Protein-Protein Docking with Dynamic Residue Protonation States

被引:16
|
作者
Kilambi, Krishna Praneeth [1 ]
Reddy, Kavan [1 ]
Gray, Jeffrey J. [1 ,2 ]
机构
[1] Johns Hopkins Univ, Dept Chem & Biomol Engn, Baltimore, MD 21287 USA
[2] Johns Hopkins Univ, Program Mol Biophys, Baltimore, MD USA
基金
美国国家卫生研究院;
关键词
CAPRI ROUNDS 20-27; PK(A) VALUES; STRUCTURAL DETERMINANTS; CRYSTAL-STRUCTURE; LIGAND-BINDING; PREDICTION; COMPLEX; PH; RESOLUTION; ENERGY;
D O I
10.1371/journal.pcbi.1004018
中图分类号
Q5 [生物化学];
学科分类号
071010 ; 081704 ;
摘要
Protein-protein interactions depend on a host of environmental factors. Local pH conditions influence the interactions through the protonation states of the ionizable residues that can change upon binding. In this work, we present a pH-sensitive docking approach, pHDock, that can sample side-chain protonation states of five ionizable residues (Asp, Glu, His, Tyr, Lys) on-the-fly during the docking simulation. pHDock produces successful local docking funnels in approximately half (79/161) the protein complexes, including 19 cases where standard RosettaDock fails. pHDock also performs better than the two control cases comprising docking at pH 7.0 or using fixed, predetermined protonation states. On average, the top-ranked pHDock structures have lower interface RMSDs and recover more native interface residue-residue contacts and hydrogen bonds compared to RosettaDock. Addition of backbone flexibility using a computationally-generated conformational ensemble further improves native contact and hydrogen bond recovery in the top-ranked structures. Although pHDock is designed to improve docking, it also successfully predicts a large pH-dependent binding affinity change in the Fc-FcRn complex, suggesting that it can be exploited to improve affinity predictions. The approaches in the study contribute to the goal of structural simulations of whole-cell protein-protein interactions including all the environmental factors, and they can be further expanded for pH-sensitive protein design.
引用
收藏
页数:14
相关论文
共 50 条
  • [31] Solvent Sites Improve Docking Performance of Protein-Protein Complexes and Protein-Protein Interface-Targeted Drugs
    Mayol, Gonzalo F.
    Defelipe, Lucas A.
    Arcon, Juan Pablo
    Turjanski, Adrian G.
    Marti, Marcelo A.
    JOURNAL OF CHEMICAL INFORMATION AND MODELING, 2022, 62 (15) : 3577 - 3588
  • [32] Discovery of binding proteins for a protein target using protein-protein docking-based virtual screening
    Zhang, Changsheng
    Tang, Bo
    Wang, Qian
    Lai, Luhua
    PROTEINS-STRUCTURE FUNCTION AND BIOINFORMATICS, 2014, 82 (10) : 2472 - 2482
  • [33] A Web Interface for Easy Flexible Protein-Protein Docking with ATTRACT
    de Vries, Sjoerd J.
    Schindler, Christina E. M.
    de Beauchene, Isaure Chauvot
    Zacharias, Martin
    BIOPHYSICAL JOURNAL, 2015, 108 (03) : 462 - 465
  • [34] Pushing the accuracy limit of shape complementarity for protein-protein docking
    Yan, Yumeng
    Huang, Sheng-You
    BMC BIOINFORMATICS, 2019, 20 (01)
  • [35] Performance and Its Limits in Rigid Body Protein-Protein Docking
    Desta, Israel T.
    Porter, Kathryn A.
    Xia, Bing
    Kozakov, Dima
    Vajda, Sandor
    STRUCTURE, 2020, 28 (09) : 1071 - +
  • [36] Efficient flexible backbone protein-protein docking for challenging targets
    Marze, Nicholas A.
    Burman, Shourya S. Roy
    Sheffler, William
    Gray, Jeffrey J.
    BIOINFORMATICS, 2018, 34 (20) : 3461 - 3469
  • [37] Protein-Protein Interactions Efficiently Modeled by Residue Cluster Classes
    Poot Velez, Albros Hermes
    Fontove, Fernando
    Del Rio, Gabriel
    INTERNATIONAL JOURNAL OF MOLECULAR SCIENCES, 2020, 21 (13) : 1 - 16
  • [38] A Geometric Complementarity-Based Tool for Protein-Protein Docking
    Sunny, Sharon
    Jayaraj, P. B.
    JOURNAL OF COMPUTATIONAL BIOPHYSICS AND CHEMISTRY, 2022, 21 (01): : 35 - 46
  • [39] Protein-protein and peptide-protein docking and refinement using ATTRACT in CAPRI
    Schindler, Christina E. M.
    de Beauchene, Isaure Chauvot
    de Vries, Sjoerd J.
    Zacharias, Martin
    PROTEINS-STRUCTURE FUNCTION AND BIOINFORMATICS, 2017, 85 (03) : 391 - 398
  • [40] FPDock: Protein-protein docking using flower pollination algorithm
    Sunny, Sharon
    Jayaraj, P. B.
    COMPUTATIONAL BIOLOGY AND CHEMISTRY, 2021, 93