Literature DB >> 32525544

A boosted unbiased molecular dynamics method for predicting ligands binding mechanisms: probing the binding pathway of dasatinib to Src-kinase.

Farzin Sohraby1, Mostafa Javaheri Moghadam1, Masoud Aliyar1, Hassan Aryapour1.   

Abstract

SUMMARY: Small molecules such as metabolites and drugs play essential roles in biological processes and pharmaceutical industry. Knowing their interactions with biomacromolecular targets demands a deep understanding of binding mechanisms. Dozens of papers have suggested that discovering of the binding event by means of conventional unbiased molecular dynamics (MD) simulation urges considerable amount of computational resources, therefore, only one who holds a cluster or a supercomputer can afford such extensive simulations. Thus, many researchers who do not own such resources are reluctant to take the benefits of running unbiased MD simulation, in full atomistic details, when studying a ligand binding pathway. Many researchers are impelled to be content with biased MD simulations which seek its validation due to its intrinsic preconceived framework. In this work, we have presented a workable stratagem to encourage everyone to perform unbiased (unguided) MD simulations, in this case a protein-ligand binding process, by typical desktop computers and so achieve valuable results in nanosecond time scale. Here, we have described a dynamical binding's process of an anticancer drug, the dasatinib, to the c-Src kinase in full atomistic details for the first time, without applying any biasing force or potential which may lead the drug to artificial interactions with the protein. We have attained multiple independent binding events which occurred in the nanosecond time scales, surprisingly as little as ∼30 ns. Both the protonated and deprotonated forms of the dasatinib reached the crystallographic binding mode without having any major intermediate state during induction.
AVAILABILITY AND IMPLEMENTATION: The links of the tutorial and technical documents are accessible in the article. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.
© The Author(s) 2020. Published by Oxford University Press. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

Entities:  

Mesh:

Substances:

Year:  2020        PMID: 32525544     DOI: 10.1093/bioinformatics/btaa565

Source DB:  PubMed          Journal:  Bioinformatics        ISSN: 1367-4803            Impact factor:   6.937


  2 in total

1.  Practical Protocols for Efficient Sampling of Kinase-Inhibitor Binding Pathways Using Two-Dimensional Replica-Exchange Molecular Dynamics.

Authors:  Ai Shinobu; Suyong Re; Yuji Sugita
Journal:  Front Mol Biosci       Date:  2022-04-29

2.  Reconstruction of the unbinding pathways of noncovalent SARS-CoV and SARS-CoV-2 3CLpro inhibitors using unbiased molecular dynamics simulations.

Authors:  Fereshteh Noroozi Tiyoula; Hassan Aryapour
Journal:  PLoS One       Date:  2022-02-09       Impact factor: 3.240

  2 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.