ConSurf: Using evolutionary data to raise testable hypotheses about protein function

Gershon Celniker, Guy Nimrod, Haim Ashkenazy, Fabian Glaser, Eric Martz, Itay Mayrose, Tal Pupko, Nir Ben-Tal*

*Corresponding author for this work

Research output: Contribution to journalReview articlepeer-review


Many mutations disappear from the population because they impair protein function and/or stability. Thus, amino acid positions that are essential for proper function evolve more slowly than others, or in other words, the slow evolutionary rate of a position reflects its importance. ConSurf (, reviewed in this manuscript, exploits this to reveal key amino acid positions that are important for maintaining the native conformation(s) of the protein and its function, be it binding, catalysis, transport, etc. Given the sequence or 3D structure of the query protein as input, a search for similar sequences is conducted and the sequences are aligned. The multiple sequence alignment is subsequently used to calculate the evolutionary rates of each amino acid site, using Bayesian or maximum-likelihood algorithms. Both algorithms take into account the evolutionary relationships between the sequences, reflected in phylogenetic trees, to alleviate problems due to uneven (biased) sampling in sequence space. This is particularly important when the number of sequences is low. The ConSurf-DB, a new release of which is presented here, provides precalculated ConSurf conservation analysis of nearly all available structures in the Protein DataBank (PDB). The usefulness of ConSurf for the study of individual proteins and mutations, as well as a range of large-scale, genome-wide applications, is reviewed.

Original languageEnglish
Pages (from-to)199-206
Number of pages8
JournalIsrael Journal of Chemistry
Issue number3-4
StatePublished - Apr 2013


  • bioinformatics
  • databases
  • genomics
  • protein models
  • protein structures


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