Computational prediction of protein hot spot residues.
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.
Department of Experimental Therapeutics, The University of Texas M.D. Anderson Cancer Center, Houston, Texas 77054, USA.
John Kenneth
JK
Morrow
Shuxing
S
Zhang
D019295:Computational Biology / Q000379:methods*; D017076:Computer-Aided Design; D015195:Drug Design; D055808:Drug Discovery / Q000379:methods; D006801:Humans; D056004:Molecular Dynamics Simulation; D011485:Protein Binding; D025941:Protein Interaction Mapping / Q000379:methods; D011506:Proteins / Q000737:chemistry / Q000378:metabolism*
D011506:Proteins