Accelerating and Automating the Free Energy Perturbation Absolute Binding Free Energy Calculation with the RED-E Function

自由能微扰 摄动(天文学) 功能(生物学) 高斯分布 能量(信号处理) 统计物理学 化学 计算机科学 生物系统 物理 计算化学 分子动力学 量子力学 进化生物学 生物
作者
Runduo Liu,Wenchao Li,Yufen Yao,Yinuo Wu,Hai‐Bin Luo,Zhe Li
出处
期刊:Journal of Chemical Information and Modeling [American Chemical Society]
卷期号:63 (24): 7755-7767 被引量:5
标识
DOI:10.1021/acs.jcim.3c01670
摘要

The accurate prediction of the binding affinities between small molecules and biological macromolecules plays a fundamental role in structure-based drug design, which is still challenging. The free energy perturbation-based absolute binding free energy (FEP-ABFE) approach has shown potential in its reliability. To correctly calculate the energy related to the ligand being restrained by the receptor, additional restraints between the ligand and the receptor are needed. However, determining the restraint parameters for individual ligands empirically is too trivial to be automated, and usually gives rise to numerical instabilities, which set back the applications of FEP-ABFE. To address these issues, we derived the analytical expression for the probability distribution of energy differences, P(ΔU), during the process of restraint addition, which is called the RED-E (restraint energy distribution at equilibrium position) function. Simulations indicated that the RED-E function can accurately describe P(ΔU) when restraints are added at the equilibrium position. Based on the RED-E function, an automatic restraint selection method was proposed to select the best restraint. With this method, there is a high phase-space overlap between the free and restrained states, such that using a 2-λ perturbation can accurately calculate the free energy of the restraint addition, which is a nearly 6 times acceleration compared with current widely used 12-λ perturbation method. The RED-E function gives insight into the non-Gaussian behavior of the sampled P(ΔU) in certain FEP processes in an analytical way. The highly automated and accelerated restraint selection also makes it possible for the large-scale application of FEP-ABFE in real drug discovery practices.
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
量子星尘发布了新的文献求助10
刚刚
xinxin发布了新的文献求助10
刚刚
傅凡桃完成签到,获得积分10
1秒前
2秒前
虫虫发布了新的文献求助10
2秒前
秋辞完成签到,获得积分10
2秒前
thadzhou完成签到,获得积分10
3秒前
SaSa完成签到,获得积分10
3秒前
芝麻福福完成签到,获得积分10
3秒前
3秒前
呜呜完成签到,获得积分10
3秒前
3秒前
科研通AI5应助LHW采纳,获得10
3秒前
CodeCraft应助花佩剑采纳,获得10
3秒前
3秒前
4秒前
youwu完成签到,获得积分10
5秒前
王文静应助wangwang采纳,获得10
5秒前
kai完成签到,获得积分10
5秒前
毛豆爸爸应助不安豁采纳,获得20
5秒前
恸哭的千鸟完成签到,获得积分10
5秒前
傲娇黄豆完成签到,获得积分10
6秒前
lili完成签到 ,获得积分10
6秒前
金皮卡发布了新的文献求助10
7秒前
HUO完成签到 ,获得积分10
7秒前
7秒前
郭豪琪发布了新的文献求助10
7秒前
7秒前
量子星尘发布了新的文献求助10
8秒前
动人的宫苴完成签到,获得积分10
8秒前
8秒前
科研欣路完成签到,获得积分10
8秒前
小杨同学应助呆萌采纳,获得10
8秒前
竹林风箫完成签到,获得积分10
9秒前
xiaoze发布了新的文献求助10
9秒前
xinxin完成签到,获得积分10
10秒前
花花的明完成签到,获得积分10
10秒前
12秒前
12秒前
圣人海完成签到,获得积分10
12秒前
高分求助中
Production Logging: Theoretical and Interpretive Elements 2700
Neuromuscular and Electrodiagnostic Medicine Board Review 1000
Statistical Methods for the Social Sciences, Global Edition, 6th edition 600
こんなに痛いのにどうして「なんでもない」と医者にいわれてしまうのでしょうか 510
Walter Gilbert: Selected Works 500
An Annotated Checklist of Dinosaur Species by Continent 500
岡本唐貴自伝的回想画集 500
热门求助领域 (近24小时)
化学 材料科学 医学 生物 工程类 有机化学 物理 生物化学 纳米技术 计算机科学 化学工程 内科学 复合材料 物理化学 电极 遗传学 量子力学 基因 冶金 催化作用
热门帖子
关注 科研通微信公众号,转发送积分 3661305
求助须知:如何正确求助?哪些是违规求助? 3222424
关于积分的说明 9745270
捐赠科研通 2931993
什么是DOI,文献DOI怎么找? 1605350
邀请新用户注册赠送积分活动 757854
科研通“疑难数据库(出版商)”最低求助积分说明 734569