PSICOV: precise structural contact prediction using sparse inverse covariance estimation on large multiple sequence alignments

MOTIVATION: The accurate prediction of residue-residue contacts, critical for maintaining the native fold of a protein, remains an open problem in the field of structural bioinformatics. Interest in this long-standing problem has increased recently with algorithmic improvements and the rapid growth in the sizes of sequence families. Progress could have major impacts in both structure and function prediction to name but two benefits. Sequence-based contact predictions are usually made by identifying correlated mutations within multiple sequence alignments (MSAs), most commonly through the information-theoretic approach of calculating mutual information between pairs of sites in proteins. These predictions are…

• EA
  Engineering and Physical Sciences Research Council

  Award: EP/H027203/1
• BA
  Biotechnology and Biological Sciences Research Council

  Awards: BB/I023992/1, BB/F010451/1