Literature DB >> 10821712

Quantized surface complementarity diversity (QSCD): a model based on small molecule-target complementarity.

E A Wintner1, C C Moallemi.   

Abstract

A model of molecular diversity is presented. The model, termed "Quantized Surface Complementarity Diversity" (QSCD), defines molecular diversity by measuring molecular complementarity to a fully enumerated set of theoretical target surfaces. Molecular diversity space is defined as the molecular complement to this set of enumerated surfaces. Using a set of known test compounds, the model is shown to be biologically relevant, consistently scoring known actives as similar. At the resolution of the model, which examines molecules "quantized" into 4.24 A cubic units and treats four points of specific energetic complementarity, the minimum number of compounds needed to fully cover molecular diversity space up to volume 1070 cubic A is estimated to be on the order of 24 million molecules. Most importantly, QSCD allows for individual points in diversity space to be filled by direct modeling of molecular libraries into detailed 3D templates of shape and functionality.

Mesh:

Year:  2000        PMID: 10821712     DOI: 10.1021/jm990504b

Source DB:  PubMed          Journal:  J Med Chem        ISSN: 0022-2623            Impact factor:   7.446


  4 in total

1.  A reagent-based strategy for the design of large combinatorial libraries: a preliminary experimental validation.

Authors:  Gergely M Makara; Huw Nash; Zhongli Zheng; Jean-Paul A Orminati; Edward A Wintner
Journal:  Mol Divers       Date:  2003       Impact factor: 2.943

2.  Mapping protein pockets through their potential small-molecule binding volumes: QSCD applied to biological protein structures.

Authors:  Keith Mason; Nehal M Patel; Aric Ledel; Ciamac C Moallemi; Edward A Wintner
Journal:  J Comput Aided Mol Des       Date:  2004-01       Impact factor: 3.686

3.  Concepts and challenges in quantitative pharmacology and model-based drug development.

Authors:  Liping Zhang; Marc Pfister; Bernd Meibohm
Journal:  AAPS J       Date:  2008-11-12       Impact factor: 4.009

4.  New compounds identified through in silico approaches reduce the α-synuclein expression by inhibiting prolyl oligopeptidase in vitro.

Authors:  Raj Kumar; Rohit Bavi; Min Gi Jo; Venkatesh Arulalapperumal; Ayoung Baek; Shailima Rampogu; Myeong Ok Kim; Keun Woo Lee
Journal:  Sci Rep       Date:  2017-09-07       Impact factor: 4.379

  4 in total

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