An efficient algorithm for matching protein binding sites for protein function prediction

Leif Ellingson, Jinfeng Zhang

Research output: Contribution to conferencePaper

Abstract

Comparison of the binding sites of proteins is an effective method for predicting protein functions based on their structure information. Despite the importance of this problem and much research in the past, it is still very challenging to predict the binding ligands from the atomic structures of protein binding sites. In this study, we designed a new algorithm based on the iterative closest point (ICP) algorithm originally designed in computer vision. The algorithm aims to find the maximum number of atoms that can be superposed between two protein binding sites (maximum common atom set), where any pair of matched atoms in the superposition has a distance smaller than a given threshold value. The search starts from similar tetrahedra between two protein binding sites obtained from 3D Delaunay triangulation and uses the Hungarian algorithm to find additional matched atoms. We show that our method can find more matched atoms than geometric hashing-based method, which has been commonly u
Original languageEnglish
StatePublished - Aug 2011

Fingerprint Dive into the research topics of 'An efficient algorithm for matching protein binding sites for protein function prediction'. Together they form a unique fingerprint.

  • Cite this