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Enhancing Drug Discovery Through In Silico Screening: Strategies to Increase True Positives Retrieval Rates

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Computational chemistry software for lead discovery has become well established in pharmaceutical industry and has found its way to the desktop computers of medicinal chemists for different purposes, providing insight on the mode of action and binding properties, and creating new ideas for lead structure refinement. In this review we investigate the performance and reliability of recent state-of-the-art data modeling techniques, as well as ligand-based and structurebased modeling approaches for 3D virtual screening. We discuss and summarize recently published success stories and lately developed techniques. Parallel screening is one of these emerging approaches allowing for efficient activity in silico profiling of several compounds against different targets or anti-targets simultaneously. This is of special interest to medicinal chemists, as the approach allows revealing unknown binding modes (‘target-fishing’) as well as integrated ADME profiling or - more generally - the prediction of off-target effects.

Keywords: ADME/Tox profiling; Data modeling; activity profiling; parallel screening; pharmacophore modeling; protein-ligand docking; target fishing; virtual screening

Document Type: Research Article


Affiliations: Department of Pharmaceutical Chemistry, Faculty of Chemistry and Pharmacy and Center for Molecular Biosciences (CMBI), University of Innsbruck, Innrain 52, A-6020 Innsbruck, Austria.

Publication date: August 1, 2008

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  • Current Medicinal Chemistry covers all the latest and outstanding developments in medicinal chemistry and rational drug design. Each issue contains a series of timely in-depth reviews written by leaders in the field covering a range of the current topics in medicinal chemistry. Current Medicinal Chemistry is an essential journal for every medicinal chemist who wishes to be kept informed and up-to-date with the latest and most important developments.

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