and examine the FK-506 inhibition of the rapamycin-induced association of FRB/FKBP12. The small size of these tags and their minimal effect on fusion protein behavior and solubility should enable new experiments for monitoring protein-protein association by fluorescence.

Analysis of temporal transcription expression profiles reveal links between protein function and developmental stages of Drosophila melanogaster.

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Wan, Cen; Lees, Jonathan G; Minneci, Federico; Orengo, Christine A; Jones, David T

2017-10-01

Accurate gene or protein function prediction is a key challenge in the post-genome era. Most current methods perform well on molecular function prediction, but struggle to provide useful annotations relating to biological process functions due to the limited power of sequence-based features in that functional domain. In this work, we systematically evaluate the predictive power of temporal transcription expression profiles for protein function prediction in Drosophila melanogaster. Our results show significantly better performance on predicting protein function when transcription expression profile-based features are integrated with sequence-derived features, compared with the sequence-derived features alone. We also observe that the combination of expression-based and sequence-based features leads to further improvement of accuracy on predicting all three domains of gene function. Based on the optimal feature combinations, we then propose a novel multi-classifier-based function prediction method for Drosophila melanogaster proteins, FFPred-fly+. Interpreting our machine learning models also allows us to identify some of the underlying links between biological processes and developmental stages of Drosophila melanogaster.

Analysis of temporal transcription expression profiles reveal links between protein function and developmental stages of Drosophila melanogaster.

Directory of Open Access Journals (Sweden)

Cen Wan

2017-10-01

Full Text Available Accurate gene or protein function prediction is a key challenge in the post-genome era. Most current methods perform well on molecular function prediction, but struggle to provide useful annotations relating to biological process functions due to the limited power of sequence-based features in that functional domain. In this work, we systematically evaluate the predictive power of temporal transcription expression profiles for protein function prediction in Drosophila melanogaster. Our results show significantly better performance on predicting protein function when transcription expression profile-based features are integrated with sequence-derived features, compared with the sequence-derived features alone. We also observe that the combination of expression-based and sequence-based features leads to further improvement of accuracy on predicting all three domains of gene function. Based on the optimal feature combinations, we then propose a novel multi-classifier-based function prediction method for Drosophila melanogaster proteins, FFPred-fly+. Interpreting our machine learning models also allows us to identify some of the underlying links between biological processes and developmental stages of Drosophila melanogaster.

AptRank: an adaptive PageRank model for protein function prediction on   bi-relational graphs.

Science.gov (United States)

Jiang, Biaobin; Kloster, Kyle; Gleich, David F; Gribskov, Michael

2017-06-15

Diffusion-based network models are widely used for protein function prediction using protein network data and have been shown to outperform neighborhood-based and module-based methods. Recent studies have shown that integrating the hierarchical structure of the Gene Ontology (GO) data dramatically improves prediction accuracy. However, previous methods usually either used the GO hierarchy to refine the prediction results of multiple classifiers, or flattened the hierarchy into a function-function similarity kernel. No study has taken the GO hierarchy into account together with the protein network as a two-layer network model. We first construct a Bi-relational graph (Birg) model comprised of both protein-protein association and function-function hierarchical networks. We then propose two diffusion-based methods, BirgRank and AptRank, both of which use PageRank to diffuse information on this two-layer graph model. BirgRank is a direct application of traditional PageRank with fixed decay parameters. In contrast, AptRank utilizes an adaptive diffusion mechanism to improve the performance of BirgRank. We evaluate the ability of both methods to predict protein function on yeast, fly and human protein datasets, and compare with four previous methods: GeneMANIA, TMC, ProteinRank and clusDCA. We design four different validation strategies: missing function prediction, de novo function prediction, guided function prediction and newly discovered function prediction to comprehensively evaluate predictability of all six methods. We find that both BirgRank and AptRank outperform the previous methods, especially in missing function prediction when using only 10% of the data for training. The MATLAB code is available at https://github.rcac.purdue.edu/mgribsko/aptrank . gribskov@purdue.edu. Supplementary data are available at Bioinformatics online. © The Author 2017. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com

UET: a database of evolutionarily-predicted functional determinants of protein sequences that cluster as functional sites in protein structures.

Science.gov (United States)

Lua, Rhonald C; Wilson, Stephen J; Konecki, Daniel M; Wilkins, Angela D; Venner, Eric; Morgan, Daniel H; Lichtarge, Olivier

2016-01-04

The structure and function of proteins underlie most aspects of biology and their mutational perturbations often cause disease. To identify the molecular determinants of function as well as targets for drugs, it is central to characterize the important residues and how they cluster to form functional sites. The Evolutionary Trace (ET) achieves this by ranking the functional and structural importance of the protein sequence positions. ET uses evolutionary distances to estimate functional distances and correlates genotype variations with those in the fitness phenotype. Thus, ET ranks are worse for sequence positions that vary among evolutionarily closer homologs but better for positions that vary mostly among distant homologs. This approach identifies functional determinants, predicts function, guides the mutational redesign of functional and allosteric specificity, and interprets the action of coding sequence variations in proteins, people and populations. Now, the UET database offers pre-computed ET analyses for the protein structure databank, and on-the-fly analysis of any protein sequence. A web interface retrieves ET rankings of sequence positions and maps results to a structure to identify functionally important regions. This UET database integrates several ways of viewing the results on the protein sequence or structure and can be found at http://mammoth.bcm.tmc.edu/uet/. © The Author(s) 2015. Published by Oxford University Press on behalf of Nucleic Acids Research.

Designing coarse grained-and atom based-potentials for protein-protein docking

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Tobi Dror

2010-11-01

Full Text Available Abstract Background Protein-protein docking is a challenging computational problem in functional genomics, particularly when one or both proteins undergo conformational change(s upon binding. The major challenge is to define a scoring function soft enough to tolerate these changes and specific enough to distinguish between near-native and "misdocked" conformations. Results Using a linear programming (LP technique, we developed two types of potentials: (i Side chain-based and (ii Heavy atom-based. To achieve this we considered a set of 161 transient complexes and generated a large set of putative docked structures (decoys, based on a shape complementarity criterion, for each complex. The demand on the potentials was to yield, for the native (correctly docked structure, a potential energy lower than those of any of the non-native (misdocked structures. We show that the heavy atom-based potentials were able to comply with this requirement but not the side chain-based one. Thus, despite the smaller number of parameters, the capability of heavy atom-based potentials to discriminate between native and "misdocked" conformations is improved relative to those of the side chain-based potentials. The performance of the atom-based potentials was evaluated by a jackknife test on a set of 50 complexes taken from the Zdock2.3 decoys set. Conclusions Our results show that, using the LP approach, we were able to train our potentials using a dataset of transient complexes only the newly developed potentials outperform three other known potentials in this test.

Functionality of extrusion--texturized whey proteins.

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Onwulata, C I; Konstance, R P; Cooke, P H; Farrell, H M

2003-11-01

Whey, a byproduct of the cheesemaking process, is concentrated by processors to make whey protein concentrates (WPC) and isolates (WPI). Only 50% of whey proteins are used in foods. In order to increase their usage, texturizing WPC, WPI, and whey albumin is proposed to create ingredients with new functionality. Extrusion processing texturizes globular proteins by shearing and stretching them into aligned or entangled fibrous bundles. In this study, WPC, WPI, and whey albumin were extruded in a twin screw extruder at approximately 38% moisture content (15.2 ml/min, feed rate 25 g/min) and, at different extrusion cook temperatures, at the same temperature for the last four zones before the die (35, 50, 75, and 100 degrees C, respectively). Protein solubility, gelation, foaming, and digestibility were determined in extrudates. Degree of extrusion-induced insolubility (denaturation) or texturization, determined by lack of solubility at pH 7 for WPI, increased from 30 to 60, 85, and 95% for the four temperature conditions 35, 50, 75, and 100 degrees C, respectively. Gel strength of extruded isolates increased initially 115% (35 degrees C) and 145% (50 degrees C), but gel strength was lost at 75 and 100 degrees C. Denaturation at these melt temperatures had minimal effect on foaming and digestibility. Varying extrusion cook temperature allowed a new controlled rate of denaturation, indicating that a texturized ingredient with a predetermined functionality based on degree of denaturation can be created.

Structural symmetry and protein function.

Science.gov (United States)

Goodsell, D S; Olson, A J

2000-01-01

The majority of soluble and membrane-bound proteins in modern cells are symmetrical oligomeric complexes with two or more subunits. The evolutionary selection of symmetrical oligomeric complexes is driven by functional, genetic, and physicochemical needs. Large proteins are selected for specific morphological functions, such as formation of rings, containers, and filaments, and for cooperative functions, such as allosteric regulation and multivalent binding. Large proteins are also more stable against denaturation and have a reduced surface area exposed to solvent when compared with many individual, smaller proteins. Large proteins are constructed as oligomers for reasons of error control in synthesis, coding efficiency, and regulation of assembly. Symmetrical oligomers are favored because of stability and finite control of assembly. Several functions limit symmetry, such as interaction with DNA or membranes, and directional motion. Symmetry is broken or modified in many forms: quasisymmetry, in which identical subunits adopt similar but different conformations; pleomorphism, in which identical subunits form different complexes; pseudosymmetry, in which different molecules form approximately symmetrical complexes; and symmetry mismatch, in which oligomers of different symmetries interact along their respective symmetry axes. Asymmetry is also observed at several levels. Nearly all complexes show local asymmetry at the level of side chain conformation. Several complexes have reciprocating mechanisms in which the complex is asymmetric, but, over time, all subunits cycle through the same set of conformations. Global asymmetry is only rarely observed. Evolution of oligomeric complexes may favor the formation of dimers over complexes with higher cyclic symmetry, through a mechanism of prepositioned pairs of interacting residues. However, examples have been found for all of the crystallographic point groups, demonstrating that functional need can drive the evolution of

Protein-based stable isotope probing.

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Jehmlich, Nico; Schmidt, Frank; Taubert, Martin; Seifert, Jana; Bastida, Felipe; von Bergen, Martin; Richnow, Hans-Hermann; Vogt, Carsten

2010-12-01

We describe a stable isotope probing (SIP) technique that was developed to link microbe-specific metabolic function to phylogenetic information. Carbon ((13)C)- or nitrogen ((15)N)-labeled substrates (typically with >98% heavy label) were used in cultivation experiments and the heavy isotope incorporation into proteins (protein-SIP) on growth was determined. The amount of incorporation provides a measure for assimilation of a substrate, and the sequence information from peptide analysis obtained by mass spectrometry delivers phylogenetic information about the microorganisms responsible for the metabolism of the particular substrate. In this article, we provide guidelines for incubating microbial cultures with labeled substrates and a protocol for protein-SIP. The protocol guides readers through the proteomics pipeline, including protein extraction, gel-free and gel-based protein separation, the subsequent mass spectrometric analysis of peptides and the calculation of the incorporation of stable isotopes into peptides. Extraction of proteins and the mass fingerprint measurements of unlabeled and labeled fractions can be performed in 2-3 d.

Determining and comparing protein function in Bacterial genome sequences

DEFF Research Database (Denmark)

Vesth, Tammi Camilla

of this class have very little homology to other known genomes making functional annotation based on sequence similarity very difficult. Inspired in part by this analysis, an approach for comparative functional annotation was created based public sequenced genomes, CMGfunc. Functionally related groups......In November 2013, there was around 21.000 different prokaryotic genomes sequenced and publicly available, and the number is growing daily with another 20.000 or more genomes expected to be sequenced and deposited by the end of 2014. An important part of the analysis of this data is the functional...... annotation of genes – the descriptions assigned to genes that describe the likely function of the encoded proteins. This process is limited by several factors, including the definition of a function which can be more or less specific as well as how many genes can actually be assigned a function based...

Nanoporous microbead supported bilayers: stability, physical characterization, and incorporation of functional transmembrane proteins.

Energy Technology Data Exchange (ETDEWEB)

Davis, Ryan W. (University of New Mexico, Albuquerque, NM); Brozik, James A. (University of New Mexico, Albuquerque, NM); Brozik, Susan Marie; Cox, Jason M. (University of New Mexico, Albuquerque, NM); Lopez, Gabriel P. (University of New Mexico, Albuquerque, NM); Barrick, Todd A. (University of New Mexico, Albuquerque, NM); Flores, Adrean (University of New Mexico, Albuquerque, NM)

2007-03-01

The introduction of functional transmembrane proteins into supported bilayer-based biomimetic systems presents a significant challenge for biophysics. Among the various methods for producing supported bilayers, liposomal fusion offers a versatile method for the introduction of membrane proteins into supported bilayers on a variety of substrates. In this study, the properties of protein containing unilamellar phosphocholine lipid bilayers on nanoporous silica microspheres are investigated. The effects of the silica substrate, pore structure, and the substrate curvature on the stability of the membrane and the functionality of the membrane protein are determined. Supported bilayers on porous silica microspheres show a significant increase in surface area on surfaces with structures in excess of 10 nm as well as an overall decrease in stability resulting from increasing pore size and curvature. Comparison of the liposomal and detergent-mediated introduction of purified bacteriorhodopsin (bR) and the human type 3 serotonin receptor (5HT3R) are investigated focusing on the resulting protein function, diffusion, orientation, and incorporation efficiency. In both cases, functional proteins are observed; however, the reconstitution efficiency and orientation selectivity are significantly enhanced through detergent-mediated protein reconstitution. The results of these experiments provide a basis for bulk ionic and fluorescent dye-based compartmentalization assays as well as single-molecule optical and single-channel electrochemical interrogation of transmembrane proteins in a biomimetic platform.

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.

Annotating Protein Functional Residues by Coupling High-Throughput Fitness Profile and Homologous-Structure Analysis.

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Du, Yushen; Wu, Nicholas C; Jiang, Lin; Zhang, Tianhao; Gong, Danyang; Shu, Sara; Wu, Ting-Ting; Sun, Ren

2016-11-01

Identification and annotation of functional residues are fundamental questions in protein sequence analysis. Sequence and structure conservation provides valuable information to tackle these questions. It is, however, limited by the incomplete sampling of sequence space in natural evolution. Moreover, proteins often have multiple functions, with overlapping sequences that present challenges to accurate annotation of the exact functions of individual residues by conservation-based methods. Using the influenza A virus PB1 protein as an example, we developed a method to systematically identify and annotate functional residues. We used saturation mutagenesis and high-throughput sequencing to measure the replication capacity of single nucleotide mutations across the entire PB1 protein. After predicting protein stability upon mutations, we identified functional PB1 residues that are essential for viral replication. To further annotate the functional residues important to the canonical or noncanonical functions of viral RNA-dependent RNA polymerase (vRdRp), we performed a homologous-structure analysis with 16 different vRdRp structures. We achieved high sensitivity in annotating the known canonical polymerase functional residues. Moreover, we identified a cluster of noncanonical functional residues located in the loop region of the PB1 β-ribbon. We further demonstrated that these residues were important for PB1 protein nuclear import through the interaction with Ran-binding protein 5. In summary, we developed a systematic and sensitive method to identify and annotate functional residues that are not restrained by sequence conservation. Importantly, this method is generally applicable to other proteins about which homologous-structure information is available. To fully comprehend the diverse functions of a protein, it is essential to understand the functionality of individual residues. Current methods are highly dependent on evolutionary sequence conservation, which is

Insights into Hox protein function from a large scale combinatorial analysis of protein domains.

Directory of Open Access Journals (Sweden)

Samir Merabet

2011-10-01

Full Text Available Protein function is encoded within protein sequence and protein domains. However, how protein domains cooperate within a protein to modulate overall activity and how this impacts functional diversification at the molecular and organism levels remains largely unaddressed. Focusing on three domains of the central class Drosophila Hox transcription factor AbdominalA (AbdA, we used combinatorial domain mutations and most known AbdA developmental functions as biological readouts to investigate how protein domains collectively shape protein activity. The results uncover redundancy, interactivity, and multifunctionality of protein domains as salient features underlying overall AbdA protein activity, providing means to apprehend functional diversity and accounting for the robustness of Hox-controlled developmental programs. Importantly, the results highlight context-dependency in protein domain usage and interaction, allowing major modifications in domains to be tolerated without general functional loss. The non-pleoitropic effect of domain mutation suggests that protein modification may contribute more broadly to molecular changes underlying morphological diversification during evolution, so far thought to rely largely on modification in gene cis-regulatory sequences.

GalaxyDock BP2 score: a hybrid scoring function for accurate protein-ligand docking

Science.gov (United States)

Baek, Minkyung; Shin, Woong-Hee; Chung, Hwan Won; Seok, Chaok

2017-07-01

Protein-ligand docking is a useful tool for providing atomic-level understanding of protein functions in nature and design principles for artificial ligands or proteins with desired properties. The ability to identify the true binding pose of a ligand to a target protein among numerous possible candidate poses is an essential requirement for successful protein-ligand docking. Many previously developed docking scoring functions were trained to reproduce experimental binding affinities and were also used for scoring binding poses. However, in this study, we developed a new docking scoring function, called GalaxyDock BP2 Score, by directly training the scoring power of binding poses. This function is a hybrid of physics-based, empirical, and knowledge-based score terms that are balanced to strengthen the advantages of each component. The performance of the new scoring function exhibits significant improvement over existing scoring functions in decoy pose discrimination tests. In addition, when the score is used with the GalaxyDock2 protein-ligand docking program, it outperformed other state-of-the-art docking programs in docking tests on the Astex diverse set, the Cross2009 benchmark set, and the Astex non-native set. GalaxyDock BP2 Score and GalaxyDock2 with this score are freely available at http://galaxy.seoklab.org/softwares/galaxydock.html.

Scoring functions for protein-protein interactions.

Science.gov (United States)

Moal, Iain H; Moretti, Rocco; Baker, David; Fernández-Recio, Juan

2013-12-01

The computational evaluation of protein-protein interactions will play an important role in organising the wealth of data being generated by high-throughput initiatives. Here we discuss future applications, report recent developments and identify areas requiring further investigation. Many functions have been developed to quantify the structural and energetic properties of interacting proteins, finding use in interrelated challenges revolving around the relationship between sequence, structure and binding free energy. These include loop modelling, side-chain refinement, docking, multimer assembly, affinity prediction, affinity change upon mutation, hotspots location and interface design. Information derived from models optimised for one of these challenges can be used to benefit the others, and can be unified within the theoretical frameworks of multi-task learning and Pareto-optimal multi-objective learning. Copyright © 2013 Elsevier Ltd. All rights reserved.

Simplified Method for Predicting a Functional Class of Proteins in Transcription Factor Complexes

KAUST Repository

Piatek, Marek J.

2013-07-12

Background:Initiation of transcription is essential for most of the cellular responses to environmental conditions and for cell and tissue specificity. This process is regulated through numerous proteins, their ligands and mutual interactions, as well as interactions with DNA. The key such regulatory proteins are transcription factors (TFs) and transcription co-factors (TcoFs). TcoFs are important since they modulate the transcription initiation process through interaction with TFs. In eukaryotes, transcription requires that TFs form different protein complexes with various nuclear proteins. To better understand transcription regulation, it is important to know the functional class of proteins interacting with TFs during transcription initiation. Such information is not fully available, since not all proteins that act as TFs or TcoFs are yet annotated as such, due to generally partial functional annotation of proteins. In this study we have developed a method to predict, using only sequence composition of the interacting proteins, the functional class of human TF binding partners to be (i) TF, (ii) TcoF, or (iii) other nuclear protein. This allows for complementing the annotation of the currently known pool of nuclear proteins. Since only the knowledge of protein sequences is required in addition to protein interaction, the method should be easily applicable to many species.Results:Based on experimentally validated interactions between human TFs with different TFs, TcoFs and other nuclear proteins, our two classification systems (implemented as a web-based application) achieve high accuracies in distinguishing TFs and TcoFs from other nuclear proteins, and TFs from TcoFs respectively.Conclusion:As demonstrated, given the fact that two proteins are capable of forming direct physical interactions and using only information about their sequence composition, we have developed a completely new method for predicting a functional class of TF interacting protein partners

High content screening for G protein-coupled receptors using cell-based protein translocation assays

DEFF Research Database (Denmark)

Grånäs, Charlotta; Lundholt, Betina Kerstin; Heydorn, Arne

2005-01-01

G protein-coupled receptors (GPCRs) have been one of the most productive classes of drug targets for several decades, and new technologies for GPCR-based discovery promise to keep this field active for years to come. While molecular screens for GPCR receptor agonist- and antagonist-based drugs...... will continue to be valuable discovery tools, the most exciting developments in the field involve cell-based assays for GPCR function. Some cell-based discovery strategies, such as the use of beta-arrestin as a surrogate marker for GPCR function, have already been reduced to practice, and have been used...... as valuable discovery tools for several years. The application of high content cell-based screening to GPCR discovery has opened up additional possibilities, such as direct tracking of GPCRs, G proteins and other signaling pathway components using intracellular translocation assays. These assays provide...

Stoichiometric balance of protein copy numbers is measurable and functionally significant in a protein-protein interaction network for yeast endocytosis.

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Holland, David O; Johnson, Margaret E

2018-03-01

Stoichiometric balance, or dosage balance, implies that proteins that are subunits of obligate complexes (e.g. the ribosome) should have copy numbers expressed to match their stoichiometry in that complex. Establishing balance (or imbalance) is an important tool for inferring subunit function and assembly bottlenecks. We show here that these correlations in protein copy numbers can extend beyond complex subunits to larger protein-protein interactions networks (PPIN) involving a range of reversible binding interactions. We develop a simple method for quantifying balance in any interface-resolved PPINs based on network structure and experimentally observed protein copy numbers. By analyzing such a network for the clathrin-mediated endocytosis (CME) system in yeast, we found that the real protein copy numbers were significantly more balanced in relation to their binding partners compared to randomly sampled sets of yeast copy numbers. The observed balance is not perfect, highlighting both under and overexpressed proteins. We evaluate the potential cost and benefits of imbalance using two criteria. First, a potential cost to imbalance is that 'leftover' proteins without remaining functional partners are free to misinteract. We systematically quantify how this misinteraction cost is most dangerous for strong-binding protein interactions and for network topologies observed in biological PPINs. Second, a more direct consequence of imbalance is that the formation of specific functional complexes depends on relative copy numbers. We therefore construct simple kinetic models of two sub-networks in the CME network to assess multi-protein assembly of the ARP2/3 complex and a minimal, nine-protein clathrin-coated vesicle forming module. We find that the observed, imperfectly balanced copy numbers are less effective than balanced copy numbers in producing fast and complete multi-protein assemblies. However, we speculate that strategic imbalance in the vesicle forming module

From Green to Blue: Site-Directed Mutagenesis of the Green Fluorescent Protein to Teach Protein Structure-Function Relationships

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Giron, Maria D.; Salto, Rafael

2011-01-01

Structure-function relationship studies in proteins are essential in modern Cell Biology. Laboratory exercises that allow students to familiarize themselves with basic mutagenesis techniques are essential in all Genetic Engineering courses to teach the relevance of protein structure. We have implemented a laboratory course based on the…

Prediction of functional sites in proteins using conserved functional group analysis.

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Innis, C Axel; Anand, A Prem; Sowdhamini, R

2004-04-02

A detailed knowledge of a protein's functional site is an absolute prerequisite for understanding its mode of action at the molecular level. However, the rapid pace at which sequence and structural information is being accumulated for proteins greatly exceeds our ability to determine their biochemical roles experimentally. As a result, computational methods are required which allow for the efficient processing of the evolutionary information contained in this wealth of data, in particular that related to the nature and location of functionally important sites and residues. The method presented here, referred to as conserved functional group (CFG) analysis, relies on a simplified representation of the chemical groups found in amino acid side-chains to identify functional sites from a single protein structure and a number of its sequence homologues. We show that CFG analysis can fully or partially predict the location of functional sites in approximately 96% of the 470 cases tested and that, unlike other methods available, it is able to tolerate wide variations in sequence identity. In addition, we discuss its potential in a structural genomics context, where automation, scalability and efficiency are critical, and an increasing number of protein structures are determined with no prior knowledge of function. This is exemplified by our analysis of the hypothetical protein Ydde_Ecoli, whose structure was recently solved by members of the North East Structural Genomics consortium. Although the proposed active site for this protein needs to be validated experimentally, this example illustrates the scope of CFG analysis as a general tool for the identification of residues likely to play an important role in a protein's biochemical function. Thus, our method offers a convenient solution to rapidly and automatically process the vast amounts of data that are beginning to emerge from structural genomics projects.

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

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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 .

Structures and Corresponding Functions of Five Types of Picornaviral 2A Proteins

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Xiaoyao Yang

2017-07-01

Full Text Available Among the few non-structural proteins encoded by the picornaviral genome, the 2A protein is particularly special, irrespective of structure or function. During the evolution of the Picornaviridae family, the 2A protein has been highly non-conserved. We believe that the 2A protein in this family can be classified into at least five distinct types according to previous studies. These five types are (A chymotrypsin-like 2A, (B Parechovirus-like 2A, (C hepatitis-A-virus-like 2A, (D Aphthovirus-like 2A, and (E 2A sequence of the genus Cardiovirus. We carried out a phylogenetic analysis and found that there was almost no homology between each type. Subsequently, we aligned the sequences within each type and found that the functional motifs in each type are highly conserved. These different motifs perform different functions. Therefore, in this review, we introduce the structures and functions of these five types of 2As separately. Based on the structures and functions, we provide suggestions to combat picornaviruses. The complexity and diversity of the 2A protein has caused great difficulties in functional and antiviral research. In this review, researchers can find useful information on the 2A protein and thus conduct improved antiviral research.

The functional properties, modification and utilization of whey proteins

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B. G. Venter

1986-03-01

Full Text Available Whey protein has an excellent nutritional value and exhibits a functional potential. In comparison with certain other food proteins, the whey protein content of essential amino acids is extremely favourable for human consumption. Depending on the heat-treatment history thereof, soluble whey proteins with utilizable functional properties, apart from high biological value, true digestibility, protein efficiency ratio and nett protein utilization, can be recovered. Various technological and chemical recovery processes have been designed. Chemically and enzymatically modified whey protein is manufactured to obtain technological and functional advantages. The important functional properties of whey proteins, namely hydration, gelation, emulsifying and foaming properties, are reviewed.

Functionalization of 3D scaffolds with protein-releasing biomaterials for intracellular delivery.

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Seras-Franzoso, Joaquin; Steurer, Christoph; Roldán, Mònica; Vendrell, Meritxell; Vidaurre-Agut, Carla; Tarruella, Anna; Saldaña, Laura; Vilaboa, Nuria; Parera, Marc; Elizondo, Elisa; Ratera, Imma; Ventosa, Nora; Veciana, Jaume; Campillo-Fernández, Alberto J; García-Fruitós, Elena; Vázquez, Esther; Villaverde, Antonio

2013-10-10

Appropriate combinations of mechanical and biological stimuli are required to promote proper colonization of substrate materials in regenerative medicine. In this context, 3D scaffolds formed by compatible and biodegradable materials are under continuous development in an attempt to mimic the extracellular environment of mammalian cells. We have here explored how novel 3D porous scaffolds constructed by polylactic acid, polycaprolactone or chitosan can be decorated with bacterial inclusion bodies, submicron protein particles formed by releasable functional proteins. A simple dipping-based decoration method tested here specifically favors the penetration of the functional particles deeper than 300μm from the materials' surface. The functionalized surfaces support the intracellular delivery of biologically active proteins to up to more than 80% of the colonizing cells, a process that is slightly influenced by the chemical nature of the scaffold. The combination of 3D soft scaffolds and protein-based sustained release systems (Bioscaffolds) offers promise in the fabrication of bio-inspired hybrid matrices for multifactorial control of cell proliferation in tissue engineering under complex architectonic setting-ups. © 2013.

Functional discrimination of membrane proteins using machine learning techniques

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Yabuki Yukimitsu

2008-03-01

Full Text Available Abstract Background Discriminating membrane proteins based on their functions is an important task in genome annotation. In this work, we have analyzed the characteristic features of amino acid residues in membrane proteins that perform major functions, such as channels/pores, electrochemical potential-driven transporters and primary active transporters. Results We observed that the residues Asp, Asn and Tyr are dominant in channels/pores whereas the composition of hydrophobic residues, Phe, Gly, Ile, Leu and Val is high in electrochemical potential-driven transporters. The composition of all the amino acids in primary active transporters lies in between other two classes of proteins. We have utilized different machine learning algorithms, such as, Bayes rule, Logistic function, Neural network, Support vector machine, Decision tree etc. for discriminating these classes of proteins. We observed that most of the algorithms have discriminated them with similar accuracy. The neural network method discriminated the channels/pores, electrochemical potential-driven transporters and active transporters with the 5-fold cross validation accuracy of 64% in a data set of 1718 membrane proteins. The application of amino acid occurrence improved the overall accuracy to 68%. In addition, we have discriminated transporters from other α-helical and β-barrel membrane proteins with the accuracy of 85% using k-nearest neighbor method. The classification of transporters and all other proteins (globular and membrane showed the accuracy of 82%. Conclusion The performance of discrimination with amino acid occurrence is better than that with amino acid composition. We suggest that this method could be effectively used to discriminate transporters from all other globular and membrane proteins, and classify them into channels/pores, electrochemical and active transporters.

Evaluation of GO-based functional similarity measures using S. cerevisiae protein interaction and expression profile data

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Du LinFang

2008-11-01

Full Text Available Abstract Background Researchers interested in analysing the expression patterns of functionally related genes usually hope to improve the accuracy of their results beyond the boundaries of currently available experimental data. Gene ontology (GO data provides a novel way to measure the functional relationship between gene products. Many approaches have been reported for calculating the similarities between two GO terms, known as semantic similarities. However, biologists are more interested in the relationship between gene products than in the scores linking the GO terms. To highlight the relationships among genes, recent studies have focused on functional similarities. Results In this study, we evaluated five functional similarity methods using both protein-protein interaction (PPI and expression data of S. cerevisiae. The receiver operating characteristics (ROC and correlation coefficient analysis of these methods showed that the maximum method outperformed the other methods. Statistical comparison of multiple- and single-term annotated proteins in biological process ontology indicated that genes with multiple GO terms may be more reliable for separating true positives from noise. Conclusion This study demonstrated the reliability of current approaches that elevate the similarity of GO terms to the similarity of proteins. Suggestions for further improvements in functional similarity analysis are also provided.

Effects of thermally induced denaturation on technological-functional properties of whey protein isolate-based films.

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Schmid, M; Krimmel, B; Grupa, U; Noller, K

2014-09-01

This study examined how and to what extent the degree of denaturation affected the technological-functional properties of whey protein isolate (WPI)-based coatings. It was observed that denaturation affected the material properties of WPI-coated films significantly. Surface energy decreased by approximately 20% compared with native coatings. Because the surface energy of a coating should be lower than that of the substrate, this might result in enhanced wettability characteristics between WPI-based solution and substrate surface. Water vapor barrier properties increased by about 35% and oxygen barrier properties increased by approximately 33%. However, significant differences were mainly observed between coatings made of fully native WPI and ones with a degree of denaturation of 25%. Higher degrees of denaturation did not lead to further improvement of material properties. This observation offers cost-saving potential: a major share of denatured whey proteins may be replaced by fully native ones that are not exposed to energy-intensive heat treatment. Furthermore, native WPI solutions can be produced with higher dry matter content without gelatinizing. Hence, less moisture has to be removed through drying, resulting in reduced energy consumption. Copyright © 2014 American Dairy Science Association. Published by Elsevier Inc. All rights reserved.

Enzymatic functionalization of a nanobody using protein insertion technology.

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Crasson, O; Rhazi, N; Jacquin, O; Freichels, A; Jérôme, C; Ruth, N; Galleni, M; Filée, P; Vandevenne, M

2015-10-01

Antibody-based products constitute one of the most attractive biological molecules for diagnostic, medical imagery and therapeutic purposes with very few side effects. Their development has become a major priority of biotech and pharmaceutical industries. Recently, a growing number of modified antibody-based products have emerged including fragments, multi-specific and conjugate antibodies. In this study, using protein engineering, we have functionalized the anti-hen egg-white lysozyme (HEWL) camelid VHH antibody fragment (cAb-Lys3), by insertion into a solvent-exposed loop of the Bacillus licheniformis β-lactamase BlaP. We showed that the generated hybrid protein conserved its enzymatic activity while the displayed nanobody retains its ability to inhibit HEWL with a nanomolar affinity range. Then, we successfully implemented the functionalized cAb-Lys3 in enzyme-linked immunosorbent assay, potentiometric biosensor and drug screening assays. The hybrid protein was also expressed on the surface of phage particles and, in this context, was able to interact specifically with HEWL while the β-lactamase activity was used to monitor phage interactions. Finally, using thrombin-cleavage sites surrounding the permissive insertion site in the β-lactamase, we reported an expression system in which the nanobody can be easily separated from its carrier protein. Altogether, our study shows that insertion into the BlaP β-lactamase constitutes a suitable technology to functionalize nanobodies and allows the creation of versatile tools that can be used in innovative biotechnological assays. © The Author 2015. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

DECK: Distance and environment-dependent, coarse-grained, knowledge-based potentials for protein-protein docking

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Vakser Ilya A

2011-07-01

Full Text Available Abstract Background Computational approaches to protein-protein docking typically include scoring aimed at improving the rank of the near-native structure relative to the false-positive matches. Knowledge-based potentials improve modeling of protein complexes by taking advantage of the rapidly increasing amount of experimentally derived information on protein-protein association. An essential element of knowledge-based potentials is defining the reference state for an optimal description of the residue-residue (or atom-atom pairs in the non-interaction state. Results The study presents a new Distance- and Environment-dependent, Coarse-grained, Knowledge-based (DECK potential for scoring of protein-protein docking predictions. Training sets of protein-protein matches were generated based on bound and unbound forms of proteins taken from the DOCKGROUND resource. Each residue was represented by a pseudo-atom in the geometric center of the side chain. To capture the long-range and the multi-body interactions, residues in different secondary structure elements at protein-protein interfaces were considered as different residue types. Five reference states for the potentials were defined and tested. The optimal reference state was selected and the cutoff effect on the distance-dependent potentials investigated. The potentials were validated on the docking decoys sets, showing better performance than the existing potentials used in scoring of protein-protein docking results. Conclusions A novel residue-based statistical potential for protein-protein docking was developed and validated on docking decoy sets. The results show that the scoring function DECK can successfully identify near-native protein-protein matches and thus is useful in protein docking. In addition to the practical application of the potentials, the study provides insights into the relative utility of the reference states, the scope of the distance dependence, and the coarse-graining of

Mutagenesis Objective Search and Selection Tool (MOSST: an algorithm to predict structure-function related mutations in proteins

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Asenjo Juan A

2011-04-01

Full Text Available Abstract Background Functionally relevant artificial or natural mutations are difficult to assess or predict if no structure-function information is available for a protein. This is especially important to correctly identify functionally significant non-synonymous single nucleotide polymorphisms (nsSNPs or to design a site-directed mutagenesis strategy for a target protein. A new and powerful methodology is proposed to guide these two decision strategies, based only on conservation rules of physicochemical properties of amino acids extracted from a multiple alignment of a protein family where the target protein belongs, with no need of explicit structure-function relationships. Results A statistical analysis is performed over each amino acid position in the multiple protein alignment, based on different amino acid physical or chemical characteristics, including hydrophobicity, side-chain volume, charge and protein conformational parameters. The variances of each of these properties at each position are combined to obtain a global statistical indicator of the conservation degree of each property. Different types of physicochemical conservation are defined to characterize relevant and irrelevant positions. The differences between statistical variances are taken together as the basis of hypothesis tests at each position to search for functionally significant mutable sites and to identify specific mutagenesis targets. The outcome is used to statistically predict physicochemical consensus sequences based on different properties and to calculate the amino acid propensities at each position in a given protein. Hence, amino acid positions are identified that are putatively responsible for function, specificity, stability or binding interactions in a family of proteins. Once these key functional positions are identified, position-specific statistical distributions are applied to divide the 20 common protein amino acids in each position of the protein

A comprehensive software suite for protein family construction and functional site prediction.

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David Renfrew Haft

Full Text Available In functionally diverse protein families, conservation in short signature regions may outperform full-length sequence comparisons for identifying proteins that belong to a subgroup within which one specific aspect of their function is conserved. The SIMBAL workflow (Sites Inferred by Metabolic Background Assertion Labeling is a data-mining procedure for finding such signature regions. It begins by using clues from genomic context, such as co-occurrence or conserved gene neighborhoods, to build a useful training set from a large number of uncharacterized but mutually homologous proteins. When training set construction is successful, the YES partition is enriched in proteins that share function with the user's query sequence, while the NO partition is depleted. A selected query sequence is then mined for short signature regions whose closest matches overwhelmingly favor proteins from the YES partition. High-scoring signature regions typically contain key residues critical to functional specificity, so proteins with the highest sequence similarity across these regions tend to share the same function. The SIMBAL algorithm was described previously, but significant manual effort, expertise, and a supporting software infrastructure were required to prepare the requisite training sets. Here, we describe a new, distributable software suite that speeds up and simplifies the process for using SIMBAL, most notably by providing tools that automate training set construction. These tools have broad utility for comparative genomics, allowing for flexible collection of proteins or protein domains based on genomic context as well as homology, a capability that can greatly assist in protein family construction. Armed with this new software suite, SIMBAL can serve as a fast and powerful in silico alternative to direct experimentation for characterizing proteins and their functional interactions.

Linking structural features of protein complexes and biological function.

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Sowmya, Gopichandran; Breen, Edmond J; Ranganathan, Shoba

2015-09-01

Protein-protein interaction (PPI) establishes the central basis for complex cellular networks in a biological cell. Association of proteins with other proteins occurs at varying affinities, yet with a high degree of specificity. PPIs lead to diverse functionality such as catalysis, regulation, signaling, immunity, and inhibition, playing a crucial role in functional genomics. The molecular principle of such interactions is often elusive in nature. Therefore, a comprehensive analysis of known protein complexes from the Protein Data Bank (PDB) is essential for the characterization of structural interface features to determine structure-function relationship. Thus, we analyzed a nonredundant dataset of 278 heterodimer protein complexes, categorized into major functional classes, for distinguishing features. Interestingly, our analysis has identified five key features (interface area, interface polar residue abundance, hydrogen bonds, solvation free energy gain from interface formation, and binding energy) that are discriminatory among the functional classes using Kruskal-Wallis rank sum test. Significant correlations between these PPI interface features amongst functional categories are also documented. Salt bridges correlate with interface area in regulator-inhibitors (r = 0.75). These representative features have implications for the prediction of potential function of novel protein complexes. The results provide molecular insights for better understanding of PPIs and their relation to biological functions. © 2015 The Protein Society.

Surface dynamics in allosteric regulation of protein-protein interactions: modulation of calmodulin functions by Ca2+.

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Yosef Y Kuttner

2013-04-01

Full Text Available Knowledge of the structural basis of protein-protein interactions (PPI is of fundamental importance for understanding the organization and functioning of biological networks and advancing the design of therapeutics which target PPI. Allosteric modulators play an important role in regulating such interactions by binding at site(s orthogonal to the complex interface and altering the protein's propensity for complex formation. In this work, we apply an approach recently developed by us for analyzing protein surfaces based on steered molecular dynamics simulation (SMD to the study of the dynamic properties of functionally distinct conformations of a model protein, calmodulin (CaM, whose ability to interact with target proteins is regulated by the presence of the allosteric modulator Ca(2+. Calmodulin is a regulatory protein that acts as an intracellular Ca(2+ sensor to control a wide variety of cellular processes. We demonstrate that SMD analysis is capable of pinpointing CaM surfaces implicated in the recognition of both the allosteric modulator Ca(2+ and target proteins. Our analysis of changes in the dynamic properties of the CaM backbone elicited by Ca(2+ binding yielded new insights into the molecular mechanism of allosteric regulation of CaM-target interactions.

Exploring Protein Function Using the Saccharomyces Genome Database.

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Wong, Edith D

2017-01-01

Elucidating the function of individual proteins will help to create a comprehensive picture of cell biology, as well as shed light on human disease mechanisms, possible treatments, and cures. Due to its compact genome, and extensive history of experimentation and annotation, the budding yeast Saccharomyces cerevisiae is an ideal model organism in which to determine protein function. This information can then be leveraged to infer functions of human homologs. Despite the large amount of research and biological data about S. cerevisiae, many proteins' functions remain unknown. Here, we explore ways to use the Saccharomyces Genome Database (SGD; http://www.yeastgenome.org ) to predict the function of proteins and gain insight into their roles in various cellular processes.

Cysteine regulation of protein function--as exemplified by NMDA-receptor modulation.

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Lipton, Stuart A; Choi, Yun-Beom; Takahashi, Hiroto; Zhang, Dongxian; Li, Weizhong; Godzik, Adam; Bankston, Laurie A

2002-09-01

Until recently cysteine residues, especially those located extracellularly, were thought to be important for metal coordination, catalysis and protein structure by forming disulfide bonds - but they were not thought to regulate protein function. However, this is not the case. Crucial cysteine residues can be involved in modulation of protein activity and signaling events via other reactions of their thiol (sulfhydryl; -SH) groups. These reactions can take several forms, such as redox events (chemical reduction or oxidation), chelation of transition metals (chiefly Zn(2+), Mn(2+) and Cu(2+)) or S-nitrosylation [the catalyzed transfer of a nitric oxide (NO) group to a thiol group]. In several cases, these disparate reactions can compete with one another for the same thiol group on a single cysteine residue, forming a molecular switch composed of a latticework of possible redox, NO or Zn(2+) modifications to control protein function. Thiol-mediated regulation of protein function can also involve reactions of cysteine residues that affect ligand binding allosterically. This article reviews the basis for these molecular cysteine switches, drawing on the NMDA receptor as an exemplary protein, and proposes a molecular model for the action of S-nitrosylation based on recently derived crystal structures.

Hypothesis: NDL proteins function in stress responses by regulating microtubule organization.

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Khatri, Nisha; Mudgil, Yashwanti

2015-01-01

N-MYC DOWNREGULATED-LIKE proteins (NDL), members of the alpha/beta hydrolase superfamily were recently rediscovered as interactors of G-protein signaling in Arabidopsis thaliana. Although the precise molecular function of NDL proteins is still elusive, in animals these proteins play protective role in hypoxia and expression is induced by hypoxia and nickel, indicating role in stress. Homology of NDL1 with animal counterpart N-MYC DOWNREGULATED GENE (NDRG) suggests similar functions in animals and plants. It is well established that stress responses leads to the microtubule depolymerization and reorganization which is crucial for stress tolerance. NDRG is a microtubule-associated protein which mediates the microtubule organization in animals by causing acetylation and increases the stability of α-tubulin. As NDL1 is highly homologous to NDRG, involvement of NDL1 in the microtubule organization during plant stress can also be expected. Discovery of interaction of NDL with protein kinesin light chain- related 1, enodomembrane family protein 70, syntaxin-23, tubulin alpha-2 chain, as a part of G protein interactome initiative encourages us to postulate microtubule stabilizing functions for NDL family in plants. Our search for NDL interactors in G protein interactome also predicts the role of NDL proteins in abiotic stress tolerance management. Based on published report in animals and predicted interacting partners for NDL in G protein interactome lead us to hypothesize involvement of NDL in the microtubule organization during abiotic stress management in plants.

Global functional atlas of Escherichia coli encompassing previously uncharacterized proteins.

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Hu, Pingzhao; Janga, Sarath Chandra; Babu, Mohan; Díaz-Mejía, J Javier; Butland, Gareth; Yang, Wenhong; Pogoutse, Oxana; Guo, Xinghua; Phanse, Sadhna; Wong, Peter; Chandran, Shamanta; Christopoulos, Constantine; Nazarians-Armavil, Anaies; Nasseri, Negin Karimi; Musso, Gabriel; Ali, Mehrab; Nazemof, Nazila; Eroukova, Veronika; Golshani, Ashkan; Paccanaro, Alberto; Greenblatt, Jack F; Moreno-Hagelsieb, Gabriel; Emili, Andrew

2009-04-28

One-third of the 4,225 protein-coding genes of Escherichia coli K-12 remain functionally unannotated (orphans). Many map to distant clades such as Archaea, suggesting involvement in basic prokaryotic traits, whereas others appear restricted to E. coli, including pathogenic strains. To elucidate the orphans' biological roles, we performed an extensive proteomic survey using affinity-tagged E. coli strains and generated comprehensive genomic context inferences to derive a high-confidence compendium for virtually the entire proteome consisting of 5,993 putative physical interactions and 74,776 putative functional associations, most of which are novel. Clustering of the respective probabilistic networks revealed putative orphan membership in discrete multiprotein complexes and functional modules together with annotated gene products, whereas a machine-learning strategy based on network integration implicated the orphans in specific biological processes. We provide additional experimental evidence supporting orphan participation in protein synthesis, amino acid metabolism, biofilm formation, motility, and assembly of the bacterial cell envelope. This resource provides a "systems-wide" functional blueprint of a model microbe, with insights into the biological and evolutionary significance of previously uncharacterized proteins.

Differential Labeling of Free and Disulfide-Bound Thiol Functions in Proteins

NARCIS (Netherlands)

Seiwert, B.; Hayen, H.; Karst, U.

2008-01-01

A method for the simultaneous determination of the number of free cysteine groups and disulfide-bound cysteine groups in proteins has been developed based on the sequential labeling of free and bound thiol functionalities with two ferrocene-based maleimide reagents. Liquid

Proteome Profiling Outperforms Transcriptome Profiling for Coexpression Based Gene Function Prediction

Energy Technology Data Exchange (ETDEWEB)

Wang, Jing; Ma, Zihao; Carr, Steven A.; Mertins, Philipp; Zhang, Hui; Zhang, Zhen; Chan, Daniel W.; Ellis, Matthew J. C.; Townsend, R. Reid; Smith, Richard D.; McDermott, Jason E.; Chen, Xian; Paulovich, Amanda G.; Boja, Emily S.; Mesri, Mehdi; Kinsinger, Christopher R.; Rodriguez, Henry; Rodland, Karin D.; Liebler, Daniel C.; Zhang, Bing

2016-11-11

Coexpression of mRNAs under multiple conditions is commonly used to infer cofunctionality of their gene products despite well-known limitations of this “guilt-by-association” (GBA) approach. Recent advancements in mass spectrometry-based proteomic technologies have enabled global expression profiling at the protein level; however, whether proteome profiling data can outperform transcriptome profiling data for coexpression based gene function prediction has not been systematically investigated. Here, we address this question by constructing and analyzing mRNA and protein coexpression networks for three cancer types with matched mRNA and protein profiling data from The Cancer Genome Atlas (TCGA) and the Clinical Proteomic Tumor Analysis Consortium (CPTAC). Our analyses revealed a marked difference in wiring between the mRNA and protein coexpression networks. Whereas protein coexpression was driven primarily by functional similarity between coexpressed genes, mRNA coexpression was driven by both cofunction and chromosomal colocalization of the genes. Functionally coherent mRNA modules were more likely to have their edges preserved in corresponding protein networks than functionally incoherent mRNA modules. Proteomic data strengthened the link between gene expression and function for at least 75% of Gene Ontology (GO) biological processes and 90% of KEGG pathways. A web application Gene2Net (http://cptac.gene2net.org) developed based on the three protein coexpression networks revealed novel gene-function relationships, such as linking ERBB2 (HER2) to lipid biosynthetic process in breast cancer, identifying PLG as a new gene involved in complement activation, and identifying AEBP1 as a new epithelial-mesenchymal transition (EMT) marker. Our results demonstrate that proteome profiling outperforms transcriptome profiling for coexpression based gene function prediction. Proteomics should be integrated if not preferred in gene function and human disease studies

Protein profile of human hepatocarcinoma cell line SMMC-7721: Identification and functional analysis

Institute of Scientific and Technical Information of China (English)

Yi Feng; Zhong-Min Tian; Ming-Xi Wan; Zhao-Bin Zheng

2007-01-01

AIM: To investigate the protein profile of human hepatocarcinoma cell line SMMC-7721, to analyze the specific functions of abundant expressed proteins in the processes of hepatocarcinoma genesis, growth and metastasis, to identify the hepatocarcinoma-specific biomarkers for the early prediction in diagnosis, and to explore the new drug targets for liver cancer therapy.METHODS: Total proteins from human hepatocarcinomacell line SMMC-7721 were separated by two-dimensional electrophoresis (2DE). The silver-stained gel was analyzed by 2DE software Image Master 2D Elite.Interesting protein spots were identified by peptide mass fingerprinting based on matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF-MS)and database searching.RESULTS: We obtained protein profile of human hepatocarcinoma cell line SMMC-7721. Among the twenty-one successfully identified proteins, mitofilin,endoplasmic reticulum protein ERp29, ubiquinol-cytochrome C reductase complex core protein Ⅰ,peroxisomal enoyl CoA hydratase, peroxiredoxin-4 and probable 3-oxoacid CoA transferase 1 precursor were the six novel proteins identified in human hepatocarcinoma cells or tissues. Specific functions of the identified heat-shock proteins were analyzed in detail, and the results suggested that these proteins might promote tumorigenesis via inhibiting cell death induced by several cancer-related stresses or via inhibiting apoptosis at multiple points in the apoptotic signal pathway. Other identified chaperones and cancer-related proteins were also analyzed.CONCLUSION: Based on the protein profile of SMMC-7721 cells, functional analysis suggests that the identified chaperones and cancer-related proteins have their own pathways to contribute to the tumorigenesis, tumor growth and metastasis of liver cancer. Furthermore, proteomic analysis is indicated to be feasible in the cancer study.

Unveiling protein functions through the dynamics of the interaction network.

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Irene Sendiña-Nadal

Full Text Available Protein interaction networks have become a tool to study biological processes, either for predicting molecular functions or for designing proper new drugs to regulate the main biological interactions. Furthermore, such networks are known to be organized in sub-networks of proteins contributing to the same cellular function. However, the protein function prediction is not accurate and each protein has traditionally been assigned to only one function by the network formalism. By considering the network of the physical interactions between proteins of the yeast together with a manual and single functional classification scheme, we introduce a method able to reveal important information on protein function, at both micro- and macro-scale. In particular, the inspection of the properties of oscillatory dynamics on top of the protein interaction network leads to the identification of misclassification problems in protein function assignments, as well as to unveil correct identification of protein functions. We also demonstrate that our approach can give a network representation of the meta-organization of biological processes by unraveling the interactions between different functional classes.

Effects of Acids, Bases, and Heteroatoms on Proximal Radial Distribution Functions for Proteins.

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Nguyen, Bao Linh; Pettitt, B Montgomery

2015-04-14

The proximal distribution of water around proteins is a convenient method of quantifying solvation. We consider the effect of charged and sulfur-containing amino acid side-chain atoms on the proximal radial distribution function (pRDF) of water molecules around proteins using side-chain analogs. The pRDF represents the relative probability of finding any solvent molecule at a distance from the closest or surface perpendicular protein atom. We consider the near-neighbor distribution. Previously, pRDFs were shown to be universal descriptors of the water molecules around C, N, and O atom types across hundreds of globular proteins. Using averaged pRDFs, a solvent density around any globular protein can be reconstructed with controllable relative error. Solvent reconstruction using the additional information from charged amino acid side-chain atom types from both small models and protein averages reveals the effects of surface charge distribution on solvent density and improves the reconstruction errors relative to simulation. Solvent density reconstructions from the small-molecule models are as effective and less computationally demanding than reconstructions from full macromolecular models in reproducing preferred hydration sites and solvent density fluctuations.

Multiplexed Imaging of Protein Phosphorylation on Membranes Based on Ti(IV) Functionalized Nanopolymers.

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Iliuk, Anton; Li, Li; Melesse, Michael; Hall, Mark C; Tao, W Andy

2016-05-17

Accurate protein phosphorylation analysis reveals dynamic cellular signaling events not evident from protein expression levels. The most dominant biochemical assay, western blotting, suffers from the inadequate availability and poor quality of phospho-specific antibodies for phosphorylated proteins. Furthermore, multiplexed assays based on antibodies are limited by steric interference between the antibodies. Here we introduce a multifunctionalized nanopolymer for the universal detection of phosphoproteins that, in combination with regular antibodies, allows multiplexed imaging and accurate determination of protein phosphorylation on membranes. © 2016 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Biomimetic devices functionalized by membrane channel proteins

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Schmidt, Jacob

2004-03-01

We are developing a new family of active materials which derive their functional properties from membrane proteins. These materials have two primary components: the proteins and the membranes themselves. I will discuss our recent work directed toward development of a generic platform for a "plug-and-play" philosophy of membrane protein engineering. By creating a stable biomimetic polymer membrane a single molecular monolayer thick, we will enable the exploitation of the function of any membrane protein, from pores and pumps to sensors and energy transducers. Our initial work has centered on the creation, study, and characterization of the biomimetic membranes. We are attempting to make large areas of membrane monolayers using Langmuir-Blodgett film formation as well as through arrays of microfabricated black lipid membrane-type septa. A number of techniques allow the insertion of protein into the membranes. As a benchmark, we have been employing a model system of voltage-gated pore proteins, which have electrically controllable porosities. I will report on the progress of this work, the characterization of the membranes, protein insertion processes, and the yield and functionality of the composite.

Improved Functional Characteristics of Whey Protein Hydrolysates in Food Industry

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Jeewanthi, Renda Kankanamge Chaturika; Lee, Na-Kyoung; Paik, Hyun-Dong

2015-01-01

This review focuses on the enhanced functional characteristics of enzymatic hydrolysates of whey proteins (WPHs) in food applications compared to intact whey proteins (WPs). WPs are applied in foods as whey protein concentrates (WPCs), whey protein isolates (WPIs), and WPHs. WPs are byproducts of cheese production, used in a wide range of food applications due to their nutritional validity, functional activities, and cost effectiveness. Enzymatic hydrolysis yields improved functional and nutritional benefits in contrast to heat denaturation or native applications. WPHs improve solubility over a wide range of pH, create viscosity through water binding, and promote cohesion, adhesion, and elasticity. WPHs form stronger but more flexible edible films than WPC or WPI. WPHs enhance emulsification, bind fat, and facilitate whipping, compared to intact WPs. Extensive hydrolyzed WPHs with proper heat applications are the best emulsifiers and addition of polysaccharides improves the emulsification ability of WPHs. Also, WPHs improve the sensorial properties like color, flavor, and texture but impart a bitter taste in case where extensive hydrolysis (degree of hydrolysis greater than 8%). It is important to consider the type of enzyme, hydrolysis conditions, and WPHs production method based on the nature of food application. PMID:26761849

Insulator function and topological domain border strength scale with architectural protein occupancy

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2014-01-01

Background Chromosome conformation capture studies suggest that eukaryotic genomes are organized into structures called topologically associating domains. The borders of these domains are highly enriched for architectural proteins with characterized roles in insulator function. However, a majority of architectural protein binding sites localize within topological domains, suggesting sites associated with domain borders represent a functionally different subclass of these regulatory elements. How topologically associating domains are established and what differentiates border-associated from non-border architectural protein binding sites remain unanswered questions. Results By mapping the genome-wide target sites for several Drosophila architectural proteins, including previously uncharacterized profiles for TFIIIC and SMC-containing condensin complexes, we uncover an extensive pattern of colocalization in which architectural proteins establish dense clusters at the borders of topological domains. Reporter-based enhancer-blocking insulator activity as well as endogenous domain border strength scale with the occupancy level of architectural protein binding sites, suggesting co-binding by architectural proteins underlies the functional potential of these loci. Analyses in mouse and human stem cells suggest that clustering of architectural proteins is a general feature of genome organization, and conserved architectural protein binding sites may underlie the tissue-invariant nature of topologically associating domains observed in mammals. Conclusions We identify a spectrum of architectural protein occupancy that scales with the topological structure of chromosomes and the regulatory potential of these elements. Whereas high occupancy architectural protein binding sites associate with robust partitioning of topologically associating domains and robust insulator function, low occupancy sites appear reserved for gene-specific regulation within topological domains. PMID

Investigation and identification of functional post-translational modification sites associated with drug binding and protein-protein interactions.

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Su, Min-Gang; Weng, Julia Tzu-Ya; Hsu, Justin Bo-Kai; Huang, Kai-Yao; Chi, Yu-Hsiang; Lee, Tzong-Yi

2017-12-21

Protein post-translational modification (PTM) plays an essential role in various cellular processes that modulates the physical and chemical properties, folding, conformation, stability and activity of proteins, thereby modifying the functions of proteins. The improved throughput of mass spectrometry (MS) or MS/MS technology has not only brought about a surge in proteome-scale studies, but also contributed to a fruitful list of identified PTMs. However, with the increase in the number of identified PTMs, perhaps the more crucial question is what kind of biological mechanisms these PTMs are involved in. This is particularly important in light of the fact that most protein-based pharmaceuticals deliver their therapeutic effects through some form of PTM. Yet, our understanding is still limited with respect to the local effects and frequency of PTM sites near pharmaceutical binding sites and the interfaces of protein-protein interaction (PPI). Understanding PTM's function is critical to our ability to manipulate the biological mechanisms of protein. In this study, to understand the regulation of protein functions by PTMs, we mapped 25,835 PTM sites to proteins with available three-dimensional (3D) structural information in the Protein Data Bank (PDB), including 1785 modified PTM sites on the 3D structure. Based on the acquired structural PTM sites, we proposed to use five properties for the structural characterization of PTM substrate sites: the spatial composition of amino acids, residues and side-chain orientations surrounding the PTM substrate sites, as well as the secondary structure, division of acidity and alkaline residues, and solvent-accessible surface area. We further mapped the structural PTM sites to the structures of drug binding and PPI sites, identifying a total of 1917 PTM sites that may affect PPI and 3951 PTM sites associated with drug-target binding. An integrated analytical platform (CruxPTM), with a variety of methods and online molecular docking

Improving protein function prediction methods with integrated literature data

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Gabow Aaron P

2008-04-01

Full Text Available Abstract Background Determining the function of uncharacterized proteins is a major challenge in the post-genomic era due to the problem's complexity and scale. Identifying a protein's function contributes to an understanding of its role in the involved pathways, its suitability as a drug target, and its potential for protein modifications. Several graph-theoretic approaches predict unidentified functions of proteins by using the functional annotations of better-characterized proteins in protein-protein interaction networks. We systematically consider the use of literature co-occurrence data, introduce a new method for quantifying the reliability of co-occurrence and test how performance differs across species. We also quantify changes in performance as the prediction algorithms annotate with increased specificity. Results We find that including information on the co-occurrence of proteins within an abstract greatly boosts performance in the Functional Flow graph-theoretic function prediction algorithm in yeast, fly and worm. This increase in performance is not simply due to the presence of additional edges since supplementing protein-protein interactions with co-occurrence data outperforms supplementing with a comparably-sized genetic interaction dataset. Through the combination of protein-protein interactions and co-occurrence data, the neighborhood around unknown proteins is quickly connected to well-characterized nodes which global prediction algorithms can exploit. Our method for quantifying co-occurrence reliability shows superior performance to the other methods, particularly at threshold values around 10% which yield the best trade off between coverage and accuracy. In contrast, the traditional way of asserting co-occurrence when at least one abstract mentions both proteins proves to be the worst method for generating co-occurrence data, introducing too many false positives. Annotating the functions with greater specificity is harder

Functional properties of whey protein and its application in nanocomposite materials and functional foods

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Walsh, Helen

Whey is a byproduct of cheese making; whey proteins are globular proteins which can be modified and polymerized to add functional benefits, these benefits can be both nutritional and structural in foods. Modified proteins can be used in non-foods, being of particular interest in polymer films and coatings. Food packaging materials, including plastics, can linings, interior coatings of paper containers, and beverage cap sealing materials, are generally made of synthetic petroleum based compounds. These synthetic materials may pose a potential human health risk due to presence of certain chemicals such as Bisphenol A (BPA). They also add to environmental pollution, being difficult to degrade. Protein-based materials do not have the same issues as synthetics and so can be used as alternatives in many packaging types. As proteins are generally hydrophilic they must be modified structurally and their performance enhanced by the addition of waterproofing agents. Polymerization of whey proteins results in a network, adding both strength and flexibility. The most interesting of the food-safe waterproofing agents are the (large aspect ratio) nanoclays. Nanoclays are relatively inexpensive, widely available and have low environmental impact. The clay surface can be modified to make it organophilic and so compatible with organic polymers. The objective of this study is the use of polymerized whey protein (PWP), with reinforcing nanoclays, to produce flexible surface coatings which limit the transfer of contents while maintaining food safety. Four smectite and kaolin type clays, one treated and three natural were assessed for strengthening qualities and the potential waterproofing and plasticizing benefits of other additives were also analyzed. The nutritional benefits of whey proteins can also be used to enhance the protein content of various foodstuffs. Drinkable yogurt is a popular beverage in the US and other countries and is considered a functional food, especially when

Functions of intrinsic disorder in transmembrane proteins

DEFF Research Database (Denmark)

Kjaergaard, Magnus; Kragelund, Birthe B.

2017-01-01

Intrinsic disorder is common in integral membrane proteins, particularly in the intracellular domains. Despite this observation, these domains are not always recognized as being disordered. In this review, we will discuss the biological functions of intrinsically disordered regions of membrane...... receptors. The functions of the disordered regions are many and varied. We will discuss selected examples including: (1) Organization of receptors, kinases, phosphatases and second messenger sources into signaling complexes. (2) Modulation of the membrane-embedded domain function by ball-and-chain like...... mechanisms. (3) Trafficking of membrane proteins. (4) Transient membrane associations. (5) Post-translational modifications most notably phosphorylation and (6) disorder-linked isoform dependent function. We finish the review by discussing the future challenges facing the membrane protein community regarding...

Analysis of substructural variation in families of enzymatic proteins with applications to protein function prediction

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Fofanov Viacheslav Y

2010-05-01

Full Text Available Abstract Background Structural variations caused by a wide range of physico-chemical and biological sources directly influence the function of a protein. For enzymatic proteins, the structure and chemistry of the catalytic binding site residues can be loosely defined as a substructure of the protein. Comparative analysis of drug-receptor substructures across and within species has been used for lead evaluation. Substructure-level similarity between the binding sites of functionally similar proteins has also been used to identify instances of convergent evolution among proteins. In functionally homologous protein families, shared chemistry and geometry at catalytic sites provide a common, local point of comparison among proteins that may differ significantly at the sequence, fold, or domain topology levels. Results This paper describes two key results that can be used separately or in combination for protein function analysis. The Family-wise Analysis of SubStructural Templates (FASST method uses all-against-all substructure comparison to determine Substructural Clusters (SCs. SCs characterize the binding site substructural variation within a protein family. In this paper we focus on examples of automatically determined SCs that can be linked to phylogenetic distance between family members, segregation by conformation, and organization by homology among convergent protein lineages. The Motif Ensemble Statistical Hypothesis (MESH framework constructs a representative motif for each protein cluster among the SCs determined by FASST to build motif ensembles that are shown through a series of function prediction experiments to improve the function prediction power of existing motifs. Conclusions FASST contributes a critical feedback and assessment step to existing binding site substructure identification methods and can be used for the thorough investigation of structure-function relationships. The application of MESH allows for an automated

GOLabeler: Improving Sequence-based Large-scale Protein Function Prediction by Learning to Rank.

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You, Ronghui; Zhang, Zihan; Xiong, Yi; Sun, Fengzhu; Mamitsuka, Hiroshi; Zhu, Shanfeng

2018-03-07

Gene Ontology (GO) has been widely used to annotate functions of proteins and understand their biological roles. Currently only advantage over state-of-the-art AFP methods. http://datamining-iip.fudan.edu.cn/golabeler. zhusf@fudan.edu.cn. Supplementary data are available at Bioinformatics online.

Annotating Protein Functional Residues by Coupling High-Throughput Fitness Profile and Homologous-Structure Analysis

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Yushen Du

2016-11-01

Full Text Available Identification and annotation of functional residues are fundamental questions in protein sequence analysis. Sequence and structure conservation provides valuable information to tackle these questions. It is, however, limited by the incomplete sampling of sequence space in natural evolution. Moreover, proteins often have multiple functions, with overlapping sequences that present challenges to accurate annotation of the exact functions of individual residues by conservation-based methods. Using the influenza A virus PB1 protein as an example, we developed a method to systematically identify and annotate functional residues. We used saturation mutagenesis and high-throughput sequencing to measure the replication capacity of single nucleotide mutations across the entire PB1 protein. After predicting protein stability upon mutations, we identified functional PB1 residues that are essential for viral replication. To further annotate the functional residues important to the canonical or noncanonical functions of viral RNA-dependent RNA polymerase (vRdRp, we performed a homologous-structure analysis with 16 different vRdRp structures. We achieved high sensitivity in annotating the known canonical polymerase functional residues. Moreover, we identified a cluster of noncanonical functional residues located in the loop region of the PB1 β-ribbon. We further demonstrated that these residues were important for PB1 protein nuclear import through the interaction with Ran-binding protein 5. In summary, we developed a systematic and sensitive method to identify and annotate functional residues that are not restrained by sequence conservation. Importantly, this method is generally applicable to other proteins about which homologous-structure information is available.

Multivesicular Bodies in Neurons: Distribution, Protein Content, and Trafficking Functions

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VON BARTHELD, CHRISTOPHER S.; ALTICK, AMY L.

2011-01-01

Summary Multivesicular bodies (MVBs) are intracellular endosomal organelles characterized by multiple internal vesicles that are enclosed within a single outer membrane. MVBs were initially regarded as purely prelysosomal structures along the degradative endosomal pathway of internalized proteins. MVBs are now known to be involved in numerous endocytic and trafficking functions, including protein sorting, recycling, transport, storage, and release. This review of neuronal MVBs summarizes their research history, morphology, distribution, accumulation of cargo and constitutive proteins, transport, and theories of functions of MVBs in neurons and glia. Due to their complex morphologies, neurons have expanded trafficking and signaling needs, beyond those of “geometrically simpler” cells, but it is not known whether neuronal MVBs perform additional transport and signaling functions. This review examines the concept of compartment-specific MVB functions in endosomal protein trafficking and signaling within synapses, axons, dendrites and cell bodies. We critically evaluate reports of the accumulation of neuronal MVBs based on evidence of stress-induced MVB formation. Furthermore, we discuss potential functions of neuronal and glial MVBs in development, in dystrophic neuritic syndromes, injury, disease, and aging. MVBs may play a role in Alzheimer’s, Huntington’s, and Niemann-Pick diseases, some types of frontotemporal dementia, prion and virus trafficking, as well as in adaptive responses of neurons to trauma and toxin or drug exposure. Functions of MVBs in neurons have been much neglected, and major gaps in knowledge currently exist. Developing truly MVB-specific markers would help to elucidate the roles of neuronal MVBs in intra- and intercellular signaling of normal and diseased neurons. PMID:21216273

Evaluation of Docking Target Functions by the Comprehensive Investigation of Protein-Ligand Energy Minima.

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Oferkin, Igor V; Katkova, Ekaterina V; Sulimov, Alexey V; Kutov, Danil C; Sobolev, Sergey I; Voevodin, Vladimir V; Sulimov, Vladimir B

2015-01-01

The adequate choice of the docking target function impacts the accuracy of the ligand positioning as well as the accuracy of the protein-ligand binding energy calculation. To evaluate a docking target function we compared positions of its minima with the experimentally known pose of the ligand in the protein active site. We evaluated five docking target functions based on either the MMFF94 force field or the PM7 quantum-chemical method with or without implicit solvent models: PCM, COSMO, and SGB. Each function was tested on the same set of 16 protein-ligand complexes. For exhaustive low-energy minima search the novel MPI parallelized docking program FLM and large supercomputer resources were used. Protein-ligand binding energies calculated using low-energy minima were compared with experimental values. It was demonstrated that the docking target function on the base of the MMFF94 force field in vacuo can be used for discovery of native or near native ligand positions by finding the low-energy local minima spectrum of the target function. The importance of solute-solvent interaction for the correct ligand positioning is demonstrated. It is shown that docking accuracy can be improved by replacement of the MMFF94 force field by the new semiempirical quantum-chemical PM7 method.

Evaluation of Docking Target Functions by the Comprehensive Investigation of Protein-Ligand Energy Minima

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Igor V. Oferkin

2015-01-01

Full Text Available The adequate choice of the docking target function impacts the accuracy of the ligand positioning as well as the accuracy of the protein-ligand binding energy calculation. To evaluate a docking target function we compared positions of its minima with the experimentally known pose of the ligand in the protein active site. We evaluated five docking target functions based on either the MMFF94 force field or the PM7 quantum-chemical method with or without implicit solvent models: PCM, COSMO, and SGB. Each function was tested on the same set of 16 protein-ligand complexes. For exhaustive low-energy minima search the novel MPI parallelized docking program FLM and large supercomputer resources were used. Protein-ligand binding energies calculated using low-energy minima were compared with experimental values. It was demonstrated that the docking target function on the base of the MMFF94 force field in vacuo can be used for discovery of native or near native ligand positions by finding the low-energy local minima spectrum of the target function. The importance of solute-solvent interaction for the correct ligand positioning is demonstrated. It is shown that docking accuracy can be improved by replacement of the MMFF94 force field by the new semiempirical quantum-chemical PM7 method.

Global functional atlas of Escherichia coli encompassing previously uncharacterized proteins.

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Pingzhao Hu

2009-04-01

Full Text Available One-third of the 4,225 protein-coding genes of Escherichia coli K-12 remain functionally unannotated (orphans. Many map to distant clades such as Archaea, suggesting involvement in basic prokaryotic traits, whereas others appear restricted to E. coli, including pathogenic strains. To elucidate the orphans' biological roles, we performed an extensive proteomic survey using affinity-tagged E. coli strains and generated comprehensive genomic context inferences to derive a high-confidence compendium for virtually the entire proteome consisting of 5,993 putative physical interactions and 74,776 putative functional associations, most of which are novel. Clustering of the respective probabilistic networks revealed putative orphan membership in discrete multiprotein complexes and functional modules together with annotated gene products, whereas a machine-learning strategy based on network integration implicated the orphans in specific biological processes. We provide additional experimental evidence supporting orphan participation in protein synthesis, amino acid metabolism, biofilm formation, motility, and assembly of the bacterial cell envelope. This resource provides a "systems-wide" functional blueprint of a model microbe, with insights into the biological and evolutionary significance of previously uncharacterized proteins.

Functional modules by relating protein interaction networks and gene expression.

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Tornow, Sabine; Mewes, H W

2003-11-01

Genes and proteins are organized on the basis of their particular mutual relations or according to their interactions in cellular and genetic networks. These include metabolic or signaling pathways and protein interaction, regulatory or co-expression networks. Integrating the information from the different types of networks may lead to the notion of a functional network and functional modules. To find these modules, we propose a new technique which is based on collective, multi-body correlations in a genetic network. We calculated the correlation strength of a group of genes (e.g. in the co-expression network) which were identified as members of a module in a different network (e.g. in the protein interaction network) and estimated the probability that this correlation strength was found by chance. Groups of genes with a significant correlation strength in different networks have a high probability that they perform the same function. Here, we propose evaluating the multi-body correlations by applying the superparamagnetic approach. We compare our method to the presently applied mean Pearson correlations and show that our method is more sensitive in revealing functional relationships.

UTILIZATION OF PLANT PROTEINS IN FUNCTIONAL NUTRITION

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V. G. Kulakov

2017-01-01

Full Text Available Development of functional food products technology is considered to be a prospect way for creating new food products. Such products are known to be popular among consumers. Utilization of plant proteins allows to widen and improve food assortment and quality. The article represents a review of plant proteins utilization in production of functional food. For optimization of flour confectionery chemical composition the authors utilized a method of receipts modeling. Simulation of combined products is based on the principles of food combinatorics and aims to create recipes of new types of food products on basis of methods of mathematical optimization by reasonable selection of the basic raw materials, ingredients, food additives and dietary supplements, totality of which ensures formation desired organoleptic, physical and chemical properties product as well as a predetermined level of food, biological and energy value. Modeling process of combined products recipes includes the following three stages: preparation of input data for the design, formalization requirements for the composition and properties of raw ingredients and quality final product, process modeling; product design with desired structural properties.

The functional range of heat shock proteins to combat environmental toxicity

International Nuclear Information System (INIS)

Mahmood, K.; Mahmood, Q.; Pervez, A.; Nasreen, S.

2012-01-01

Almost all the organisms possess a system to cope with the harsh physiochemical factors of environment. Such a system is based on a group of stress genes, which show rapid responses in form of stress proteins, especially heat shock proteins, when cells are confronted with insult. Heat shock proteins are now known to express in response to variety of toxic and stress conditions including diseases. As a molecular chaperone, against cytotoxicity, these ensure the functional ability of cells by repairing the denatured proteins, cellular structures like cytoskeleton and centrosomes and processes dealing with protein synthesis are stabilized or repaired during a second stress in stress tolerant cells and organisms. In unstressed cells these play an imperative role in the synthesis and transport of normal proteins. Their role in certain diseases reveals their potential application in medical field. Certain Hsp are helpful in coping carcinogenicity caused environmental pollutants and have been suggested to have anti-apoptotic, anti stress and anti-allergic function. Their expression is tissue and species specific with respect to type, intensity and duration of a toxicant. These are developmentally regulated and help in process of differentiation and thus their abnormal regulation impairs the normal development. However, their role as bio marker in risk assessment of environmental pollution warrants further research. Due to broad functional range, therefore, present review is embracing the functional aspects of smaller and Hsp 70 families expressing in animals under toxic conditions. (author)

Prediction of Protein-Protein Interactions Related to Protein Complexes Based on Protein Interaction Networks

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Peng Liu

2015-01-01

Full Text Available A method for predicting protein-protein interactions based on detected protein complexes is proposed to repair deficient interactions derived from high-throughput biological experiments. Protein complexes are pruned and decomposed into small parts based on the adaptive k-cores method to predict protein-protein interactions associated with the complexes. The proposed method is adaptive to protein complexes with different structure, number, and size of nodes in a protein-protein interaction network. Based on different complex sets detected by various algorithms, we can obtain different prediction sets of protein-protein interactions. The reliability of the predicted interaction sets is proved by using estimations with statistical tests and direct confirmation of the biological data. In comparison with the approaches which predict the interactions based on the cliques, the overlap of the predictions is small. Similarly, the overlaps among the predicted sets of interactions derived from various complex sets are also small. Thus, every predicted set of interactions may complement and improve the quality of the original network data. Meanwhile, the predictions from the proposed method replenish protein-protein interactions associated with protein complexes using only the network topology.

STRING 8--a global view on proteins and their functional interactions in 630 organisms

DEFF Research Database (Denmark)

Jensen, Lars Juhl; Kuhn, Michael; Stark, Manuel

2008-01-01

Functional partnerships between proteins are at the core of complex cellular phenotypes, and the networks formed by interacting proteins provide researchers with crucial scaffolds for modeling, data reduction and annotation. STRING is a database and web resource dedicated to protein-protein inter......Functional partnerships between proteins are at the core of complex cellular phenotypes, and the networks formed by interacting proteins provide researchers with crucial scaffolds for modeling, data reduction and annotation. STRING is a database and web resource dedicated to protein......-protein interactions, including both physical and functional interactions. It weights and integrates information from numerous sources, including experimental repositories, computational prediction methods and public text collections, thus acting as a meta-database that maps all interaction evidence onto a common set...... of genomes and proteins. The most important new developments in STRING 8 over previous releases include a URL-based programming interface, which can be used to query STRING from other resources, improved interaction prediction via genomic neighborhood in prokaryotes, and the inclusion of protein structures...

Tandem assays of protein and glucose with functionalized core/shell particles based on magnetic separation and surface-enhanced Raman scattering.

Science.gov (United States)

Kong, Xianming; Yu, Qian; Lv, Zhongpeng; Du, Xuezhong

2013-10-11

Tandem assays of protein and glucose in combination with mannose-functionalized Fe3 O4 @SiO2 and Ag@SiO2 tag particles have promising potential in effective magnetic separation and highly sensitive and selective SERS assays of biomaterials. It is for the first time that tandem assay of glucose is developed using SERS based on the Con A-sandwiched microstructures between the functionalized magnetic and tag particles. Copyright © 2013 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

HomPPI: a class of sequence homology based protein-protein interface prediction methods

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Dobbs Drena

2011-06-01

Full Text Available Abstract Background Although homology-based methods are among the most widely used methods for predicting the structure and function of proteins, the question as to whether interface sequence conservation can be effectively exploited in predicting protein-protein interfaces has been a subject of debate. Results We studied more than 300,000 pair-wise alignments of protein sequences from structurally characterized protein complexes, including both obligate and transient complexes. We identified sequence similarity criteria required for accurate homology-based inference of interface residues in a query protein sequence. Based on these analyses, we developed HomPPI, a class of sequence homology-based methods for predicting protein-protein interface residues. We present two variants of HomPPI: (i NPS-HomPPI (Non partner-specific HomPPI, which can be used to predict interface residues of a query protein in the absence of knowledge of the interaction partner; and (ii PS-HomPPI (Partner-specific HomPPI, which can be used to predict the interface residues of a query protein with a specific target protein. Our experiments on a benchmark dataset of obligate homodimeric complexes show that NPS-HomPPI can reliably predict protein-protein interface residues in a given protein, with an average correlation coefficient (CC of 0.76, sensitivity of 0.83, and specificity of 0.78, when sequence homologs of the query protein can be reliably identified. NPS-HomPPI also reliably predicts the interface residues of intrinsically disordered proteins. Our experiments suggest that NPS-HomPPI is competitive with several state-of-the-art interface prediction servers including those that exploit the structure of the query proteins. The partner-specific classifier, PS-HomPPI can, on a large dataset of transient complexes, predict the interface residues of a query protein with a specific target, with a CC of 0.65, sensitivity of 0.69, and specificity of 0.70, when homologs of

Human Milk: Bioactive Proteins/Peptides and Functional Properties.

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Lönnerdal, Bo

2016-06-23

Breastfeeding has been associated with many benefits, both in the short and in the long term. Infants being breastfed generally have less illness and have better cognitive development at 1 year of age than formula-fed infants. Later in life, they have a lower risk of obesity, diabetes and cardiovascular disease. Several components in breast milk may be responsible for these different outcomes, but bioactive proteins/peptides likely play a major role. Some proteins in breast milk are comparatively resistant towards digestion and may therefore exert their functions in the gastrointestinal tract in intact form or as larger fragments. Other milk proteins may be partially digested in the upper small intestine and the resulting peptides may exert functions in the lower small intestine. Lactoferrin, lysozyme and secretory IgA have been found intact in the stool of breastfed infants and are therefore examples of proteins that are resistant against proteolytic degradation in the gut. Together, these proteins serve protective roles against infection and support immune function in the immature infant. α-lactalbumin, β-casein, κ-casein and osteopontin are examples of proteins that are partially digested in the upper small intestine, and the resulting peptides influence functions in the gut. Such functions include stimulation of immune function, mineral and trace element absorption and defense against infection. © 2016 Nestec Ltd., Vevey/S. Karger AG, Basel.

Forging the Basis for Developing Protein-Ligand Interaction Scoring Functions.

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Liu, Zhihai; Su, Minyi; Han, Li; Liu, Jie; Yang, Qifan; Li, Yan; Wang, Renxiao

2017-02-21

In structure-based drug design, scoring functions are widely used for fast evaluation of protein-ligand interactions. They are often applied in combination with molecular docking and de novo design methods. Since the early 1990s, a whole spectrum of protein-ligand interaction scoring functions have been developed. Regardless of their technical difference, scoring functions all need data sets combining protein-ligand complex structures and binding affinity data for parametrization and validation. However, data sets of this kind used to be rather limited in terms of size and quality. On the other hand, standard metrics for evaluating scoring function used to be ambiguous. Scoring functions are often tested in molecular docking or even virtual screening trials, which do not directly reflect the genuine quality of scoring functions. Collectively, these underlying obstacles have impeded the invention of more advanced scoring functions. In this Account, we describe our long-lasting efforts to overcome these obstacles, which involve two related projects. On the first project, we have created the PDBbind database. It is the first database that systematically annotates the protein-ligand complexes in the Protein Data Bank (PDB) with experimental binding data. This database has been updated annually since its first public release in 2004. The latest release (version 2016) provides binding data for 16 179 biomolecular complexes in PDB. Data sets provided by PDBbind have been applied to many computational and statistical studies on protein-ligand interaction and various subjects. In particular, it has become a major data resource for scoring function development. On the second project, we have established the Comparative Assessment of Scoring Functions (CASF) benchmark for scoring function evaluation. Our key idea is to decouple the "scoring" process from the "sampling" process, so scoring functions can be tested in a relatively pure context to reflect their quality. In our

Transcription Factor Functional Protein-Protein Interactions in Plant Defense Responses

Directory of Open Access Journals (Sweden)

Murilo S. Alves

2014-03-01

Full Text Available Responses to biotic stress in plants lead to dramatic reprogramming of gene expression, favoring stress responses at the expense of normal cellular functions. Transcription factors are master regulators of gene expression at the transcriptional level, and controlling the activity of these factors alters the transcriptome of the plant, leading to metabolic and phenotypic changes in response to stress. The functional analysis of interactions between transcription factors and other proteins is very important for elucidating the role of these transcriptional regulators in different signaling cascades. In this review, we present an overview of protein-protein interactions for the six major families of transcription factors involved in plant defense: basic leucine zipper containing domain proteins (bZIP, amino-acid sequence WRKYGQK (WRKY, myelocytomatosis related proteins (MYC, myeloblastosis related proteins (MYB, APETALA2/ ETHYLENE-RESPONSIVE ELEMENT BINDING FACTORS (AP2/EREBP and no apical meristem (NAM, Arabidopsis transcription activation factor (ATAF, and cup-shaped cotyledon (CUC (NAC. We describe the interaction partners of these transcription factors as molecular responses during pathogen attack and the key components of signal transduction pathways that take place during plant defense responses. These interactions determine the activation or repression of response pathways and are crucial to understanding the regulatory networks that modulate plant defense responses.

Endosome-based protein trafficking and Ca2+ homeostasis in the heart

Directory of Open Access Journals (Sweden)

Jerry eCurran

2015-02-01

Full Text Available The ability to dynamically regulate, traffic, retain, and recycle proteins within the cell membrane is fundamental to life and central to the normal function of the heart and cardiovascular system. In the heart, these systems are essential for the regulation of cardiac calcium, both at the level of the plasma membrane, but also at local domains of the endoplasmic reticulum, sarcoplasmic reticulum, mitochondria, nucleus, and nuclear envelope. One intracellular pathway often overlooked in relation to cardiovascular calcium regulation and signaling is the endosome-based trafficking pathway. Highlighting its importance, this system and its molecular components are evolutionarily conserved across all metazoans. However, remarkably little is known of how endosome-based protein trafficking and recycling functions within mammalian cells systems, especially in the heart. The vast majority of what is known has been derived from heterologous cell systems. However, recently, more appropriate cell and animal models been developed that have allowed researchers to begin to understand how this system functions within the intact physiological environment. All excitable cells, including cardiomyocytes, depend on the proper expression and organization of multiple ion channels, pumps, exchangers, and transporters within the plasma membrane. As the endosomal system acts to regulate the expression and localization of membrane proteins, understanding the in vivo function of this system in the heart is important. This review will focus on endosome-based protein trafficking in the heart in both health and disease. Special emphasis will be given to the role played by the family of endocytic regulatory proteins, C-terminal Eps15 homology domain -containing proteins (EHDs, as recent data demonstrates that this family of proteins is essential for the proper trafficking and localization and of key proteins involved in excitation-contraction coupling.

A multi-angular mass spectrometric view at cyclic nucleotide signaling proteins : Structure/function and protein interactions of cAMP- and cGMP-dependent protein kinase

NARCIS (Netherlands)

Scholten, A.

2006-01-01

The primary focus of this thesis is the two kinases PKA and PKG, cAMP and cGMP dependent protein kinase respectively. PKA and PKG are studied both at structure/function level as well as at the level of interaction with other proteins in tissue. Our primary methods are all based on mass spectrometry.

Dissociation of activated protein C functions by elimination of protein S cofactor enhancement.

LENUS (Irish Health Repository)

Harmon, Shona

2008-11-07

Activated protein C (APC) plays a critical anticoagulant role in vivo by inactivating procoagulant factor Va and factor VIIIa and thus down-regulating thrombin generation. In addition, APC bound to the endothelial cell protein C receptor can initiate protease-activated receptor-1 (PAR-1)-mediated cytoprotective signaling. Protein S constitutes a critical cofactor for the anticoagulant function of APC but is not known to be involved in regulating APC-mediated protective PAR-1 signaling. In this study we utilized a site-directed mutagenesis strategy to characterize a putative protein S binding region within the APC Gla domain. Three single amino acid substitutions within the APC Gla domain (D35T, D36A, and A39V) were found to mildly impair protein S-dependent anticoagulant activity (<2-fold) but retained entirely normal cytoprotective activity. However, a single amino acid substitution (L38D) ablated the ability of protein S to function as a cofactor for this APC variant. Consequently, in assays of protein S-dependent factor Va proteolysis using purified proteins or in the plasma milieu, APC-L38D variant exhibited minimal residual anticoagulant activity compared with wild type APC. Despite the location of Leu-38 in the Gla domain, APC-L38D interacted normally with endothelial cell protein C receptor and retained its ability to trigger PAR-1 mediated cytoprotective signaling in a manner indistinguishable from that of wild type APC. Consequently, elimination of protein S cofactor enhancement of APC anticoagulant function represents a novel and effective strategy by which to separate the anticoagulant and cytoprotective functions of APC for potential therapeutic gain.

A collaborative filtering approach for protein-protein docking scoring functions.

Science.gov (United States)

Bourquard, Thomas; Bernauer, Julie; Azé, Jérôme; Poupon, Anne

2011-04-22

A protein-protein docking procedure traditionally consists in two successive tasks: a search algorithm generates a large number of candidate conformations mimicking the complex existing in vivo between two proteins, and a scoring function is used to rank them in order to extract a native-like one. We have already shown that using Voronoi constructions and a well chosen set of parameters, an accurate scoring function could be designed and optimized. However to be able to perform large-scale in silico exploration of the interactome, a near-native solution has to be found in the ten best-ranked solutions. This cannot yet be guaranteed by any of the existing scoring functions. In this work, we introduce a new procedure for conformation ranking. We previously developed a set of scoring functions where learning was performed using a genetic algorithm. These functions were used to assign a rank to each possible conformation. We now have a refined rank using different classifiers (decision trees, rules and support vector machines) in a collaborative filtering scheme. The scoring function newly obtained is evaluated using 10 fold cross-validation, and compared to the functions obtained using either genetic algorithms or collaborative filtering taken separately. This new approach was successfully applied to the CAPRI scoring ensembles. We show that for 10 targets out of 12, we are able to find a near-native conformation in the 10 best ranked solutions. Moreover, for 6 of them, the near-native conformation selected is of high accuracy. Finally, we show that this function dramatically enriches the 100 best-ranking conformations in near-native structures.

Functionalization of whey proteins by reactive supercritical fluid extrusion

Directory of Open Access Journals (Sweden)

Khanitta Ruttarattanamongkol

2012-09-01

Full Text Available Whey protein, a by-product from cheese-making, is often used in a variety of food formulations due to its unsurpassednutritional quality and inherent functional properties. However, the possibilities for the improvement and upgrading of wheyprotein utilization still need to be explored. Reactive supercritical fluid extrusion (SCFX is a novel technique that has beenrecently reported to successfully functionalize commercially available whey proteins into a product with enhanced functionalproperties. The specific goal of this review is to provide fundamental understanding of the reinforcement mechanism andprocessing of protein functionalization by reactive SCFX process. The superimposed extrusion variables and their interactionmechanism affect the physico-chemical properties of whey proteins. By understanding the structure, functional properties andprocessing relationships of such materials, the rational design criteria for novel functionalized proteins could be developedand effectively utilized in food systems.

PROTEOTRONICS: The emerging science of protein-based electronic devices

International Nuclear Information System (INIS)

Alfinito, Eleonora; Pousset, Jeremy; Reggiani, Lino

2015-01-01

Protein-mediated charge transport is of relevant importance in the design of protein based electronics and in attaining an adequate level of understanding of protein functioning. This is particularly true for the case of transmembrane proteins, like those pertaining to the G protein coupled receptors (GPCRs). These proteins are involved in a broad range of biological processes like catalysis, substance transport, etc., thus being the target of a large number of clinically used drugs. This paper briefly reviews a variety of experiments devoted to investigate charge transport in proteins and present a unified theoretical model able to relate macroscopic experimental results with the conformations of the amino acids backbone of the single protein. (paper)

Usher protein functions in hair cells and photoreceptors.

Science.gov (United States)

Cosgrove, Dominic; Zallocchi, Marisa

2014-01-01

The 10 different genes associated with the deaf/blind disorder, Usher syndrome, encode a number of structurally and functionally distinct proteins, most expressed as multiple isoforms/protein variants. Functional characterization of these proteins suggests a role in stereocilia development in cochlear hair cells, likely owing to adhesive interactions in hair bundles. In mature hair cells, homodimers of the Usher cadherins, cadherin 23 and protocadherin 15, interact to form a structural fiber, the tip link, and the linkages that anchor the taller stereocilia's actin cytoskeleton core to the shorter adjacent stereocilia and the elusive mechanotransduction channels, explaining the deafness phenotype when these molecular interactions are perturbed. The conundrum is that photoreceptors lack a synonymous mechanotransduction apparatus, and so a common theory for Usher protein function in the two neurosensory cell types affected in Usher syndrome is lacking. Recent evidence linking photoreceptor cell dysfunction in the shaker 1 mouse model for Usher syndrome to light-induced protein translocation defects, combined with localization of an Usher protein interactome at the periciliary region of the photoreceptors suggests Usher proteins might regulate protein trafficking between the inner and outer segments of photoreceptors. A distinct Usher protein complex is trafficked to the ribbon synapses of hair cells, and synaptic defects have been reported in Usher mutants in both hair cells and photoreceptors. This review aims to clarify what is known about Usher protein function at the synaptic and apical poles of hair cells and photoreceptors and the prospects for identifying a unifying pathobiological mechanism to explain deaf/blindness in Usher syndrome. Copyright © 2013 Elsevier Ltd. All rights reserved.

S-Layer Protein-Based Biosensors

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Bernhard Schuster

2018-04-01

Full Text Available The present paper highlights the application of bacterial surface (S- layer proteins as versatile components for the fabrication of biosensors. One technologically relevant feature of S-layer proteins is their ability to self-assemble on many surfaces and interfaces to form a crystalline two-dimensional (2D protein lattice. The S-layer lattice on the surface of a biosensor becomes part of the interface architecture linking the bioreceptor to the transducer interface, which may cause signal amplification. The S-layer lattice as ultrathin, highly porous structure with functional groups in a well-defined special distribution and orientation and an overall anti-fouling characteristics can significantly raise the limit in terms of variety and the ease of bioreceptor immobilization, compactness of bioreceptor molecule arrangement, sensitivity, specificity, and detection limit for many types of biosensors. The present paper discusses and summarizes examples for the successful implementation of S-layer lattices on biosensor surfaces in order to give a comprehensive overview on the application potential of these bioinspired S-layer protein-based biosensors.

S-Layer Protein-Based Biosensors.

Science.gov (United States)

Schuster, Bernhard

2018-04-11

The present paper highlights the application of bacterial surface (S-) layer proteins as versatile components for the fabrication of biosensors. One technologically relevant feature of S-layer proteins is their ability to self-assemble on many surfaces and interfaces to form a crystalline two-dimensional (2D) protein lattice. The S-layer lattice on the surface of a biosensor becomes part of the interface architecture linking the bioreceptor to the transducer interface, which may cause signal amplification. The S-layer lattice as ultrathin, highly porous structure with functional groups in a well-defined special distribution and orientation and an overall anti-fouling characteristics can significantly raise the limit in terms of variety and the ease of bioreceptor immobilization, compactness of bioreceptor molecule arrangement, sensitivity, specificity, and detection limit for many types of biosensors. The present paper discusses and summarizes examples for the successful implementation of S-layer lattices on biosensor surfaces in order to give a comprehensive overview on the application potential of these bioinspired S-layer protein-based biosensors.

Intrinsically Disordered Proteins in a Physics-Based World

Directory of Open Access Journals (Sweden)

Jianhan Chen

2010-12-01

Full Text Available Intrinsically disordered proteins (IDPs are a newly recognized class of functional proteins that rely on a lack of stable structure for function. They are highly prevalent in biology, play fundamental roles, and are extensively involved in human diseases. For signaling and regulation, IDPs often fold into stable structures upon binding to specific targets. The mechanisms of these coupled binding and folding processes are of significant importance because they underlie the organization of regulatory networks that dictate various aspects of cellular decision-making. This review first discusses the challenge in detailed experimental characterization of these heterogeneous and dynamics proteins and the unique and exciting opportunity for physics-based modeling to make crucial contributions, and then summarizes key lessons from recent de novo simulations of the structure and interactions of several regulatory IDPs.

Overlapping functions of argonaute proteins in patterning and morphogenesis of Drosophila embryos.

Directory of Open Access Journals (Sweden)

Wibke J Meyer

2006-08-01

Full Text Available Argonaute proteins are essential components of the molecular machinery that drives RNA silencing. In Drosophila, different members of the Argonaute family of proteins have been assigned to distinct RNA silencing pathways. While Ago1 is required for microRNA function, Ago2 is a crucial component of the RNA-induced silencing complex in siRNA-triggered RNA interference. Drosophila Ago2 contains an unusual amino-terminus with two types of imperfect glutamine-rich repeats (GRRs of unknown function. Here we show that the GRRs of Ago2 are essential for the normal function of the protein. Alleles with reduced numbers of GRRs cause specific disruptions in two morphogenetic processes associated with the midblastula transition: membrane growth and microtubule-based organelle transport. These defects do not appear to result from disruption of siRNA-dependent processes but rather suggest an interference of the mutant Ago2 proteins in an Ago1-dependent pathway. Using loss-of-function alleles, we further demonstrate that Ago1 and Ago2 act in a partially redundant manner to control the expression of the segment-polarity gene wingless in the early embryo. Our findings argue against a strict separation of Ago1 and Ago2 functions and suggest that these proteins act in concert to control key steps of the midblastula transition and of segmental patterning.

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,

Alkylation damage by lipid electrophiles targets functional protein systems.

Science.gov (United States)

Codreanu, Simona G; Ullery, Jody C; Zhu, Jing; Tallman, Keri A; Beavers, William N; Porter, Ned A; Marnett, Lawrence J; Zhang, Bing; Liebler, Daniel C

2014-03-01

Protein alkylation by reactive electrophiles contributes to chemical toxicities and oxidative stress, but the functional impact of alkylation damage across proteomes is poorly understood. We used Click chemistry and shotgun proteomics to profile the accumulation of proteome damage in human cells treated with lipid electrophile probes. Protein target profiles revealed three damage susceptibility classes, as well as proteins that were highly resistant to alkylation. Damage occurred selectively across functional protein interaction networks, with the most highly alkylation-susceptible proteins mapping to networks involved in cytoskeletal regulation. Proteins with lower damage susceptibility mapped to networks involved in protein synthesis and turnover and were alkylated only at electrophile concentrations that caused significant toxicity. Hierarchical susceptibility of proteome systems to alkylation may allow cells to survive sublethal damage while protecting critical cell functions.

Alkylation Damage by Lipid Electrophiles Targets Functional Protein Systems*

Science.gov (United States)

Codreanu, Simona G.; Ullery, Jody C.; Zhu, Jing; Tallman, Keri A.; Beavers, William N.; Porter, Ned A.; Marnett, Lawrence J.; Zhang, Bing; Liebler, Daniel C.

2014-01-01

Protein alkylation by reactive electrophiles contributes to chemical toxicities and oxidative stress, but the functional impact of alkylation damage across proteomes is poorly understood. We used Click chemistry and shotgun proteomics to profile the accumulation of proteome damage in human cells treated with lipid electrophile probes. Protein target profiles revealed three damage susceptibility classes, as well as proteins that were highly resistant to alkylation. Damage occurred selectively across functional protein interaction networks, with the most highly alkylation-susceptible proteins mapping to networks involved in cytoskeletal regulation. Proteins with lower damage susceptibility mapped to networks involved in protein synthesis and turnover and were alkylated only at electrophile concentrations that caused significant toxicity. Hierarchical susceptibility of proteome systems to alkylation may allow cells to survive sublethal damage while protecting critical cell functions. PMID:24429493

KARAKTERISTIK FUNGSIONAL PROTEIN MISELIUM JAMUR TIRAM MERAH MUDA DAN MERANG [Functional Characteristics of Protein Mycelium of Pink Oyster and Paddy Straw Mushrooms

Directory of Open Access Journals (Sweden)

Sukarno*

2014-06-01

Full Text Available Mycelium of mushroom contained high protein, which determined its functional characteristics such as water holding capacity (WHC, oil holding capacity (OAC, emulsion stability, and gel formation. This study aimed to determine the protein functional properties of Pleurotus flabellatus and Volvariella volvacea mycelia. Information obtained can be used to increase utilization of the mycelia as source of food. Mycelia biomass were obtained by growing the fungal cultures in Potato Dextrose Broth (PDB on shaker at 100-150 rpm. Mycelia were harvested three times at 7, 8, and 9-days after inoculation for measuring their protein contents by kjehdahl method. Functional properties of mycelium protein measured were WHC, OAC, emulsion stability, and gel formation by folding test method. Based on the analysis of protein content in dry weight basis, 8-day old P. flabellatus and V. volvacea mycelia produced the highest protein contents with the value were 31.72 and 19.98%, respectively. Further analysis of protein functional properties showed that P. flabellatus mycelium had 10.38% of WHC, 0.52 mL/g of OAC, 57.14% of emulsion stability and gel strength level with the valueof 2, whereas the V. volvacea mycelium had 15.89% of WHC, 0.80 mL/g of OAC, 48.69% of emulsion stability, and did not form a gel. Protein functional properties of P. flabellatus were better than that of V. volvacea mycelium in terms of protein content, emulsion stability, and gel formation.

Mapping functional prion-prion protein interaction sites using prion protein based peptide-arrays

NARCIS (Netherlands)

Rigter, A.; Priem, J.; Timmers-Parohi, D.; Langeveld, J.; Bossers, A.

2009-01-01

Protein-protein interactions are at the basis of most if not all biological processes in living cells. Therefore, adapting existing techniques or developing new techniques to study interactions between proteins are of importance in elucidating which amino acid sequences contribute to these

Processing and characteristics of canola protein-based biodegradable packaging: A review.

Science.gov (United States)

Zhang, Yachuan; Liu, Qiang; Rempel, Curtis

2018-02-11

Interest increased recently in manufacturing food packaging, such as films and coatings, from protein-based biopolymers. Among various protein sources, canola protein is a novel source for manufacturing polymer films. It can be concentrated or isolated by aqueous extraction technology followed by protein precipitation. Using this procedure, it was claimed that more than 99% of protein was extracted from the defatted canola meal, and protein recovery was 87.5%. Canola protein exhibits thermoplastic properties when plasticizers are present, including water, glycerol, polyethylene glycol, and sorbitol. Addition of these plasticizers allows the canola protein to undergo glass transition and facilitates deformation and processability. Normally, canola protein-based bioplastics showed low mechanical properties, which had tensile strength (TS) of 1.19 to 4.31 MPa. So, various factors were explored to improve it, including blending with synthetic polymers, modifying protein functionality through controlled denaturation, and adding cross-linking agents. Canola protein-based bioplastics were reported to have glass transition temperature, T g , below -50°C but it highly depends on the plasticizer content. Canola protein-based bioplastics have demonstrated comparable mechanical and moisture barrier properties compared with other plant protein-based bioplastics. They have great potential in food packaging applications, including their use as wraps, sacks, sachets, or pouches.

Broadening the functionality of a J-protein/Hsp70 molecular chaperone system.

Science.gov (United States)

Schilke, Brenda A; Ciesielski, Szymon J; Ziegelhoffer, Thomas; Kamiya, Erina; Tonelli, Marco; Lee, Woonghee; Cornilescu, Gabriel; Hines, Justin K; Markley, John L; Craig, Elizabeth A

2017-10-01

By binding to a multitude of polypeptide substrates, Hsp70-based molecular chaperone systems perform a range of cellular functions. All J-protein co-chaperones play the essential role, via action of their J-domains, of stimulating the ATPase activity of Hsp70, thereby stabilizing its interaction with substrate. In addition, J-proteins drive the functional diversity of Hsp70 chaperone systems through action of regions outside their J-domains. Targeting to specific locations within a cellular compartment and binding of specific substrates for delivery to Hsp70 have been identified as modes of J-protein specialization. To better understand J-protein specialization, we concentrated on Saccharomyces cerevisiae SIS1, which encodes an essential J-protein of the cytosol/nucleus. We selected suppressors that allowed cells lacking SIS1 to form colonies. Substitutions changing single residues in Ydj1, a J-protein, which, like Sis1, partners with Hsp70 Ssa1, were isolated. These gain-of-function substitutions were located at the end of the J-domain, suggesting that suppression was connected to interaction with its partner Hsp70, rather than substrate binding or subcellular localization. Reasoning that, if YDJ1 suppressors affect Ssa1 function, substitutions in Hsp70 itself might also be able to overcome the cellular requirement for Sis1, we carried out a selection for SSA1 suppressor mutations. Suppressing substitutions were isolated that altered sites in Ssa1 affecting the cycle of substrate interaction. Together, our results point to a third, additional means by which J-proteins can drive Hsp70's ability to function in a wide range of cellular processes-modulating the Hsp70-substrate interaction cycle.

Usher protein functions in hair cells and photoreceptors

OpenAIRE

Cosgrove, Dominic; Zallocchi, Marisa

2013-01-01

The 10 different genes associated with the deaf/blind disorder, Usher syndrome, encode a number of structurally and functionally distinct proteins, most expressed as multiple isoforms/protein variants. Functional characterization of these proteins suggests a role in stereocilia development in cochlear hair cells, likely owing to adhesive interactions in hair bundles. In mature hair cells, homodimers of the Usher cadherins, cadherin 23 and protocadherin 15, interact to form a structural fiber,...

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)

Sequence-based prediction of protein protein interaction using a deep-learning algorithm.

Science.gov (United States)

Sun, Tanlin; Zhou, Bo; Lai, Luhua; Pei, Jianfeng

2017-05-25

Protein-protein interactions (PPIs) are critical for many biological processes. It is therefore important to develop accurate high-throughput methods for identifying PPI to better understand protein function, disease occurrence, and therapy design. Though various computational methods for predicting PPI have been developed, their robustness for prediction with external datasets is unknown. Deep-learning algorithms have achieved successful results in diverse areas, but their effectiveness for PPI prediction has not been tested. We used a stacked autoencoder, a type of deep-learning algorithm, to study the sequence-based PPI prediction. The best model achieved an average accuracy of 97.19% with 10-fold cross-validation. The prediction accuracies for various external datasets ranged from 87.99% to 99.21%, which are superior to those achieved with previous methods. To our knowledge, this research is the first to apply a deep-learning algorithm to sequence-based PPI prediction, and the results demonstrate its potential in this field.

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.

Health effects of an increased protein intake on kidney function and colorectal cancer risk factors, including the role of animal and plant protein sources – the PREVIEW project

DEFF Research Database (Denmark)

Møller, Grith

intake, including the role of animal and plant protein in pre-diabetic, overweight or obese individuals on health outcomes: markers of kidney function and putative risk factors for colorectal cancer as well as insulin sensitivity and kidney function in healthy individuals. The thesis is based on PREVIEW......, especially plant protein, on insulin sensitivity and kidney function. In paper II, the aim of the study was to assess the effect after one year of a higher protein intake on kidney function, measured by in creatinine clearance. This was investigated in pre-diabetic older adults based on a sub-group of 310...... pre-diabetic individuals included in the PREVIEW RCT. We found that a higher protein intake was associated with a significant increase in urea to creatinine ratio and serum urea after one year. There were no associations between increased protein intake and creatinine clearance, estimated glomerular...

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.

Proteomics-Based Analysis of Protein Complexes in Pluripotent Stem Cells and Cancer Biology.

Science.gov (United States)

Sudhir, Putty-Reddy; Chen, Chung-Hsuan

2016-03-22

A protein complex consists of two or more proteins that are linked together through protein-protein interactions. The proteins show stable/transient and direct/indirect interactions within the protein complex or between the protein complexes. Protein complexes are involved in regulation of most of the cellular processes and molecular functions. The delineation of protein complexes is important to expand our knowledge on proteins functional roles in physiological and pathological conditions. The genetic yeast-2-hybrid method has been extensively used to characterize protein-protein interactions. Alternatively, a biochemical-based affinity purification coupled with mass spectrometry (AP-MS) approach has been widely used to characterize the protein complexes. In the AP-MS method, a protein complex of a target protein of interest is purified using a specific antibody or an affinity tag (e.g., DYKDDDDK peptide (FLAG) and polyhistidine (His)) and is subsequently analyzed by means of MS. Tandem affinity purification, a two-step purification system, coupled with MS has been widely used mainly to reduce the contaminants. We review here a general principle for AP-MS-based characterization of protein complexes and we explore several protein complexes identified in pluripotent stem cell biology and cancer biology as examples.

Nutritional and functional properties of whey proteins concentrate and isolate

OpenAIRE

Zoran Herceg; Anet Režek

2006-01-01

Whey protein fractions represent 18 - 20 % of total milk nitrogen content. Nutritional value in addition to diverse physico - chemical and functional properties make whey proteins highly suitable for application in foodstuffs. In the most cases, whey proteins are used because of their functional properties. Whey proteins possess favourable functional characteristics such as gelling, water binding, emulsification and foaming ability. Due to application of new process techniques (membrane fract...

Knowledge, perceptions and preferences of elderly regarding protein-enriched functional food.

Science.gov (United States)

van der Zanden, Lotte D T; van Kleef, Ellen; de Wijk, René A; van Trijp, Hans C M

2014-09-01

Promoting protein consumption in the elderly population may contribute to improving the quality of their later years in life. Our study aimed to explore knowledge, perceptions and preferences of elderly consumers regarding protein-enriched food. We conducted three focus groups with independently living (ID) elderly (N = 24, Mage = 67 years) and three with elderly living in a residential home (RH) (N = 18, Mage = 83 years). Both the ID and RH elderly were predominantly sceptical about functional food in general. Confusion, distrust and a perceived lack of personal relevance were main perceived barriers to purchasing and consuming these products, although a majority of the participants did report occasionally consuming at least one type of functional food. For the ID elderly, medical advice was an important facilitator that could overcome barriers to purchasing and consuming protein-enriched food, indicating the importance of personal relevance for this group. For the RH elderly, in contrast, sensory appeal of protein-enriched foods was a facilitator. Carrier preferences were similar for the two groups; the elderly preferred protein-enriched foods based on healthy products that they consumed frequently. Future studies should explore ways to deal with the confusion and distrust regarding functional food within the heterogeneous population of elderly. Copyright © 2014 Elsevier Ltd. All rights reserved.

Evaluating a variety of text-mined features for automatic protein function prediction with GOstruct.

Science.gov (United States)

Funk, Christopher S; Kahanda, Indika; Ben-Hur, Asa; Verspoor, Karin M

2015-01-01

Most computational methods that predict protein function do not take advantage of the large amount of information contained in the biomedical literature. In this work we evaluate both ontology term co-mention and bag-of-words features mined from the biomedical literature and analyze their impact in the context of a structured output support vector machine model, GOstruct. We find that even simple literature based features are useful for predicting human protein function (F-max: Molecular Function =0.408, Biological Process =0.461, Cellular Component =0.608). One advantage of using literature features is their ability to offer easy verification of automated predictions. We find through manual inspection of misclassifications that some false positive predictions could be biologically valid predictions based upon support extracted from the literature. Additionally, we present a "medium-throughput" pipeline that was used to annotate a large subset of co-mentions; we suggest that this strategy could help to speed up the rate at which proteins are curated.

Identification of functional candidates amongst hypothetical proteins of Mycobacterium leprae Br4923, a causative agent of leprosy.

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Naqvi, Ahmad Abu Turab; Ahmad, Faizan; Hassan, Md Imtaiyaz

2015-01-01

Mycobacterium leprae is an intracellular obligate parasite that causes leprosy in humans, and it leads to the destruction of peripheral nerves and skin deformation. Here, we report an extensive analysis of the hypothetical proteins (HPs) from M. leprae strain Br4923, assigning their functions to better understand the mechanism of pathogenesis and to search for potential therapeutic interventions. The genome of M. leprae encodes 1604 proteins, of which the functions of 632 are not known (HPs). In this paper, we predicted the probable functions of 312 HPs. First, we classified all HPs into families and subfamilies on the basis of sequence similarity, followed by domain assignment, which provides many clues for their possible function. However, the functions of 320 proteins were not predicted because of low sequence similarity with proteins of known function. Annotated HPs were categorized into enzymes, binding proteins, transporters, and proteins involved in cellular processes. We found several novel proteins whose functions were unknown for M. leprae. These proteins have a requisite association with bacterial virulence and pathogenicity. Finally, our sequence-based analysis will be helpful for further validation and the search for potential drug targets while developing effective drugs to cure leprosy.

Stapled Voltage-Gated Calcium Channel (CaV) α-Interaction Domain (AID) Peptides Act As Selective Protein-Protein Interaction Inhibitors of CaV Function.

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Findeisen, Felix; Campiglio, Marta; Jo, Hyunil; Abderemane-Ali, Fayal; Rumpf, Christine H; Pope, Lianne; Rossen, Nathan D; Flucher, Bernhard E; DeGrado, William F; Minor, Daniel L

2017-06-21

For many voltage-gated ion channels (VGICs), creation of a properly functioning ion channel requires the formation of specific protein-protein interactions between the transmembrane pore-forming subunits and cystoplasmic accessory subunits. Despite the importance of such protein-protein interactions in VGIC function and assembly, their potential as sites for VGIC modulator development has been largely overlooked. Here, we develop meta-xylyl (m-xylyl) stapled peptides that target a prototypic VGIC high affinity protein-protein interaction, the interaction between the voltage-gated calcium channel (Ca V ) pore-forming subunit α-interaction domain (AID) and cytoplasmic β-subunit (Ca V β). We show using circular dichroism spectroscopy, X-ray crystallography, and isothermal titration calorimetry that the m-xylyl staples enhance AID helix formation are structurally compatible with native-like AID:Ca V β interactions and reduce the entropic penalty associated with AID binding to Ca V β. Importantly, electrophysiological studies reveal that stapled AID peptides act as effective inhibitors of the Ca V α 1 :Ca V β interaction that modulate Ca V function in an Ca V β isoform-selective manner. Together, our studies provide a proof-of-concept demonstration of the use of protein-protein interaction inhibitors to control VGIC function and point to strategies for improved AID-based Ca V modulator design.

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

Automatically extracting functionally equivalent proteins from SwissProt

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Martin Andrew CR

2008-10-01

Full Text Available Abstract Background There is a frequent need to obtain sets of functionally equivalent homologous proteins (FEPs from different species. While it is usually the case that orthology implies functional equivalence, this is not always true; therefore datasets of orthologous proteins are not appropriate. The information relevant to extracting FEPs is contained in databanks such as UniProtKB/Swiss-Prot and a manual analysis of these data allow FEPs to be extracted on a one-off basis. However there has been no resource allowing the easy, automatic extraction of groups of FEPs – for example, all instances of protein C. We have developed FOSTA, an automatically generated database of FEPs annotated as having the same function in UniProtKB/Swiss-Prot which can be used for large-scale analysis. The method builds a candidate list of homologues and filters out functionally diverged proteins on the basis of functional annotations using a simple text mining approach. Results Large scale evaluation of our FEP extraction method is difficult as there is no gold-standard dataset against which the method can be benchmarked. However, a manual analysis of five protein families confirmed a high level of performance. A more extensive comparison with two manually verified functional equivalence datasets also demonstrated very good performance. Conclusion In summary, FOSTA provides an automated analysis of annotations in UniProtKB/Swiss-Prot to enable groups of proteins already annotated as functionally equivalent, to be extracted. Our results demonstrate that the vast majority of UniProtKB/Swiss-Prot functional annotations are of high quality, and that FOSTA can interpret annotations successfully. Where FOSTA is not successful, we are able to highlight inconsistencies in UniProtKB/Swiss-Prot annotation. Most of these would have presented equal difficulties for manual interpretation of annotations. We discuss limitations and possible future extensions to FOSTA, and

Scoring protein interaction decoys using exposed residues (SPIDER): a novel multibody interaction scoring function based on frequent geometric patterns of interfacial residues.

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Khashan, Raed; Zheng, Weifan; Tropsha, Alexander

2012-08-01

Accurate prediction of the structure of protein-protein complexes in computational docking experiments remains a formidable challenge. It has been recognized that identifying native or native-like poses among multiple decoys is the major bottleneck of the current scoring functions used in docking. We have developed a novel multibody pose-scoring function that has no theoretical limit on the number of residues contributing to the individual interaction terms. We use a coarse-grain representation of a protein-protein complex where each residue is represented by its side chain centroid. We apply a computational geometry approach called Almost-Delaunay tessellation that transforms protein-protein complexes into a residue contact network, or an undirectional graph where vertex-residues are nodes connected by edges. This treatment forms a family of interfacial graphs representing a dataset of protein-protein complexes. We then employ frequent subgraph mining approach to identify common interfacial residue patterns that appear in at least a subset of native protein-protein interfaces. The geometrical parameters and frequency of occurrence of each "native" pattern in the training set are used to develop the new SPIDER scoring function. SPIDER was validated using standard "ZDOCK" benchmark dataset that was not used in the development of SPIDER. We demonstrate that SPIDER scoring function ranks native and native-like poses above geometrical decoys and that it exceeds in performance a popular ZRANK scoring function. SPIDER was ranked among the top scoring functions in a recent round of CAPRI (Critical Assessment of PRedicted Interactions) blind test of protein-protein docking methods. Copyright © 2012 Wiley Periodicals, Inc.

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.

Protein functional features are reflected in the patterns of mRNA translation speed.

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López, Daniel; Pazos, Florencio

2015-07-09

The degeneracy of the genetic code makes it possible for the same amino acid string to be coded by different messenger RNA (mRNA) sequences. These "synonymous mRNAs" may differ largely in a number of aspects related to their overall translational efficiency, such as secondary structure content and availability of the encoded transfer RNAs (tRNAs). Consequently, they may render different yields of the translated polypeptides. These mRNA features related to translation efficiency are also playing a role locally, resulting in a non-uniform translation speed along the mRNA, which has been previously related to some protein structural features and also used to explain some dramatic effects of "silent" single-nucleotide-polymorphisms (SNPs). In this work we perform the first large scale analysis of the relationship between three experimental proxies of mRNA local translation efficiency and the local features of the corresponding encoded proteins. We found that a number of protein functional and structural features are reflected in the patterns of ribosome occupancy, secondary structure and tRNA availability along the mRNA. One or more of these proxies of translation speed have distinctive patterns around the mRNA regions coding for certain protein local features. In some cases the three patterns follow a similar trend. We also show specific examples where these patterns of translation speed point to the protein's important structural and functional features. This support the idea that the genome not only codes the protein functional features as sequences of amino acids, but also as subtle patterns of mRNA properties which, probably through local effects on the translation speed, have some consequence on the final polypeptide. These results open the possibility of predicting a protein's functional regions based on a single genomic sequence, and have implications for heterologous protein expression and fine-tuning protein function.

Functional anthology of intrinsic disorder. 1. Biological processes and functions of proteins with long disordered regions.

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Xie, Hongbo; Vucetic, Slobodan; Iakoucheva, Lilia M; Oldfield, Christopher J; Dunker, A Keith; Uversky, Vladimir N; Obradovic, Zoran

2007-05-01

Identifying relationships between function, amino acid sequence, and protein structure represents a major challenge. In this study, we propose a bioinformatics approach that identifies functional keywords in the Swiss-Prot database that correlate with intrinsic disorder. A statistical evaluation is employed to rank the significance of these correlations. Protein sequence data redundancy and the relationship between protein length and protein structure were taken into consideration to ensure the quality of the statistical inferences. Over 200,000 proteins from the Swiss-Prot database were analyzed using this approach. The predictions of intrinsic disorder were carried out using PONDR VL3E predictor of long disordered regions that achieves an accuracy of above 86%. Overall, out of the 710 Swiss-Prot functional keywords that were each associated with at least 20 proteins, 238 were found to be strongly positively correlated with predicted long intrinsically disordered regions, whereas 302 were strongly negatively correlated with such regions. The remaining 170 keywords were ambiguous without strong positive or negative correlation with the disorder predictions. These functions cover a large variety of biological activities and imply that disordered regions are characterized by a wide functional repertoire. Our results agree well with literature findings, as we were able to find at least one illustrative example of functional disorder or order shown experimentally for the vast majority of keywords showing the strongest positive or negative correlation with intrinsic disorder. This work opens a series of three papers, which enriches the current view of protein structure-function relationships, especially with regards to functionalities of intrinsically disordered proteins, and provides researchers with a novel tool that could be used to improve the understanding of the relationships between protein structure and function. The first paper of the series describes our

Emerging functions of ribosomal proteins in gene-specific transcription and translation

International Nuclear Information System (INIS)

Lindstroem, Mikael S.

2009-01-01

Ribosomal proteins have remained highly conserved during evolution presumably reflecting often critical functions in ribosome biogenesis or mature ribosome function. In addition, several ribosomal proteins possess distinct extra-ribosomal functions in apoptosis, DNA repair and transcription. An increasing number of ribosomal proteins have been shown to modulate the trans-activation function of important regulatory proteins such as NF-κB, p53, c-Myc and nuclear receptors. Furthermore, a subset of ribosomal proteins can bind directly to untranslated regions of mRNA resulting in transcript-specific translational control outside of the ribosome itself. Collectively, these findings suggest that ribosomal proteins may have a wider functional repertoire within the cell than previously thought. The future challenge is to identify and validate these novel functions in the background of an often essential primary function in ribosome biogenesis and cell growth.

The PANTHER database of protein families, subfamilies, functions and pathways

OpenAIRE

Mi, Huaiyu; Lazareva-Ulitsky, Betty; Loo, Rozina; Kejariwal, Anish; Vandergriff, Jody; Rabkin, Steven; Guo, Nan; Muruganujan, Anushya; Doremieux, Olivier; Campbell, Michael J.; Kitano, Hiroaki; Thomas, Paul D.

2004-01-01

PANTHER is a large collection of protein families that have been subdivided into functionally related subfamilies, using human expertise. These subfamilies model the divergence of specific functions within protein families, allowing more accurate association with function (ontology terms and pathways), as well as inference of amino acids important for functional specificity. Hidden Markov models (HMMs) are built for each family and subfamily for classifying additional protein sequences. The l...

The Link between Dietary Protein Intake, Skeletal Muscle Function and Health in Older Adults

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Jamie I. Baum

2015-07-01

Full Text Available Skeletal muscle mass and function are progressively lost with age, a condition referred to as sarcopenia. By the age of 60, many older adults begin to be affected by muscle loss. There is a link between decreased muscle mass and strength and adverse health outcomes such as obesity, diabetes and cardiovascular disease. Data suggest that increasing dietary protein intake at meals may counterbalance muscle loss in older individuals due to the increased availability of amino acids, which stimulate muscle protein synthesis by activating the mammalian target of rapamycin (mTORC1. Increased muscle protein synthesis can lead to increased muscle mass, strength and function over time. This review aims to address the current recommended dietary allowance (RDA for protein and whether or not this value meets the needs for older adults based upon current scientific evidence. The current RDA for protein is 0.8 g/kg body weight/day. However, literature suggests that consuming protein in amounts greater than the RDA can improve muscle mass, strength and function in older adults.

Functional Advantages of Conserved Intrinsic Disorder in RNA-Binding Proteins.

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Varadi, Mihaly; Zsolyomi, Fruzsina; Guharoy, Mainak; Tompa, Peter

2015-01-01

Proteins form large macromolecular assemblies with RNA that govern essential molecular processes. RNA-binding proteins have often been associated with conformational flexibility, yet the extent and functional implications of their intrinsic disorder have never been fully assessed. Here, through large-scale analysis of comprehensive protein sequence and structure datasets we demonstrate the prevalence of intrinsic structural disorder in RNA-binding proteins and domains. We addressed their functionality through a quantitative description of the evolutionary conservation of disordered segments involved in binding, and investigated the structural implications of flexibility in terms of conformational stability and interface formation. We conclude that the functional role of intrinsically disordered protein segments in RNA-binding is two-fold: first, these regions establish extended, conserved electrostatic interfaces with RNAs via induced fit. Second, conformational flexibility enables them to target different RNA partners, providing multi-functionality, while also ensuring specificity. These findings emphasize the functional importance of intrinsically disordered regions in RNA-binding proteins.

Functional Advantages of Conserved Intrinsic Disorder in RNA-Binding Proteins.

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Mihaly Varadi

Full Text Available Proteins form large macromolecular assemblies with RNA that govern essential molecular processes. RNA-binding proteins have often been associated with conformational flexibility, yet the extent and functional implications of their intrinsic disorder have never been fully assessed. Here, through large-scale analysis of comprehensive protein sequence and structure datasets we demonstrate the prevalence of intrinsic structural disorder in RNA-binding proteins and domains. We addressed their functionality through a quantitative description of the evolutionary conservation of disordered segments involved in binding, and investigated the structural implications of flexibility in terms of conformational stability and interface formation. We conclude that the functional role of intrinsically disordered protein segments in RNA-binding is two-fold: first, these regions establish extended, conserved electrostatic interfaces with RNAs via induced fit. Second, conformational flexibility enables them to target different RNA partners, providing multi-functionality, while also ensuring specificity. These findings emphasize the functional importance of intrinsically disordered regions in RNA-binding proteins.

Protein-based nanostructures as carriers for photo-physically active molecules in biosystems

OpenAIRE

Delcanale, Pietro

2017-01-01

In nature, many proteins function as carriers, being able to bind, transport and possibly release a ligand within a biological system. Protein-based carriers are interesting systems for drug delivery, with the remarkable advantage of being water-soluble and, as inherent components of biosystems, highly bio-compatible. This work focuses on the use of protein-based carriers for the delivery of hydrophobic photo-physically active molecules, whose structure and chemical properties lead to spontan...

Coiled-Coil Proteins Facilitated the Functional Expansion of the Centrosome

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Kuhn, Michael; Hyman, Anthony A.; Beyer, Andreas

2014-01-01

Repurposing existing proteins for new cellular functions is recognized as a main mechanism of evolutionary innovation, but its role in organelle evolution is unclear. Here, we explore the mechanisms that led to the evolution of the centrosome, an ancestral eukaryotic organelle that expanded its functional repertoire through the course of evolution. We developed a refined sequence alignment technique that is more sensitive to coiled coil proteins, which are abundant in the centrosome. For proteins with high coiled-coil content, our algorithm identified 17% more reciprocal best hits than BLAST. Analyzing 108 eukaryotic genomes, we traced the evolutionary history of centrosome proteins. In order to assess how these proteins formed the centrosome and adopted new functions, we computationally emulated evolution by iteratively removing the most recently evolved proteins from the centrosomal protein interaction network. Coiled-coil proteins that first appeared in the animal–fungi ancestor act as scaffolds and recruit ancestral eukaryotic proteins such as kinases and phosphatases to the centrosome. This process created a signaling hub that is crucial for multicellular development. Our results demonstrate how ancient proteins can be co-opted to different cellular localizations, thereby becoming involved in novel functions. PMID:24901223

Dynamic functional modules in co-expressed protein interaction networks of dilated cardiomyopathy

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Oyang Yen-Jen

2010-10-01

Full Text Available Abstract Background Molecular networks represent the backbone of molecular activity within cells and provide opportunities for understanding the mechanism of diseases. While protein-protein interaction data constitute static network maps, integration of condition-specific co-expression information provides clues to the dynamic features of these networks. Dilated cardiomyopathy is a leading cause of heart failure. Although previous studies have identified putative biomarkers or therapeutic targets for heart failure, the underlying molecular mechanism of dilated cardiomyopathy remains unclear. Results We developed a network-based comparative analysis approach that integrates protein-protein interactions with gene expression profiles and biological function annotations to reveal dynamic functional modules under different biological states. We found that hub proteins in condition-specific co-expressed protein interaction networks tended to be differentially expressed between biological states. Applying this method to a cohort of heart failure patients, we identified two functional modules that significantly emerged from the interaction networks. The dynamics of these modules between normal and disease states further suggest a potential molecular model of dilated cardiomyopathy. Conclusions We propose a novel framework to analyze the interaction networks in different biological states. It successfully reveals network modules closely related to heart failure; more importantly, these network dynamics provide new insights into the cause of dilated cardiomyopathy. The revealed molecular modules might be used as potential drug targets and provide new directions for heart failure therapy.

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

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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.

SVM-Prot 2016: A Web-Server for Machine Learning Prediction of Protein Functional Families from Sequence Irrespective of Similarity.

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Li, Ying Hong; Xu, Jing Yu; Tao, Lin; Li, Xiao Feng; Li, Shuang; Zeng, Xian; Chen, Shang Ying; Zhang, Peng; Qin, Chu; Zhang, Cheng; Chen, Zhe; Zhu, Feng; Chen, Yu Zong

2016-01-01

Knowledge of protein function is important for biological, medical and therapeutic studies, but many proteins are still unknown in function. There is a need for more improved functional prediction methods. Our SVM-Prot web-server employed a machine learning method for predicting protein functional families from protein sequences irrespective of similarity, which complemented those similarity-based and other methods in predicting diverse classes of proteins including the distantly-related proteins and homologous proteins of different functions. Since its publication in 2003, we made major improvements to SVM-Prot with (1) expanded coverage from 54 to 192 functional families, (2) more diverse protein descriptors protein representation, (3) improved predictive performances due to the use of more enriched training datasets and more variety of protein descriptors, (4) newly integrated BLAST analysis option for assessing proteins in the SVM-Prot predicted functional families that were similar in sequence to a query protein, and (5) newly added batch submission option for supporting the classification of multiple proteins. Moreover, 2 more machine learning approaches, K nearest neighbor and probabilistic neural networks, were added for facilitating collective assessment of protein functions by multiple methods. SVM-Prot can be accessed at http://bidd2.nus.edu.sg/cgi-bin/svmprot/svmprot.cgi.

Single proteins that serve linked functions in intracellular and extracellular microenvironments

Energy Technology Data Exchange (ETDEWEB)

Radisky, Derek C.; Stallings-Mann, Melody; Hirai, Yohei; Bissell, Mina J.

2009-06-03

Maintenance of organ homeostasis and control of appropriate response to environmental alterations requires intimate coordination of cellular function and tissue organization. An important component of this coordination may be provided by proteins that can serve distinct, but linked, functions on both sides of the plasma membrane. Here we present a novel hypothesis in which non-classical secretion can provide a mechanism through which single proteins can integrate complex tissue functions. Single genes can exert a complex, dynamic influence through a number of different processes that act to multiply the function of the gene product(s). Alternative splicing can create many different transcripts that encode proteins of diverse, even antagonistic, function from a single gene. Posttranslational modifications can alter the stability, activity, localization, and even basic function of proteins. A protein can exist in different subcellular localizations. More recently, it has become clear that single proteins can function both inside and outside the cell. These proteins often lack defined secretory signal sequences, and transit the plasma membrane by mechanisms separate from the classical ER/Golgi secretory process. When examples of such proteins are examined individually, the multifunctionality and lack of a signal sequence are puzzling - why should a protein with a well known function in one context function in such a distinct fashion in another? We propose that one reason for a single protein to perform intracellular and extracellular roles is to coordinate organization and maintenance of a global tissue function. Here, we describe in detail three specific examples of proteins that act in this fashion, outlining their specific functions in the extracellular space and in the intracellular space, and we discuss how these functions may be linked. We present epimorphin/syntaxin-2, which may coordinate morphogenesis of secretory organs (as epimorphin) with control of

Concomitant prediction of function and fold at the domain level with GO-based profiles.

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Lopez, Daniel; Pazos, Florencio

2013-01-01

Predicting the function of newly sequenced proteins is crucial due to the pace at which these raw sequences are being obtained. Almost all resources for predicting protein function assign functional terms to whole chains, and do not distinguish which particular domain is responsible for the allocated function. This is not a limitation of the methodologies themselves but it is due to the fact that in the databases of functional annotations these methods use for transferring functional terms to new proteins, these annotations are done on a whole-chain basis. Nevertheless, domains are the basic evolutionary and often functional units of proteins. In many cases, the domains of a protein chain have distinct molecular functions, independent from each other. For that reason resources with functional annotations at the domain level, as well as methodologies for predicting function for individual domains adapted to these resources are required.We present a methodology for predicting the molecular function of individual domains, based on a previously developed database of functional annotations at the domain level. The approach, which we show outperforms a standard method based on sequence searches in assigning function, concomitantly predicts the structural fold of the domains and can give hints on the functionally important residues associated to the predicted function.

GRIP: A web-based system for constructing Gold Standard datasets for protein-protein interaction prediction

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Zheng Huiru

2009-01-01

Full Text Available Abstract Background Information about protein interaction networks is fundamental to understanding protein function and cellular processes. Interaction patterns among proteins can suggest new drug targets and aid in the design of new therapeutic interventions. Efforts have been made to map interactions on a proteomic-wide scale using both experimental and computational techniques. Reference datasets that contain known interacting proteins (positive cases and non-interacting proteins (negative cases are essential to support computational prediction and validation of protein-protein interactions. Information on known interacting and non interacting proteins are usually stored within databases. Extraction of these data can be both complex and time consuming. Although, the automatic construction of reference datasets for classification is a useful resource for researchers no public resource currently exists to perform this task. Results GRIP (Gold Reference dataset constructor from Information on Protein complexes is a web-based system that provides researchers with the functionality to create reference datasets for protein-protein interaction prediction in Saccharomyces cerevisiae. Both positive and negative cases for a reference dataset can be extracted, organised and downloaded by the user. GRIP also provides an upload facility whereby users can submit proteins to determine protein complex membership. A search facility is provided where a user can search for protein complex information in Saccharomyces cerevisiae. Conclusion GRIP is developed to retrieve information on protein complex, cellular localisation, and physical and genetic interactions in Saccharomyces cerevisiae. Manual construction of reference datasets can be a time consuming process requiring programming knowledge. GRIP simplifies and speeds up this process by allowing users to automatically construct reference datasets. GRIP is free to access at http://rosalind.infj.ulst.ac.uk/GRIP/.

Protein mislocalization: mechanisms, functions and clinical applications in cancer

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Wang, Xiaohong; Li, Shulin

2014-01-01

The changes from normal cells to cancer cells are primarily regulated by genome instability, which foster hallmark functions of cancer through multiple mechanisms including protein mislocalization. Mislocalization of these proteins, including oncoproteins, tumor suppressors, and other cancer-related proteins, can interfere with normal cellular function and cooperatively drive tumor development and metastasis. This review describes the cancer-related effects of protein subcellular mislocalization, the related mislocalization mechanisms, and the potential application of this knowledge to cancer diagnosis, prognosis, and therapy. PMID:24709009

Binding Direction-Based Two-Dimensional Flattened Contact Area Computing Algorithm for Protein-Protein Interactions.

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Kang, Beom Sik; Pugalendhi, GaneshKumar; Kim, Ku-Jin

2017-10-13

Interactions between protein molecules are essential for the assembly, function, and regulation of proteins. The contact region between two protein molecules in a protein complex is usually complementary in shape for both molecules and the area of the contact region can be used to estimate the binding strength between two molecules. Although the area is a value calculated from the three-dimensional surface, it cannot represent the three-dimensional shape of the surface. Therefore, we propose an original concept of two-dimensional contact area which provides further information such as the ruggedness of the contact region. We present a novel algorithm for calculating the binding direction between two molecules in a protein complex, and then suggest a method to compute the two-dimensional flattened area of the contact region between two molecules based on the binding direction.

Evolutionary Conservation and Emerging Functional Diversity of the Cytosolic Hsp70:J Protein Chaperone Network of Arabidopsis thaliana.

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Verma, Amit K; Diwan, Danish; Raut, Sandeep; Dobriyal, Neha; Brown, Rebecca E; Gowda, Vinita; Hines, Justin K; Sahi, Chandan

2017-06-07

Heat shock proteins of 70 kDa (Hsp70s) partner with structurally diverse Hsp40s (J proteins), generating distinct chaperone networks in various cellular compartments that perform myriad housekeeping and stress-associated functions in all organisms. Plants, being sessile, need to constantly maintain their cellular proteostasis in response to external environmental cues. In these situations, the Hsp70:J protein machines may play an important role in fine-tuning cellular protein quality control. Although ubiquitous, the functional specificity and complexity of the plant Hsp70:J protein network has not been studied. Here, we analyzed the J protein network in the cytosol of Arabidopsis thaliana and, using yeast genetics, show that the functional specificities of most plant J proteins in fundamental chaperone functions are conserved across long evolutionary timescales. Detailed phylogenetic and functional analysis revealed that increased number, regulatory differences, and neofunctionalization in J proteins together contribute to the emerging functional diversity and complexity in the Hsp70:J protein network in higher plants. Based on the data presented, we propose that higher plants have orchestrated their "chaperome," especially their J protein complement, according to their specialized cellular and physiological stipulations. Copyright © 2017 Verma et al.

Lactococcus lactis, an alternative system for functional expression of peripheral and intrinsic Arabidopsis membrane proteins.

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Annie Frelet-Barrand

Full Text Available BACKGROUND: Despite their functional and biotechnological importance, the study of membrane proteins remains difficult due to their hydrophobicity and their low natural abundance in cells. Furthermore, into established heterologous systems, these proteins are frequently only produced at very low levels, toxic and mis- or unfolded. Lactococcus lactis, a gram-positive lactic bacterium, has been traditionally used in food fermentations. This expression system is also widely used in biotechnology for large-scale production of heterologous proteins. Various expression vectors, based either on constitutive or inducible promoters, are available for this system. While previously used to produce bacterial and eukaryotic membrane proteins, the ability of this system to produce plant membrane proteins was until now not tested. METHODOLOGY/PRINCIPAL FINDINGS: The aim of this work was to test the expression, in Lactococcus lactis, of either peripheral or intrinsic Arabidopsis membrane proteins that could not be produced, or in too low amount, using more classical heterologous expression systems. In an effort to easily transfer genes from Gateway-based Arabidopsis cDNA libraries to the L. lactis expression vector pNZ8148, we first established a cloning strategy compatible with Gateway entry vectors. Interestingly, the six tested Arabidopsis membrane proteins could be produced, in Lactococcus lactis, at levels compatible with further biochemical analyses. We then successfully developed solubilization and purification processes for three of these proteins. Finally, we questioned the functionality of a peripheral and an intrinsic membrane protein, and demonstrated that both proteins were active when produced in this system. CONCLUSIONS/SIGNIFICANCE: Altogether, these data suggest that Lactococcus lactis might be an attractive system for the efficient and functional production of difficult plant membrane proteins.

The structure and function of endophilin proteins

DEFF Research Database (Denmark)

Kjaerulff, Ole; Brodin, Lennart; Jung, Anita

2011-01-01

Members of the BAR domain protein superfamily are essential elements of cellular traffic. Endophilins are among the best studied BAR domain proteins. They have a prominent function in synaptic vesicle endocytosis (SVE), receptor trafficking and apoptosis, and in other processes that require...

Collagen targeting using multivalent protein-functionalized dendrimers

NARCIS (Netherlands)

Breurken, M.; Lempens, E.H.M.; Temming, R.P.; Helms, B.A.; Meijer, E.W.; Merkx, M.

2011-01-01

Collagen is an attractive marker for tissue remodeling in a variety of common disease processes. Here we report the preparation of protein dendrimers as multivalent collagen targeting ligands by native chemical ligation of the collagen binding protein CNA35 to cysteine-functionalized dendritic

Computational design of proteins with novel structure and functions

International Nuclear Information System (INIS)

Yang Wei; Lai Lu-Hua

2016-01-01

Computational design of proteins is a relatively new field, where scientists search the enormous sequence space for sequences that can fold into desired structure and perform desired functions. With the computational approach, proteins can be designed, for example, as regulators of biological processes, novel enzymes, or as biotherapeutics. These approaches not only provide valuable information for understanding of sequence–structure–function relations in proteins, but also hold promise for applications to protein engineering and biomedical research. In this review, we briefly introduce the rationale for computational protein design, then summarize the recent progress in this field, including de novo protein design, enzyme design, and design of protein–protein interactions. Challenges and future prospects of this field are also discussed. (topical review)

Milk protein tailoring to improve functional and biological properties

Directory of Open Access Journals (Sweden)

JEAN-MARC CHOBERT

2012-01-01

Full Text Available Proteins are involved in every aspects of life: structure, motion, catalysis, recognition and regulation. Today's highly sophisticated science of the modifications of proteins has ancient roots. The tailoring of proteins for food and medical uses precedes the beginning of what is called biochemistry. Chemical modification of proteins was pursued early in the twentieth century as an analytical procedure for side-chain amino acids. Later, methods were developed for specific inactivation of biologically active proteins and titration of their essential groups. Enzymatic modifications were mainly developed in the seventies when many more enzymes became economically available. Protein engineering has become a valuable tool for creating or improving proteins for practical use and has provided new insights into protein structure and function. The actual and potential use of milk proteins as food ingredients has been a popular topic for research over the past 40 years. With today's sophisticated analytical, biochemical and biological research tools, the presence of compounds with biological activity has been demonstrated. Improvements in separation techniques and enzyme technology have enabled efficient and economic isolation and modification of milk proteins, which has made possible their use as functional foods, dietary supplements, nutraceuticals and medical foods. In this review, some chemical and enzymatic modifications of milk proteins are described, with particular focus on their functional and biological properties.

Protein sequencing via nanopore based devices: a nanofluidics perspective

Science.gov (United States)

Chinappi, Mauro; Cecconi, Fabio

2018-05-01

Proteins perform a huge number of central functions in living organisms, thus all the new techniques allowing their precise, fast and accurate characterization at single-molecule level certainly represent a burst in proteomics with important biomedical impact. In this review, we describe the recent progresses in the developing of nanopore based devices for protein sequencing. We start with a critical analysis of the main technical requirements for nanopore protein sequencing, summarizing some ideas and methodologies that have recently appeared in the literature. In the last sections, we focus on the physical modelling of the transport phenomena occurring in nanopore based devices. The multiscale nature of the problem is discussed and, in this respect, some of the main possible computational approaches are illustrated.

A probabilistic fragment-based protein structure prediction algorithm.

Directory of Open Access Journals (Sweden)

David Simoncini

Full Text Available Conformational sampling is one of the bottlenecks in fragment-based protein structure prediction approaches. They generally start with a coarse-grained optimization where mainchain atoms and centroids of side chains are considered, followed by a fine-grained optimization with an all-atom representation of proteins. It is during this coarse-grained phase that fragment-based methods sample intensely the conformational space. If the native-like region is sampled more, the accuracy of the final all-atom predictions may be improved accordingly. In this work we present EdaFold, a new method for fragment-based protein structure prediction based on an Estimation of Distribution Algorithm. Fragment-based approaches build protein models by assembling short fragments from known protein structures. Whereas the probability mass functions over the fragment libraries are uniform in the usual case, we propose an algorithm that learns from previously generated decoys and steers the search toward native-like regions. A comparison with Rosetta AbInitio protocol shows that EdaFold is able to generate models with lower energies and to enhance the percentage of near-native coarse-grained decoys on a benchmark of [Formula: see text] proteins. The best coarse-grained models produced by both methods were refined into all-atom models and used in molecular replacement. All atom decoys produced out of EdaFold's decoy set reach high enough accuracy to solve the crystallographic phase problem by molecular replacement for some test proteins. EdaFold showed a higher success rate in molecular replacement when compared to Rosetta. Our study suggests that improving low resolution coarse-grained decoys allows computational methods to avoid subsequent sampling issues during all-atom refinement and to produce better all-atom models. EdaFold can be downloaded from http://www.riken.jp/zhangiru/software.html [corrected].

Divergence, recombination and retention of functionality during protein evolution

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Xu Yanlong O

2005-09-01

Full Text Available Abstract We have only a vague idea of precisely how protein sequences evolve in the context of protein structure and function. This is primarily because structural and functional contexts are not easily predictable from the primary sequence, and evaluating patterns of evolution at individual residue positions is also difficult. As a result of increasing biodiversity in genomics studies, progress is being made in detecting context-dependent variation in substitution processes, but it remains unclear exactly what context-dependent patterns we should be looking for. To address this, we have been simulating protein evolution in the context of structure and function using lattice models of proteins and ligands (or substrates. These simulations include thermodynamic features of protein stability and population dynamics. We refer to this approach as 'ab initio evolution' to emphasise the fact that the equilibrium details of fitness distributions arise from the physical principles of the system and not from any preconceived notions or arbitrary mathematical distributions. Here, we present results on the retention of functionality in homologous recombinants following population divergence. A central result is that protein structure characteristics can strongly influence recombinant functionality. Exceptional structures with many sequence options evolve quickly and tend to retain functionality -- even in highly diverged recombinants. By contrast, the more common structures with fewer sequence options evolve more slowly, but the fitness of recombinants drops off rapidly as homologous proteins diverge. These results have implications for understanding viral evolution, speciation and directed evolutionary experiments. Our analysis of the divergence process can also guide improved methods for accurately approximating folding probabilities in more complex but realistic systems.

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

Usher proteins in inner ear structure and function.

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Ahmed, Zubair M; Frolenkov, Gregory I; Riazuddin, Saima

2013-11-01

Usher syndrome (USH) is a neurosensory disorder affecting both hearing and vision in humans. Linkage studies of families of USH patients, studies in animals, and characterization of purified proteins have provided insight into the molecular mechanisms of hearing. To date, 11 USH proteins have been identified, and evidence suggests that all of them are crucial for the function of the mechanosensory cells of the inner ear, the hair cells. Most USH proteins are localized to the stereocilia of the hair cells, where mechano-electrical transduction (MET) of sound-induced vibrations occurs. Therefore, elucidation of the functions of USH proteins in the stereocilia is a prerequisite to understanding the exact mechanisms of MET.

Moonlighting microtubule-associated proteins: regulatory functions by day and pathological functions at night.

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Oláh, J; Tőkési, N; Lehotzky, A; Orosz, F; Ovádi, J

2013-11-01

The sensing, integrating, and coordinating features of the eukaryotic cells are achieved by the complex ultrastructural arrays and multifarious functions of the cytoskeletal network. Cytoskeleton comprises fibrous protein networks of microtubules, actin, and intermediate filaments. These filamentous polymer structures are highly dynamic and undergo constant and rapid reorganization during cellular processes. The microtubular system plays a crucial role in the brain, as it is involved in an enormous number of cellular events including cell differentiation and pathological inclusion formation. These multifarious functions of microtubules can be achieved by their decoration with proteins/enzymes that exert specific effects on the dynamics and organization of the cytoskeleton and mediate distinct functions due to their moonlighting features. This mini-review focuses on two aspects of the microtubule cytoskeleton. On the one hand, we describe the heteroassociation of tubulin/microtubules with metabolic enzymes, which in addition to their catalytic activities stabilize microtubule structures via their cross-linking functions. On the other hand, we focus on the recently identified moonlighting tubulin polymerization promoting protein, TPPP/p25. TPPP/p25 is a microtubule-associated protein and it displays distinct physiological or pathological (aberrant) functions; thus it is a prototype of Neomorphic Moonlighting Proteins. The expression of TPPP/p25 is finely controlled in the human brain; this protein is indispensable for the development of projections of oligodendrocytes that are responsible for the ensheathment of axons. The nonphysiological, higher or lower TPPP/p25 level leads to distinct CNS diseases. Mechanisms contributing to the control of microtubule stability and dynamics by metabolic enzymes and TPPP/p25 will be discussed. Copyright © 2013 Wiley Periodicals, Inc.

Extraction, characterization, nutritional and functional properties of Roselle (Hibiscus sabdariffa Linn seed proteins

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Fatoumata Tounkara

2013-04-01

Full Text Available Physicochemical, nutritional and functional properties of protein fractions and protein isolate (RSPI from Roselle seedwere investigated. The protein content was 91.50, 93.77, 81.55, 71.30 and 40.83% for RSPI, globulin, albumin, glutelin andprolamin, respectively. The functional properties were variable among samples. Glutelin possessed the highest water holdingcapacity and albumin the lowest. The oil holding capacity ranged from 3.47 to 7.23 mL/g and the emulsifying capacity from95 to 18 mL/g. Glutelin had the higher foam capacity, while RSPI showed the more stable foam. The molecular weight of allsamples ranged from 55,000 Da to below 14,300 Da. All the estimated nutritional parameters based on amino acids compositionsuggested that Roselle protein fractions and its isolates have good nutritional quality and could be a good source of proteinfortification for a variety of food products for protein deficient consumers as well as a potential food ingredient.

Functional Anthology of Intrinsic Disorder. I. Biological Processes and Functions of Proteins with Long Disordered Regions

Science.gov (United States)

Xie, Hongbo; Vucetic, Slobodan; Iakoucheva, Lilia M.; Oldfield, Christopher J.; Dunker, A. Keith; Uversky, Vladimir N.; Obradovic, Zoran

2008-01-01

Identifying relationships between function, amino acid sequence and protein structure represents a major challenge. In this study we propose a bioinformatics approach that identifies functional keywords in the Swiss-Prot database that correlate with intrinsic disorder. A statistical evaluation is employed to rank the significance of these correlations. Protein sequence data redundancy and the relationship between protein length and protein structure were taken into consideration to ensure the quality of the statistical inferences. Over 200,000 proteins from Swiss-Prot database were analyzed using this approach. The predictions of intrinsic disorder were carried out using PONDR VL3E predictor of long disordered regions that achieves an accuracy of above 86%. Overall, out of the 710 Swiss-Prot functional keywords that were each associated with at least 20 proteins, 238 were found to be strongly positively correlated with predicted long intrinsically disordered regions, whereas 302 were strongly negatively correlated with such regions. The remaining 170 keywords were ambiguous without strong positive or negative correlation with the disorder predictions. These functions cover a large variety of biological activities and imply that disordered regions are characterized by a wide functional repertoire. Our results agree well with literature findings, as we were able to find at least one illustrative example of functional disorder or order shown experimentally for the vast majority of keywords showing the strongest positive or negative correlation with intrinsic disorder. This work opens a series of three papers, which enriches the current view of protein structure-function relationships, especially with regards to functionalities of intrinsically disordered proteins and provides researchers with a novel tool that could be used to improve the understanding of the relationships between protein structure and function. The first paper of the series describes our statistical

Novel function of Wsc proteins as a methanol-sensing machinery in the yeast Pichia pastoris.

Science.gov (United States)

Ohsawa, Shin; Yurimoto, Hiroya; Sakai, Yasuyoshi

2017-04-01

Wsc family proteins are plasma membrane spanning sensor proteins conserved from yeasts to mammalian cells. We studied the functional roles of Wsc family proteins in the methylotrophic yeast Pichia pastoris, and found that PpWsc1 and PpWsc3 function as methanol-sensors during growth on methanol. PpWsc1 responds to a lower range of methanol concentrations than PpWsc3. PpWsc1, but not PpWsc3, also functions during high temperature stress, but PpWsc1 senses methanol as a signal that is distinct from high-temperature stress. We also found that PpRom2, which is known to function downstream of the Wsc family proteins in the cell wall integrity pathway, was also involved in sensing methanol. Based on these results, these PpWsc family proteins were demonstrated to be involved in sensing methanol and transmitting the signal via their cytoplasmic tail to the nucleus via PpRom2, which plays a critical role in regulating expression of a subset of methanol-inducible genes to coordinate well-balanced methanol metabolism. © 2017 John Wiley & Sons Ltd.

The function of communities in protein interaction networks at multiple scales

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Jones Nick S

2010-07-01

Full Text Available Abstract Background If biology is modular then clusters, or communities, of proteins derived using only protein interaction network structure should define protein modules with similar biological roles. We investigate the link between biological modules and network communities in yeast and its relationship to the scale at which we probe the network. Results Our results demonstrate that the functional homogeneity of communities depends on the scale selected, and that almost all proteins lie in a functionally homogeneous community at some scale. We judge functional homogeneity using a novel test and three independent characterizations of protein function, and find a high degree of overlap between these measures. We show that a high mean clustering coefficient of a community can be used to identify those that are functionally homogeneous. By tracing the community membership of a protein through multiple scales we demonstrate how our approach could be useful to biologists focusing on a particular protein. Conclusions We show that there is no one scale of interest in the community structure of the yeast protein interaction network, but we can identify the range of resolution parameters that yield the most functionally coherent communities, and predict which communities are most likely to be functionally homogeneous.

Identifying the molecular functions of electron transport proteins using radial basis function networks and biochemical properties.

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Le, Nguyen-Quoc-Khanh; Nguyen, Trinh-Trung-Duong; Ou, Yu-Yen

2017-05-01

The electron transport proteins have an important role in storing and transferring electrons in cellular respiration, which is the most proficient process through which cells gather energy from consumed food. According to the molecular functions, the electron transport chain components could be formed with five complexes with several different electron carriers and functions. Therefore, identifying the molecular functions in the electron transport chain is vital for helping biologists understand the electron transport chain process and energy production in cells. This work includes two phases for discriminating electron transport proteins from transport proteins and classifying categories of five complexes in electron transport proteins. In the first phase, the performances from PSSM with AAIndex feature set were successful in identifying electron transport proteins in transport proteins with achieved sensitivity of 73.2%, specificity of 94.1%, and accuracy of 91.3%, with MCC of 0.64 for independent data set. With the second phase, our method can approach a precise model for identifying of five complexes with different molecular functions in electron transport proteins. The PSSM with AAIndex properties in five complexes achieved MCC of 0.51, 0.47, 0.42, 0.74, and 1.00 for independent data set, respectively. We suggest that our study could be a power model for determining new proteins that belongs into which molecular function of electron transport proteins. Copyright © 2017 Elsevier Inc. All rights reserved.

Conformational and functional variants of CD44-targeted protein nanoparticles bio-produced in bacteria

International Nuclear Information System (INIS)

Pesarrodona, Mireia; Conchillo-Solé, Oscar; Unzueta, Ugutz; Xu, Zhikun; Ferrer-Miralles, Neus; Daura, Xavier; Vázquez, Esther; Villaverde, Antonio; Fernández, Yolanda; Foradada, Laia; Schwartz, Simó Jr; Abasolo, Ibane; Sánchez-Chardi, Alejandro; Roldán, Mónica; Villegas, Sandra; Rinas, Ursula

2016-01-01

Biofabrication is attracting interest as a means to produce nanostructured functional materials because of its operational versatility and full scalability. Materials based on proteins are especially appealing, as the structure and functionality of proteins can be adapted by genetic engineering. Furthermore, strategies and tools for protein production have been developed and refined steadily for more than 30 years. However, protein conformation and therefore activity might be sensitive to production conditions. Here, we have explored whether the downstream strategy influences the structure and biological activities, in vitro and in vivo, of a self-assembling, CD44-targeted protein-only nanoparticle produced in Escherichia coli. This has been performed through the comparative analysis of particles built from soluble protein species or protein versions obtained by in vitro protein extraction from inclusion bodies, through mild, non-denaturing procedures. These methods have been developed recently as a convenient alternative to the use of toxic chaotropic agents for protein resolubilization from protein aggregates. The results indicate that the resulting material shows substantial differences in its physicochemical properties and its biological performance at the systems level, and that its building blocks are sensitive to the particular protein source. (paper)

Predicting Structure and Function for Novel Proteins of an Extremophilic Iron Oxidizing Bacterium

Science.gov (United States)

Wheeler, K.; Zemla, A.; Banfield, J.; Thelen, M.

2007-12-01

Proteins isolated from uncultivated microbial populations represent the functional components of microbial processes and contribute directly to community fitness under natural conditions. Investigations into proteins in the environment are hindered by the lack of genome data, or where available, the high proportion of proteins of unknown function. We have identified thousands of proteins from biofilms in the extremely acidic drainage outflow of an iron mine ecosystem (1). With an extensive genomic and proteomic foundation, we have focused directly on the problem of several hundred proteins of unknown function within this well-defined model system. Here we describe the geobiological insights gained by using a high throughput computational approach for predicting structure and function of 421 novel proteins from the biofilm community. We used a homology based modeling system to compare these proteins to those of known structure (AS2TS) (2). This approach has resulted in the assignment of structures to 360 proteins (85%) and provided functional information for up to 75% of the modeled proteins. Detailed examination of the modeling results enables confident, high-throughput prediction of the roles of many of the novel proteins within the microbial community. For instance, one prediction places a protein in the phosphoenolpyruvate/pyruvate domain superfamily as a carboxylase that fills in a gap in an otherwise complete carbon cycle. Particularly important for a community in such a metal rich environment is the evolution of over 25% of the novel proteins that contain a metal cofactor; of these, one third are likely Fe containing proteins. Two of the most abundant proteins in biofilm samples are unusual c-type cytochromes. Both of these proteins catalyze iron- oxidation, a key metabolic reaction supporting the energy requirements of this community. Structural models of these cytochromes verify our experimental results on heme binding and electron transfer reactivity, and

Functional studies on the phosphatidychloride transfer protein

NARCIS (Netherlands)

Brouwer, A.P.M. de

2002-01-01

The phosphatidylcholine transfer protein (PC-TP) has been studied for over 30 years now. Despite extensive research concerning the biochemical, biophysical and structural properties of PC-TP, the function of this protein is still elusive. We have studied in vitro the folding and the mechanism of PC

Functional dynamics of cell surface membrane proteins.

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Nishida, Noritaka; Osawa, Masanori; Takeuchi, Koh; Imai, Shunsuke; Stampoulis, Pavlos; Kofuku, Yutaka; Ueda, Takumi; Shimada, Ichio

2014-04-01

Cell surface receptors are integral membrane proteins that receive external stimuli, and transmit signals across plasma membranes. In the conventional view of receptor activation, ligand binding to the extracellular side of the receptor induces conformational changes, which convert the structure of the receptor into an active conformation. However, recent NMR studies of cell surface membrane proteins have revealed that their structures are more dynamic than previously envisioned, and they fluctuate between multiple conformations in an equilibrium on various timescales. In addition, NMR analyses, along with biochemical and cell biological experiments indicated that such dynamical properties are critical for the proper functions of the receptors. In this review, we will describe several NMR studies that revealed direct linkage between the structural dynamics and the functions of the cell surface membrane proteins, such as G-protein coupled receptors (GPCRs), ion channels, membrane transporters, and cell adhesion molecules. Copyright © 2013 Elsevier Inc. All rights reserved.

Chimeras taking shape: Potential functions of proteins encoded by chimeric RNA transcripts

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Frenkel-Morgenstern, Milana; Lacroix, Vincent; Ezkurdia, Iakes; Levin, Yishai; Gabashvili, Alexandra; Prilusky, Jaime; del Pozo, Angela; Tress, Michael; Johnson, Rory; Guigo, Roderic; Valencia, Alfonso

2012-01-01

Chimeric RNAs comprise exons from two or more different genes and have the potential to encode novel proteins that alter cellular phenotypes. To date, numerous putative chimeric transcripts have been identified among the ESTs isolated from several organisms and using high throughput RNA sequencing. The few corresponding protein products that have been characterized mostly result from chromosomal translocations and are associated with cancer. Here, we systematically establish that some of the putative chimeric transcripts are genuinely expressed in human cells. Using high throughput RNA sequencing, mass spectrometry experimental data, and functional annotation, we studied 7424 putative human chimeric RNAs. We confirmed the expression of 175 chimeric RNAs in 16 human tissues, with an abundance varying from 0.06 to 17 RPKM (Reads Per Kilobase per Million mapped reads). We show that these chimeric RNAs are significantly more tissue-specific than non-chimeric transcripts. Moreover, we present evidence that chimeras tend to incorporate highly expressed genes. Despite the low expression level of most chimeric RNAs, we show that 12 novel chimeras are translated into proteins detectable in multiple shotgun mass spectrometry experiments. Furthermore, we confirm the expression of three novel chimeric proteins using targeted mass spectrometry. Finally, based on our functional annotation of exon organization and preserved domains, we discuss the potential features of chimeric proteins with illustrative examples and suggest that chimeras significantly exploit signal peptides and transmembrane domains, which can alter the cellular localization of cognate proteins. Taken together, these findings establish that some chimeric RNAs are translated into potentially functional proteins in humans. PMID:22588898

Prediction of Protein-Protein Interaction By Metasample-Based Sparse Representation

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Xiuquan Du

2015-01-01

Full Text Available Protein-protein interactions (PPIs play key roles in many cellular processes such as transcription regulation, cell metabolism, and endocrine function. Understanding these interactions takes a great promotion to the pathogenesis and treatment of various diseases. A large amount of data has been generated by experimental techniques; however, most of these data are usually incomplete or noisy, and the current biological experimental techniques are always very time-consuming and expensive. In this paper, we proposed a novel method (metasample-based sparse representation classification, MSRC for PPIs prediction. A group of metasamples are extracted from the original training samples and then use the l1-regularized least square method to express a new testing sample as the linear combination of these metasamples. PPIs prediction is achieved by using a discrimination function defined in the representation coefficients. The MSRC is applied to PPIs dataset; it achieves 84.9% sensitivity, and 94.55% specificity, which is slightly lower than support vector machine (SVM and much higher than naive Bayes (NB, neural networks (NN, and k-nearest neighbor (KNN. The result shows that the MSRC is efficient for PPIs prediction.

Preparation of a novel dual-function strong cation exchange/hydrophobic interaction chromatography stationary phase for protein separation.

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Zhao, Kailou; Yang, Li; Wang, Xuejiao; Bai, Quan; Yang, Fan; Wang, Fei

2012-08-30

We have explored a novel dual-function stationary phase which combines both strong cation exchange (SCX) and hydrophobic interaction chromatography (HIC) characteristics. The novel dual-function stationary phase is based on porous and spherical silica gel functionalized with ligand containing sulfonic and benzyl groups capable of electrostatic and hydrophobic interaction functionalities, which displays HIC character in a high salt concentration, and IEC character in a low salt concentration in mobile phase employed. As a result, it can be employed to separate proteins with SCX and HIC modes, respectively. The resolution and selectivity of the dual-function stationary phase were evaluated under both HIC and SCX modes with standard proteins and can be comparable to that of conventional IEC and HIC columns. More than 96% of mass and bioactivity recoveries of proteins can be achieved in both HIC and SCX modes, respectively. The results indicated that the novel dual-function column could replace two individual SCX and HIC columns for protein separation. Mixed retention mechanism of proteins on this dual-function column based on stoichiometric displacement theory (SDT) in LC was investigated to find the optimal balance of the magnitude of electrostatic and hydrophobic interactions between protein and the ligand on the silica surface in order to obtain high resolution and selectivity for protein separation. In addition, the effects of the hydrophobicity of the ligand of the dual-function packings and pH of the mobile phase used on protein separation were also investigated in detail. The results show that the ligand with suitable hydrophobicity to match the electrostatic interaction is very important to prepare the dual-function stationary phase, and a better resolution and selectivity can be obtained at pH 6.5 in SCX mode. Therefore, the dual-function column can replace two individual SCX and HIC columns for protein separation and be used to set up two-dimensional liquid

A pairwise residue contact area-based mean force potential for discrimination of native protein structure

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Pezeshk Hamid

2010-01-01

Full Text Available Abstract Background Considering energy function to detect a correct protein fold from incorrect ones is very important for protein structure prediction and protein folding. Knowledge-based mean force potentials are certainly the most popular type of interaction function for protein threading. They are derived from statistical analyses of interacting groups in experimentally determined protein structures. These potentials are developed at the atom or the amino acid level. Based on orientation dependent contact area, a new type of knowledge-based mean force potential has been developed. Results We developed a new approach to calculate a knowledge-based potential of mean-force, using pairwise residue contact area. To test the performance of our approach, we performed it on several decoy sets to measure its ability to discriminate native structure from decoys. This potential has been able to distinguish native structures from the decoys in the most cases. Further, the calculated Z-scores were quite high for all protein datasets. Conclusions This knowledge-based potential of mean force can be used in protein structure prediction, fold recognition, comparative modelling and molecular recognition. The program is available at http://www.bioinf.cs.ipm.ac.ir/softwares/surfield

Functions and structures of eukaryotic recombination proteins

International Nuclear Information System (INIS)

Ogawa, Tomoko

1994-01-01

We have found that Rad51 and RecA Proteins form strikingly similar structures together with dsDNA and ATP. Their right handed helical nucleoprotein filaments extend the B-form DNA double helixes to 1.5 times in length and wind the helix. The similarity and uniqueness of their structures must reflect functional homologies between these proteins. Therefore, it is highly probable that similar recombination proteins are present in various organisms of different evolutional states. We have succeeded to clone RAD51 genes from human, mouse, chicken and fission yeast genes, and found that the homologues are widely distributed in eukaryotes. The HsRad51 and MmRad51 or ChRad51 proteins consist of 339 amino acids differing only by 4 or 12 amino acids, respectively, and highly homologous to both yeast proteins, but less so to Dmcl. All of these proteins are homologous to the region from residues 33 to 240 of RecA which was named ''homologous core. The homologous core is likely to be responsible for functions common for all of them, such as the formation of helical nucleoprotein filament that is considered to be involved in homologous pairing in the recombination reaction. The mouse gene is transcribed at a high level in thymus, spleen, testis, and ovary, at lower level in brain and at a further lower level in some other tissues. It is transcribed efficiently in recombination active tissues. A clear functional difference of Rad51 homologues from RecA was suggested by the failure of heterologous genes to complement the deficiency of Scrad51 mutants. This failure seems to reflect the absence of a compatible partner, such as ScRad52 protein in the case of ScRad51 protein, between different species. Thus, these discoveries play a role of the starting point to understand the fundamental gene targeting in mammalian cells and in gene therapy. (J.P.N.)

Functional similarities between the dictyostelium protein AprA and the human protein dipeptidyl-peptidase IV.

Science.gov (United States)

Herlihy, Sarah E; Tang, Yu; Phillips, Jonathan E; Gomer, Richard H

2017-03-01

Autocrine proliferation repressor protein A (AprA) is a protein secreted by Dictyostelium discoideum cells. Although there is very little sequence similarity between AprA and any human protein, AprA has a predicted structural similarity to the human protein dipeptidyl peptidase IV (DPPIV). AprA is a chemorepellent for Dictyostelium cells, and DPPIV is a chemorepellent for neutrophils. This led us to investigate if AprA and DPPIV have additional functional similarities. We find that like AprA, DPPIV is a chemorepellent for, and inhibits the proliferation of, D. discoideum cells, and that AprA binds some DPPIV binding partners such as fibronectin. Conversely, rAprA has DPPIV-like protease activity. These results indicate a functional similarity between two eukaryotic chemorepellent proteins with very little sequence similarity, and emphasize the usefulness of using a predicted protein structure to search a protein structure database, in addition to searching for proteins with similar sequences. © 2016 The Protein Society.

Production of functional protein hydrolysates from Egyptian breeds ...

African Journals Online (AJOL)

Production of functional protein hydrolysates from Egyptian breeds of soybean and lupin seeds. AA khalil, SS Mohamed, FS Taha, EN Karlsson. Abstract. Enzymatic hydrolysis is an agro-processing aid that can be utilized in order to improve nutritional quality of protein extracts from many sources. In this study, protein ...

Membrane Protein Production in Lactococcus lactis for Functional Studies.

Science.gov (United States)

Seigneurin-Berny, Daphne; King, Martin S; Sautron, Emiline; Moyet, Lucas; Catty, Patrice; André, François; Rolland, Norbert; Kunji, Edmund R S; Frelet-Barrand, Annie

2016-01-01

Due to their unique properties, expression and study of membrane proteins in heterologous systems remains difficult. Among the bacterial systems available, the Gram-positive lactic bacterium, Lactococcus lactis, traditionally used in food fermentations, is nowadays widely used for large-scale production and functional characterization of bacterial and eukaryotic membrane proteins. The aim of this chapter is to describe the different possibilities for the functional characterization of peripheral or intrinsic membrane proteins expressed in Lactococcus lactis.

Knowledge base and neural network approach for protein secondary structure prediction.

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Patel, Maulika S; Mazumdar, Himanshu S

2014-11-21

Protein structure prediction is of great relevance given the abundant genomic and proteomic data generated by the genome sequencing projects. Protein secondary structure prediction is addressed as a sub task in determining the protein tertiary structure and function. In this paper, a novel algorithm, KB-PROSSP-NN, which is a combination of knowledge base and modeling of the exceptions in the knowledge base using neural networks for protein secondary structure prediction (PSSP), is proposed. The knowledge base is derived from a proteomic sequence-structure database and consists of the statistics of association between the 5-residue words and corresponding secondary structure. The predicted results obtained using knowledge base are refined with a Backpropogation neural network algorithm. Neural net models the exceptions of the knowledge base. The Q3 accuracy of 90% and 82% is achieved on the RS126 and CB396 test sets respectively which suggest improvement over existing state of art methods. Copyright © 2014 Elsevier Ltd. All rights reserved.

Diversity and functions of protein glycosylation in insects.

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Walski, Tomasz; De Schutter, Kristof; Van Damme, Els J M; Smagghe, Guy

2017-04-01

The majority of proteins is modified with carbohydrate structures. This modification, called glycosylation, was shown to be crucial for protein folding, stability and subcellular location, as well as protein-protein interactions, recognition and signaling. Protein glycosylation is involved in multiple physiological processes, including embryonic development, growth, circadian rhythms, cell attachment as well as maintenance of organ structure, immunity and fertility. Although the general principles of glycosylation are similar among eukaryotic organisms, insects synthesize a distinct repertoire of glycan structures compared to plants and vertebrates. Consequently, a number of unique insect glycans mediate functions specific to this class of invertebrates. For instance, the core α1,3-fucosylation of N-glycans is absent in vertebrates, while in insects this modification is crucial for the development of wings and the nervous system. At present, most of the data on insect glycobiology comes from research in Drosophila. Yet, progressively more information on the glycan structures and the importance of glycosylation in other insects like beetles, caterpillars, aphids and bees is becoming available. This review gives a summary of the current knowledge and recent progress related to glycan diversity and function(s) of protein glycosylation in insects. We focus on N- and O-glycosylation, their synthesis, physiological role(s), as well as the molecular and biochemical basis of these processes. Copyright © 2017 Elsevier Ltd. All rights reserved.

FY 1999 report on the results on analysis of protein functions; 1999 nendo tanpakushitsu kino kaiseki seika hokokusho

Energy Technology Data Exchange (ETDEWEB)

NONE

2001-03-01

This project is aimed at construction of the intellectual infrastructures for biotechnologies, in order to accelerate development of the Japanese technologies and activate their application to industries. Described herein are the FY 1999 results. These infrastructures are for functional analysis of protein which will be one of the key issues in genome analysis, and collection and analysis of biological information. This project includes a total of 9 research and development themes for four research categories: frequency analysis of gene expression (development of the gene expression profile database system for functional analysis of human genome, and analysis of the gene expression and protein functions by the ECA chip technology), function analysis by the biological model (high-performance analysis by the bio-project, database system for drug metabolizing enzymes, analysis of gene functions using mutant mice, and simple genome function analysis of murine individuals using the RNAi effect), protein expression (function validation of unknown human genes based on the useful biological model, and protein function analysis using multi-purpose destination vectors), and protein function prediction by the information science method. (NEDO)

Metaproteomics of Colonic Microbiota Unveils Discrete Protein Functions among Colitic Mice and Control Groups.

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Moon, Clara; Stupp, Gregory S; Su, Andrew I; Wolan, Dennis W

2018-02-01

Metaproteomics can greatly assist established high-throughput sequencing methodologies to provide systems biological insights into the alterations of microbial protein functionalities correlated with disease-associated dysbiosis of the intestinal microbiota. Here, the authors utilize the well-characterized murine T cell transfer model of colitis to find specific changes within the intestinal luminal proteome associated with inflammation. MS proteomic analysis of colonic samples permitted the identification of ≈10 000-12 000 unique peptides that corresponded to 5610 protein clusters identified across three groups, including the colitic Rag1 -/- T cell recipients, isogenic Rag1 -/- controls, and wild-type mice. The authors demonstrate that the colitic mice exhibited a significant increase in Proteobacteria and Verrucomicrobia and show that such alterations in the microbial communities contributed to the enrichment of specific proteins with transcription and translation gene ontology terms. In combination with 16S sequencing, the authors' metaproteomics-based microbiome studies provide a foundation for assessing alterations in intestinal luminal protein functionalities in a robust and well-characterized mouse model of colitis, and set the stage for future studies to further explore the functional mechanisms of altered protein functionalities associated with dysbiosis and inflammation. © 2018 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Gα and regulator of G-protein signaling (RGS) protein pairs maintain functional compatibility and conserved interaction interfaces throughout evolution despite frequent loss of RGS proteins in plants.

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Hackenberg, Dieter; McKain, Michael R; Lee, Soon Goo; Roy Choudhury, Swarup; McCann, Tyler; Schreier, Spencer; Harkess, Alex; Pires, J Chris; Wong, Gane Ka-Shu; Jez, Joseph M; Kellogg, Elizabeth A; Pandey, Sona

2017-10-01

Signaling pathways regulated by heterotrimeric G-proteins exist in all eukaryotes. The regulator of G-protein signaling (RGS) proteins are key interactors and critical modulators of the Gα protein of the heterotrimer. However, while G-proteins are widespread in plants, RGS proteins have been reported to be missing from the entire monocot lineage, with two exceptions. A single amino acid substitution-based adaptive coevolution of the Gα:RGS proteins was proposed to enable the loss of RGS in monocots. We used a combination of evolutionary and biochemical analyses and homology modeling of the Gα and RGS proteins to address their expansion and its potential effects on the G-protein cycle in plants. Our results show that RGS proteins are widely distributed in the monocot lineage, despite their frequent loss. There is no support for the adaptive coevolution of the Gα:RGS protein pair based on single amino acid substitutions. RGS proteins interact with, and affect the activity of, Gα proteins from species with or without endogenous RGS. This cross-functional compatibility expands between the metazoan and plant kingdoms, illustrating striking conservation of their interaction interface. We propose that additional proteins or alternative mechanisms may exist which compensate for the loss of RGS in certain plant species. © 2016 The Authors. New Phytologist © 2016 New Phytologist Trust.

Diversity, classification and function of the plant protein kinase superfamily

OpenAIRE

Lehti-Shiu, Melissa D.; Shiu, Shin-Han

2012-01-01

Eukaryotic protein kinases belong to a large superfamily with hundreds to thousands of copies and are components of essentially all cellular functions. The goals of this study are to classify protein kinases from 25 plant species and to assess their evolutionary history in conjunction with consideration of their molecular functions. The protein kinase superfamily has expanded in the flowering plant lineage, in part through recent duplications. As a result, the flowering plant protein kinase r...

Functional similarities between the dictyostelium protein AprA and the human protein dipeptidyl‐peptidase IV

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Herlihy, Sarah E.; Tang, Yu; Phillips, Jonathan E.

2017-01-01

Abstract Autocrine proliferation repressor protein A (AprA) is a protein secreted by Dictyostelium discoideum cells. Although there is very little sequence similarity between AprA and any human protein, AprA has a predicted structural similarity to the human protein dipeptidyl peptidase IV (DPPIV). AprA is a chemorepellent for Dictyostelium cells, and DPPIV is a chemorepellent for neutrophils. This led us to investigate if AprA and DPPIV have additional functional similarities. We find that like AprA, DPPIV is a chemorepellent for, and inhibits the proliferation of, D. discoideum cells, and that AprA binds some DPPIV binding partners such as fibronectin. Conversely, rAprA has DPPIV‐like protease activity. These results indicate a functional similarity between two eukaryotic chemorepellent proteins with very little sequence similarity, and emphasize the usefulness of using a predicted protein structure to search a protein structure database, in addition to searching for proteins with similar sequences. PMID:28028841

Dissecting protein loops with a statistical scalpel suggests a functional implication of some structural motifs.

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

2011-06-20

One of the strategies for protein function annotation is to search particular structural motifs that are known to be shared by proteins with a given function. Here, we present a systematic extraction of structural motifs of seven residues from protein loops and we explore their correspondence with functional sites. Our approach is based on the structural alphabet HMM-SA (Hidden Markov Model - Structural Alphabet), which allows simplification of protein structures into uni-dimensional sequences, and advanced pattern statistics adapted to short sequences. Structural motifs of interest are selected by looking for structural motifs significantly over-represented in SCOP superfamilies in protein loops. We discovered two types of structural motifs significantly over-represented in SCOP superfamilies: (i) ubiquitous motifs, shared by several superfamilies and (ii) superfamily-specific motifs, over-represented in few superfamilies. A comparison of ubiquitous words with known small structural motifs shows that they contain well-described motifs as turn, niche or nest motifs. A comparison between superfamily-specific motifs and biological annotations of Swiss-Prot reveals that some of them actually correspond to functional sites involved in the binding sites of small ligands, such as ATP/GTP, NAD(P) and SAH/SAM. Our findings show that statistical over-representation in SCOP superfamilies is linked to functional features. The detection of over-represented motifs within structures simplified by HMM-SA is therefore a promising approach for prediction of functional sites and annotation of uncharacterized proteins.

Dissecting protein loops with a statistical scalpel suggests a functional implication of some structural motifs

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Martin Juliette

2011-06-01

Full Text Available Abstract Background One of the strategies for protein function annotation is to search particular structural motifs that are known to be shared by proteins with a given function. Results Here, we present a systematic extraction of structural motifs of seven residues from protein loops and we explore their correspondence with functional sites. Our approach is based on the structural alphabet HMM-SA (Hidden Markov Model - Structural Alphabet, which allows simplification of protein structures into uni-dimensional sequences, and advanced pattern statistics adapted to short sequences. Structural motifs of interest are selected by looking for structural motifs significantly over-represented in SCOP superfamilies in protein loops. We discovered two types of structural motifs significantly over-represented in SCOP superfamilies: (i ubiquitous motifs, shared by several superfamilies and (ii superfamily-specific motifs, over-represented in few superfamilies. A comparison of ubiquitous words with known small structural motifs shows that they contain well-described motifs as turn, niche or nest motifs. A comparison between superfamily-specific motifs and biological annotations of Swiss-Prot reveals that some of them actually correspond to functional sites involved in the binding sites of small ligands, such as ATP/GTP, NAD(P and SAH/SAM. Conclusions Our findings show that statistical over-representation in SCOP superfamilies is linked to functional features. The detection of over-represented motifs within structures simplified by HMM-SA is therefore a promising approach for prediction of functional sites and annotation of uncharacterized proteins.

An attempt to understand kidney's protein handling function by comparing plasma and urine proteomes.

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Lulu Jia

Full Text Available BACKGROUND: With the help of proteomics technology, the human plasma and urine proteomes, which closely represent the protein compositions of the input and output of the kidney, respectively, have been profiled in much greater detail by different research teams. Many datasets have been accumulated to form "reference profiles" of the plasma and urine proteomes. Comparing these two proteomes may help us understand the protein handling aspect of kidney function in a way, however, which has been unavailable until the recent advances in proteomics technology. METHODOLOGY/PRINCIPAL FINDINGS: After removing secreted proteins downstream of the kidney, 2611 proteins in plasma and 1522 in urine were identified with high confidence and compared based on available proteomic data to generate three subproteomes, the plasma-only subproteome, the plasma-and-urine subproteome, and the urine-only subproteome, and they correspond to three groups of proteins that are handled in three different ways by the kidney. The available experimental molecular weights of the proteins in the three subproteomes were collected and analyzed. Since the functions of the overrepresented proteins in the plasma-and-urine subproteome are probably the major functions that can be routinely regulated by excretion from the kidney in physiological conditions, Gene Ontology term enrichment in the plasma-and-urine subproteome versus the whole plasma proteome was analyzed. Protease activity, calcium and growth factor binding proteins, and coagulation and immune response-related proteins were found to be enriched. CONCLUSION/SIGNIFICANCE: The comparison method described in this paper provides an illustration of a new approach for studying organ functions with a proteomics methodology. Because of its distinctive input (plasma and output (urine, it is reasonable to predict that the kidney will be the first organ whose functions are further elucidated by proteomic methods in the near future. It

New in protein structure and function annotation: hotspots, single nucleotide polymorphisms and the 'Deep Web'.

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Bromberg, Yana; Yachdav, Guy; Ofran, Yanay; Schneider, Reinhard; Rost, Burkhard

2009-05-01

The rapidly increasing quantity of protein sequence data continues to widen the gap between available sequences and annotations. Comparative modeling suggests some aspects of the 3D structures of approximately half of all known proteins; homology- and network-based inferences annotate some aspect of function for a similar fraction of the proteome. For most known protein sequences, however, there is detailed knowledge about neither their function nor their structure. Comprehensive efforts towards the expert curation of sequence annotations have failed to meet the demand of the rapidly increasing number of available sequences. Only the automated prediction of protein function in the absence of homology can close the gap between available sequences and annotations in the foreseeable future. This review focuses on two novel methods for automated annotation, and briefly presents an outlook on how modern web software may revolutionize the field of protein sequence annotation. First, predictions of protein binding sites and functional hotspots, and the evolution of these into the most successful type of prediction of protein function from sequence will be discussed. Second, a new tool, comprehensive in silico mutagenesis, which contributes important novel predictions of function and at the same time prepares for the onset of the next sequencing revolution, will be described. While these two new sub-fields of protein prediction represent the breakthroughs that have been achieved methodologically, it will then be argued that a different development might further change the way biomedical researchers benefit from annotations: modern web software can connect the worldwide web in any browser with the 'Deep Web' (ie, proprietary data resources). The availability of this direct connection, and the resulting access to a wealth of data, may impact drug discovery and development more than any existing method that contributes to protein annotation.

Geometrical comparison of two protein structures using Wigner-D functions.

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Saberi Fathi, S M; White, Diana T; Tuszynski, Jack A

2014-10-01

In this article, we develop a quantitative comparison method for two arbitrary protein structures. This method uses a root-mean-square deviation characterization and employs a series expansion of the protein's shape function in terms of the Wigner-D functions to define a new criterion, which is called a "similarity value." We further demonstrate that the expansion coefficients for the shape function obtained with the help of the Wigner-D functions correspond to structure factors. Our method addresses the common problem of comparing two proteins with different numbers of atoms. We illustrate it with a worked example. © 2014 Wiley Periodicals, Inc.

Identifying Hierarchical and Overlapping Protein Complexes Based on Essential Protein-Protein Interactions and “Seed-Expanding” Method

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Jun Ren

2014-01-01

Full Text Available Many evidences have demonstrated that protein complexes are overlapping and hierarchically organized in PPI networks. Meanwhile, the large size of PPI network wants complex detection methods have low time complexity. Up to now, few methods can identify overlapping and hierarchical protein complexes in a PPI network quickly. In this paper, a novel method, called MCSE, is proposed based on λ-module and “seed-expanding.” First, it chooses seeds as essential PPIs or edges with high edge clustering values. Then, it identifies protein complexes by expanding each seed to a λ-module. MCSE is suitable for large PPI networks because of its low time complexity. MCSE can identify overlapping protein complexes naturally because a protein can be visited by different seeds. MCSE uses the parameter λ_th to control the range of seed expanding and can detect a hierarchical organization of protein complexes by tuning the value of λ_th. Experimental results of S. cerevisiae show that this hierarchical organization is similar to that of known complexes in MIPS database. The experimental results also show that MCSE outperforms other previous competing algorithms, such as CPM, CMC, Core-Attachment, Dpclus, HC-PIN, MCL, and NFC, in terms of the functional enrichment and matching with known protein complexes.

The family of light-harvesting-related proteins (LHCs, ELIPs, HLIPs): was the harvesting of light their primary function?

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Montané, M H; Kloppstech, K

2000-11-27

Light-harvesting complex proteins (LHCs) and early light-induced proteins (ELIPs) are essential pigment-binding components of the thylakoid membrane and are encoded by one of the largest and most complex higher plant gene families. The functional diversification of these proteins corresponded to the transition from extrinsic (phycobilisome-based) to intrinsic (LHC-based) light-harvesting antenna systems during the evolution of chloroplasts from cyanobacteria, yet the functional basis of this diversification has been elusive. Here, we propose that the original function of LHCs and ELIPs was not to collect light and to transfer its energy content to the reaction centers but to disperse the absorbed energy of light in the form of heat or fluorescence. These energy-dispersing proteins are believed to have originated in cyanobacteria as one-helix, highly light-inducible proteins (HLIPs) that later acquired four helices through two successive gene duplication steps. We suggest that the ELIPs arose first in this succession, with a primary function in energy dispersion for protection of photosynthetic pigments from photo-oxidation. We consider the LHC I and II families as more recent and very successful evolutionary additions to this family that ultimately attained a new function, thereby replacing the ancestral extrinsic light-harvesting system. Our model accounts for the non-photochemical quenching role recently shown for higher plant psbS proteins.

Protections of bovine serum albumin protein from damage on functionalized graphene-based electrodes by flavonoids.

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Sun, Bolu; Gou, Yuqiang; Xue, Zhiyuan; Zheng, Xiaoping; Ma, Yuling; Hu, Fangdi; Zhao, Wanghong

2016-05-01

A sensitive electrochemical sensor based on bovine serum albumin (BSA)/poly (diallyldimethylammonium chloride) (PDDA) functionalized graphene nanosheets (PDDA-G) composite film modified glassy carbon electrode (BSA/PDDA-G/GCE) had been developed to investigate the oxidative protein damage and protections of protein from damage by flavonoids. The performance of this sensor was remarkably improved due to excellent electrical conductivity, strong adsorptive ability, and large effective surface area of PDDA-G. The BSA/PDDA-G/GCE displayed the greatest degree of BSA oxidation damage at 40 min incubation time and in the pH 5.0 Fenton reagent system (12.5 mM FeSO4, 50 mM H2O2). The antioxidant activities of four flavonoids had been compared by fabricated sensor based on the relative peak current ratio of SWV, because flavonoids prevented BSA damage caused by Fenton reagent and affected the BSA signal in a solution containing Co(bpy)3(3+). The sensor was characterized by cyclic voltammetry (CV), electrochemical impedance spectroscopy (EIS), and scanning electron microscopy (SEM). UV-vis spectrophotometry and FTIR were also used to investigate the generation of hydroxyl radical and BSA damage, respectively. On the basis of results from electrochemical methods, the order of the antioxidant activities of flavonoids is as follows: (+)-catechin>kaempferol>apigenin>naringenin. A novel, direct SWV analytical method for detection of BSA damage and assessment of the antioxidant activities of four flavonoids was developed and this electrochemical method provided a simple, inexpensive and rapid detection of BSA damage and evaluation of the antioxidant activities of samples. Copyright © 2016 Elsevier B.V. All rights reserved.

Tet protein function during Drosophila development.

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Fei Wang

Full Text Available The TET (Ten-eleven translocation 1, 2 and 3 proteins have been shown to function as DNA hydroxymethylases in vertebrates and their requirements have been documented extensively. Recently, the Tet proteins have been shown to also hydroxylate 5-methylcytosine in RNA. 5-hydroxymethylcytosine (5hmrC is enriched in messenger RNA but the function of this modification has yet to be elucidated. Because Cytosine methylation in DNA is barely detectable in Drosophila, it serves as an ideal model to study the biological function of 5hmrC. Here, we characterized the temporal and spatial expression and requirement of Tet throughout Drosophila development. We show that Tet is essential for viability as Tet complete loss-of-function animals die at the late pupal stage. Tet is highly expressed in neuronal tissues and at more moderate levels in somatic muscle precursors in embryos and larvae. Depletion of Tet in muscle precursors at early embryonic stages leads to defects in larval locomotion and late pupal lethality. Although Tet knock-down in neuronal tissue does not cause lethality, it is essential for neuronal function during development through its affects upon locomotion in larvae and the circadian rhythm of adult flies. Further, we report the function of Tet in ovarian morphogenesis. Together, our findings provide basic insights into the biological function of Tet in Drosophila, and may illuminate observed neuronal and muscle phenotypes observed in vertebrates.

Challenges in the Development of Functional Assays of Membrane Proteins

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Sophie Demarche

2012-11-01

Full Text Available Lipid bilayers are natural barriers of biological cells and cellular compartments. Membrane proteins integrated in biological membranes enable vital cell functions such as signal transduction and the transport of ions or small molecules. In order to determine the activity of a protein of interest at defined conditions, the membrane protein has to be integrated into artificial lipid bilayers immobilized on a surface. For the fabrication of such biosensors expertise is required in material science, surface and analytical chemistry, molecular biology and biotechnology. Specifically, techniques are needed for structuring surfaces in the micro- and nanometer scale, chemical modification and analysis, lipid bilayer formation, protein expression, purification and solubilization, and most importantly, protein integration into engineered lipid bilayers. Electrochemical and optical methods are suitable to detect membrane activity-related signals. The importance of structural knowledge to understand membrane protein function is obvious. Presently only a few structures of membrane proteins are solved at atomic resolution. Functional assays together with known structures of individual membrane proteins will contribute to a better understanding of vital biological processes occurring at biological membranes. Such assays will be utilized in the discovery of drugs, since membrane proteins are major drug targets.

Using RNA Interference to Study Protein Function

OpenAIRE

Curtis, Carol D.; Nardulli, Ann M.

2009-01-01

RNA interference can be extremely useful in determining the function of an endogenously-expressed protein in its normal cellular environment. In this chapter, we describe a method that uses small interfering RNA (siRNA) to knock down mRNA and protein expression in cultured cells so that the effect of a putative regulatory protein on gene expression can be delineated. Methods of assessing the effectiveness of the siRNA procedure using real time quantitative PCR and Western analysis are also in...

Intricate knots in proteins: Function and evolution.

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Peter Virnau

2006-09-01

Full Text Available Our investigation of knotted structures in the Protein Data Bank reveals the most complicated knot discovered to date. We suggest that the occurrence of this knot in a human ubiquitin hydrolase might be related to the role of the enzyme in protein degradation. While knots are usually preserved among homologues, we also identify an exception in a transcarbamylase. This allows us to exemplify the function of knots in proteins and to suggest how they may have been created.

Exploring overlapping functional units with various structure in protein interaction networks.

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Xiao-Fei Zhang

Full Text Available Revealing functional units in protein-protein interaction (PPI networks are important for understanding cellular functional organization. Current algorithms for identifying functional units mainly focus on cohesive protein complexes which have more internal interactions than external interactions. Most of these approaches do not handle overlaps among complexes since they usually allow a protein to belong to only one complex. Moreover, recent studies have shown that other non-cohesive structural functional units beyond complexes also exist in PPI networks. Thus previous algorithms that just focus on non-overlapping cohesive complexes are not able to present the biological reality fully. Here, we develop a new regularized sparse random graph model (RSRGM to explore overlapping and various structural functional units in PPI networks. RSRGM is principally dominated by two model parameters. One is used to define the functional units as groups of proteins that have similar patterns of connections to others, which allows RSRGM to detect non-cohesive structural functional units. The other one is used to represent the degree of proteins belonging to the units, which supports a protein belonging to more than one revealed unit. We also propose a regularizer to control the smoothness between the estimators of these two parameters. Experimental results on four S. cerevisiae PPI networks show that the performance of RSRGM on detecting cohesive complexes and overlapping complexes is superior to that of previous competing algorithms. Moreover, RSRGM has the ability to discover biological significant functional units besides complexes.

Immobilizing affinity proteins to nitrocellulose: a toolbox for paper-based assay developers.

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Holstein, Carly A; Chevalier, Aaron; Bennett, Steven; Anderson, Caitlin E; Keniston, Karen; Olsen, Cathryn; Li, Bing; Bales, Brian; Moore, David R; Fu, Elain; Baker, David; Yager, Paul

2016-02-01

To enable enhanced paper-based diagnostics with improved detection capabilities, new methods are needed to immobilize affinity reagents to porous substrates, especially for capture molecules other than IgG. To this end, we have developed and characterized three novel methods for immobilizing protein-based affinity reagents to nitrocellulose membranes. We have demonstrated these methods using recombinant affinity proteins for the influenza surface protein hemagglutinin, leveraging the customizability of these recombinant "flu binders" for the design of features for immobilization. The three approaches shown are: (1) covalent attachment of thiolated affinity protein to an epoxide-functionalized nitrocellulose membrane, (2) attachment of biotinylated affinity protein through a nitrocellulose-binding streptavidin anchor protein, and (3) fusion of affinity protein to a novel nitrocellulose-binding anchor protein for direct coupling and immobilization. We also characterized the use of direct adsorption for the flu binders, as a point of comparison and motivation for these novel methods. Finally, we demonstrated that these novel methods can provide improved performance to an influenza hemagglutinin assay, compared to a traditional antibody-based capture system. Taken together, this work advances the toolkit available for the development of next-generation paper-based diagnostics.

Crystallization of bi-functional ligand protein complexes.

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Antoni, Claudia; Vera, Laura; Devel, Laurent; Catalani, Maria Pia; Czarny, Bertrand; Cassar-Lajeunesse, Evelyn; Nuti, Elisa; Rossello, Armando; Dive, Vincent; Stura, Enrico Adriano

2013-06-01

Homodimerization is important in signal transduction and can play a crucial role in many other biological systems. To obtaining structural information for the design of molecules able to control the signalization pathways, the proteins involved will have to be crystallized in complex with ligands that induce dimerization. Bi-functional drugs have been generated by linking two ligands together chemically and the relative crystallizability of complexes with mono-functional and bi-functional ligands has been evaluated. There are problems associated with crystallization with such ligands, but overall, the advantages appear to be greater than the drawbacks. The study involves two matrix metalloproteinases, MMP-12 and MMP-9. Using flexible and rigid linkers we show that it is possible to control the crystal packing and that by changing the ligand-enzyme stoichiometric ratio, one can toggle between having one bi-functional ligand binding to two enzymes and having the same ligand bound to each enzyme. The nature of linker and its point of attachment on the ligand can be varied to aid crystallization, and such variations can also provide valuable structural information about the interactions made by the linker with the protein. We report here the crystallization and structure determination of seven ligand-dimerized complexes. These results suggest that the use of bi-functional drugs can be extended beyond the realm of protein dimerization to include all drug design projects. Copyright © 2013 Elsevier Inc. All rights reserved.

Chronic dietary supplementation with soy protein improves muscle function in rats.

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Ramzi J Khairallah

Full Text Available Athletes as well as elderly or hospitalized patients use dietary protein supplementation to maintain or grow skeletal muscle. It is recognized that high quality protein is needed for muscle accretion, and can be obtained from both animal and plant-based sources. There is interest to understand whether these sources differ in their ability to maintain or stimulate muscle growth and function. In this study, baseline muscle performance was assessed in 50 adult Sprague-Dawley rats after which they were assigned to one of five semi-purified "Western" diets (n = 10/group differing only in protein source, namely 19 kcal% protein from either milk protein isolate (MPI, whey protein isolate (WPI, soy protein isolate (SPI, soy protein concentrate (SPC or enzyme-treated soy protein (SPE. The diets were fed for 8 weeks at which point muscle performance testing was repeated and tissues were collected for analysis. There was no significant difference in food consumption or body weights over time between the diet groups nor were there differences in terminal organ and muscle weights or in serum lipids, creatinine or myostatin. Compared with MPI-fed rats, rats fed WPI and SPC displayed a greater maximum rate of contraction using the in vivo measure of muscle performance (p<0.05 with increases ranging from 13.3-27.5% and 22.8-29.5%, respectively at 60, 80, 100 and 150 Hz. When the maximum force was normalized to body weight, SPC-fed rats displayed increased force compared to MPI (p<0.05, whereas when normalized to gastrocnemius weight, WPI-fed rats displayed increased force compared to MPI (p<0.05. There was no difference between groups using in situ muscle performance. In conclusion, soy protein consumption, in high-fat diet, resulted in muscle function comparable to whey protein and improved compared to milk protein. The benefits seen with soy or whey protein were independent of changes in muscle mass or fiber cross-sectional area.

Molecular design and nanoparticle-mediated intracellular delivery of functional proteins to target cellular pathways

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Shah, Dhiral Ashwin

functional proteins can be delivered intracellularly in vitro using nanoparticles and used to target key signaling proteins and regulate cell signaling pathways. The same concept of naturally occurring protein-protein interactions can also be implemented to selectively bring intracellular protein targets in close proximity to proteasomal degradation machinery in cells and effect their depletion from the cellular compartments. This approach will be able to not only target entire pool of proteins to ubiquitination-mediated degradation, but also to specific sub-pools of posttranslationally modified proteins in the cell, provided peptides having distinct binding affinities are identified for posttranslational modifications. This system can then be tested for intracellular protein delivery using nanoparticle carriers to identify roles of different posttranslational modifications on the protein's activity. In future work, we propose to develop a cellular detection system, based on GFP complementation, which can be used to evaluate the efficiency of different protein delivery carriers to internalize proteins into the cell cytosol. We envision the application of nanoscale materials as intracellular protein delivery vehicles to target diverse cell signaling pathways at the posttranslational level, and subsequent metabolic manipulation, which may have interesting therapeutic properties and can potentially target stem cell fate.

Post-translational processing targets functionally diverse proteins in Mycoplasma hyopneumoniae.

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Tacchi, Jessica L; Raymond, Benjamin B A; Haynes, Paul A; Berry, Iain J; Widjaja, Michael; Bogema, Daniel R; Woolley, Lauren K; Jenkins, Cheryl; Minion, F Chris; Padula, Matthew P; Djordjevic, Steven P

2016-02-01

Mycoplasma hyopneumoniae is a genome-reduced, cell wall-less, bacterial pathogen with a predicted coding capacity of less than 700 proteins and is one of the smallest self-replicating pathogens. The cell surface of M. hyopneumoniae is extensively modified by processing events that target the P97 and P102 adhesin families. Here, we present analyses of the proteome of M. hyopneumoniae-type strain J using protein-centric approaches (one- and two-dimensional GeLC-MS/MS) that enabled us to focus on global processing events in this species. While these approaches only identified 52% of the predicted proteome (347 proteins), our analyses identified 35 surface-associated proteins with widely divergent functions that were targets of unusual endoproteolytic processing events, including cell adhesins, lipoproteins and proteins with canonical functions in the cytosol that moonlight on the cell surface. Affinity chromatography assays that separately used heparin, fibronectin, actin and host epithelial cell surface proteins as bait recovered cleavage products derived from these processed proteins, suggesting these fragments interact directly with the bait proteins and display previously unrecognized adhesive functions. We hypothesize that protein processing is underestimated as a post-translational modification in genome-reduced bacteria and prokaryotes more broadly, and represents an important mechanism for creating cell surface protein diversity. © 2016 The Authors.

Role of AAA(+)-proteins in peroxisome biogenesis and function.

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Grimm, Immanuel; Erdmann, Ralf; Girzalsky, Wolfgang

2016-05-01

Mutations in the PEX1 gene, which encodes a protein required for peroxisome biogenesis, are the most common cause of the Zellweger spectrum diseases. The recognition that Pex1p shares a conserved ATP-binding domain with p97 and NSF led to the discovery of the extended family of AAA+-type ATPases. So far, four AAA+-type ATPases are related to peroxisome function. Pex6p functions together with Pex1p in peroxisome biogenesis, ATAD1/Msp1p plays a role in membrane protein targeting and a member of the Lon-family of proteases is associated with peroxisomal quality control. This review summarizes the current knowledge on the AAA+-proteins involved in peroxisome biogenesis and function.

A sight on protein-based nanoparticles as drug/gene delivery systems.

Science.gov (United States)

Salatin, Sara; Jelvehgari, Mitra; Maleki-Dizaj, Solmaz; Adibkia, Khosro

2015-01-01

Polymeric nanomaterials have extensively been applied for the preparation of targeted and controlled release drug/gene delivery systems. However, problems involved in the formulation of synthetic polymers such as using of the toxic solvents and surfactants have limited their desirable applications. In this regard, natural biomolecules including proteins and polysaccharide are suitable alternatives due to their safety. According to literature, protein-based nanoparticles possess many advantages for drug and gene delivery such as biocompatibility, biodegradability and ability to functionalize with targeting ligands. This review provides a general sight on the application of biodegradable protein-based nanoparticles in drug/gene delivery based on their origins. Their unique physicochemical properties that help them to be formulated as pharmaceutical carriers are also discussed.

Protein loop modeling using a new hybrid energy function and its application to modeling in inaccurate structural environments.

Directory of Open Access Journals (Sweden)

Hahnbeom Park

Full Text Available Protein loop modeling is a tool for predicting protein local structures of particular interest, providing opportunities for applications involving protein structure prediction and de novo protein design. Until recently, the majority of loop modeling methods have been developed and tested by reconstructing loops in frameworks of experimentally resolved structures. In many practical applications, however, the protein loops to be modeled are located in inaccurate structural environments. These include loops in model structures, low-resolution experimental structures, or experimental structures of different functional forms. Accordingly, discrepancies in the accuracy of the structural environment assumed in development of the method and that in practical applications present additional challenges to modern loop modeling methods. This study demonstrates a new strategy for employing a hybrid energy function combining physics-based and knowledge-based components to help tackle this challenge. The hybrid energy function is designed to combine the strengths of each energy component, simultaneously maintaining accurate loop structure prediction in a high-resolution framework structure and tolerating minor environmental errors in low-resolution structures. A loop modeling method based on global optimization of this new energy function is tested on loop targets situated in different levels of environmental errors, ranging from experimental structures to structures perturbed in backbone as well as side chains and template-based model structures. The new method performs comparably to force field-based approaches in loop reconstruction in crystal structures and better in loop prediction in inaccurate framework structures. This result suggests that higher-accuracy predictions would be possible for a broader range of applications. The web server for this method is available at http://galaxy.seoklab.org/loop with the PS2 option for the scoring function.

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.

Stringent homology-based prediction of H. sapiens-M. tuberculosis H37Rv protein-protein interactions.

Science.gov (United States)

Zhou, Hufeng; Gao, Shangzhi; Nguyen, Nam Ninh; Fan, Mengyuan; Jin, Jingjing; Liu, Bing; Zhao, Liang; Xiong, Geng; Tan, Min; Li, Shijun; Wong, Limsoon

2014-04-08

H. sapiens-M. tuberculosis H37Rv protein-protein interaction (PPI) data are essential for understanding the infection mechanism of the formidable pathogen M. tuberculosis H37Rv. Computational prediction is an important strategy to fill the gap in experimental H. sapiens-M. tuberculosis H37Rv PPI data. Homology-based prediction is frequently used in predicting both intra-species and inter-species PPIs. However, some limitations are not properly resolved in several published works that predict eukaryote-prokaryote inter-species PPIs using intra-species template PPIs. We develop a stringent homology-based prediction approach by taking into account (i) differences between eukaryotic and prokaryotic proteins and (ii) differences between inter-species and intra-species PPI interfaces. We compare our stringent homology-based approach to a conventional homology-based approach for predicting host-pathogen PPIs, based on cellular compartment distribution analysis, disease gene list enrichment analysis, pathway enrichment analysis and functional category enrichment analysis. These analyses support the validity of our prediction result, and clearly show that our approach has better performance in predicting H. sapiens-M. tuberculosis H37Rv PPIs. Using our stringent homology-based approach, we have predicted a set of highly plausible H. sapiens-M. tuberculosis H37Rv PPIs which might be useful for many of related studies. Based on our analysis of the H. sapiens-M. tuberculosis H37Rv PPI network predicted by our stringent homology-based approach, we have discovered several interesting properties which are reported here for the first time. We find that both host proteins and pathogen proteins involved in the host-pathogen PPIs tend to be hubs in their own intra-species PPI network. Also, both host and pathogen proteins involved in host-pathogen PPIs tend to have longer primary sequence, tend to have more domains, tend to be more hydrophilic, etc. And the protein domains from both

A sequence-based dynamic ensemble learning system for protein ligand-binding site prediction

KAUST Repository

Chen, Peng

2015-12-03

Background: Proteins have the fundamental ability to selectively bind to other molecules and perform specific functions through such interactions, such as protein-ligand binding. Accurate prediction of protein residues that physically bind to ligands is important for drug design and protein docking studies. Most of the successful protein-ligand binding predictions were based on known structures. However, structural information is not largely available in practice due to the huge gap between the number of known protein sequences and that of experimentally solved structures

A sequence-based dynamic ensemble learning system for protein ligand-binding site prediction

KAUST Repository

Chen, Peng; Hu, ShanShan; Zhang, Jun; Gao, Xin; Li, Jinyan; Xia, Junfeng; Wang, Bing

2015-01-01

Background: Proteins have the fundamental ability to selectively bind to other molecules and perform specific functions through such interactions, such as protein-ligand binding. Accurate prediction of protein residues that physically bind to ligands is important for drug design and protein docking studies. Most of the successful protein-ligand binding predictions were based on known structures. However, structural information is not largely available in practice due to the huge gap between the number of known protein sequences and that of experimentally solved structures

JAFA: a protein function annotation meta-server

DEFF Research Database (Denmark)

Friedberg, Iddo; Harder, Tim; Godzik, Adam

2006-01-01

Annotations, or JAFA server. JAFA queries several function prediction servers with a protein sequence and assembles the returned predictions in a legible, non-redundant format. In this manner, JAFA combines the predictions of several servers to provide a comprehensive view of what are the predicted functions...

Sub-grouping and sub-functionalization of the RIFIN multi-copy protein family

Directory of Open Access Journals (Sweden)

Sonnhammer Erik L

2008-01-01

Full Text Available Abstract Background Parasitic protozoans possess many multicopy gene families which have central roles in parasite survival and virulence. The number and variability of members of these gene families often make it difficult to predict possible functions of the encoded proteins. The families of extra-cellular proteins that are exposed to a host immune response have been driven via immune selection to become antigenically variant, and thereby avoid immune recognition while maintaining protein function to establish a chronic infection. Results We have combined phylogenetic and function shift analyses to study the evolution of the RIFIN proteins, which are antigenically variant and are encoded by the largest multicopy gene family in Plasmodium falciparum. We show that this family can be subdivided into two major groups that we named A- and B-RIFIN proteins. This suggested sub-grouping is supported by a recently published study that showed that, despite the presence of the Plasmodium export (PEXEL motif in all RIFIN variants, proteins from each group have different cellular localizations during the intraerythrocytic life cycle of the parasite. In the present study we show that function shift analysis, a novel technique to predict functional divergence between sub-groups of a protein family, indicates that RIFINs have undergone neo- or sub-functionalization. Conclusion These results question the general trend of clustering large antigenically variant protein groups into homogenous families. Assigning functions to protein families requires their subdivision into meaningful groups such as we have shown for the RIFIN protein family. Using phylogenetic and function shift analysis methods, we identify new directions for the investigation of this broad and complex group of proteins.

Refinement of protein termini in template-based modeling using conformational space annealing.

Science.gov (United States)

Park, Hahnbeom; Ko, Junsu; Joo, Keehyoung; Lee, Julian; Seok, Chaok; Lee, Jooyoung

2011-09-01

The rapid increase in the number of experimentally determined protein structures in recent years enables us to obtain more reliable protein tertiary structure models than ever by template-based modeling. However, refinement of template-based models beyond the limit available from the best templates is still needed for understanding protein function in atomic detail. In this work, we develop a new method for protein terminus modeling that can be applied to refinement of models with unreliable terminus structures. The energy function for terminus modeling consists of both physics-based and knowledge-based potential terms with carefully optimized relative weights. Effective sampling of both the framework and terminus is performed using the conformational space annealing technique. This method has been tested on a set of termini derived from a nonredundant structure database and two sets of termini from the CASP8 targets. The performance of the terminus modeling method is significantly improved over our previous method that does not employ terminus refinement. It is also comparable or superior to the best server methods tested in CASP8. The success of the current approach suggests that similar strategy may be applied to other types of refinement problems such as loop modeling or secondary structure rearrangement. Copyright © 2011 Wiley-Liss, Inc.

Designing sequence to control protein function in an EF-hand protein.

Science.gov (United States)

Bunick, Christopher G; Nelson, Melanie R; Mangahas, Sheryll; Hunter, Michael J; Sheehan, Jonathan H; Mizoue, Laura S; Bunick, Gerard J; Chazin, Walter J

2004-05-19

The extent of conformational change that calcium binding induces in EF-hand proteins is a key biochemical property specifying Ca(2+) sensor versus signal modulator function. To understand how differences in amino acid sequence lead to differences in the response to Ca(2+) binding, comparative analyses of sequence and structures, combined with model building, were used to develop hypotheses about which amino acid residues control Ca(2+)-induced conformational changes. These results were used to generate a first design of calbindomodulin (CBM-1), a calbindin D(9k) re-engineered with 15 mutations to respond to Ca(2+) binding with a conformational change similar to that of calmodulin. The gene for CBM-1 was synthesized, and the protein was expressed and purified. Remarkably, this protein did not exhibit any non-native-like molten globule properties despite the large number of mutations and the nonconservative nature of some of them. Ca(2+)-induced changes in CD intensity and in the binding of the hydrophobic probe, ANS, implied that CBM-1 does undergo Ca(2+) sensorlike conformational changes. The X-ray crystal structure of Ca(2+)-CBM-1 determined at 1.44 A resolution reveals the anticipated increase in hydrophobic surface area relative to the wild-type protein. A nascent calmodulin-like hydrophobic docking surface was also found, though it is occluded by the inter-EF-hand loop. The results from this first calbindomodulin design are discussed in terms of progress toward understanding the relationships between amino acid sequence, protein structure, and protein function for EF-hand CaBPs, as well as the additional mutations for the next CBM design.

CHAPTER 9 : Virus-based systems for functional materials

NARCIS (Netherlands)

Verwegen, Martijn; Cornelissen, Jeroen J.L.M.; Boker, Alexander; van Rijn, Patrick

2015-01-01

Virus-based bionanotechnology holds the promise of control over the structure, properties and functionality of materials at the nanometre scale. After all, viruses, and by extension virus-like particles (VLPs), represent some of the largest hierarchical protein constructs found in Nature. Their

Structural and Function Prediction of Musa acuminata subsp. Malaccensis Protein

Directory of Open Access Journals (Sweden)

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.

Functional characterization of Arabidopsis thaliana transthyretin-like protein.

Science.gov (United States)

Pessoa, João; Sárkány, Zsuzsa; Ferreira-da-Silva, Frederico; Martins, Sónia; Almeida, Maria R; Li, Jianming; Damas, Ana M

2010-02-18

Arabidopsis thaliana transthyretin-like (TTL) protein is a potential substrate in the brassinosteroid signalling cascade, having a role that moderates plant growth. Moreover, sequence homology revealed two sequence domains similar to 2-oxo-4-hydroxy-4-carboxy-5-ureidoimidazoline (OHCU) decarboxylase (N-terminal domain) and 5-hydroxyisourate (5-HIU) hydrolase (C-terminal domain). TTL is a member of the transthyretin-related protein family (TRP), which comprises a number of proteins with sequence homology to transthyretin (TTR) and the characteristic C-terminal sequence motif Tyr-Arg-Gly-Ser. TRPs are single domain proteins that form tetrameric structures with 5-HIU hydrolase activity. Experimental evidence is fundamental for knowing if TTL is a tetrameric protein, formed by the association of the 5-HIU hydrolase domains and, in this case, if the structural arrangement allows for OHCU decarboxylase activity. This work reports about the biochemical and functional characterization of TTL. The TTL gene was cloned and the protein expressed and purified for biochemical and functional characterization. The results show that TTL is composed of four subunits, with a moderately elongated shape. We also found evidence for 5-HIU hydrolase and OHCU decarboxylase activities in vitro, in the full-length protein. The Arabidopsis thaliana transthyretin-like (TTL) protein is a tetrameric bifunctional enzyme, since it has 5-HIU hydrolase and OHCU decarboxylase activities, which were simultaneously observed in vitro.

Direct Capture of Functional Proteins from Mammalian Plasma Membranes into Nanodiscs.

Science.gov (United States)

Roy, Jahnabi; Pondenis, Holly; Fan, Timothy M; Das, Aditi

2015-10-20

Mammalian plasma membrane proteins make up the largest class of drug targets yet are difficult to study in a cell free system because of their intransigent nature. Herein, we perform direct encapsulation of plasma membrane proteins derived from mammalian cells into a functional nanodisc library. Peptide fingerprinting was used to analyze the proteome of the incorporated proteins in nanodiscs and to further demonstrate that the lipid composition of the nanodiscs directly affects the class of protein that is incorporated. Furthermore, the functionality of the incorporated membrane proteome was evaluated by measuring the activity of membrane proteins: Na(+)/K(+)-ATPase and receptor tyrosine kinases. This work is the first report of the successful establishment and characterization of a cell free functional library of mammalian membrane proteins into nanodiscs.

Functional classification of protein structures by local structure matching in graph representation.

Science.gov (United States)

Mills, Caitlyn L; Garg, Rohan; Lee, Joslynn S; Tian, Liang; Suciu, Alexandru; Cooperman, Gene; Beuning, Penny J; Ondrechen, Mary Jo

2018-03-31

As a result of high-throughput protein structure initiatives, over 14,400 protein structures have been solved by structural genomics (SG) centers and participating research groups. While the totality of SG data represents a tremendous contribution to genomics and structural biology, reliable functional information for these proteins is generally lacking. Better functional predictions for SG proteins will add substantial value to the structural information already obtained. Our method described herein, Graph Representation of Active Sites for Prediction of Function (GRASP-Func), predicts quickly and accurately the biochemical function of proteins by representing residues at the predicted local active site as graphs rather than in Cartesian coordinates. We compare the GRASP-Func method to our previously reported method, structurally aligned local sites of activity (SALSA), using the ribulose phosphate binding barrel (RPBB), 6-hairpin glycosidase (6-HG), and Concanavalin A-like Lectins/Glucanase (CAL/G) superfamilies as test cases. In each of the superfamilies, SALSA and the much faster method GRASP-Func yield similar correct classification of previously characterized proteins, providing a validated benchmark for the new method. In addition, we analyzed SG proteins using our SALSA and GRASP-Func methods to predict function. Forty-one SG proteins in the RPBB superfamily, nine SG proteins in the 6-HG superfamily, and one SG protein in the CAL/G superfamily were successfully classified into one of the functional families in their respective superfamily by both methods. This improved, faster, validated computational method can yield more reliable predictions of function that can be used for a wide variety of applications by the community. © 2018 The Authors Protein Science published by Wiley Periodicals, Inc. on behalf of The Protein Society.

Traceless affinity labeling of endogenous proteins for functional analysis in living cells.

Science.gov (United States)

Hayashi, Takahiro; Hamachi, Itaru

2012-09-18

Protein labeling and imaging techniques have provided tremendous opportunities to study the structure, function, dynamics, and localization of individual proteins in the complex environment of living cells. Molecular biology-based approaches, such as GFP-fusion tags and monoclonal antibodies, have served as important tools for the visualization of individual proteins in cells. Although these techniques continue to be valuable for live cell imaging, they have a number of limitations that have only been addressed by recent progress in chemistry-based approaches. These chemical approaches benefit greatly from the smaller probe sizes that should result in fewer perturbations to proteins and to biological systems as a whole. Despite the research in this area, so far none of these labeling techniques permit labeling and imaging of selected endogenous proteins in living cells. Researchers have widely used affinity labeling, in which the protein of interest is labeled by a reactive group attached to a ligand, to identify and characterize proteins. Since the first report of affinity labeling in the early 1960s, efforts to fine-tune the chemical structures of both the reactive group and ligand have led to protein labeling with excellent target selectivity in the whole proteome of living cells. Although the chemical probes used for affinity labeling generally inactivate target proteins, this strategy holds promise as a valuable tool for the labeling and imaging of endogenous proteins in living cells and by extension in living animals. In this Account, we summarize traceless affinity labeling, a technique explored mainly in our laboratory. In our overview of the different labeling techniques, we emphasize the challenge of designing chemical probes that allow for dissociation of the affinity module (often a ligand) after the labeling reaction so that the labeled protein retains its native function. This feature distinguishes the traceless labeling approach from the traditional

SM30 protein function during sea urchin larval spicule formation.

Science.gov (United States)

Wilt, Fred; Killian, Christopher E; Croker, Lindsay; Hamilton, Patricia

2013-08-01

A central issue in better understanding the process of biomineralization is to elucidate the function of occluded matrix proteins present in mineralized tissues. A potent approach to addressing this issue utilizes specific inhibitors of expression of known genes. Application of antisense oligonucleotides that specifically suppress translation of a given mRNA are capable of causing aberrant biomineralization, thereby revealing, at least in part, a likely function of the protein and gene under investigation. We have applied this approach to study the possible function(s) of the SM30 family of proteins, which are found in spicules, teeth, spines, and tests of Strongylocentrotus purpuratus as well as other euechinoid sea urchins. It is possible using the anti-SM30 morpholino-oligonucleotides (MO's) to reduce the level of these proteins to very low levels, yet the development of skeletal spicules in the embryo shows little or no aberration. This surprising result requires re-thinking about the role of these, and possibly other occluded matrix proteins. Copyright © 2013 Elsevier Inc. All rights reserved.

Physicochemical and functional properties of protein concentrate from by-product of coconut processing.

Science.gov (United States)

Rodsamran, Pattrathip; Sothornvit, Rungsinee

2018-02-15

Coconut cake, a by-product from milk and oil extractions, contains a high amount of protein. Protein extraction from coconut milk cake and coconut oil cake was investigated. The supernatant and precipitate protein powders from both coconut milk and oil cakes were compared based on their physicochemical and functional properties. Glutelin was the predominant protein fraction in both coconut cakes. Protein powders from milk cake presented higher water and oil absorption capacities than those from oil cake. Both protein powders from oil cake exhibited better foaming capacity and a better emulsifying activity index than those from milk cake. Coconut proteins were mostly solubilized in strong acidic and alkaline solutions. Minimum solubility was observed at pH 4, confirming the isoelectric point of coconut protein. Therefore, the coconut residues after extractions might be a potential alternative renewable plant protein source to use asa food ingredient to enhance food nutrition and quality. Copyright © 2017 Elsevier Ltd. All rights reserved.

Conformationally Preorganized Diastereomeric Norbornane-Based Maltosides for Membrane Protein Study

DEFF Research Database (Denmark)

Das, Manabendra; Du, Yang; Ribeiro, Orquidea

2017-01-01

were generally better at stabilizing membrane proteins than short alkyl chain agents. Furthermore, use of one well-behaving NBM enabled us to attain a marked stabilization and clear visualization of a challenging membrane protein complex using electron microscopy. Thus, this study not only describes......Detergents are essential tools for functional and structural studies of membrane proteins. However, conventional detergents are limited in their scope and utility, particularly for eukaryotic membrane proteins. Thus, there are major efforts to develop new amphipathic agents with enhanced properties....... Here, a novel class of diastereomeric agents with a preorganized conformation, designated norbornane-based maltosides (NBMs), were prepared and evaluated for their ability to solubilize and stabilize membrane proteins. Representative NBMs displayed enhanced behaviors compared to n...

A Protein-Based Ferritin Bio-Nanobattery

Directory of Open Access Journals (Sweden)

Gerald D. Watt

2012-01-01

Full Text Available Nanostructured materials are increasingly important for the construction of electrochemical energy storage devices that will meet the needs of portable nanodevices. Here we describe the development of a nanoenergy storage system based on inorganic mineral phases contained in ferritin proteins. The electrochemical cell consists of an anode containing ~2000 iron atoms as Fe(OH2 in the hollow protein interior of ferritin and a cathode containing ~2000 of Co(OH3 in a separate ferritin molecule. The achieved initial voltage output from a combination of Fe2+- and Co3+-ferritins adsorbed on gold electrodes was ~500 mV, while a combination of Fe2+- and Co3+-ferritins immobilized on gold produced a voltage of 350–405 mV. When fully discharged, Fe(OH3 and Co(OH2 are the products of a single electron transfer per metal atom from anode to cathode. The spent components can be regenerated by chemical or electrochemical methods restoring battery function. The properties of ferritins are presented and their unique characteristics are described, which have led to the development of a functional bio-nanobattery.

Radiation effects on viscosimetry of protein based solutions

International Nuclear Information System (INIS)

Sabato, S.F.; Lacroix, M.

2002-01-01

Due to their good functional properties allied to their excellent nutritional value, milk protein isolates and soy protein concentrates have gained a crescent interest. These proteins could have their structural properties improved when some treatments are applied, such as gamma irradiation, alone or in presence of other compounds, as a plasticizer. In this work, solutions of those proteins were mixed with a generally recognized as safe plasticizer, glycerol. These mixtures (8% protein (w/v) base) at two ratios 1:1 and 2:1 (protein:glycerol) were submitted to a gamma irradiation treatment ( 60 Co), at doses 0, 5, 15 and 25 kGy, and their rheological performance was studied. As irradiation dose increased viscosity measurements decayed significantly (p<0.05) for mixture soy/glycerol and calcium caseinate/glycerol. The mixture sodium caseinate/glycerol showed a trend to form aggregation of macromolecules with dose of 5 kGy, while the apparent viscosity for dispersions containing whey/glycerol remained almost constant as irradiation dose increases. In the case of soy protein isolate and sodium caseinate, a mixture of 2:1 showed a significant higher viscosity (p<0.05) than a mixture of 1:1

Radiation effects on viscosimetry of protein based solutions

Energy Technology Data Exchange (ETDEWEB)

Sabato, S.F.; Lacroix, M. E-mail: monique.lacroix@inrs-iaf.uquebec.ca

2002-03-01

Due to their good functional properties allied to their excellent nutritional value, milk protein isolates and soy protein concentrates have gained a crescent interest. These proteins could have their structural properties improved when some treatments are applied, such as gamma irradiation, alone or in presence of other compounds, as a plasticizer. In this work, solutions of those proteins were mixed with a generally recognized as safe plasticizer, glycerol. These mixtures (8% protein (w/v) base) at two ratios 1:1 and 2:1 (protein:glycerol) were submitted to a gamma irradiation treatment ({sup 60}Co), at doses 0, 5, 15 and 25 kGy, and their rheological performance was studied. As irradiation dose increased viscosity measurements decayed significantly (p<0.05) for mixture soy/glycerol and calcium caseinate/glycerol. The mixture sodium caseinate/glycerol showed a trend to form aggregation of macromolecules with dose of 5 kGy, while the apparent viscosity for dispersions containing whey/glycerol remained almost constant as irradiation dose increases. In the case of soy protein isolate and sodium caseinate, a mixture of 2:1 showed a significant higher viscosity (p<0.05) than a mixture of 1:1.

An Atlas of Peroxiredoxins Created Using an Active Site Profile-Based Approach to Functionally Relevant Clustering of Proteins.

Directory of Open Access Journals (Sweden)

Angela F Harper

2017-02-01

Full Text Available Peroxiredoxins (Prxs or Prdxs are a large protein superfamily of antioxidant enzymes that rapidly detoxify damaging peroxides and/or affect signal transduction and, thus, have roles in proliferation, differentiation, and apoptosis. Prx superfamily members are widespread across phylogeny and multiple methods have been developed to classify them. Here we present an updated atlas of the Prx superfamily identified using a novel method called MISST (Multi-level Iterative Sequence Searching Technique. MISST is an iterative search process developed to be both agglomerative, to add sequences containing similar functional site features, and divisive, to split groups when functional site features suggest distinct functionally-relevant clusters. Superfamily members need not be identified initially-MISST begins with a minimal representative set of known structures and searches GenBank iteratively. Further, the method's novelty lies in the manner in which isofunctional groups are selected; rather than use a single or shifting threshold to identify clusters, the groups are deemed isofunctional when they pass a self-identification criterion, such that the group identifies itself and nothing else in a search of GenBank. The method was preliminarily validated on the Prxs, as the Prxs presented challenges of both agglomeration and division. For example, previous sequence analysis clustered the Prx functional families Prx1 and Prx6 into one group. Subsequent expert analysis clearly identified Prx6 as a distinct functionally relevant group. The MISST process distinguishes these two closely related, though functionally distinct, families. Through MISST search iterations, over 38,000 Prx sequences were identified, which the method divided into six isofunctional clusters, consistent with previous expert analysis. The results represent the most complete computational functional analysis of proteins comprising the Prx superfamily. The feasibility of this novel method is

Phospholipid liposomes functionalized by protein

Science.gov (United States)

Glukhova, O. E.; Savostyanov, G. V.; Grishina, O. A.

2015-03-01

Finding new ways to deliver neurotrophic drugs to the brain in newborns is one of the contemporary problems of medicine and pharmaceutical industry. Modern researches in this field indicate the promising prospects of supramolecular transport systems for targeted drug delivery to the brain which can overcome the blood-brain barrier (BBB). Thus, the solution of this problem is actual not only for medicine, but also for society as a whole because it determines the health of future generations. Phospholipid liposomes due to combination of lipo- and hydrophilic properties are considered as the main future objects in medicine for drug delivery through the BBB as well as increasing their bioavailability and toxicity. Liposomes functionalized by various proteins were used as transport systems for ease of liposomes use. Designing of modification oligosaccharide of liposomes surface is promising in the last decade because it enables the delivery of liposomes to specific receptor of human cells by selecting ligand and it is widely used in pharmacology for the treatment of several diseases. The purpose of this work is creation of a coarse-grained model of bilayer of phospholipid liposomes, functionalized by specific to the structural elements of the BBB proteins, as well as prediction of the most favorable orientation and position of the molecules in the generated complex by methods of molecular docking for the formation of the structure. Investigation of activity of the ligand molecule to protein receptor of human cells by the methods of molecular dynamics was carried out.

Protein domain recurrence and order can enhance prediction of protein functions

KAUST Repository

Abdel Messih, Mario A.; Chitale, Meghana; Bajic, Vladimir B.; Kihara, Daisuke; Gao, Xin

2012-01-01

Motivation: Burgeoning sequencing technologies have generated massive amounts of genomic and proteomic data. Annotating the functions of proteins identified in this data has become a big and crucial problem. Various computational methods have been

Jatropha seed protein functional properties for technical applications

NARCIS (Netherlands)

Lestari, D.; Mulder, W.J.; Sanders, J.P.M.

2011-01-01

Jatropha press cake, by-product after oil expression from Jatropha seeds, contains 24–28% protein on dry basis. Objectives of this research were to investigate functional properties, such as solubility, emulsifying, foaming, film forming, and adhesive properties, of Jatropha press cake proteins and

Protections of bovine serum albumin protein from damage on functionalized graphene-based electrodes by flavonoids

Energy Technology Data Exchange (ETDEWEB)

Sun, Bolu [School of Pharmacy, Lanzhou University, Lanzhou 730000 (China); Gou, Yuqiang [Lanzhou Military Command Center for Disease Prevention and Control, Lanzhou 730000 (China); Xue, Zhiyuan; Zheng, Xiaoping; Ma, Yuling [School of Pharmacy, Lanzhou University, Lanzhou 730000 (China); Hu, Fangdi, E-mail: hufd@lzu.edu.cn [School of Pharmacy, Lanzhou University, Lanzhou 730000 (China); Zhao, Wanghong, E-mail: wanghongzhao@sina.com [Department of Stomatology, Nanfang Hospital, Southern Medical University, Guangzhou 51515 (China)

2016-05-01

A sensitive electrochemical sensor based on bovine serum albumin (BSA)/poly (diallyldimethylammonium chloride) (PDDA) functionalized graphene nanosheets (PDDA-G) composite film modified glassy carbon electrode (BSA/PDDA-G/GCE) had been developed to investigate the oxidative protein damage and protections of protein from damage by flavonoids. The performance of this sensor was remarkably improved due to excellent electrical conductivity, strong adsorptive ability, and large effective surface area of PDDA-G. The BSA/PDDA-G/GCE displayed the greatest degree of BSA oxidation damage at 40 min incubation time and in the pH 5.0 Fenton reagent system (12.5 mM FeSO{sub 4}, 50 mM H{sub 2}O{sub 2}). The antioxidant activities of four flavonoids had been compared by fabricated sensor based on the relative peak current ratio of SWV, because flavonoids prevented BSA damage caused by Fenton reagent and affected the BSA signal in a solution containing Co(bpy){sub 3}{sup 3+}. The sensor was characterized by cyclic voltammetry (CV), electrochemical impedance spectroscopy (EIS), and scanning electron microscopy (SEM). UV–vis spectrophotometry and FTIR were also used to investigate the generation of hydroxyl radical and BSA damage, respectively. On the basis of results from electrochemical methods, the order of the antioxidant activities of flavonoids is as follows: (+)-catechin > kaempferol > apigenin > naringenin. A novel, direct SWV analytical method for detection of BSA damage and assessment of the antioxidant activities of four flavonoids was developed and this electrochemical method provided a simple, inexpensive and rapid detection of BSA damage and evaluation of the antioxidant activities of samples. - Highlights: • Hydroxyl radicals were produced by Fenton reagents. • An electrochemical bovine serum albumin (BSA) damage sensor was successfully fabricated. • The proposed biosensor can assess the antioxidant capacity of four flavonoids. • The order of antioxidant

Protections of bovine serum albumin protein from damage on functionalized graphene-based electrodes by flavonoids

International Nuclear Information System (INIS)

Sun, Bolu; Gou, Yuqiang; Xue, Zhiyuan; Zheng, Xiaoping; Ma, Yuling; Hu, Fangdi; Zhao, Wanghong

2016-01-01

A sensitive electrochemical sensor based on bovine serum albumin (BSA)/poly (diallyldimethylammonium chloride) (PDDA) functionalized graphene nanosheets (PDDA-G) composite film modified glassy carbon electrode (BSA/PDDA-G/GCE) had been developed to investigate the oxidative protein damage and protections of protein from damage by flavonoids. The performance of this sensor was remarkably improved due to excellent electrical conductivity, strong adsorptive ability, and large effective surface area of PDDA-G. The BSA/PDDA-G/GCE displayed the greatest degree of BSA oxidation damage at 40 min incubation time and in the pH 5.0 Fenton reagent system (12.5 mM FeSO_4, 50 mM H_2O_2). The antioxidant activities of four flavonoids had been compared by fabricated sensor based on the relative peak current ratio of SWV, because flavonoids prevented BSA damage caused by Fenton reagent and affected the BSA signal in a solution containing Co(bpy)_3"3"+. The sensor was characterized by cyclic voltammetry (CV), electrochemical impedance spectroscopy (EIS), and scanning electron microscopy (SEM). UV–vis spectrophotometry and FTIR were also used to investigate the generation of hydroxyl radical and BSA damage, respectively. On the basis of results from electrochemical methods, the order of the antioxidant activities of flavonoids is as follows: (+)-catechin > kaempferol > apigenin > naringenin. A novel, direct SWV analytical method for detection of BSA damage and assessment of the antioxidant activities of four flavonoids was developed and this electrochemical method provided a simple, inexpensive and rapid detection of BSA damage and evaluation of the antioxidant activities of samples. - Highlights: • Hydroxyl radicals were produced by Fenton reagents. • An electrochemical bovine serum albumin (BSA) damage sensor was successfully fabricated. • The proposed biosensor can assess the antioxidant capacity of four flavonoids. • The order of antioxidant activities of flavonoids is

Soft Cysteine Signaling Network: The Functional Significance of Cysteine in Protein Function and the Soft Acids/Bases Thiol Chemistry That Facilitates Cysteine Modification.

Science.gov (United States)

Wible, Ryan S; Sutter, Thomas R

2017-03-20

The unique biophysical and electronic properties of cysteine make this molecule one of the most biologically critical amino acids in the proteome. The defining sulfur atom in cysteine is much larger than the oxygen and nitrogen atoms more commonly found in the other amino acids. As a result of its size, the valence electrons of sulfur are highly polarizable. Unique protein microenvironments favor the polarization of sulfur, thus increasing the overt reactivity of cysteine. Here, we provide a brief overview of the endogenous generation of reactive oxygen and electrophilic species and specific examples of enzymes and transcription factors in which the oxidation or covalent modification of cysteine in those proteins modulates their function. The perspective concludes with a discussion of cysteine chemistry and biophysics, the hard and soft acids and bases model, and the proposal of the Soft Cysteine Signaling Network: a hypothesis proposing the existence of a complex signaling network governed by layered chemical reactivity and cross-talk in which the chemical modification of reactive cysteine in biological networks triggers the reorganization of intracellular biochemistry to mitigate spikes in endogenous or exogenous oxidative or electrophilic stress.

Interactions Between Flavonoid-Rich Extracts and Sodium Caseinate Modulate Protein Functionality and Flavonoid Bioaccessibility in Model Food Systems.

Science.gov (United States)

Elegbede, Jennifer L; Li, Min; Jones, Owen G; Campanella, Osvaldo H; Ferruzzi, Mario G

2018-05-01

With growing interest in formulating new food products with added protein and flavonoid-rich ingredients for health benefits, direct interactions between these ingredient classes becomes critical in so much as they may impact protein functionality, product quality, and flavonoids bioavailability. In this study, sodium caseinate (SCN)-based model products (foams and emulsions) were formulated with grape seed extract (GSE, rich in galloylated flavonoids) and green tea extract (GTE, rich in nongalloylated flavonoids), respectively, to assess changes in functional properties of SCN and impacts on flavonoid bioaccessibility. Experiments with pure flavonoids suggested that galloylated flavonoids reduced air-water interfacial tension of 0.01% SCN dispersions more significantly than nongalloylated flavonoids at high concentrations (>50 μg/mL). This observation was supported by changes in stability of 5% SCN foam, which showed that foam stability was increased at high levels of GSE (≥50 μg/mL, P < 0.05) but was not affected by GTE. However, flavonoid extracts had modest effects on SCN emulsion. In addition, galloylated flavonoids had higher bioaccessibility in both SCN foam and emulsion. These results suggest that SCN-flavonoid binding interactions can modulate protein functionality leading to difference in performance and flavonoid bioaccessibility of protein-based products. As information on the beneficial health effects of flavonoids expands, it is likely that usage of these ingredients in consumer foods will increase. However, the necessary levels to provide such benefits may exceed those that begin to impact functionality of the macronutrients such as proteins. Flavonoid inclusion within protein matrices may modulate protein functionality in a food system and modify critical consumer traits or delivery of these beneficial plant-derived components. The product matrices utilized in this study offer relevant model systems to evaluate how fortification with flavonoid

RACK1, A Multifaceted Scaffolding Protein: Structure and Function

LENUS (Irish Health Repository)

Adams, David R

2011-10-06

Abstract The Receptor for Activated C Kinase 1 (RACK1) is a member of the tryptophan-aspartate repeat (WD-repeat) family of proteins and shares significant homology to the β subunit of G-proteins (Gβ). RACK1 adopts a seven-bladed β-propeller structure which facilitates protein binding. RACK1 has a significant role to play in shuttling proteins around the cell, anchoring proteins at particular locations and in stabilising protein activity. It interacts with the ribosomal machinery, with several cell surface receptors and with proteins in the nucleus. As a result, RACK1 is a key mediator of various pathways and contributes to numerous aspects of cellular function. Here, we discuss RACK1 gene and structure and its role in specific signaling pathways, and address how posttranslational modifications facilitate subcellular location and translocation of RACK1. This review condenses several recent studies suggesting a role for RACK1 in physiological processes such as development, cell migration, central nervous system (CN) function and circadian rhythm as well as reviewing the role of RACK1 in disease.

Functionalization of SU-8 photoresist surfaces with IgG proteins

International Nuclear Information System (INIS)

Blagoi, Gabriela; Keller, Stephan; Johansson, Alicia; Boisen, Anja; Dufva, Martin

2008-01-01

The negative epoxy-based photoresist SU-8 has a variety of applications within microelectromechanical systems (MEMS) and lab-on-a-chip systems. Here, several methods to functionalize SU-8 surfaces with IgG proteins were investigated. Fluorescent labeled proteins and fluorescent sandwich immunoassays were employed to characterize the binding efficiency of model proteins to bare SU-8 surface, SU-8 treated with cerium ammonium nitrate (CAN) etchant and CAN treated surfaces modified by aminosilanization. The highest binding capacity of antibodies was observed on bare SU-8. This explains why bare SU-8 in a functional fluorescent sandwich immunoassay detecting C-reactive protein (CRP) gave twice as high signal as compared with the other two surfaces. Immunoassays performed on bare SU-8 and CAN treated SU-8 resulted in detection limits of CRP of 30 and 80 ng/ml respectively which is sufficient for detecting CRP in clinical samples, where concentrations of 3-10 μg/ml are normal for healthy individuals. In conclusion, bare SU-8 and etched SU-8 can be modified with antibodies by a simple adsorption procedure which simplifies building lab-on-a-chip systems in SU-8. Additionally, we report the fabrication process and use of microwells created in a SU-8 layer with the same dimensions as a standard microscope glass slide that could fit into fluorescent scanners. The SU-8 microwells minimize the reagent consumption and are straightforward to handle compared to SU-8 coated microscope slides

Functional genomics in zebrafish permits rapid characterization of novel platelet membrane proteins.

Science.gov (United States)

O'Connor, Marie N; Salles, Isabelle I; Cvejic, Ana; Watkins, Nicholas A; Walker, Adam; Garner, Stephen F; Jones, Chris I; Macaulay, Iain C; Steward, Michael; Zwaginga, Jaap-Jan; Bray, Sarah L; Dudbridge, Frank; de Bono, Bernard; Goodall, Alison H; Deckmyn, Hans; Stemple, Derek L; Ouwehand, Willem H

2009-05-07

In this study, we demonstrate the suitability of the vertebrate Danio rerio (zebrafish) for functional screening of novel platelet genes in vivo by reverse genetics. Comparative transcript analysis of platelets and their precursor cell, the megakaryocyte, together with nucleated blood cell elements, endothelial cells, and erythroblasts, identified novel platelet membrane proteins with hitherto unknown roles in thrombus formation. We determined the phenotype induced by antisense morpholino oligonucleotide (MO)-based knockdown of 5 of these genes in a laser-induced arterial thrombosis model. To validate the model, the genes for platelet glycoprotein (GP) IIb and the coagulation protein factor VIII were targeted. MO-injected fish showed normal thrombus initiation but severely impaired thrombus growth, consistent with the mouse knockout phenotypes, and concomitant knockdown of both resulted in spontaneous bleeding. Knockdown of 4 of the 5 novel platelet proteins altered arterial thrombosis, as demonstrated by modified kinetics of thrombus initiation and/or development. We identified a putative role for BAMBI and LRRC32 in promotion and DCBLD2 and ESAM in inhibition of thrombus formation. We conclude that phenotypic analysis of MO-injected zebrafish is a fast and powerful method for initial screening of novel platelet proteins for function in thrombosis.

ROLE OF TYROSINE-SULFATED PROTEINS IN RETINAL STRUCTURE AND FUNCTION

Science.gov (United States)

Kanan, Y.; Al-Ubaidi, M.R.

2014-01-01

The extracellular matrix (ECM) plays a significant role in cellular and retinal health. The study of retinal tyrosine-sulfated proteins is an important first step toward understanding the role of ECM in retinal health and diseases. These secreted proteins are members of the retinal ECM. Tyrosine sulfation was shown to be necessary for the development of proper retinal structure and function. The importance of tyrosine sulfation is further demonstrated by the evolutionary presence of tyrosylprotein sulfotransferases, enzymes that catalyze proteins’ tyrosine sulfation, and the compensatory abilities of these enzymes. Research has identified four tyrosine-sulfated retinal proteins: fibulin 2, vitronectin, complement factor H (CFH), and opticin. Vitronectin and CFH regulate the activation of the complement system and are involved in the etiology of some cases of age-related macular degeneration. Analysis of the role of tyrosine sulfation in fibulin function showed that sulfation influences the protein's ability to regulate growth and migration. Although opticin was recently shown to exhibit anti-angiogenic properties, it is not yet determined what role sulfation plays in that function. Future studies focusing on identifying all of the tyrosine-sulfated retinal proteins would be instrumental in determining the impact of sulfation on retinal protein function in retinal homeostasis and diseases. PMID:25819460

Evaluation of several two-step scoring functions based on linear interaction energy, effective ligand size, and empirical pair potentials for prediction of protein-ligand binding geometry and free energy.

Science.gov (United States)

Rahaman, Obaidur; Estrada, Trilce P; Doren, Douglas J; Taufer, Michela; Brooks, Charles L; Armen, Roger S

2011-09-26

The performances of several two-step scoring approaches for molecular docking were assessed for their ability to predict binding geometries and free energies. Two new scoring functions designed for "step 2 discrimination" were proposed and compared to our CHARMM implementation of the linear interaction energy (LIE) approach using the Generalized-Born with Molecular Volume (GBMV) implicit solvation model. A scoring function S1 was proposed by considering only "interacting" ligand atoms as the "effective size" of the ligand and extended to an empirical regression-based pair potential S2. The S1 and S2 scoring schemes were trained and 5-fold cross-validated on a diverse set of 259 protein-ligand complexes from the Ligand Protein Database (LPDB). The regression-based parameters for S1 and S2 also demonstrated reasonable transferability in the CSARdock 2010 benchmark using a new data set (NRC HiQ) of diverse protein-ligand complexes. The ability of the scoring functions to accurately predict ligand geometry was evaluated by calculating the discriminative power (DP) of the scoring functions to identify native poses. The parameters for the LIE scoring function with the optimal discriminative power (DP) for geometry (step 1 discrimination) were found to be very similar to the best-fit parameters for binding free energy over a large number of protein-ligand complexes (step 2 discrimination). Reasonable performance of the scoring functions in enrichment of active compounds in four different protein target classes established that the parameters for S1 and S2 provided reasonable accuracy and transferability. Additional analysis was performed to definitively separate scoring function performance from molecular weight effects. This analysis included the prediction of ligand binding efficiencies for a subset of the CSARdock NRC HiQ data set where the number of ligand heavy atoms ranged from 17 to 35. This range of ligand heavy atoms is where improved accuracy of predicted ligand

Integrating Model-Based Learning and Animations for Enhancing Students' Understanding of Proteins Structure and Function

Science.gov (United States)

Barak, Miri; Hussein-Farraj, Rania

2013-01-01

This paper describes a study conducted in the context of chemistry education reforms in Israel. The study examined a new biochemistry learning unit that was developed to promote in-depth understanding of 3D structures and functions of proteins and nucleic acids. Our goal was to examine whether, and to what extent teaching and learning via…

Functional characterization of Arabidopsis thaliana transthyretin-like protein

Directory of Open Access Journals (Sweden)

Almeida Maria R

2010-02-01

Full Text Available Abstract Background Arabidopsis thaliana transthyretin-like (TTL protein is a potential substrate in the brassinosteroid signalling cascade, having a role that moderates plant growth. Moreover, sequence homology revealed two sequence domains similar to 2-oxo-4-hydroxy-4-carboxy-5-ureidoimidazoline (OHCU decarboxylase (N-terminal domain and 5-hydroxyisourate (5-HIU hydrolase (C-terminal domain. TTL is a member of the transthyretin-related protein family (TRP, which comprises a number of proteins with sequence homology to transthyretin (TTR and the characteristic C-terminal sequence motif Tyr-Arg-Gly-Ser. TRPs are single domain proteins that form tetrameric structures with 5-HIU hydrolase activity. Experimental evidence is fundamental for knowing if TTL is a tetrameric protein, formed by the association of the 5-HIU hydrolase domains and, in this case, if the structural arrangement allows for OHCU decarboxylase activity. This work reports about the biochemical and functional characterization of TTL. Results The TTL gene was cloned and the protein expressed and purified for biochemical and functional characterization. The results show that TTL is composed of four subunits, with a moderately elongated shape. We also found evidence for 5-HIU hydrolase and OHCU decarboxylase activities in vitro, in the full-length protein. Conclusions The Arabidopsis thaliana transthyretin-like (TTL protein is a tetrameric bifunctional enzyme, since it has 5-HIU hydrolase and OHCU decarboxylase activities, which were simultaneously observed in vitro.

Ku proteins function as corepressors to regulate farnesoid X receptor-mediated gene expression

International Nuclear Information System (INIS)

Ohno, Masae; Kunimoto, Masaaki; Nishizuka, Makoto; Osada, Shigehiro; Imagawa, Masayoshi

2009-01-01

The farnesoid X receptor (FXR; NR1H4) is a member of the nuclear receptor superfamily and regulates the expression of genes involved in enterohepatic circulation and the metabolism of bile acids. Based on functional analyses, nuclear receptors are divided into regions A-F. To explore the cofactors interacting with FXR, we performed a pull-down assay using GST-fused to the N-terminal A/B region and the C region, which are required for the ligand-independent transactivation and DNA-binding, respectively, of FXR, and nuclear extracts from HeLa cells. We identified DNA-dependent protein kinase catalytic subunit (DNA-PKcs), Ku80, and Ku70 as FXR associated factors. These proteins are known to have an important role in DNA repair, recombination, and transcription. DNA-PKcs mainly interacted with the A/B region of FXR, whereas the Ku proteins interacted with the C region and with the D region (hinge region). Chromatin immunoprecipitation assays revealed that the Ku proteins associated with FXR on the bile salt export pump (BSEP) promoter. Furthermore, we demonstrated that ectopic expression of the Ku proteins decreased the promoter activity and expression of BSEP gene mediated by FXR. These results suggest that the Ku proteins function as corepressors for FXR.

Liver Function Status in some Nigerian Children with Protein Energy ...

African Journals Online (AJOL)

Objective: To ascertain functional status of the liver in Nigeria Children with Protein energy malnutrition. Materials and Methods: Liver function tests were performed on a total of 88 children with protein energy malnutrition (PEM). These were compared with 22 apparently well-nourished children who served as controls.

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.

Configurable Resistive Switching between Memory and Threshold Characteristics for Protein-Based Devices

KAUST Repository

Wang, Hong

2015-05-01

The employ of natural biomaterials as the basic building blocks of electronic devices is of growing interest for biocompatible and green electronics. Here, resistive switching (RS) devices based on naturally silk protein with configurable functionality are demonstrated. The RS type of the devices can be effectively and exactly controlled by controlling the compliance current in the set process. Memory RS can be triggered by a higher compliance current, while threshold RS can be triggered by a lower compliance current. Furthermore, two types of memory devices, working in random access and WORM modes, can be achieved with the RS effect. The results suggest that silk protein possesses the potential for sustainable electronics and data storage. In addition, this finding would provide important guidelines for the performance optimization of biomaterials based memory devices and the study of the underlying mechanism behind the RS effect arising from biomaterials. Resistive switching (RS) devices with configurable functionality based on protein are successfully achieved. © 2015 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Lipid Bilayer Composition Affects Transmembrane Protein Orientation and Function

Directory of Open Access Journals (Sweden)

Katie D. Hickey

2011-01-01

Full Text Available Sperm membranes change in structure and composition upon ejaculation to undergo capacitation, a molecular transformation which enables spermatozoa to undergo the acrosome reaction and be capable of fertilization. Changes to the membrane environment including lipid composition, specifically lipid microdomains, may be responsible for enabling capacitation. To study the effect of lipid environment on proteins, liposomes were created using lipids extracted from bull sperm membranes, with or without a protein (Na+ K+-ATPase or -amylase. Protein incorporation, function, and orientation were determined. Fluorescence resonance energy transfer (FRET confirmed protein inclusion in the lipid bilayer, and protein function was confirmed using a colourometric assay of phosphate production from ATP cleavage. In the native lipid liposomes, ATPase was oriented with the subunit facing the outer leaflet, while changing the lipid composition to 50% native lipids and 50% exogenous lipids significantly altered this orientation of Na+ K+-ATPase within the membranes.

Hypothesis: NDL proteins function in stress responses by regulating microtubule organization

OpenAIRE

Khatri, Nisha; Mudgil, Yashwanti

2015-01-01

N-MYC DOWNREGULATED-LIKE proteins (NDL), members of the alpha/beta hydrolase superfamily were recently rediscovered as interactors of G-protein signaling in Arabidopsis thaliana. Although the precise molecular function of NDL proteins is still elusive, in animals these proteins play protective role in hypoxia and expression is induced by hypoxia and nickel, indicating role in stress. Homology of NDL1 with animal counterpart N-MYC DOWNREGULATED GENE (NDRG) suggests similar functions in animals...