Constraining Protein Docking with Coevolution Data for Medical Research

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

3 Citations (Scopus)

Abstract

Protein interaction is essential to all biological systems, from the assembly of multimeric complexes to processes such as transport, catalysis and gene regulation. Unfortunately, the prediction of protein-protein interactions is a difficult problem, often with modest success rates, in part because docking algorithms must filter a very large number of possibilities and then attempt to identify a correct model among many incorrect candidates. This paper presents a scoring function to estimate contacts in coevolving proteins, shows how the predicted contacts can constrain the filtering stage and significantly reduce the number of incorrect candidates, and illustrates the application of this method to the docking of two complexes of medical relevance, one involving a chromosome condensation regulator homologous to a protein responsible for retinitis pigmentosa and the other a cyclin-dependent kinase, a likely target for cancer therapy.
Original languageUnknown
Title of host publicationLecture Notes in Computer Science
Pages110-114
ISBN (Electronic)978-3-642-38326-7
DOIs
Publication statusPublished - 1 Jan 2013
EventAIME - Artificial Intelligence in Medicine -
Duration: 1 Jan 2013 → …

Conference

ConferenceAIME - Artificial Intelligence in Medicine
Period1/01/13 → …

Cite this