Structure-activity relationships molecular similarity, virtual screening

In this chapter, we will give a brief introduction to the basic concepts of chemoinformatics and their relevance to chemical library design. In Section 2, we will describe chemical representation, molecular data, and molecular data mining in computer we will introduce some of the chemoinformatics concepts such as molecular descriptors, chemical space, dimension reduction, similarity and diversity and we will review the most useful methods and applications of chemoinformatics, the quantitative structure-activity relationship (QSAR), the quantitative structure-property relationship (QSPR), multiobjective optimization, and virtual screening. In Section 3, we will outline some of the elements of library design and connect chemoinformatics tools, such as molecular similarity, molecular diversity, and multiple objective optimizations, with designing optimal libraries. Finally, we will put library design into perspective in Section 4. 

The conceptual basis for similarity analysis is provided by the similarity-property principle that states that similar molecules have similar biological activity.This rather intuitive principle has been widely accepted and substantiated by a wealth of observations. The success of many similarity-based virtual screening calculations can only be rationalized on the basis of this principle. However, minor modifications in molecular structure can dramatically alter the biological activity of a small molecule. This situation is exploited in lead optimization elforts, but limits the potential of similarity methods. These considerations also suggest that there must be fundamental dilferences between the structure-activity relationships (SARs). Thus, difierent types of SARs are expected to critically determine the success of similarity methods and systematic SAR analysis helps to better understand on a case-by-case basis why similarity methods might succeed or fail. 

Peltason, L. and Bajorath, J. (2007). Molecular similarity analysis uncovers heterogeneous structure-activity relationships and variable activity landscapes. Chem. Biol. 14, 489 97. Peltason, L. and Bajorath, J. (2008). Molecular similarity analysis in virtual screening. In "Chemoinformatics Approaches to Virtual Screening", (A. Vamek and A. Tropsha, eds), pp. 120-147. RSC Publishing, Cambridge, UK. 

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