Merav Fichman

PREDICT modeling and in‐silico screening for G‐protein coupled receptors

G‐protein coupled receptors (GPCRs) are a major group of drug targets for which only one x‐ray structure is known (the nondrugable rhodopsin), limiting the application of structure‐based drug discovery to GPCRs. In this paper we present the details of PREDICT, a new algorithmic approach for modeling the 3D structure of GPCRs without relying on homology to rhodopsin. PREDICT, which focuses on the transmembrane domain of GPCRs, starts from the primary sequence of the receptor, simultaneously optimizing multiple ‘decoy’ conformations of the protein in order to find its most stable structure, culminating in a virtual receptor‐ligand complex. In this paper we present a comprehensive analysis of three PREDICT models for the dopamine D2, neurokinin NK1, and neuropeptide Y Y1 receptors. A shorter discussion of the CCR3 receptor model is also included. All models were found to be in good agreement with a large body of experimental data. The quality of the PREDICT models, at least for drug discovery purposes, was evaluated by their successful utilization in in‐silico screening. Virtual screening using all three PREDICT models yielded enrichment factors 9‐fold to 44‐fold better than random screening. Namely, the PREDICT models can be used to identify active small‐molecule ligands embedded in large compound libraries with an efficiency comparable to that obtained using crystal structures for non‐GPCR targets. Proteins 2004.

G Protein Coupled Receptors - In Silico Drug Discovery and Design

In silico drug discovery is a complex process requiring flexibility and ingenuity in method selection and a careful validation of work protocols. GPCR in silico drug discovery poses additional challenges due to the paucity of crystallographic data. This paper starts by reviewing selected GPCR in silico screening programs reported in the literature, including both structure-based and ligand-based approaches. Particular emphasis is given to library design, binding mode selection, process validation and compound selection for biological testing. Following literature review, we provide insights into in silico methodologies and process workflows used at EPIX to drive over 20 highly successful screening and lead optimization programs performed since 2001. Applications of the various methodologies discussed are demonstrated by examples from recent programs that have not yet been published.