Edge weights in a protein elastic network reorganize collective motions and render long-range sensitivity responses

分子动力学 灵敏度(控制系统) 统计物理学 不对称 物理 黑森矩阵 摄动(天文学) 弹道 方向(向量空间) 常量(计算机编程) 特征向量 生物系统 数学 计算机科学 几何学 量子力学 生物 工程类 应用数学 程序设计语言 电子工程
作者
Chieh Cheng Yu,Nixon Raj,Jhih‐Wei Chu
出处
期刊:Journal of Chemical Physics [American Institute of Physics]
卷期号:156 (24) 被引量:2
标识
DOI:10.1063/5.0095107
摘要

The effects of inter-residue interactions on protein collective motions are analyzed by comparing two elastic network models (ENM)-structural contact ENM (SC-ENM) and molecular dynamics (MD)-ENM-with the edge weights computed from an all-atom MD trajectory by structure-mechanics statistical learning. A theoretical framework is devised to decompose the eigenvalues of ENM Hessian into contributions from individual springs and to compute the sensitivities of positional fluctuations and covariances to spring constant variation. Our linear perturbation approach quantifies the response mechanisms as softness modulation and orientation shift. All contacts of Cα positions in SC-ENM have an identical spring constant by fitting the profile of root-of-mean-squared-fluctuation calculated from an all-atom MD simulation, and the same trajectory data are also used to compute the specific spring constant of each contact as an MD-ENM edge weight. We illustrate that the soft-mode reorganization can be understood in terms of gaining weights along the structural contacts of low elastic strengths and loosing magnitude along those of high rigidities. With the diverse mechanical strengths encoded in protein dynamics, MD-ENM is found to have more pronounced long-range couplings and sensitivity responses with orientation shift identified as a key player in driving the specific residues to have high sensitivities. Furthermore, the responses of perturbing the springs of different residues are found to have asymmetry in the action-reaction relationship. In understanding the mutation effects on protein functional properties, such as long-range communications, our results point in the directions of collective motions as a major effector.
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
莫之白发布了新的文献求助10
1秒前
JY发布了新的文献求助10
2秒前
4秒前
JY完成签到,获得积分10
8秒前
8秒前
chenyu发布了新的文献求助20
9秒前
康谨发布了新的文献求助100
11秒前
11秒前
13秒前
jtj完成签到 ,获得积分10
13秒前
章章完成签到,获得积分10
14秒前
科研通AI2S应助科研通管家采纳,获得10
15秒前
科研通AI5应助科研通管家采纳,获得10
15秒前
bean应助科研通管家采纳,获得10
15秒前
科研通AI5应助科研通管家采纳,获得10
15秒前
思源应助科研通管家采纳,获得10
15秒前
zhzzhz应助科研通管家采纳,获得10
15秒前
15秒前
wy.he应助科研通管家采纳,获得10
15秒前
无花果应助科研通管家采纳,获得10
15秒前
上官若男应助科研通管家采纳,获得10
15秒前
科研通AI5应助科研通管家采纳,获得10
15秒前
大模型应助科研通管家采纳,获得10
15秒前
领导范儿应助科研通管家采纳,获得10
16秒前
bean应助科研通管家采纳,获得10
16秒前
Ava应助科研通管家采纳,获得10
16秒前
wy.he应助科研通管家采纳,获得10
16秒前
科研通AI5应助科研通管家采纳,获得10
16秒前
李爱国应助科研通管家采纳,获得10
16秒前
wy.he应助科研通管家采纳,获得10
16秒前
梅哈完成签到 ,获得积分10
16秒前
00完成签到,获得积分10
17秒前
starwan发布了新的文献求助10
17秒前
张张发布了新的文献求助10
18秒前
SciGPT应助qiehahah采纳,获得10
18秒前
阜睿发布了新的文献求助10
18秒前
小马甲应助奇迹大多采纳,获得10
21秒前
23秒前
abib完成签到,获得积分10
23秒前
Upupupiu完成签到 ,获得积分10
24秒前
高分求助中
【此为提示信息,请勿应助】请按要求发布求助,避免被关 20000
ISCN 2024 – An International System for Human Cytogenomic Nomenclature (2024) 3000
Continuum Thermodynamics and Material Modelling 2000
Encyclopedia of Geology (2nd Edition) 2000
105th Edition CRC Handbook of Chemistry and Physics 1600
Maneuvering of a Damaged Navy Combatant 650
China—Art—Modernity: A Critical Introduction to Chinese Visual Expression from the Beginning of the Twentieth Century to the Present Day 360
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 3776990
求助须知:如何正确求助?哪些是违规求助? 3322387
关于积分的说明 10210034
捐赠科研通 3037721
什么是DOI,文献DOI怎么找? 1666843
邀请新用户注册赠送积分活动 797700
科研通“疑难数据库(出版商)”最低求助积分说明 758012