Computer applications for prediction of protein–protein interactions and rational drug design

• Main Authors: Solène Grosdidier, Max Totrov, Juan Fernández-Recio
• Format: Article
• Language: English
• Published: Dove Medical Press 2009-11-01
• Series: Advances and Applications in Bioinformatics and Chemistry
• Online Access: http://www.dovepress.com/computer-applications-for-prediction-of-proteinndashprotein-interactio-a3715

Solène Grosdidier1, Max Totrov2, Juan Fernández-Recio11Life Sciences Department, Barcelona Supercomputing Center, Barcelona, Spain; 2Molsoft LLC, La Jolla, CA, USAAbstract: In recent years, protein–protein interactions are becoming the object of increasing attention in many different fields, such as structural biology, molecular biology, systems biology, and drug discovery. From a structural biology perspective, it would be desirable to integrate current efforts into the structural proteomics programs. Given that experimental determination of many protein–protein complex structures is highly challenging, and in the context of current high-performance computational capabilities, different computer tools are being developed to help in this task. Among them, computational docking aims to predict the structure of a protein–protein complex starting from the atomic coordinates of its individual components, and in recent years, a growing number of docking approaches are being reported with increased predictive capabilities. The improvement of speed and accuracy of these docking methods, together with the modeling of the interaction networks that regulate the most critical processes in a living organism, will be essential for computational proteomics. The ultimate goal is the rational design of drugs capable of specifically inhibiting or modifying protein–protein interactions of therapeutic significance. While rational design of protein–protein interaction inhibitors is at its very early stage, the first results are promising.Keywords: protein–protein interactions, drug design, protein docking, structural prediction, virtual ligand screening, hot-spots