ArticleBMC bioinformatics2007
Background frequencies for residue variability estimates: BLOSUM revisited.
Article in BMC bioinformatics, 2007. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.
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5 citing papers in PubMed.
- Characterizing and predicting ccRCC-causing missense mutations in Von Hippel-Lindau disease.Human molecular genetics · 2024Article
- Identification of evolutionarily stable functional and immunogenic sites across the SARS-CoV-2 proteome and the greater coronavirus family.Research square · 2021Article
- Towards a gamete matching platform: using immunogenetics and artificial intelligence to predict recurrent miscarriage.NPJ digital medicine · 2019Article
- Determinants, discriminants, conserved residues--a heuristic approach to detection of functional divergence in protein families.PloS one · 2011Article
- A comparative study of conservation and variation scores.BMC bioinformatics · 2010Article
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Authors and funding
3 authors.
Funding
Abstract
backgroundShannon entropy applied to columns of multiple sequence alignments as a score of residue conservation has proven one of the most fruitful ideas in bioinformatics. This straightforward and intuitively appealing measure clearly shows the regions of a protein under increased evolutionary pressure, highlighting their functional importance. The inability of the column entropy to differentiate between residue types, however, limits its resolution power.
resultsIn this work we suggest generalizing Shannon's expression to a function with similar mathematical properties, that, at the same time, includes observed propensities of residue types to mutate to each other. To do that, we revisit the original construction of BLOSUM matrices, and re-interpret them as mutation probability matrices. These probabilities are then used as background frequencies in the revised residue conservation measure.
conclusionWe show that joint entropy with BLOSUM-proportional probabilities as a reference distribution enables detection of protein functional sites comparable in quality to a time-costly maximum-likelihood evolution simulation method (rate4site), and offers greater resolution than the Shannon entropy alone, in particular in the cases when the available sequences are of narrow evolutionary scope.
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