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用于分析组合文库和筛选集的新方法:使用HARPick清理设计过程。

New methodology for profiling combinatorial libraries and screening sets: cleaning up the design process with HARPick.

作者信息

Good A C, Lewis R A

机构信息

Rhône-Poulenc Rorer, Dagenham, Essex, United Kingdom.

出版信息

J Med Chem. 1997 Nov 21;40(24):3926-36. doi: 10.1021/jm970403i.

Abstract

Combinatorial chemistry is a tool of increasing importance in the field of ligand design, as it can yield huge increases in the number of compounds available for screening. Unfortunately, it is often the case that the number of molecules which could theoretically be constructed greatly exceeds potential synthesis and screening capacity. For this new technology to be fully exploited, it will become vital to design libraries with reference to the properties of compounds already in existence, if the added value of each new molecular collection is truly to be maximized. Similarly, if we are to take full advantage of the potential of combinatorial chemistry in lead optimization, it is important that our library design paradigms are flexible, with diversity scoring functions that can be modified to suit particular projects. Here these challenges are addressed through the introduction of a novel computer-aided library design tool known as HARPick (heuristic algorithm for reagent picking). The program is accessible to the bench chemist, and incorporates several significant advances over currently available approaches. These include product-based diversity calculations that can be constrained at the reagent level; diversity measures constructed from multiple descriptors; improved pharmacophore key information and full pharmacophore profiling of entire molecular databases. The potential of these improvements to aid in diversity profiling is illustrated through comparison with established methodology, and possible further enhancements are discussed.

摘要

组合化学在配体设计领域是一种越来越重要的工具,因为它能极大地增加可供筛选的化合物数量。不幸的是,理论上可构建的分子数量往往大大超过潜在的合成和筛选能力。要充分利用这项新技术,如果要真正最大化每个新分子库的附加值,那么参照已存在化合物的性质来设计库就变得至关重要。同样,如果我们要充分利用组合化学在先导化合物优化方面的潜力,那么我们的库设计范式必须灵活,要有可修改以适应特定项目的多样性评分函数。在此,通过引入一种名为HARPick(试剂挑选启发式算法)的新型计算机辅助库设计工具来应对这些挑战。该程序可供实验化学家使用,并且相对于目前可用的方法有多项重大进展。这些进展包括可在试剂层面进行约束的基于产物的多样性计算;由多个描述符构建的多样性度量;改进的药效团关键信息以及对整个分子数据库的完整药效团分析。通过与既定方法进行比较,说明了这些改进在辅助多样性分析方面的潜力,并讨论了可能的进一步增强措施。

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