Virtual screening for compounds that mimic protein–protein interface epitopes

Modulation of protein–protein interactions (PPI) has emerged as a new concept in rational drug design. Here, we present a computational protocol for identifying potential PPI inhibitors. Relevant regions of interfaces (epitopes) are predicted for three‐dimensional protein models and serve as queries for virtual compound screening. We present a computational screening protocol that incorporates two different pharmacophore models. One model is based on the mathematical concept of autocorrelation vectors and the other utilizes fuzzy labeled graphs. In a proof‐of‐concept study, we were able to identify serine protease inhibitors using a predicted trypsin epitope as query. Our virtual screening framework may be suited for rapid identification of PPI inhibitors and suggesting bioactive tool compounds. Copyright for JCC Journal: © 2011 Wiley Periodicals, Inc. J Comput Chem, 2011