Literature DB >> 30855664

Protein-ligand interaction fingerprints for accurate prediction of dissociation rates of p38 MAPK Type II inhibitors.

Duo Zhang1,2, Shuheng Huang1,2, Hu Mei1,2, MuliadiYeremia Kevin2, Tingting Shi2, Linxin Chen2.   

Abstract

Binding/unbinding kinetics are key determinants of drug potencies. However, there are still a lot of challenges in predicting kinetic properties during early-stage drug development. In this work, position-restrained molecular dynamics simulations combined with energy decomposition were applied to extract protein-ligand interaction (PLI) fingerprints along the unbinding pathway of 20 p38 mitogen-activated protein kinase (p38 MAPK) Type II inhibitors. The results showed that the electrostatic and/or van der Waals interaction fingerprints at three key positions can be used for accurate prediction of the dissociation rate constants (koff) of p38 MAPK Type II inhibitors. The strategy proposed in this paper can provide not only an efficient method of predicting the dissociation rates of the p38 MAPK Type II inhibitors, but also the atom-level mechanism of enthalpy-driven unbinding process.
© The Author(s) 2019. Published by Oxford University Press. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

Entities:  

Keywords:  dissociation rate constant; inhibitors; p38 mitogen-activated protein kinase; position-restrained molecular dynamics; prediction; protein–ligand interaction fingerprints

Year:  2019        PMID: 30855664     DOI: 10.1093/intbio/zyz004

Source DB:  PubMed          Journal:  Integr Biol (Camb)        ISSN: 1757-9694            Impact factor:   2.192


  2 in total

1.  In Silico Prediction of the Dissociation Rate Constants of Small Chemical Ligands by 3D-Grid-Based VolSurf Method.

Authors:  Shuheng Huang; Linxin Chen; Hu Mei; Duo Zhang; Tingting Shi; Zuyin Kuang; Yu Heng; Lei Xu; Xianchao Pan
Journal:  Int J Mol Sci       Date:  2020-04-02       Impact factor: 5.923

Review 2.  Druggable Transient Pockets in Protein Kinases.

Authors:  Koji Umezawa; Isao Kii
Journal:  Molecules       Date:  2021-01-27       Impact factor: 4.411

  2 in total

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