Suppr超能文献

片段结合蛋白的共溶剂模拟确定引导先导化合物生长的热点。

Cosolvent Simulations with Fragment-Bound Proteins Identify Hot Spots to Direct Lead Growth.

机构信息

Department of Medicinal Chemistry, College of Pharmacy, 428 Church Street, Ann Arbor, Michigan 48109-1065, United States.

出版信息

J Chem Theory Comput. 2022 Jun 14;18(6):3829-3844. doi: 10.1021/acs.jctc.1c01054. Epub 2022 May 9.

Abstract

In drug design, chemical groups are sequentially added to improve a weak-binding fragment into a tight-binding lead molecule. Often, the direction to make these additions is unclear, and there are numerous chemical modifications to choose. Lead development can be guided by crystal structures of the fragment-bound protein, but this alone is unable to capture structural changes like closing or opening of the binding site and any side-chain movements. Accounting for adaptation of the site requires a dynamic approach. Here, we use molecular dynamics calculations of small organic solvents with protein-fragment pairs to reveal the nearest "hot spots". These close hot spots show the direction to make appropriate additions and suggest types of chemical modifications that could improve binding affinity. Mixed-solvent molecular dynamics (MixMD) is a cosolvent simulation technique that is well established for finding binding "hot spots" in active sites and allosteric sites of proteins. We simulated 20 fragment-bound and apo forms of key pharmaceutical targets to map out hot spots for potential lead space. Furthermore, we analyzed whether the presence of a fragment facilitates the probes' binding in the lead space, a type of binding cooperativity. To the best of our knowledge, this is the first use of cosolvent MD conducted with bound inhibitors in the simulation. Our work provides a general framework to extract molecular features of binding sites to choose chemical groups for growing lead molecules. Of the 20 systems, 17 systems were well mapped by MixMD. For the three not-mapped systems, two had lead growth out into solution away from the protein, and the third had very small modifications which indicated no nearby hot spots. Therefore, our lack of mapping in three systems was appropriate given the experimental data (true-negative cases). The simulations are run for very short time scales, making this method tractable for use in the pharmaceutical industry.

摘要

在药物设计中,通过依次添加化学基团,将弱结合片段改良为强结合的先导分子。通常,这些添加的方向并不明确,并且有许多化学修饰可供选择。先导化合物的开发可以通过结合蛋白的晶体结构来指导,但仅这一点无法捕捉到结合位点的关闭或打开以及任何侧链运动等结构变化。要考虑到该位点的适应性,需要采用动态方法。在这里,我们使用小分子有机溶剂与蛋白-片段对的分子动力学计算来揭示最近的“热点”。这些紧密的热点显示了进行适当添加的方向,并提出了可能提高结合亲和力的化学修饰类型。混合溶剂分子动力学(MixMD)是一种溶剂模拟技术,已被广泛用于寻找蛋白质活性位点和别构位点的结合“热点”。我们模拟了 20 个关键药物靶标的片段结合和无配体形式,以绘制潜在先导化合物空间的热点图。此外,我们分析了片段的存在是否有利于探针在先导化合物空间中的结合,这是一种结合协同作用。据我们所知,这是首次在模拟中使用结合抑制剂进行溶剂 MD。我们的工作提供了一个通用框架,用于提取结合位点的分子特征,以选择用于生长先导分子的化学基团。在所研究的 20 个系统中,有 17 个系统可以很好地通过 MixMD 进行映射。对于未映射的三个系统,有两个系统的先导化合物生长到远离蛋白质的溶液中,第三个系统的修饰非常小,表明没有附近的热点。因此,考虑到实验数据(真阴性情况),我们在三个系统中没有进行映射是合适的。模拟的时间尺度非常短,使得这种方法在制药行业中具有可操作性。

相似文献

3
Moving Beyond Active-Site Detection: MixMD Applied to Allosteric Systems.超越活性位点检测:MixMD应用于变构系统
J Phys Chem B. 2016 Aug 25;120(33):8685-95. doi: 10.1021/acs.jpcb.6b03515. Epub 2016 Jun 17.
7
Predicting Displaceable Water Sites Using Mixed-Solvent Molecular Dynamics.利用混合溶剂分子动力学预测可置换水的位置。
J Chem Inf Model. 2018 Feb 26;58(2):305-314. doi: 10.1021/acs.jcim.7b00268. Epub 2018 Jan 16.

本文引用的文献

2
Fragment-to-Lead Medicinal Chemistry Publications in 2018.2018 年片段至先导化合物的药物化学出版物。
J Med Chem. 2020 May 14;63(9):4430-4444. doi: 10.1021/acs.jmedchem.9b01581. Epub 2020 Jan 22.
5
Fragment-to-Lead Medicinal Chemistry Publications in 2017.2017 年片段至先导化合物药物化学出版物
J Med Chem. 2019 Apr 25;62(8):3857-3872. doi: 10.1021/acs.jmedchem.8b01472. Epub 2018 Nov 21.

文献AI研究员

20分钟写一篇综述,助力文献阅读效率提升50倍。

立即体验

用中文搜PubMed

大模型驱动的PubMed中文搜索引擎

马上搜索

文档翻译

学术文献翻译模型,支持多种主流文档格式。

立即体验