ArticleBMC bioinformatics2011
New methods to measure residues coevolution in proteins.
Article in BMC bioinformatics, 2011. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.
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Who cites it
7 citing papers in PubMed.
- Genetic Analysis of Patients with Congenital Hypogonadotropic Hypogonadism: A Case Series.International journal of molecular sciences · 2023Article
- Protein sites with more coevolutionary connections tend to evolve slower, while more variable protein families acquire higher coevolutionary connections.F1000Research · 2017Article
- Emerging Computational Methods for the Rational Discovery of Allosteric Drugs.Chemical reviews · 2016Review
- A new ensemble coevolution system for detecting HIV-1 protein coevolution.Biology direct · 2015Article
- Quantum coupled mutation finder: predicting functionally or structurally important sites in proteins using quantum Jensen-Shannon divergence and CUDA programming.BMC bioinformatics · 2014Article
- Improving the thermostability of alpha-amylase by combinatorial coevolving-site saturation mutagenesis.BMC bioinformatics · 2012Article
- Coupled mutation finder: a new entropy-based method quantifying phylogenetic noise for the detection of compensatory mutations.BMC bioinformatics · 2012Article
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4 authors.
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Abstract
backgroundThe covariation of two sites in a protein is often used as the degree of their coevolution. To quantify the covariation many methods have been developed and most of them are based on residues position-specific frequencies by using the mutual information (MI) model.
resultsIn the paper, we proposed several new measures to incorporate new biological constraints in quantifying the covariation. The first measure is the mutual information with the amino acid background distribution (MIB), which incorporates the amino acid background distribution into the marginal distribution of the MI model. The modification is made to remove the effect of amino acid evolutionary pressure in measuring covariation. The second measure is the mutual information of residues physicochemical properties (MIP), which is used to measure the covariation of physicochemical properties of two sites. The third measure called MIBP is proposed by applying residues physicochemical properties into the MIB model. Moreover, scores of our new measures are applied to a robust indicator conn(k) in finding the covariation signal of each site.
conclusionsWe find that incorporating amino acid background distribution is effective in removing the effect of evolutionary pressure of amino acids. Thus the MIB measure describes more biological background information for the coevolution of residues. Besides, our analysis also reveals that the covariation of physicochemical properties is a new aspect of coevolution information.
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