Improving structural similarity based virtual screening using background knowledge

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چکیده

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Improving structural similarity based virtual screening using background knowledge

BACKGROUND Virtual screening in the form of similarity rankings is often applied in the early drug discovery process to rank and prioritize compounds from a database. This similarity ranking can be achieved with structural similarity measures. However, their general nature can lead to insufficient performance in some application cases. In this paper, we provide a link between ranking-based virt...

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This paper summarizes recent work at the University of Sheffield on virtual screening methods that use 2D fingerprint measures of structural similarity. A detailed comparison of a large number of similarity coefficients demonstrates that the well-known Tanimoto coefficient remains the method of choice for the computation of fingerprint-based similarity, despite possessing some inherent biases r...

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An algorithm for similarity-based virtual screening

The virtual screening methods and techniques become one of the important and sophisticated ways of drug discovery, and molecules clustering, they are many methods proposed and applied in virtual screening, most of these screening methods used similarity coefficients to quantify the extent to which objects resemble one another. The result of using these similarity coefficients achieves a good re...

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Developing new medical drugs is expensive. Among the first steps is a screening process, in which molecules in existing chemical libraries are tested for activity against a given target. This requires a lot of resources and manpower. Therefore it has become common to perform a virtual screening, where computers are used for predicting the activity of very large libraries of molecules, to identi...

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ژورنال

عنوان ژورنال: Journal of Cheminformatics

سال: 2013

ISSN: 1758-2946

DOI: 10.1186/1758-2946-5-50