Molecular interaction fields in drug discovery: recent advances and future perspectives

Abstract

Drug discovery is a highly complex and costly process, and in recent years, the pharmaceutical industry has shifted from traditional to genomics‐ and proteomics‐based drug research strategies. The identification of druggable target sites, promising hits, and high quality leads are crucial steps in the early stages of drug discovery projects. Pharmacokinetic (PK) and drug metabolism profiling to optimize bioavailability, clearance, and toxicity are increasingly important areas to prevent costly failures in preclinical and clinical studies. The integration of a wide variety of technologies and expertise in multidisciplinary research teams combining synergistic effects between experimental and computational approaches on the selection and optimization of bioactive compounds to pass these hurdles is now commonplace, although there remain challenging areas. Molecular interaction fields (MIFs) are widely used in a range of applications to support the discovery teams, characterizing molecules according to their favorable interaction sites and therefore enabling predictions to be made about how molecules might interact. The utility of MIF‐based in silico approaches in drug design is extremely broad, including approaches to support experimental design in hit‐finding, lead‐optimization, physicochemical property prediction and PK modeling, drug metabolism prediction, and toxicity. WIREs Comput Mol Sci 2013, 3:594–613. doi: 10.1002/wcms.1150 This article is categorized under: Computer and Information Science > Chemoinformatics

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