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通过自动导航片段化学空间发现新型 BRD4 配体骨架。

Discovery of Novel BRD4 Ligand Scaffolds by Automated Navigation of the Fragment Chemical Space.

机构信息

Departament de Farmacia i Tecnología Farmacèutica, i Fisicoquímica, Institut de Biomedicina (IBUB), Universitat de Barcelona, Av. Joan XXIII, 27-31, E-08028 Barcelona, Spain.

Laboratory of Medicinal Chemistry (Associated Unit to CSIC), Department of Pharmacology, Toxicology and Medicinal Chemistry, Faculty of Pharmacy and Food Sciences, and Institute of Biomedicine (IBUB), University of Barcelona, Av. Joan XXIII, 27-31, E-08028 Barcelona, Spain.

出版信息

J Med Chem. 2021 Dec 23;64(24):17887-17900. doi: 10.1021/acs.jmedchem.1c01108. Epub 2021 Dec 13.

Abstract

Fragment-based drug discovery (FBDD) is a very effective hit identification method. However, the evolution of fragment hits into suitable leads remains challenging and largely artisanal. Fragment evolution is often scaffold-centric, meaning that its outcome depends crucially on the chemical structure of the starting fragment. Considering that fragment screening libraries cover only a small proportion of the corresponding chemical space, hits should be seen as probes highlighting privileged areas of the chemical space rather than actual starting points. We have developed an automated computational pipeline to mine the chemical space around any specific fragment hit, rapidly finding analogues that share a common interaction motif but are structurally novel and diverse. On a prospective application on the bromodomain-containing protein 4 (BRD4), starting from a known fragment, the platform yields active molecules with nonobvious scaffold changes. The procedure is fast and inexpensive and has the potential to uncover many hidden opportunities in FBDD.

摘要

基于片段的药物发现(FBDD)是一种非常有效的命中鉴定方法。然而,将片段命中物进化为合适的先导物仍然具有挑战性,而且在很大程度上是手工操作。片段进化通常以骨架为中心,这意味着其结果在很大程度上取决于起始片段的化学结构。考虑到片段筛选文库仅覆盖相应化学空间的一小部分,命中物应被视为突出化学空间特权区域的探针,而不是实际的起点。我们开发了一种自动化的计算管道,用于挖掘任何特定片段命中物周围的化学空间,快速找到具有共同相互作用模式但结构新颖多样的类似物。在针对包含溴结构域蛋白 4(BRD4)的前瞻性应用中,从已知的片段开始,该平台产生了具有非明显骨架变化的活性分子。该过程快速且廉价,有可能在 FBDD 中发现许多隐藏的机会。

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