Large-Scale Analysis of Bioactive Ligand Conformational Strain Energy by Ab Initio Calculation

蛋白质数据库 分子内力 化学 从头算 分子力学 晶格能 能量最小化 分子动力学 结晶学 配体(生物化学) 计算化学 晶体结构 立体化学 有机化学 受体 生物化学
作者
Jiahui Tong,Suwen Zhao
出处
期刊:Journal of Chemical Information and Modeling [American Chemical Society]
卷期号:61 (3): 1180-1192 被引量:29
标识
DOI:10.1021/acs.jcim.0c01197
摘要

Ligand conformational strain energy (LCSE) plays an important role in virtual screening and lead optimization. While various studies have provided insights into LCSE for small-molecule ligands in the Protein Data Bank (PDB), conclusions are inconsistent mainly due to small datasets, poor quality control of crystal structures, and molecular mechanics (MM) or low-level quantum mechanics (QM) calculations. Here, we built a high-quality dataset (LigBoundConf) of 8145 ligand-bound conformations from PDB crystal structures and calculated LCSE at the M062X-D3/ma-TZVPP (SMD)//M062X-D3/def2-SVP(SMD) level for each case in the dataset. The mean/median LCSE is 4.6/3.7 kcal/mol for 6672 successfully calculated cases, which is significantly lower than the estimates based on molecular mechanics in many previous analyses. Especially, when removing ligands with nonaromatic ring(s) that are prone to have large LCSEs due to electron density overfitting, the mean/median LCSE was reduced to 3.3/2.5 kcal/mol. We further reveal that LCSE is correlated with several ligand properties, including formal atomic charge, molecular weight, number of rotatable bonds, and number of hydrogen-bond donors and acceptors. In addition, our results show that although summation of torsion strains is a good approximation of LCSE for most cases, for a small fraction (about 6%) of our dataset, it underestimates LCSEs if ligands could form nonlocal intramolecular interactions in the unbound state. Taken together, our work provides a comprehensive profile of LCSE for ligands in PDB, which could help ligand conformation generation, ligand docking pose evaluation, and lead optimization.
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
曾经山柏完成签到,获得积分10
刚刚
酷波er应助俊逸的鲜花采纳,获得10
刚刚
芝士椰果完成签到,获得积分10
1秒前
科研学徒发布了新的文献求助10
2秒前
bobo发布了新的文献求助10
2秒前
4秒前
专注的小凝关注了科研通微信公众号
4秒前
5秒前
HAHA完成签到,获得积分10
5秒前
6秒前
yuan完成签到,获得积分20
8秒前
完美凝海完成签到,获得积分10
8秒前
核桃发布了新的文献求助10
8秒前
Ava应助bcc666采纳,获得10
9秒前
10秒前
搜集达人应助aganer采纳,获得10
12秒前
Ting5201完成签到 ,获得积分10
14秒前
爆米花应助柔弱糖豆采纳,获得10
15秒前
科研韭菜完成签到 ,获得积分10
15秒前
孙文霞完成签到,获得积分10
15秒前
16秒前
wanci应助你可真下饭采纳,获得10
16秒前
共享精神应助科研通管家采纳,获得10
16秒前
勤奋的秋寒完成签到,获得积分10
16秒前
英姑应助科研通管家采纳,获得10
16秒前
斯文败类应助科研通管家采纳,获得10
16秒前
bkagyin应助科研通管家采纳,获得30
16秒前
田様应助科研通管家采纳,获得10
16秒前
浮游应助科研通管家采纳,获得10
16秒前
orixero应助科研通管家采纳,获得10
16秒前
华仔应助科研通管家采纳,获得10
16秒前
斯文败类应助科研通管家采纳,获得10
16秒前
Hello应助科研通管家采纳,获得10
16秒前
17秒前
FashionBoy应助科研通管家采纳,获得10
17秒前
17秒前
完美世界应助科研通管家采纳,获得10
17秒前
李爱国应助科研通管家采纳,获得10
17秒前
dddd应助科研通管家采纳,获得10
17秒前
呵呵应助科研通管家采纳,获得50
17秒前
高分求助中
Signals, Systems, and Signal Processing 610
Annie Ernaux: De la perte au corps glorieux 600
Petrology and Plate Tectonics,2025 500
Circular Polar Constellations Providing Continuous Single or Multiple Coverage Above a Specified Latitude 400
Burger's Medicinal Chemistry and Drug Discovery 400
Probability and Stochastic Processes 333
New directions for experimental lessons in science teaching: Myth, Mystery, Necessity? by Emily K. da Silva Cunha Souto (Author), Flávia Lins Silva (Author) 333
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 6742762
求助须知:如何正确求助?哪些是违规求助? 8473912
关于积分的说明 18075779
捐赠科研通 6012453
什么是DOI,文献DOI怎么找? 3003900
邀请新用户注册赠送积分活动 1980422
关于科研通互助平台的介绍 1945325