Computational prediction of protein hot spot residues

John Kenneth Morrow, Shuxing Zhang

Research output: Contribution to journalArticlepeer-review

91 Scopus citations

Abstract

Most biological processes involve multiple proteins interacting with each other. It has been recently discovered that certain residues in these protein-protein interactions, which are called hot spots, contribute more significantly to binding affinity than others. Hot spot residues have unique and diverse energetic properties that make them challenging yet important targets in the modulation of protein-protein complexes. Design of therapeutic agents that interact with hot spot residues has proven to be a valid methodology in disrupting unwanted protein-protein interactions. Using biological methods to determine which residues are hot spots can be costly and time consuming. Recent advances in computational approaches to predict hot spots have incorporated a myriad of features, and have shown increasing predictive successes. Here we review the state of knowledge around protein-protein interactions, hot spots, and give an overview of multiple in silico prediction techniques of hot spot residues.

Original languageEnglish (US)
Pages (from-to)1255-1265
Number of pages11
JournalCurrent pharmaceutical design
Volume18
Issue number9
DOIs
StatePublished - Mar 2012

Keywords

  • Alanine scanning
  • Hot spot residues
  • In silico prediction
  • Protein-protein interactions
  • Structure-based drug discovery
  • Traf6

ASJC Scopus subject areas

  • Pharmacology
  • Drug Discovery

Fingerprint

Dive into the research topics of 'Computational prediction of protein hot spot residues'. Together they form a unique fingerprint.

Cite this