Fine-tuning activation specificity of G-protein-coupled receptors via automated path searching

受体 G蛋白偶联受体 化学 S1PR1型 生物发光 锚蛋白重复序列 生物系统 生物物理学 生物 生物化学 基因 癌症研究 血管内皮生长因子A 血管内皮生长因子 血管内皮生长因子受体
作者
Rujuan Ti,Bin Pang,Leiye Yu,Bing Siang Gan,Wenzhuo Ma,Arieh Warshel,Ruobing Ren,Lizhe Zhu
出处
期刊:Proceedings of the National Academy of Sciences of the United States of America [National Academy of Sciences]
卷期号:121 (8): e2317893121-e2317893121 被引量:11
标识
DOI:10.1073/pnas.2317893121
摘要

Physics-based simulation methods can grant atomistic insights into the molecular origin of the function of biomolecules. However, the potential of such approaches has been hindered by their low efficiency, including in the design of selective agonists where simulations of myriad protein–ligand combinations are necessary. Here, we describe an automated input-free path searching protocol that offers (within 14 d using Graphics Processing Unit servers) a minimum free energy path (MFEP) defined in high-dimension configurational space for activating sphingosine-1-phosphate receptors (S1PRs) by arbitrary ligands. The free energy distributions along the MFEP for four distinct ligands and three S1PRs reached a remarkable agreement with Bioluminescence Resonance Energy Transfer (BRET) measurements of G-protein dissociation. In particular, the revealed transition state structures pointed out toward two S1PR3 residues F263/I284, that dictate the preference of existing agonists CBP307 and BAF312 on S1PR1/5. Swapping these residues between S1PR1 and S1PR3 reversed their response to the two agonists in BRET assays. These results inspired us to design improved agonists with both strong polar head and bulky hydrophobic tail for higher selectivity on S1PR1. Through merely three in silico iterations, our tool predicted a unique compound scaffold. BRET assays confirmed that both chiral forms activate S1PR1 at nanomolar concentration, 1 to 2 orders of magnitude less than those for S1PR3/5. Collectively, these results signify the promise of our approach in fine agonist design for G-protein-coupled receptors.
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
Owen应助Xyoung采纳,获得10
1秒前
fern发布了新的文献求助10
1秒前
3秒前
3秒前
3秒前
维多利亚发布了新的文献求助10
4秒前
5秒前
科研通AI6.4应助ZGG采纳,获得10
5秒前
xuan发布了新的文献求助10
8秒前
8秒前
qiqi完成签到,获得积分10
8秒前
筱亦发布了新的文献求助10
9秒前
mylsdy完成签到,获得积分20
10秒前
11秒前
12秒前
图图to发布了新的文献求助10
12秒前
Lvj完成签到,获得积分20
13秒前
德兰完成签到,获得积分10
13秒前
852应助明理的秀采纳,获得10
13秒前
senli2018发布了新的文献求助10
14秒前
14秒前
CHEN完成签到,获得积分10
14秒前
14秒前
15秒前
15秒前
研友_RLN2yL完成签到,获得积分10
16秒前
Lvj发布了新的文献求助10
16秒前
xuan发布了新的文献求助10
17秒前
fern完成签到,获得积分10
18秒前
nian完成签到,获得积分10
18秒前
19秒前
菲菲发布了新的文献求助10
20秒前
xixi发布了新的文献求助10
21秒前
蛋黄酱发布了新的文献求助30
23秒前
23秒前
叮叮咚咚完成签到,获得积分10
23秒前
英俊的铭应助sakuya采纳,获得30
24秒前
25秒前
xuan发布了新的文献求助10
26秒前
26秒前
高分求助中
Markov Chain Monte Carlo 10000
(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
Common Foundations of American and East Asian Modernisation: From Alexander Hamilton to Junichero Koizumi 5000
Pediatric Dermoscopy Trichoscopy & Onychoscopy 2030
Matrix Methods in Data Mining and Pattern Recognition Second Edition 610
Handbuch Trainingswissenschaft – Trainingslehre 500
Additive Manufacturing Design and Applications (ASM Handbook, Volume 24A) 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 7576578
求助须知:如何正确求助?哪些是违规求助? 9156162
关于积分的说明 19587874
捐赠科研通 7160479
什么是DOI,文献DOI怎么找? 3265037
关于科研通互助平台的介绍 2430187
邀请新用户注册赠送积分活动 2255662