Abstract
BackgroundWhile the conserved positions of a multiple sequence alignment (MSA) are clearly of interest, non-conserved positions can also be important because, for example, destabilizing effects at one position can be compensated by stabilizing effects at another position. Different methods have been developed to recognize the evolutionary relationship between amino acid sites, and to disentangle functional/structural dependencies from historical/phylogenetic ones.Methodology/Principal FindingsWe have used two complementary approaches to test the efficacy of these methods. In the first approach, we have used a new program, MSAvolve, for the in silico evolution of MSAs, which records a detailed history of all covarying positions, and builds a global coevolution matrix as the accumulated sum of individual matrices for the positions forced to co-vary, the recombinant coevolution, and the stochastic coevolution. We have simulated over 1600 MSAs for 8 protein families, which reflect sequences of different sizes and proteins with widely different functions. The calculated coevolution matrices were compared with the coevolution matrices obtained for the same evolved MSAs with different coevolution detection methods. In a second approach we have evaluated the capacity of the different methods to predict close contacts in the representative X-ray structures of an additional 150 protein families using only experimental MSAs.Conclusions/SignificanceMethods based on the identification of global correlations between pairs were found to be generally superior to methods based only on local correlations in their capacity to identify coevolving residues using either simulated or experimental MSAs. However, the significant variability in the performance of different methods with different proteins suggests that the simulation of MSAs that replicate the statistical properties of the experimental MSA can be a valuable tool to identify the coevolution detection method that is most effective in each case.
Highlights
During the past decade many efforts have been devoted to uncover the evolutionary dynamic of organisms through the examination of multiple sequence alignments (MSAs)
In a second approach we have evaluated the capacity of the different methods to predict close contacts in the representative X-ray structures of the 8 aforementioned families, represented by MSAs with less than 500 sequences, and an additional 150 protein families, represented by MSAs with over 1000 sequences
Development of the differential binary methods The differential binary methods were developed empirically using the feature of MSAvolve that allows a direct comparison between the true coevolution signal buried in a simulated MSA and the coevolution signal identified a posteriori by a coevolution detection method. Rationale for these methods initially stems from the consideration that the Mutual Information (MI) between two positions (i and j) in a MSA contains two kinds of information: (a) the first kind is just the information that something changes: for example when the amino acid at position i changes from sequence 1 (s1) to sequence 2 (s2), the aa at position j changes from s1 to s2. (b) the second kind is the information about what aa changes at i from s1 to s2, compared to what aa changes at j from s1 to s2
Summary
During the past decade many efforts have been devoted to uncover the evolutionary dynamic of organisms through the examination of multiple sequence alignments (MSAs). The destabilizing effects of a given amino acid at one position can be compensated by the stabilizing effect of a certain amino acid at another position. The existence of physical and functional interactions between sites in protein sequences leads to non-independence of their evolution: in other words, two (or more) positions in a protein sequence could be coevolving, and for any mutation to become fixed at such sites, compensatory mutations are needed at the related sites. While the conserved positions of a multiple sequence alignment (MSA) are clearly of interest, non-conserved positions can be important because, for example, destabilizing effects at one position can be compensated by stabilizing effects at another position. Different methods have been developed to recognize the evolutionary relationship between amino acid sites, and to disentangle functional/structural dependencies from historical/phylogenetic ones
Sign-in/Register to view highlights & summary Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a call
