Computational Design of Lysine Targeting Covalent Binders Using Rosetta

作者
Barr Tivon,Jan Wiese,Matthias Philipp Müller,Ronen Gabizon,Daniel Rauh,Nir London
出处
期刊:Journal of Chemical Information and Modeling [American Chemical Society]
卷期号:65 (11): 5612-5622 被引量:4
标识
DOI:10.1021/acs.jcim.5c00212
摘要

High Resolution Image Download MS PowerPoint Slide Chemical probes that form a covalent bond with their target protein have been established as a powerful tool for investigating proteins and modulating their activity, but until recently were mostly targeting cysteine residues. Covalent binders that target lysine residues are increasingly reported. Covalent binding to lysine involves challenges such as the increased p K a of the side chain and its considerable flexibility. Here, we describe two computational methods to derivatize lysine-binding covalent small-molecules based on known noncovalent binders, approaching the design problem from two opposite directions. In a “ligand-side” approach, we scan different ligand positions to install an electrophile and dock these derivatized ligands into the target protein. In a “protein-side” approach, we install an electrophile on the target lysine and model its conformational space to find suitable installation vectors on the ligand. We applied both of these protocols retrospectively to a data set of electrophilic ligands and to a data set of vitamin B6 covalently bound to a receptor lysine residue. Our ligand-side protocol successfully identified the known covalent binder in 80% and 86% of cases, while the protein-side protocol achieved identification rates of 56% and 82%, respectively. We prospectively validated these protocols by designing and testing a new lysine-targeting MKK7 inhibitor. Mass-spectrometry and crystallography validated the covalent binding to the target lysine. Applying these protocols to a data set of known kinase inhibitors identified high-confidence covalent candidates for more than 200 human kinases, demonstrating the potential impact of our protocols.

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
田様的应助被chenzy采纳,获得10
1秒前
1秒前
学霸业的应助被萝卜花采纳,获得10
2秒前
2秒前
2秒前
sue完成签到,获得积分20
3秒前
善良雪碧完成签到,获得积分10
3秒前
4秒前
熊火焰完成签到,获得积分10
4秒前
wp发布了新的文献求助10
5秒前
优秀的马道完成签到,获得积分10
5秒前
CipherSage的应助被王志杰采纳,获得10
5秒前
6秒前
6秒前
6秒前
谢雷XIELei的应助被云开采纳,获得30
6秒前
xcp发布了新的文献求助10
7秒前
blueming发布了新的文献求助10
7秒前
8秒前
9秒前
铁锅挂面发布了新的文献求助10
9秒前
zjs发布了新的文献求助20
10秒前
10秒前
王林发布了新的文献求助10
10秒前
英俊的铭的应助被eric采纳,获得10
11秒前
今天也要加油鸭完成签到,获得积分10
11秒前
sue发布了新的文献求助30
11秒前
wp完成签到,获得积分10
11秒前
11秒前
凯k发布了新的文献求助10
12秒前
Lucian发布了新的文献求助10
12秒前
1128发布了新的文献求助200
12秒前
萤火虫发布了新的文献求助10
12秒前
烟花的应助被随风而动采纳,获得30
12秒前
救了个命发布了新的文献求助10
13秒前
酷酷绮南发布了新的文献求助10
13秒前
完美世界的应助被江阳宏采纳,获得10
13秒前
bkagyin的应助被甲基绿小恐龙采纳,获得30
14秒前
14秒前
学术雷锋的应助被执着的映之采纳,获得10
15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
Energie-Contracting 1500
Spec 401: Standards for Jet Fuel Facility and Equipment Commissioning and Flushing at Airports, 2026.1 (Original Issue) 1000
Spec 103: Standard for Jet Fuel Quality Control at Airports, Revision 2026.1 1000
Mathematical models in hydrology 1000
Klimaschutzrecht durch den Energiesektor im Mehrebenensystem – Ein Rechtsvergleich 1000
Les Mots du discours 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 计算机科学 工程类 有机化学 化学工程 生物化学 物理 复合材料 内科学 催化作用 光电子学 人工智能 细胞生物学 无机化学 物理化学 数学
热门帖子
关注 科研通微信公众号,转发送积分 8089179
求助须知:如何正确求助?哪些是违规求助? 9502120
关于积分的说明 21429241
捐赠科研通 7660640
什么是DOI,文献DOI怎么找? 3404222
关于科研通互助平台的介绍 2532661
邀请新用户注册赠送积分活动 2442760