Abstract
Interprotein contact prediction using multiple sequence alignments (MSAs) is a useful approach to help detect protein–protein interfaces. Different computational methods have been developed in recent years as an approximation to solve this problem. However, as there are discrepancies in the results provided by them, there is still no consensus on which is the best performing methodology. To address this problem, I-COMS (interprotein COrrelated Mutations Server) is presented. I-COMS allows to estimate covariation between residues of different proteins by four different covariation methods. It provides a graphical and interactive output that helps compare results obtained using different methods. I-COMS automatically builds the required MSA for the calculation and produces a rich visualization of either intraprotein and/or interprotein covariating positions in a circos representation. Furthermore, comparison between any two methods is available as well as the overlap between any or all four methodologies. In addition, as a complementary source of information, a matrix visualization of the corresponding scores is made available and the density plot distribution of the inter, intra and inter+intra scores are calculated. Finally, all the results can be downloaded (including MSAs, scores and graphics) for comparison and visualization and/or for further analysis.
Highlights
Recent work has demonstrated the accuracy of coevolutionbased protein contact prediction using several approaches as mutual information (MI) [1,2,3], direct couplings [4,5,6,7,8,9] and more recently pseudo-likelihood-based approaches [8,10]
The average product correction (APC) method of Dunn et al (2008) [20] was applied to reduce the background MI signal for each pair of residues and the MI scores were translated into MI z-scores by comparing the MI values for each pair of position with a distribution of prediction scores obtained from a large set of randomized multiple sequence alignments (MSAs)
The z-score is calculated as the number of standard deviations that the observed MI value falls above the mean value obtained from the randomized MSAs
Summary
Recent work has demonstrated the accuracy of coevolutionbased protein contact prediction using several approaches as mutual information (MI) [1,2,3], direct couplings [4,5,6,7,8,9] and more recently pseudo-likelihood-based approaches [8,10]. For genes with few homologs, the closest hit may not be the closest homolog [16] We understand that this may be a strong limitation and for this reason, we allow the user to load its own alignments based on a more accurate orthology assignment and leave this auto-assignment possibility for less expert users (or when other approach is not possible because of the low number of sequences). All the results can be downloaded (including MSAs, scores and graphics) to further analysis, comparison and visualization This website is free and open to all users and there is no login requirement.
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