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创建并虚拟筛选荧光标记化合物数据库以发现靶点特异性分子探针。

Creating and virtually screening databases of fluorescently-labelled compounds for the discovery of target-specific molecular probes.

作者信息

Kamstra Rhiannon L, Dadgar Saedeh, Wigg John, Chowdhury Morshed A, Phenix Christopher P, Floriano Wely B

机构信息

Department of Chemistry, Lakehead University, Thunder Bay, ON, P7B 5E1, Canada.

出版信息

J Comput Aided Mol Des. 2014 Nov;28(11):1129-42. doi: 10.1007/s10822-014-9789-0. Epub 2014 Aug 24.

Abstract

Our group has recently demonstrated that virtual screening is a useful technique for the identification of target-specific molecular probes. In this paper, we discuss some of our proof-of-concept results involving two biologically relevant target proteins, and report the development of a computational script to generate large databases of fluorescence-labelled compounds for computer-assisted molecular design. The virtual screening of a small library of 1,153 fluorescently-labelled compounds against two targets, and the experimental testing of selected hits reveal that this approach is efficient at identifying molecular probes, and that the screening of a labelled library is preferred over the screening of base compounds followed by conjugation of confirmed hits. The automated script for library generation explores the known reactivity of commercially available dyes, such as NHS-esters, to create large virtual databases of fluorescence-tagged small molecules that can be easily synthesized in a laboratory. A database of 14,862 compounds, each tagged with the ATTO680 fluorophore was generated with the automated script reported here. This library is available for downloading and it is suitable for virtual ligand screening aiming at the identification of target-specific fluorescent molecular probes.

摘要

我们的团队最近证明,虚拟筛选是一种用于识别靶点特异性分子探针的有用技术。在本文中,我们讨论了一些涉及两种生物学相关靶蛋白的概念验证结果,并报告了一个计算脚本的开发,该脚本用于生成用于计算机辅助分子设计的荧光标记化合物大型数据库。针对两个靶点对一个包含1153种荧光标记化合物的小型文库进行虚拟筛选,并对选定的命中化合物进行实验测试,结果表明这种方法在识别分子探针方面是有效的,并且与先筛选基础化合物然后对确认的命中化合物进行缀合相比,筛选标记文库更可取。用于文库生成的自动化脚本探索了市售染料(如NHS酯)的已知反应性,以创建可在实验室轻松合成的荧光标记小分子的大型虚拟数据库。使用本文报道的自动化脚本生成了一个包含14862种化合物的数据库,每种化合物都标记有ATTO680荧光团。该文库可供下载,适用于旨在识别靶点特异性荧光分子探针的虚拟配体筛选。

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