Virtual screening overview

Walters WP, Stahl MT, Murcko MA. Virtual screening—An overview. Drug Discovery Today 1998 3 160-78. 

Lyne PD. Structure-based virtual screening an overview. Drug Discov Today 2002 7 1047-55. 

It should be pointed out that one is focused on properties of molecules in the absence of the receptor in contrast to the detailed focus on the complex in drug design studies. Many approaches to similarity fail to even consider chirality, a common discriminator of receptors. For a recent overview of the current status of virtual screening in lead discovery, see the review by Oprea and Matter [82]. 

M URCKO, M.A. Virtual screening - an overview. Drug Disc. Today 1998, 3, 160-178. 

The concepts of molecular similarity (1-3) and molecular diversity (4,5) play important roles in modern approaches to computer-aided molecular design. Molecular similarity provides the simplest, and most widely used, method for virtual screening and underlies the use of clustering methods on chemical databases. Molecular diversity analysis provides a range of tools for exploring the extent to which a set of molecules spans structural space, and underlies many approaches to compound selection and to the design of combinatorial libraries. Many different similarity and diversity methods have been described in the literature, and new methods continue to appear. This raises the question of how one can compare different methods, so as to identify the most appropriate method(s) for some particular application this chapter provides an overview of the ways in which this can be carried out, illustrating such comparisons by,... 

Walter, W. P., Stahl, M. T., Murcko, M. A. (1998) Virtual screening-an overview. Drug Discav TodayS, 160-178. 

Lyne, P. D. Structure-Based Virtual Screening An Overview. Drug Disc. Today. 2002, 7, 1047-1055. 

Hou TJ, Xu XJ. Recent development and application of virtual screening in drug discovery an overview. Curr Pharm Des 2004 10 1011-1033. 

Todeschini R, Consonni V (2000) Handbook of molecular descriptors. In Mannhold R, Kubinyi H, Timmerman H (eds), Methods and principles in medicinal chemistry 11. WILEY-VCH, Weinheim. Walters WP, Stahl MT, Murcko MA (1998) Virtual screening — and overview. Drug Discov Today 3 160—178. Ward JH (1963) Hierarchical grouping to optimize an objective function. J Am Stat Assoc 58 236—244. Warmuth MK, Liao J, Ratsch G et al. (2003) Active learning with support vector machines in the drug discovery process. J Chem Inf Comput Sci 43 667—673. 

In this chapter we overview some probabilistic methods used for biological activity prediction, paying particular attention to the problems of creation of the training and evaluation sets, validation of (Q)SAR models, estimation of prediction accuracy, interpretation of the prediction results and their application in virtual screening. 

Chemical library design has always been an important component of chemoinformatics studies and it could be viewed in fact a special case of virtual screening. Chapter 9 by W. Zheng and S.R. Johnson provides an expert overview of computational approaches that are employed in the design of targeted and diverse chemical libraries, including the use of property i.e., ADMET) filters. 

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