Comparative Analysis of Protein Surface Hydrophobicity Maps Determined by Sparse Sampling INDUS and Spatial Aggregation Propensity

生物系统 背景(考古学) 化学 折叠(DSP实现) 表面蛋白 蛋白质折叠 曲面(拓扑) 疏水效应 化学物理 有机化学 数学 生物化学 几何学 生物 病毒学 古生物学 工程类 电气工程
作者
Imee Sinha,Shekhar Garde,Steven M. Cramer
出处
期刊:Journal of Physical Chemistry B [American Chemical Society]
卷期号:127 (48): 10304-10314 被引量:3
标识
DOI:10.1021/acs.jpcb.3c04902
摘要

Protein surface hydrophobicity plays a central role in various biological processes such as protein folding and aggregation, as well as in the design and manufacturing of biotherapeutics. While the hydrophobicity of protein surface patches has been linked to their constituent residue hydropathies, recent research has shown that protein surface hydrophobicity is more complex and characterized by the response of water to these surfaces. In this work, we employ water density perturbations to map the surface hydrophobicity of a set of model proteins using sparse indirect umbrella sampling simulations (SSI). This technique is used to identify hydrophobic surface patches for the set of model proteins, and the results are compared to those obtained from the widely adopted spatial aggregation propensity (SAP) technique. While SAP-based calculations show agreement with SSI in some cases, there are several examples of disagreement. We identify four general classes of difference in behavior and study factors that contribute to these differences. We find that the SAP method can sometimes mask the effect of weakly nonpolar or isolated nonpolar residues that can lead to strong hydrophobic patches on the protein surface. In addition, hydrophobic patches identified by SAP can exhibit shifts in both position and strength on the SSI map. Our results demonstrate that the combination of topography and chemical context controls the hydrophobicity of a given patch above and beyond the intrinsic polarity of the residues present on the patch surface. The availability of more accurate protein hydrophobicity maps in concert with new classes of hydrophobic molecular descriptors may create significant opportunities for in silico prediction of protein behavior for a range of applications, such as protein design, biomanufacturability, and downstream bioprocessing.
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
yjh123应助十三号失眠采纳,获得100
刚刚
yy发布了新的文献求助10
1秒前
花开那年完成签到,获得积分10
2秒前
surgeon发布了新的文献求助10
2秒前
任性的曼卉完成签到,获得积分10
3秒前
3秒前
3秒前
wanci应助科研通管家采纳,获得10
3秒前
ding应助科研通管家采纳,获得10
3秒前
3秒前
顾矜应助科研通管家采纳,获得10
4秒前
nnnn发布了新的文献求助10
4秒前
Lucas应助科研通管家采纳,获得10
4秒前
Mia完成签到 ,获得积分10
4秒前
SciGPT应助科研通管家采纳,获得10
4秒前
慕青应助科研通管家采纳,获得50
4秒前
5秒前
molihuakai应助科研通管家采纳,获得10
5秒前
李健应助科研通管家采纳,获得10
5秒前
lixinglei应助科研通管家采纳,获得20
5秒前
5秒前
沈小小应助科研通管家采纳,获得10
5秒前
小马甲应助科研通管家采纳,获得10
5秒前
雪山飞龙发布了新的文献求助50
5秒前
斯文败类应助科研通管家采纳,获得10
6秒前
小二郎应助科研通管家采纳,获得10
6秒前
小蘑菇应助科研通管家采纳,获得10
6秒前
木木完成签到 ,获得积分10
6秒前
华仔应助科研通管家采纳,获得10
6秒前
阳光完成签到,获得积分10
6秒前
彭于晏应助科研通管家采纳,获得10
6秒前
爆米花应助科研通管家采纳,获得10
6秒前
6秒前
今后应助科研通管家采纳,获得10
7秒前
LJW完成签到 ,获得积分10
7秒前
lixinglei应助科研通管家采纳,获得20
7秒前
李健应助科研通管家采纳,获得10
7秒前
7秒前
斯文败类应助科研通管家采纳,获得10
7秒前
星辰大海应助科研通管家采纳,获得10
7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
Matrix Methods in Data Mining and Pattern Recognition Second Edition 510
Discerning Saints: Moralization of Intrinsic Motivation and Selective Prosociality at Work 500
Handbuch Trainingswissenschaft – Trainingslehre 500
Additive Manufacturing Design and Applications (ASM Handbook, Volume 24A) 500
Variations: A More Diverse Picture of Contemporary Art 400
Induction Heating and Heat Treatment (ASM Handbook, Volume 4C) 300
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 7588181
求助须知:如何正确求助?哪些是违规求助? 9166458
关于积分的说明 19618533
捐赠科研通 7168284
什么是DOI,文献DOI怎么找? 3266975
关于科研通互助平台的介绍 2431879
邀请新用户注册赠送积分活动 2258921