Analysis diversity

R.A. Lewis, S.D. Pickett, D.E. Qark. Computer-aided molecular diversity analysis and combinatorial library design, in Reviews in Computational Chemistry, Vol. 16, K.B. Opkowitz, D.B. Boyd (Eds.). Wiley-VCH, New York. 2000. pp. 8-51. 

Chemoinformatics (or cheminformatics) deals with the storage, retrieval, and analysis of chemical and biological data. Specifically, it involves the development and application of software systems for the management of combinatorial chemical projects, rational design of chemical libraries, and analysis of the obtained chemical and biological data. The major research topics of chemoinformatics involve QSAR and diversity analysis. The researchers should address several important issues. First, chemical structures should be characterized by calculable molecular descriptors that provide quantitative representation of chemical structures. Second, special measures should be developed on the basis of these descriptors in order to quantify structural similarities between pairs of molecules. Finally, adequate computational methods should be established for the efficient sampling of the huge combinatorial structural space of chemical libraries. 

Many reports have been published that address various aspects of diversity analysis in the context of chemical library design and database mining [77-84]. 

Absorption maximum wavelengths, correlation equations for, 20 508t Absorption, metabolism, distribution, and excretion (ADME), predicting using diversity analysis, 6 18 Absorption properties, of sutures,... 

Rule-based structure generation techniques, 16 751-752 Rule of 5, in diversity analysis, 6 18 Rules... 

Richard A. Lewis, Stephen D. Pickett, and David E. Clark, Computer-Aided Molecular Diversity Analysis and Combinatorial Library Design. 

The linear models within each pool were subjected to a diversity analysis procedure in order to discard redundant equations based on roughly similar descriptor choices. 

A significant percentage of any compound library will inevitably fall into small clusters unsuitable to rigorous statistical evaluation. These must be considered separately - in our case, using diversity analysis with BCUT descriptors [39] to supplement the list derived from clustering. Throughout this process, we use visualization to assess data quality, identify potential problems such as edge effects, and check trends and patterns. 

The 5 k actives with percent inhibition of 25 to 40% and that feU into clusters of less than five compounds were treated separately using BCUT diversity analysis, as described in Section 6.2.5. A cell-based selection biased by primary activity from six bins per each of six axes yielded 1258 compounds. The combined selection from filtering, clustering, and diversity totaled 6986 compounds representing 3337 ring scaffolds and was submitted for confirmation assays. Note that the full set of 16 k filtered actives contained 9254 ring hashcodes, so the selected set covers 36.1% of the represented scaffolds. Because of the presence of duplicate samples in the corporate screening collection, 7275 samples were pulled and assayed. 

Brown, R.D. Descriptors for diversity analysis. Perspect. Drug. Disc. Des. 1997, 7/8, 31-49. 

Menard, P.R., Lewis, R.A., and Mason, J.S. Chemistry space metrics in diversity analysis, library design, and compound selection. J. Comput. Chem. Inf. Sci. 1998, 38, 1204-1213. 

D.E. Computer-aided molecular diversity analysis and combinatorial library design. Rev. Comput. Chem. 2000, 14... 

Schnur, D.M. Design and diversity analysis of large combinatorial libraries using cell-based methods. /. Chem. Inf. Comput. Sci. 1999, 39, 36-45. 

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,... 

The principal aim of molecular diversity analysis is to identify structurally diverse (synonyms are dissimilar, disparate, and heterogeneous) sets of compounds that can then be tested for bioactivity, the assumption being that a structurally diverse set will generate more structure-activity information than will a set of compounds identified at random. The sets of compounds can be selected from an existing corporate or public database, or can be the result of a systematic combinatorial library design process (4,5). 

Spencer, R. W. (1997) Diversity analysis in high throughput screening. J. Biomol. Screen. 2, 69-70. 

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