A family of evolution-entropy hybrid methods for ranking protein residues by importance

J Mol Biol. 2004 Mar 5;336(5):1265-82. doi: 10.1016/j.jmb.2003.12.078.


In order to identify the amino acids that determine protein structure and function it is useful to rank them by their relative importance. Previous approaches belong to two groups; those that rely on statistical inference, and those that focus on phylogenetic analysis. Here, we introduce a class of hybrid methods that combine evolutionary and entropic information from multiple sequence alignments. A detailed analysis in insulin receptor kinase domain and tests on proteins that are well-characterized experimentally show the hybrids' greater robustness with respect to the input choice of sequences, as well as improved sensitivity and specificity of prediction. This is a further step toward proteome scale analysis of protein structure and function.

Publication types

  • Research Support, Non-U.S. Gov't
  • Research Support, U.S. Gov't, Non-P.H.S.
  • Research Support, U.S. Gov't, P.H.S.

MeSH terms

  • Amino Acid Sequence
  • Amino Acids
  • Animals
  • Entropy
  • Evolution, Molecular
  • Humans
  • Models, Genetic*
  • Models, Molecular
  • Proteins / chemistry
  • Proteins / genetics
  • Receptor, Insulin / chemistry*
  • Receptor, Insulin / genetics
  • Sequence Alignment


  • Amino Acids
  • Proteins
  • Receptor, Insulin