G protein-coupled receptors: In silico drug discovery in 3D

作者
Oren M. Becker,Yael Marantz,Sharon Shacham,Boaz Inbal,Alexander Heifetz,Ori Kalid,Shay Bar‐Haim,Dora Toledo Warshaviak,Merav Fichman,Silvia Noiman
出处
期刊:Proceedings of the National Academy of Sciences of the United States of America [National Academy of Sciences]
卷期号:101 (31): 11304-11309 被引量:146
标识
DOI:10.1073/pnas.0401862101
摘要

The application of structure-based in silico methods to drug discovery is still considered a major challenge, especially when the x-ray structure of the target protein is unknown. Such is the case with human G protein-coupled receptors (GPCRs), one of the most important families of drug targets, where in the absence of x-ray structures, one has to rely on in silico 3D models. We report repeated success in using ab initio in silico GPCR models, generated by the predict method, for blind in silico screening when applied to a set of five different GPCR drug targets. More than 100,000 compounds were typically screened in silico for each target, leading to a selection of <100 "virtual hit" compounds to be tested in the lab. In vitro binding assays of the selected compounds confirm high hit rates, of 12-21% (full dose-response curves, Ki < 5 microM). In most cases, the best hit was a novel compound (New Chemical Entity) in the 1- to 100-nM range, with very promising pharmacological properties, as measured by a variety of in vitro and in vivo assays. These assays validated the quality of the hits as lead compounds for drug discovery. The results demonstrate the usefulness and robustness of ab initio in silico 3D models and of in silico screening for GPCR drug discovery.

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
zouzh发布了新的文献求助10
2秒前
咯噔完成签到,获得积分10
3秒前
深情安青应助tkx是流氓兔采纳,获得10
4秒前
nanfeng发布了新的文献求助10
5秒前
梦自然完成签到 ,获得积分10
6秒前
6秒前
wudan发布了新的文献求助10
6秒前
从容发布了新的文献求助10
6秒前
浩浩浩完成签到,获得积分10
9秒前
9秒前
爱的看到完成签到,获得积分10
9秒前
科研通AI6.4应助lexiao采纳,获得10
10秒前
10秒前
13秒前
门前大桥下应助仁爱乐萱采纳,获得10
13秒前
13秒前
从容发布了新的文献求助10
16秒前
豆豆发布了新的文献求助10
17秒前
17秒前
18秒前
橙子一直跑完成签到 ,获得积分10
18秒前
20秒前
20秒前
21秒前
lexiao完成签到,获得积分10
21秒前
廖智慧完成签到,获得积分10
22秒前
CodeCraft应助星夜冰光采纳,获得30
23秒前
凤起董完成签到,获得积分10
23秒前
wudan完成签到,获得积分10
23秒前
24秒前
24秒前
27秒前
27秒前
Lucas应助苗条的一兰采纳,获得10
27秒前
yanzi发布了新的文献求助10
28秒前
善良曼寒完成签到,获得积分10
28秒前
豆豆完成签到,获得积分20
28秒前
小马完成签到,获得积分10
29秒前
lexiao发布了新的文献求助10
29秒前
31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
2026年中国辛酸癸酸聚乙二醇甘油酯行业市场现状调查及投资机会研判报告 1000
2026年中国辛酸癸酸聚乙二醇甘油酯行业市场规模及竞争格局分析报告 1000
48V Low-voltage Power Distribution Network (PDN) Architecture Industry Report, 2024 800
Fundamentals of Pharmaceutical and Biologics Regulations: A Global Perspective, Second Edition 700
Resiliency Scale for Adolescents--Chinese Version 600
Matrix Methods in Data Mining and Pattern Recognition Second Edition 510
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 7319914
求助须知:如何正确求助?哪些是违规求助? 8935558
关于积分的说明 18942683
捐赠科研通 6978402
什么是DOI,文献DOI怎么找? 3214414
关于科研通互助平台的介绍 2382311
邀请新用户注册赠送积分活动 2193506