Relationship between Hot Spot Residues and Ligand Binding Hot Spots in Protein-Protein Interfaces

被引:0
|
作者
Zerbe, Brandon S. [1 ]
Hall, David R. [1 ]
Vajda, Sandor [1 ,2 ]
Whitty, Adrian [2 ]
Kozakov, Dima [1 ]
机构
[1] Boston Univ, Dept Biomed Engn, Boston, MA 02215 USA
[2] Boston Univ, Dept Chem, Boston, MA 02215 USA
关键词
LOCAL STRUCTURAL ALIGNMENT; SMALL-MOLECULE INHIBITORS; X-RAY CRYSTALLOGRAPHY; DRUG DISCOVERY; SOLVENT ACCESSIBILITY; BIOPHYSICAL METHODS; CRYSTAL-STRUCTURES; SITES; IDENTIFICATION; DOMAIN;
D O I
10.1021/ci300175u
中图分类号
R914 [药物化学];
学科分类号
100701 ;
摘要
In the context of protein-protein interactions, the term "hot spot" refers to a residue or cluster of residues that makes a major contribution to the binding free energy, as determined by alanine scanning mutagenesis. In contrast, in pharmaceutical research, a hot spot is a site on a target protein that has high propensity for ligand binding and hence is potentially important for drug discovery. Here we examine the relationship between these two hot spot concepts by comparing alanine scanning data for a set of 15 proteins with results from mapping the protein surfaces for sites that can bind fragment sized small molecules. We find the two types of hot spots are largely complementary; the residues protruding into hot spot regions identified by computational mapping or experimental fragment screening are almost always themselves hot spot residues as defined by alanine scanning experiments. Conversely, a residue that is found by alanine scanning to contribute little to binding rarely interacts with hot spot regions on the partner protein identified by fragment mapping. In spite of the strong correlation between the two hot spot concepts, they fundamentally differ, however. In particular, while identification of a hot spot by alanine scanning establishes the potential to generate substantial interaction energy with a binding partner, there are additional topological requirements to be a hot spot for small molecule binding. Hence, only a minority of hot spots identified by alanine scanning represent sites that are potentially useful for small inhibitor binding, and it is this subset that is identified by experimental or computational fragment screening.
引用
收藏
页码:2236 / 2244
页数:9
相关论文
共 50 条
  • [31] SemiHS: An Iterative Semi-Supervised Approach for Predicting Protein-protein Interaction Hot Spots
    Deng, Lei
    Guan, Ji-Hong
    Dong, Qi-Wen
    Zhou, Shui-Geng
    PROTEIN AND PEPTIDE LETTERS, 2011, 18 (09) : 896 - 905
  • [32] Boosting Prediction Performance of Protein-Protein Interaction Hot Spots by Using Structural Neighborhood Properties
    Deng, Lei
    Guan, Jihong
    Wei, Xiaoming
    Yi, Yuan
    Zhang, Qiangfeng Cliff
    Zhou, Shuigeng
    JOURNAL OF COMPUTATIONAL BIOLOGY, 2013, 20 (11) : 878 - 891
  • [33] XGBPRH: Prediction of Binding Hot Spots at Protein-RNA Interfaces Utilizing Extreme Gradient Boosting
    Deng, Lei
    Sui, Yuanchao
    Zhang, Jingpu
    GENES, 2019, 10 (03)
  • [34] Composition of Overlapping Protein-Protein and Protein-Ligand Interfaces
    Mohamed, Ruzianisra
    Degac, Jennifer
    Helms, Volkhard
    PLOS ONE, 2015, 10 (10):
  • [35] Accurate Prediction of Protein Hot Spots Residues Based on Gentle AdaBoost Algorithm
    Sun, Zhen
    Zhang, Jun
    Zheng, Chun-Hou
    Wang, Bing
    Chen, Peng
    INTELLIGENT COMPUTING THEORIES AND APPLICATION, ICIC 2016, PT I, 2016, 9771 : 742 - 749
  • [36] Machine Learning Approaches for Protein-Protein Interaction Hot Spot Prediction: Progress and Comparative Assessment
    Liu, Siyu
    Liu, Chuyao
    Deng, Lei
    MOLECULES, 2018, 23 (10):
  • [37] Implication of Terminal Residues at Protein-Protein and Protein-DNA Interfaces
    Martin, Olivier M. F.
    Etheve, Loic
    Launay, Guillaume
    Martin, Juliette
    PLOS ONE, 2016, 11 (09):
  • [38] Prediction and Analysis of Hot Region in Protein-Protein Interactions
    Lin, Xiaoli
    Zhang, Xiaolong
    2016 IEEE INTERNATIONAL CONFERENCE ON BIOINFORMATICS AND BIOMEDICINE (BIBM), 2016, : 1598 - 1603
  • [39] Conservation of hot regions in protein-protein interaction in evolution
    Hu, Jing
    Li, Jiarui
    Chen, Nansheng
    Zhang, Xiaolong
    METHODS, 2016, 110 : 73 - 80
  • [40] Prediction of hot spots in protein interfaces using a random forest model with hybrid features
    Wang, Lin
    Liu, Zhi-Ping
    Zhang, Xiang-Sun
    Chen, Luonan
    PROTEIN ENGINEERING DESIGN & SELECTION, 2012, 25 (03) : 119 - 126