Evaluation of the binding performance of flavonoids to estrogen receptor alpha by Autodock, Autodock Vina and Surflex-Dock

自动停靠 码头 对接(动物) 化学 氢键 结合位点 立体化学 组合化学 生物化学 有机化学 分子 生物信息学 医学 护理部 基因
作者
Qiao Xue,Liu Xian,Paul Russell,Jin Li,Wenxiao Pan,Jianjie Fu,Aiqian Zhang
出处
期刊:Ecotoxicology and Environmental Safety [Elsevier BV]
卷期号:233: 113323-113323 被引量:132
标识
DOI:10.1016/j.ecoenv.2022.113323
摘要

Molecular docking is a widely used method to predict the binding modes of small-molecule ligands to the target binding site. However, it remains a challenge to identify the correct binding conformation and the corresponding binding affinity for a series of structurally similar ligands, especially those with weak binding. An understanding of the various relative attributes of popular docking programs is required to ensure a successful docking outcome. In this study, we systematically compared the performance of three popular docking programs, Autodock, Autodock Vina, and Surflex-Dock for a series of structurally similar weekly binding flavonoids (22) binding to the estrogen receptor alpha (ERα). For these flavonoids-ERα interactions, Surflex-Dock showed higher accuracy than Autodock and Autodock Vina. The hydrogen bond overweighting by Autodock and Autodock Vina led to incorrect binding results, while Surflex-Dock effectively balanced both hydrogen bond and hydrophobic interactions. Moreover, the selection of initial receptor structure is critical as it influences the docking conformations of flavonoids-ERα complexes. The flexible docking method failed to further improve the docking accuracy of the semi-flexible docking method for such chemicals. In addition, binding interaction analysis revealed that 8 residues, including Ala350, Glu353, Leu387, Arg394, Phe404, Gly521, His524, and Leu525, are the key residues in ERα-flavonoids complexes. This work provides reference for assessing molecular interactions between ERα and flavonoid-like chemicals and provides instructive information for other environmental chemicals.
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
1秒前
阳光he完成签到,获得积分10
1秒前
张菲菲发布了新的文献求助10
2秒前
玖拾贰完成签到,获得积分20
2秒前
Akim应助123采纳,获得10
2秒前
我是老大应助小鱼采纳,获得10
2秒前
平淡小白菜完成签到,获得积分10
2秒前
14999发布了新的文献求助10
3秒前
爆米花应助fxx采纳,获得10
5秒前
5秒前
5秒前
8秒前
wanci应助cyyyyyyyyyy采纳,获得10
8秒前
9秒前
10秒前
CipherSage应助金福珠采纳,获得10
10秒前
12秒前
12秒前
13秒前
净坛使者完成签到,获得积分10
13秒前
小鱼发布了新的文献求助10
13秒前
14秒前
土豪的琪完成签到,获得积分10
15秒前
兴奋的嚣完成签到 ,获得积分10
15秒前
LL关闭了LL文献求助
16秒前
16秒前
zzzzzz发布了新的文献求助10
18秒前
笑点低炳发布了新的文献求助10
19秒前
无私幼蓉发布了新的文献求助10
19秒前
20秒前
CodeCraft应助蓝02333采纳,获得10
20秒前
LV完成签到 ,获得积分10
20秒前
Hello应助HappyR采纳,获得10
21秒前
orixero应助小麦采纳,获得10
21秒前
21秒前
花筱一完成签到,获得积分10
22秒前
Lucas应助那天晚上我竟然采纳,获得10
23秒前
鱼圆杂铺发布了新的文献求助500
24秒前
24秒前
自由山槐发布了新的文献求助40
25秒前
高分求助中
The Wiley Blackwell Companion to Diachronic and Historical Linguistics 3000
HANDBOOK OF CHEMISTRY AND PHYSICS 106th edition 1000
ASPEN Adult Nutrition Support Core Curriculum, Fourth Edition 1000
AnnualResearch andConsultation Report of Panorama survey and Investment strategy onChinaIndustry 1000
Decentring Leadership 800
Signals, Systems, and Signal Processing 610
GMP in Practice: Regulatory Expectations for the Pharmaceutical Industry 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 物理 内科学 复合材料 催化作用 物理化学 光电子学 电极 细胞生物学 基因 无机化学
热门帖子
关注 科研通微信公众号,转发送积分 6286723
求助须知:如何正确求助?哪些是违规求助? 8105478
关于积分的说明 16952568
捐赠科研通 5352060
什么是DOI,文献DOI怎么找? 2844237
邀请新用户注册赠送积分活动 1821614
关于科研通互助平台的介绍 1677853