Optimizing Protein–Protein van der Waals Interactions for the AMBER ff9x/ff12 Force Field

作者
Dail Chapman,Jonathan K. Steck,Paul S. Nerenberg
出处
期刊:Journal of Chemical Theory and Computation [American Chemical Society]
卷期号:10 (1): 273-281 被引量:29
标识
DOI:10.1021/ct400610x
摘要

The quality of molecular dynamics (MD) simulations relies heavily on the accuracy of the underlying force field. In recent years, considerable effort has been put into developing more accurate dihedral angle potentials for MD force fields, but relatively little work has focused on the nonbonded parameters, many of which are two decades old. In this work, we assess the accuracy of protein-protein van der Waals interactions in the AMBER ff9x/ff12 force field. Across a test set of 44 neat organic liquids containing the moieties present in proteins, we find root-mean-square (RMS) errors of 1.26 kcal/mol in enthalpy of vaporization and 0.36 g/cm(3) in liquid densities. We then optimize the van der Waals radii and well depths for all of the relevant atom types using these observables, which lowers the RMS errors in enthalpy of vaporization and liquid density of our validation set to 0.59 kcal/mol (53% reduction) and 0.019 g/cm(3) (46% reduction), respectively. Limitations in our parameter optimization were evident for certain atom types, however, and we discuss the implications of these observations for future force field development.

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
Imstemcell完成签到,获得积分10
刚刚
wu先生完成签到,获得积分10
1秒前
bai123发布了新的文献求助10
1秒前
1秒前
落后安青发布了新的文献求助10
2秒前
5111完成签到,获得积分10
2秒前
科研通AI2S应助合适面包采纳,获得10
3秒前
DengLipan应助星宫金魁采纳,获得30
3秒前
3秒前
人类懂王发布了新的文献求助10
4秒前
所所应助Leo采纳,获得10
4秒前
4秒前
Wuyiqin完成签到,获得积分10
6秒前
whb发布了新的文献求助10
7秒前
传奇3应助hh采纳,获得10
9秒前
9秒前
李爱国应助人类懂王采纳,获得10
9秒前
9秒前
10秒前
Ava应助nn采纳,获得10
10秒前
希望天下0贩的0应助nn采纳,获得10
10秒前
佩佩发布了新的文献求助10
10秒前
10秒前
星辰大海应助nn采纳,获得10
10秒前
斯文败类应助nn采纳,获得10
10秒前
顾矜应助老鱼吹浪采纳,获得10
11秒前
李健的粉丝团团长应助nn采纳,获得10
11秒前
科研通AI6.4应助Lynn采纳,获得10
11秒前
bkagyin应助bai123采纳,获得10
11秒前
大强完成签到,获得积分10
13秒前
14秒前
yimi发布了新的文献求助30
14秒前
合适面包发布了新的文献求助10
14秒前
16秒前
拼搏西牛发布了新的文献求助10
16秒前
高欣然完成签到,获得积分10
16秒前
16秒前
人生几何完成签到,获得积分10
18秒前
18秒前
19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
China Pluperfect I: Epistemology of Past and Outside in Chinese Art 520
Matrix Methods in Data Mining and Pattern Recognition Second Edition 510
Governing Growth: Us Industrial Policy from Hamilton to Trump 500
The fast track to determining transfer functions of linear circuits: The student guide 500
The Analytical and Numerical Solution of Electric and Magnetic Fields 500
Synthesis of P-Chiral Phosphine Ligands and Their Applications in Asymmetric Catalysis 400
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 7624552
求助须知:如何正确求助?哪些是违规求助? 9199667
关于积分的说明 19723259
捐赠科研通 7195607
什么是DOI,文献DOI怎么找? 3273562
关于科研通互助平台的介绍 2435728
邀请新用户注册赠送积分活动 2269409