Gianti Eleonora, Sartori Luca
Computational Sciences Group, Department of Chemistry (Congenia s.r.l.), Genextra S.p.A., Milan MI 20100, Italy.
J Chem Inf Model. 2008 Nov;48(11):2129-39. doi: 10.1021/ci800219h.
The use of small molecule libraries for fragment-based primary screening (FBS) is a well-known approach to identify protein binders in the low affinity range. However, the search, analysis, and selection of suitable screening fragments can be a lengthy process, because of the large number of compounds that must be analyzed for different levels of ring/substituents identification and submitted to selection/exclusion criteria based on their physicochemical properties. The purpose of the present work is to propose a strategy to identify substructures from databases of known drugs, which can be used as templates for the generation of libraries of "privileged fragments" that are able to provide high-quality hits. The entire process has been developed integrating Pipeline Pilot (Accelrys Inc., San Diego, CA; http://www.accelrys.com ) native components and user-defined molecular files containing ISIS-like substructure query features (Symyx, San Ramon, CA; http://www.symyx.com ). The method is effortless, easy to put in place, and fast enough to be iteratively applied to different sources of druglike compounds.
使用小分子文库进行基于片段的初筛（FBS）是一种在低亲和力范围内识别蛋白质结合物的知名方法。然而，由于必须针对不同水平的环/取代基识别分析大量化合物，并根据其物理化学性质提交至选择/排除标准，因此寻找、分析和选择合适的筛选片段可能是一个漫长的过程。本研究的目的是提出一种从已知药物数据库中识别子结构的策略，该策略可作为生成能够提供高质量命中物的“特权片段”文库的模板。整个过程是通过整合Pipeline Pilot（Accelrys公司，加利福尼亚州圣地亚哥；http://www.accelrys.com ）原生组件和包含ISIS类子结构查询功能的用户定义分子文件（Symyx公司，加利福尼亚州圣拉蒙；http://www.symyx.com ）来开发的。该方法简便易行，易于实施，且速度足够快，可迭代应用于不同来源的类药物化合物。
