Co-evolution techniques are reshaping the way we do structural bioinformatics
نویسندگان
چکیده
Co-evolution techniques were originally conceived to assist in protein structure prediction by inferring pairs of residues that share spatial proximity. However, the functional relationships that can be extrapolated from co-evolution have also proven to be useful in a wide array of structural bioinformatics applications. These techniques are a powerful way to extract structural and functional information in a sequence-rich world.
منابع مشابه
Combining co-evolution and secondary structure prediction to improve fragment library generation.
Motivation Recent advances in co-evolution techniques have made possible the accurate prediction of protein structures in the absence of a template. Here, we provide a general approach that further utilizes co- evolution constraints to generate better fragment libraries for fragment-based protein structure prediction. Results We have compared five different fragment library generation program...
متن کاملLarge-scale co-evolution analysis of protein structural interlogues using the global protein structural interactome map (PSIMAP)
MOTIVATION Interacting pairs of proteins should co-evolve to maintain functional and structural complementarity. Consequently, such a pair of protein families shows similarity between their phylogenetic trees. Although the tendency of co-evolution has been known for various ligand-receptor pairs, it has not been studied systematically in the widest possible scope. We investigated the degree of ...
متن کاملStructural bioinformatics NeBcon: protein contact map prediction using neural network training coupled with naı̈ve Bayes classifiers
Motivation: Recent CASP experiments have witnessed exciting progress on folding large-size nonhumongous proteins with the assistance of co-evolution based contact predictions. The success is however anecdotal due to the requirement of the contact prediction methods for the high volume of sequence homologs that are not available to most of the non-humongous protein targets. Development of effici...
متن کاملNeBcon: protein contact map prediction using neural network training coupled with naïve Bayes classifiers
Motivation Recent CASP experiments have witnessed exciting progress on folding large-size non-humongous proteins with the assistance of co-evolution based contact predictions. The success is however anecdotal due to the requirement of the contact prediction methods for the high volume of sequence homologs that are not available to most of the non-humongous protein targets. Development of effici...
متن کاملNeBcon: protein contact map prediction using neural network training coupled with naı̈ve Bayes classifiers
Motivation: Recent CASP experiments have witnessed exciting progress on folding large-size nonhumongous proteins with the assistance of co-evolution based contact predictions. The success is however anecdotal due to the requirement of the contact prediction methods for the high volume of sequence homologs that are not available to most of the non-humongous protein targets. Development of effici...
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عنوان ژورنال:
دوره 6 شماره
صفحات -
تاریخ انتشار 2017