![]() A very extensive and informative review with emphasis on quantitative analysis of protein–ligand interactions. ![]() Approaches to the description and prediction of the binding affinity of small-molecule ligands to macromolecular receptors. Virtual screening: an effective tool for lead structure discovery. Integration of virtual and high-throughput screening. High-throughput crystallography for lead discovery in drug design. The protein data bank and structural genomics. Westbrook, J., Feng, Z., Chen, L., Yang, H. The protein data bank and the challenge of structural genomics. We attempt to distinguish between the problems of docking compounds into target sites and of scoring docked conformations, because the available data indicate that numerous robust and accurate docking algorithms are available, whereas imperfections of scoring functions continue to be a major limiting factor.īerman, H. This article reviews basic concepts and specific features of small-molecule–protein docking methods and several selected applications, with particular emphasis on hit identification and lead optimization. These algorithms are complemented by scoring functions that are designed to predict the biological activity through the evaluation of interactions between compounds and potential targets. The process begins with the application of docking algorithms that pose small molecules in the active site. ![]() ![]() In general, there are two aims of docking studies: accurate structural modelling and correct prediction of activity.ĭocking is generally devised as a multi-step process in which each step introduces one or more additional degrees of complexity. The docking process involves the prediction of ligand conformation and orientation (or posing) within a targeted binding site. One key such methodology - docking of small molecules to protein binding sites - was pioneered during the early 1980s, and remains a highly active area of research. Computational methodologies have become a crucial component of many drug discovery programmes, from hit identification to lead optimization and beyond. ![]()
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