Structural investigation of vesnarinone at the pore domains of open and open-inactivated states of hERG1 K+ channel

Gülru Kayık, Nurcan Tüzün, Serdar Durdagi*

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

5 Citations (Scopus)

Abstract

In this study, the dynamics of vesnarinone bounded hERG1 K+ channels are investigated using in silico approaches such as molecular docking, molecular dynamics (MD) simulations, MM/PBSA (Molecular Mechanics/Poisson Boltzmann Surface Area) calculations and Principal Component Analysis (PCA). Vesnarinone (a cardiotonic agent) falls into a category of drugs that inhibit phosphodiesterase 3-type (PDE3) enzymes. PDE3 enzymes have specific roles in the dehydyrolysis of intracellular second messengers 3′,5′-cyclic adenosine monophosphate (cAMP) and 3′,5′-cyclic guanosine monophosphate (cGMP). Thus, PDE3 inhibitors elevate the intracellular concentrations of these substrates. However, it is also known that vesnarinone inhibits the human ether-à-go-go-related gene (hERG) channels. Since inhibition of hERG channels may cause life-threatening arrhythmias, leading to Torsades de pointes (TdP) and long QT syndrome (LQTS), it is important to understand the particular residue-drug interactions and hERG channel dynamics. Applying the computational approaches in this study, have helped to elucidate the possible binding patterns and time evaluation dynamics of this drug at hERG1 channel models (both in its open and open-inactivated states) together with the crucial amino acid residues that mostly contribute in binding processes via interaction binding energy decomposition analysis.

Original languageEnglish
Pages (from-to)399-412
Number of pages14
JournalJournal of Molecular Graphics and Modelling
Volume77
DOIs
Publication statusPublished - Oct 2017

Bibliographical note

Publisher Copyright:
© 2017 Elsevier Inc.

Funding

We acknowledge the National Center for High Performance Computing of Turkey (UHEM) under Grant 10982010 , Istanbul Technical University Research Fund ( BAP 38208 ) and The Scientific and Technological Research Council of Turkey (TUBITAK) under 2214-A Research Grant, for supporting this study. Gülru Kayık would also like to thank Prof. Tiziano Tuccinardi and Dr. Gabriella Ortore from the Molecular Modeling&Virtual Screening Laboratory at the Department of Pharmacy, Pisa University for hosting her during the period of TUBITAK 2214-A Research Fellowship Program and partially providing the computational resources for the current study.

FundersFunder number
Istanbul Technical University Research FundBAP 38208
TUBITAK
Türkiye Bilimsel ve Teknolojik Araştirma Kurumu

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