Optimal contact definition for reconstruction of Contact Maps

Duarte, José M.; Sathyapriya, R.; Stehr, Henning; Filippis, Ioannis; Lappé, Michael

doi:10.1186/1471-2105-11-283

Cited by 52 publications

(75 citation statements)

References 37 publications

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“…In Table 5, the results of predictions in which the numbers of predicted contacts are equal to one fourth or one third of the number of true contacts are listed for each protein family. Although the number of contacts well scales with the chain length [59], the ratio of the number of contacts to the chain length somewhat varies depending on proteins as shown in Table 5. One third of the total number of true contacts is equal to the sequence length in the case of Trypsin, which has the largest number, 3.0, of contacts per residue in Table 5, and equal to half of the sequence length in the case of Trans_reg_c and 7tm_1, which have the smallest number, 1.5, of contacts per residue.…”

Section: Resultsmentioning

confidence: 99%

Prediction of Contact Residue Pairs Based on Co-Substitution between Sites in Protein Structures

Miyazawa

2013

PLoS ONE

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Residue-residue interactions that fold a protein into a unique three-dimensional structure and make it play a specific function impose structural and functional constraints in varying degrees on each residue site. Selective constraints on residue sites are recorded in amino acid orders in homologous sequences and also in the evolutionary trace of amino acid substitutions. A challenge is to extract direct dependences between residue sites by removing phylogenetic correlations and indirect dependences through other residues within a protein or even through other molecules. Rapid growth of protein families with unknown folds requires an accurate de novo prediction method for protein structure. Recent attempts of disentangling direct from indirect dependences of amino acid types between residue positions in multiple sequence alignments have revealed that inferred residue-residue proximities can be sufficient information to predict a protein fold without the use of known three-dimensional structures. Here, we propose an alternative method of inferring coevolving site pairs from concurrent and compensatory substitutions between sites in each branch of a phylogenetic tree. Substitution probability and physico-chemical changes (volume, charge, hydrogen-bonding capability, and others) accompanied by substitutions at each site in each branch of a phylogenetic tree are estimated with the likelihood of each substitution, and their direct correlations between sites are used to detect concurrent and compensatory substitutions. In order to extract direct dependences between sites, partial correlation coefficients of the characteristic changes along branches between sites, in which linear multiple dependences on feature vectors at other sites are removed, are calculated and used to rank coevolving site pairs. Accuracy of contact prediction based on the present coevolution score is comparable to that achieved by a maximum entropy model of protein sequences for 15 protein families taken from the Pfam release 26.0. Besides, this excellent accuracy indicates that compensatory substitutions are significant in protein evolution.

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Section: Resultsmentioning

confidence: 99%

Prediction of Contact Residue Pairs Based on Co-Substitution between Sites in Protein Structures

Miyazawa

2013

PLoS ONE

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“…To this aim, a commonly used threshold is 8 angstroms (Å ) [44], a threshold that is also adopted in this paper. In order to measure the distance between two amino acids, it is necessary to use a reference atom of each amino acid, the most commonly used being the alpha carbon and the beta carbon of amino acids [15]. In our method, we use the beta carbon (with the exception of glycine, which has no beta carbon, and for which its alpha carbon is used).…”

Section: Contact Map Predictionmentioning

confidence: 99%

Evolutionary decision rules for predicting protein contact maps

Chamorro

Asencio-Cortés

Divina

et al. 2012

Pattern Anal Applic

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Protein structure prediction is currently one of the main open challenges in Bioinformatics. The protein contact map is an useful, and commonly used, representation for protein 3D structure and represents binary proximities (contact or non-contact) between each pair of amino acids of a protein. In this work, we propose a multiobjective evolutionary approach for contact map prediction based on physico-chemical properties of amino acids. The evolutionary algorithm produces a set of decision rules that identifies contacts between amino acids. The rules obtained by the algorithm impose a set of conditions based on amino acid properties to predict contacts. We present results obtained by our approach on four different protein data sets. A statistical study was also performed to extract valid conclusions from the set of prediction rules generated by our algorithm. Results obtained confirm the validity of our proposal.

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“…However, for predicting folds of sequences which do not have homologous templates (hard sequences), the optimal way of utilizing predicted contacts is still an ongoing research. For instance, experiments on true contact reconstruction have suggested that 9 Å or more distance threshold delivers best reconstruction with Cβ atom [10, 11], but the Critical Assessment of Protein Structure Prediction (CASP)’s definition of 8 Å threshold is still widely used to predict contacts [1–3, 6, 12]. Marks et al have even demonstrated successful structure predictions using Cα atoms and 7 Å threshold for defining contacts [13].…”

Section: Introductionmentioning

confidence: 99%

ConEVA: a toolbox for comprehensive assessment of protein contacts

et al. 2016

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BackgroundIn recent years, successful contact prediction methods and contact-guided ab initio protein structure prediction methods have highlighted the importance of incorporating contact information into protein structure prediction methods. It is also observed that for almost all globular proteins, the quality of contact prediction dictates the accuracy of structure prediction. Hence, like many existing evaluation measures for evaluating 3D protein models, various measures are currently used to evaluate predicted contacts, with the most popular ones being precision, coverage and distance distribution score (Xd).ResultsWe have built a web application and a downloadable tool, ConEVA, for comprehensive assessment and detailed comparison of predicted contacts. Besides implementing existing measures for contact evaluation we have implemented new and useful methods of contact visualization using chord diagrams and comparison using Jaccard similarity computations. For a set (or sets) of predicted contacts, the web application runs even when a native structure is not available, visualizing the contact coverage and similarity between predicted contacts. We applied the tool on various contact prediction data sets and present our findings and insights we obtained from the evaluation of effective contact assessments. ConEVA is publicly available at http://cactus.rnet.missouri.edu/coneva/.ConclusionConEVA is useful for a range of contact related analysis and evaluations including predicted contact comparison, investigation of individual protein folding using predicted contacts, and analysis of contacts in a structure of interest.

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Optimal contact definition for reconstruction of Contact Maps

Cited by 52 publications

References 37 publications

Prediction of Contact Residue Pairs Based on Co-Substitution between Sites in Protein Structures

Prediction of Contact Residue Pairs Based on Co-Substitution between Sites in Protein Structures

Evolutionary decision rules for predicting protein contact maps

ConEVA: a toolbox for comprehensive assessment of protein contacts

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