dc.contributor.author
Talagayev, Valerij
dc.contributor.author
Chen, Yu
dc.contributor.author
Doering, Niklas Piet
dc.contributor.author
Obendorf, Leon
dc.contributor.author
Denzinger, Katrin
dc.contributor.author
Puls, Kristina
dc.contributor.author
Lam, Kevin
dc.contributor.author
Liu, Sijie
dc.contributor.author
Wolf, Clemens Alexander
dc.contributor.author
Noonan, Theresa
dc.contributor.author
Breznik, Marko
dc.contributor.author
Knaus, Petra
dc.contributor.author
Wolber, Gerhard
dc.date.accessioned
2025-03-05T12:45:19Z
dc.date.available
2025-03-05T12:45:19Z
dc.identifier.uri
https://refubium.fu-berlin.de/handle/fub188/46593
dc.identifier.uri
http://dx.doi.org/10.17169/refubium-46307
dc.description.abstract
Molecular dynamics (MD) simulations have become an essential tool for studying the dynamics of biological systems and exploring protein–ligand interactions. OpenMM is a modern, open-source software toolkit designed for MD simulations. Until now, it has lacked a module dedicated to building receptor–ligand systems, which is highly useful for investigating protein–ligand interactions for drug discovery. We therefore introduce OpenMMDL, an open-source toolkit that enables the preparation and simulation of protein–ligand complexes in OpenMM, along with the subsequent analysis of protein–ligand interactions. OpenMMDL consists of three main components: OpenMMDL Setup, a graphical user interface based on Python Flask to prepare protein and simulation settings, OpenMMDL Simulation to perform MD simulations with consecutive trajectory postprocessing, and finally OpenMMDL Analysis to analyze simulation results with respect to ligand binding. OpenMMDL is not only a versatile tool for analyzing protein–ligand interactions and generating ligand binding modes throughout simulations; it also tracks and clusters water molecules, particularly those exhibiting minimal displacement from their previous coordinates, providing insights into solvent dynamics. We applied OpenMMDL to study ligand–receptor interactions across diverse biological systems, including LDN-193189 and LDN-212854 with ALK2 (kinases), nifedipine and amlodipine in Cav1.1 (ion channels), LSD in 5-HT2B (G-protein coupled receptors), letrozole in CYP19A1 (cytochrome P450 oxygenases), flavin mononucleotide binding the FMN-riboswitch (RNAs), ligand C08 bound to TLR8 (toll-like receptor), and PZM21 bound to MOR (opioid receptor), highlighting distinct functionalities of OpenMMDL. OpenMMDL is publicly available at https://github.com/wolberlab/OpenMMDL.
en
dc.format.extent
12 Seiten
dc.rights.uri
https://creativecommons.org/licenses/by/4.0/
dc.subject
Binding modes
en
dc.subject
Computational chemistry
en
dc.subject
Molecular mechanics
en
dc.subject.ddc
500 Naturwissenschaften und Mathematik::540 Chemie::540 Chemie und zugeordnete Wissenschaften
dc.title
OpenMMDL - Simplifying the Complex: Building, Simulating, and Analyzing Protein–Ligand Systems in OpenMM
dc.type
Wissenschaftlicher Artikel
dcterms.bibliographicCitation.doi
10.1021/acs.jcim.4c02158
dcterms.bibliographicCitation.journaltitle
Journal of Chemical Information and Modeling
dcterms.bibliographicCitation.number
4
dcterms.bibliographicCitation.pagestart
1967
dcterms.bibliographicCitation.pageend
1978
dcterms.bibliographicCitation.volume
65
dcterms.bibliographicCitation.url
https://doi.org/10.1021/acs.jcim.4c02158
refubium.affiliation
Biologie, Chemie, Pharmazie
refubium.affiliation.other
Institut für Pharmazie

refubium.affiliation.other
Institut für Chemie und Biochemie

refubium.funding
ACS Publications
refubium.note.author
Die Publikation wurde aus Open Access Publikationsgeldern der Freien Universität Berlin gefördert.
refubium.resourceType.isindependentpub
no
dcterms.accessRights.openaire
open access
dcterms.isPartOf.eissn
1549-960X