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.
|Title of host publication||Lecture Notes in Computer Science|
|Publication status||Published - 1 Jan 2013|
|Event||AIME - Artificial Intelligence in Medicine - |
Duration: 1 Jan 2013 → …
|Conference||AIME - Artificial Intelligence in Medicine|
|Period||1/01/13 → …|