Medicinal Chemistry Projects Requiring Imaginative Structure-Based Drug Design Methods

对接(动物) 药效团 药物发现 计算生物学 化学 蛋白质-配体对接 组合化学 虚拟筛选 小分子 药品 立体化学 计算机科学 生物化学 药理学 生物 医学 护理部
作者
Nicolas Moitessier,Joshua Pottel,Éric Therrien,Pablo Englebienne,Zhaomin Liu,Anna Tomberg,Christopher R. Corbeil
出处
期刊:Accounts of Chemical Research [American Chemical Society]
卷期号:49 (9): 1646-1657 被引量:73
标识
DOI:10.1021/acs.accounts.6b00185
摘要

Computational methods for docking small molecules to proteins are prominent in drug discovery. There are hundreds, if not thousands, of documented examples-and several pertinent cases within our research program. Fifteen years ago, our first docking-guided drug design project yielded nanomolar metalloproteinase inhibitors and illustrated the potential of structure-based drug design. Subsequent applications of docking programs to the design of integrin antagonists, BACE-1 inhibitors, and aminoglycosides binding to bacterial RNA demonstrated that available docking programs needed significant improvement. At that time, docking programs primarily considered flexible ligands and rigid proteins. We demonstrated that accounting for protein flexibility, employing displaceable water molecules, and using ligand-based pharmacophores improved the docking accuracy of existing methods-enabling the design of bioactive molecules. The success prompted the development of our own program, Fitted, implementing all of these aspects. The primary motivation has always been to respond to the needs of drug design studies; the majority of the concepts behind the evolution of Fitted are rooted in medicinal chemistry projects and collaborations. Several examples follow: (1) Searching for HDAC inhibitors led us to develop methods considering drug-zinc coordination and its effect on the pKa of surrounding residues. (2) Targeting covalent prolyl oligopeptidase (POP) inhibitors prompted an update to Fitted to identify reactive groups and form bonds with a given residue (e.g., a catalytic residue) when the geometry allows it. Fitted-the first fully automated covalent docking program-was successfully applied to the discovery of four new classes of covalent POP inhibitors. As a result, efficient stereoselective syntheses of a few screening hits were prioritized rather than synthesizing large chemical libraries-yielding nanomolar inhibitors. (3) In order to study the metabolism of POP inhibitors by cytochrome P450 enzymes (CYPs)-for toxicology studies-the program Impacts was derived from Fitted and helped us to reveal a complex metabolism with unforeseen stereocenter isomerizations. These efforts, combined with those of other docking software developers, have strengthened our understanding of the complex drug-protein binding process while providing the medicinal chemistry community with useful tools that have led to drug discoveries. In this Account, we describe our contributions over the past 15 years-within their historical context-to the design of drug candidates, including BACE-1 inhibitors, POP covalent inhibitors, G-quadruplex binders, and aminoglycosides binding to nucleic acids. We also remark the necessary developments of docking programs, specifically Fitted, that enabled structure-based design to flourish and yielded multiple fruitful, rational medicinal chemistry campaigns.
最长约 10秒,即可获得该文献文件

科研通智能强力驱动
Strongly Powered by AbleSci AI
科研通是完全免费的文献互助平台,具备全网最快的应助速度,最高的求助完成率。 对每一个文献求助,科研通都将尽心尽力,给求助人一个满意的交代。
实时播报
刚刚
苏沐阳发布了新的文献求助10
刚刚
1秒前
1秒前
小零完成签到,获得积分10
2秒前
xbz123qwe完成签到,获得积分10
2秒前
开朗雪珍发布了新的文献求助30
2秒前
li发布了新的文献求助10
2秒前
Yue完成签到 ,获得积分10
3秒前
3秒前
allshestar完成签到 ,获得积分0
4秒前
FashionBoy应助十一采纳,获得10
4秒前
LJS发布了新的文献求助10
4秒前
CJH发布了新的文献求助10
5秒前
5秒前
Nicole发布了新的文献求助10
5秒前
5秒前
uun发布了新的文献求助10
5秒前
sana发布了新的文献求助30
6秒前
彭于晏应助一期一会采纳,获得10
6秒前
yalifeng完成签到,获得积分10
6秒前
6秒前
DHVZA发布了新的文献求助10
8秒前
研友_LapYN8发布了新的文献求助10
8秒前
传奇3应助eye2eye采纳,获得10
9秒前
hehe完成签到,获得积分10
9秒前
完美世界应助苏沐阳采纳,获得10
9秒前
10秒前
苦瓜大王完成签到,获得积分10
10秒前
科目三应助韩嘉玺采纳,获得10
11秒前
11秒前
小元完成签到,获得积分10
12秒前
TTMGF发布了新的文献求助10
12秒前
13171524612关注了科研通微信公众号
12秒前
科研通AI6.2应助Summer采纳,获得10
13秒前
15秒前
zz52678发布了新的文献求助10
16秒前
16秒前
17秒前
科目三应助开朗雪珍采纳,获得10
17秒前
高分求助中
(应助此贴封号)【重要!!请各用户(尤其是新用户)详细阅读】【科研通的精品贴汇总】 10000
Navigating Normative Orders. Interdisciplinary Perspectives 800
Organizational Behavior 510
Management and the Arts 510
Matrix Methods in Data Mining and Pattern Recognition Second Edition 510
CLSI VET01S-2024 Performance Standards for Antimicrobial Disk and Dilution Susceptibility Tests for Bacteria Isolated From Animals (7th Ed) 500
A Case Study on Hotels as Noncongregate Emergency Living Accommodations for Returning Citizens 500
热门求助领域 (近24小时)
化学 材料科学 医学 生物 纳米技术 工程类 有机化学 化学工程 生物化学 计算机科学 内科学 物理 复合材料 催化作用 细胞生物学 无机化学 光电子学 物理化学 电极 基因
热门帖子
关注 科研通微信公众号,转发送积分 7757784
求助须知:如何正确求助?哪些是违规求助? 9304178
关于积分的说明 20278620
捐赠科研通 7341583
什么是DOI,文献DOI怎么找? 3312062
关于科研通互助平台的介绍 2462735
邀请新用户注册赠送积分活动 2325860