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BioinformaticsJournal of Chemical Information and Modeling
Peer-reviewed journal article

MDPath: Unraveling Allosteric Communication Paths of Drug Targets through Molecular Dynamics Simulations

Niklas Piet DoeringiD, Marvin TaterraiD, Marcel BermúdeziD, Gerhard WolberiD

Abstract

Understanding allosteric communication in proteins remains a critical challenge for structure-based, rational drug design. We present MDPath, a Python toolkit for analyzing allosteric communication paths in molecular dynamics simulations using NMI-based analysis. We demonstrate MDPaths ability to identify both established and novel GPCR allosteric mechanisms using the {beta}2-adrenoceptor, adenosine A2A receptor, and {micro}-opioid receptor as model systems. The toolkit reveals ligand-specific allosteric effects in {beta}2-adrenoceptor and MOR, illustrating how protein-ligand interactions drive conformational changes. Analysis of ABL1 kinase in complex with allosteric and orthosteric inhibitors demonstrates the broader applicability of the approach. Ultimately, MDPath provides an open-source framework for mapping allosteric communication within proteins, advancing structure-based drug design (https://github.com/wolberlab/mdpath).

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