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
刚刚
Jeff完成签到,获得积分10
1秒前
1秒前
杜青发布了新的文献求助10
1秒前
krislan完成签到,获得积分10
1秒前
努力努力再努力给努力努力再努力的求助进行了留言
2秒前
2秒前
2秒前
赵小瑜发布了新的文献求助10
2秒前
cc21完成签到,获得积分10
3秒前
今后应助阿萨十大采纳,获得10
3秒前
cdercder应助酸菜爱生活采纳,获得10
3秒前
3秒前
小岛猫粮发布了新的文献求助10
4秒前
wangxw完成签到,获得积分10
5秒前
zzzz发布了新的文献求助10
5秒前
5秒前
123发布了新的文献求助10
5秒前
淡然丹寒完成签到 ,获得积分10
5秒前
hanm发布了新的文献求助10
6秒前
cc发布了新的文献求助10
7秒前
隐形曼青应助傻聪明蛋采纳,获得10
8秒前
所所应助pubg采纳,获得10
9秒前
严三笑完成签到,获得积分10
10秒前
10秒前
10秒前
supercheese完成签到,获得积分20
10秒前
思源应助Jay采纳,获得10
10秒前
顾矜应助qiting0519采纳,获得30
10秒前
10秒前
10秒前
冷静发布了新的文献求助10
11秒前
13秒前
阿萨十大发布了新的文献求助10
14秒前
JML发布了新的文献求助10
15秒前
GGBond发布了新的文献求助10
15秒前
科研通AI6.4应助杜青采纳,获得10
15秒前
Mcdull完成签到,获得积分10
16秒前
16秒前
淡漠发布了新的文献求助10
17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
Geist der Kunst und Kultur 1000
Resistance Spot Welding Dataset for Automobile Body-in-White Quality Analysis 748
悉尼大学博士学位论文,题目:Modelling and testing of one-sided stitched laminated composites. 作者:Kristopher P. Plain 700
Machine Learning for Asset Management and Pricing 600
Numerical analysis of the coupled atmosphere-ocean models (CAO II). II 600
Models for the coupled atmosphere and ocean 600
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 7407274
求助须知:如何正确求助?哪些是违规求助? 9011814
关于积分的说明 19192850
捐赠科研通 7040519
什么是DOI,文献DOI怎么找? 3232530
关于科研通互助平台的介绍 2394520
邀请新用户注册赠送积分活动 2214735