EvDTree: structure-dependent substitution profiles based on decision tree classification of 3D environments

Background: Structure-dependent substitution matrices increase the accuracy of sequence alignments when the 3D structure of one sequence is known, and are successful e.g. in fold recognition. We propose a new automated method, EvDTree, based on a decision tree algorithm, for automatic derivation of amino acid substitution probabilities from a set of sequence-structure alignments. The main advantage over other approaches is an unbiased automatic selection of the most informative structural descriptors and associated values or thresholds. This feature allows automatic derivation of structure-dependent substitution scores for any specific set of structures, without the need to empirically determine best descriptors and parameters. Results: Decision trees for residue substitutions were constructed for each residue type from sequence-structure alignments extracted from the HOMSTRAD database. For each tree cluster, environment-dependent substitution profiles were derived. The resulting stru...

• Type: Journal
• Year: 2005
• Where: BMCBI
• Authors: Jean-Christophe Gelly, Laurent Chiche, Jérôme Gracy
• Keywords: BMCBI 2005, Structure-dependent Substitution, Structure-dependent Substitution Scores, Substitution Scores