Literature DB >> 27936518

Computational investigation of proton transfer, pKa shifts and pH-optimum of protein-DNA and protein-RNA complexes.

Yunhui Peng1, Emil Alexov1.   

Abstract

Protein-nucleic acid interactions play a crucial role in many biological processes. This work investigates the changes of pKa values and protonation states of ionizable groups (including nucleic acid bases) that may occur at protein-nucleic acid binding. Taking advantage of the recently developed pKa calculation tool DelphiPka, we utilize the large protein-nucleic acid interaction database (NPIDB database) to model pKa shifts caused by binding. It has been found that the protein's interfacial basic residues experience favorable electrostatic interactions while the protein acidic residues undergo proton uptake to reduce the energy cost upon the binding. This is in contrast with observations made for protein-protein complexes. In terms of DNA/RNA, both base groups and phosphate groups of nucleotides are found to participate in binding. Some DNA/RNA bases undergo pKa shifts at complex formation, with the binding process tending to suppress charged states of nucleic acid bases. In addition, a weak correlation is found between the pH-optimum of protein-DNA/RNA binding free energy and the pH-optimum of protein folding free energy. Overall, the pH-dependence of protein-nucleic acid binding is not predicted to be as significant as that of protein-protein association. Proteins 2017; 85:282-295.
© 2016 Wiley Periodicals, Inc. © 2016 Wiley Periodicals, Inc.

Entities:  

Keywords:  electrostatic interactions; optimum pH; pKa changes; protein-nucleic acid interactions; proton transfer

Mesh:

Substances:

Year:  2017        PMID: 27936518     DOI: 10.1002/prot.25221

Source DB:  PubMed          Journal:  Proteins        ISSN: 0887-3585


  9 in total

1.  Predicting protein-DNA binding free energy change upon missense mutations using modified MM/PBSA approach: SAMPDI webserver.

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Journal:  Bioinformatics       Date:  2018-03-01       Impact factor: 6.937

2.  Electrostatic features for nucleocapsid proteins of SARS-CoV and SARS-CoV-2.

Authors:  Wenhan Guo; Yixin Xie; Alan E Lopez-Hernandez; Shengjie Sun; Lin Li
Journal:  Math Biosci Eng       Date:  2021-03-09       Impact factor: 2.080

3.  Prediction of pKa Values for Neutral and Basic Drugs based on Hybrid Artificial Intelligence Methods.

Authors:  Mengshan Li; Huaijing Zhang; Bingsheng Chen; Yan Wu; Lixin Guan
Journal:  Sci Rep       Date:  2018-03-05       Impact factor: 4.379

4.  The pH Effects on SARS-CoV and SARS-CoV-2 Spike Proteins in the Process of Binding to hACE2.

Authors:  Yixin Xie; Wenhan Guo; Alan Lopez-Hernadez; Shaolei Teng; Lin Li
Journal:  Res Sq       Date:  2021-09-09

5.  The pH Effects on SARS-CoV and SARS-CoV-2 Spike Proteins in the Process of Binding to hACE2.

Authors:  Yixin Xie; Wenhan Guo; Alan Lopez-Hernadez; Shaolei Teng; Lin Li
Journal:  Pathogens       Date:  2022-02-11

6.  Gaussian-Based Smooth Dielectric Function: A Surface-Free Approach for Modeling Macromolecular Binding in Solvents.

Authors:  Arghya Chakravorty; Zhe Jia; Yunhui Peng; Nayere Tajielyato; Lisi Wang; Emil Alexov
Journal:  Front Mol Biosci       Date:  2018-03-27

Review 7.  Computational Approaches to Prioritize Cancer Driver Missense Mutations.

Authors:  Feiyang Zhao; Lei Zheng; Alexander Goncearenco; Anna R Panchenko; Minghui Li
Journal:  Int J Mol Sci       Date:  2018-07-20       Impact factor: 5.923

8.  DNA mismatches reveal conformational penalties in protein-DNA recognition.

Authors:  Ariel Afek; Honglue Shi; Atul Rangadurai; Harshit Sahay; Alon Senitzki; Suela Xhani; Mimi Fang; Raul Salinas; Zachery Mielko; Miles A Pufall; Gregory M K Poon; Tali E Haran; Maria A Schumacher; Hashim M Al-Hashimi; Raluca Gordân
Journal:  Nature       Date:  2020-10-21       Impact factor: 49.962

9.  Computational Investigation of the pH Dependence of Stability of Melanosome Proteins: Implication for Melanosome formation and Disease.

Authors:  Mahesh Koirala; H B Mihiri Shashikala; Jacob Jeffries; Bohua Wu; Stacie K Loftus; Jonathan H Zippin; Emil Alexov
Journal:  Int J Mol Sci       Date:  2021-07-31       Impact factor: 5.923

  9 in total

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