Libraries virtual screens

Topliss tree and Craig plot Factorial, central composite and D-optimal designs Principal properties of substituents Drug-like properties Combinatorial libraries Virtual screens IV Determining relationships between chemical and biological data A Overview... 

Research projects in pharmaceutical industry that are in an early phase need bioactive chemotypes as potential lead structures for optimization. Hits with a medium or even weak activity can serve as leads if the overall profile looks attractive. HTS of the in-house compound libraries is the most common source of these lead structures. If information about the 3D structure of the target and/or about bioactive ligand(s) is available, virtual screening can be used to add further active chemotypes either from the existing compounds, for example, from vendor catalogues, or from the virtual chemical space, for example, from virtual combinatorial libraries. Virtual screening can also be used to select a subset from the in-house screening collection if a full HTS is not possible due to cost or time limitations. 

Virtual screening assists the selection of compounds for screening in-house libraries and compounds from external suppliers. Two different strategies can be applied ... 

HTS data as well as virtual screening can guide and direct the design of combinatorial libraries. A genetic algorithm (GA) can be applied to the generation of combinatorial libraries [18. The number of compounds accessible by combinatorial synthesis often exceeds the number of compounds which can be syiithcsii ed... 

PRO SELECT One of the first reported tools for the virtual screening of libraries for fit into a protein active site Protherics Molecular Design Ltd. http //www.protherics. com [30]... 

Savchuk NP, Balakin KV. Data mining approaches for enhancement of knowledge-based content of de novo chemical libraries. In Alvarez H, Shoichet B, editors, Virtual screening in drug discovery. New York CRC Press, 2005. p. 121-49. 

Cathepsin D. The design of inhibitors of the aspartyl protease cathepsin D started from a virtual library of peptide analogs that contained the typical hydroxyethylamine isoster for the cleavable peptide bond. As the availability of starting materials would have generated a library of about 1 billion compounds, virtual screening was applied to reduce this multitude of candidate structures to a reasonable number. The backbone of a peptide... 

Shoichet BK. Virtual screening of chemical libraries. Nature 2004 432 862-5. 

Stahl M. Structure-based library design. In Bohm HJ, Schneider G, editors. Virtual screening for bioactive molecules (Vol. 10 of Mannhold R, Kubinyi H, Timmerman H, editors. Methods and principles in medicinal chemistry). Wein-heim Wiley-VCH, 2000, pp. 229-64. 

In modern drug discovery speed and cost control are important in addition to high quality. In silica virtual screening for drugability [159] is a good first step in library... 

Closely related to the use of PSA in virtual screening is its application in the design of combinatorial libraries with optimal properties. These applications are reviewed further in Refs. [46, 47], for example. 

As stated above, an advantage of virtual screening is that any compound, real or virtual, can be screened and the user is not restricted to those compounds available in corporate or external collections. The technology can also be used to screen proposed libraries and even select monomers for a combinatorial library based on 3D fit to the target structure. 

Another group has evaluated self-organizing maps [63] and shape/ pharmacophore models [64]. They developed a new method termed SQUIRREL to compare molecules in terms of both shape and pharmacophore points. Thus from a commercial library of 199,272 compounds, 1926 were selected based on self-organizing maps trained on peroxisome proliferator-activated receptor a (PPARa) "activity islands." The compounds were further evaluated with SQUIRREL and 7 out of 21 molecules selected were found to be active in PPARa. Furthermore, a new virtual screening technique (PhAST) was developed based on representation of molecules as text strings that describe their pharmacophores [65]. 

Roche, O., Trube, G Zuegge, J., Pflimlin, P., Alanine, A. and Schneider, G. (2002) A virtual screening method for prediction of the HERG potassium channel liability of compound libraries. Chembiochem A European Journal of Chemical Biology, 3, 455-459. 

Walters, W. P., Murcko, M.A., Library filtering systems and prediction of drug-like properties, in Virtual screening for bioactive molecules, H.-J. Bohm,G. Schneider, Editors. 2000, Wi-ley-VCH New York. p. 15-32. 

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