OpenMMDL - Simplifying the Complex: Building, Simulating, and Analyzing Protein-Ligand Systems in OpenMM.

OpenMMDL is a new open-source toolkit that extends the molecular dynamics software OpenMM with modules for building, simulating, and analyzing protein-ligand complexes. It comprises three components: a graphical setup interface, a simulation module with trajectory postprocessing, and an analysis module that tracks ligand binding modes and clusters water molecules with minimal displacement. The toolkit was applied to seven diverse biological systems: kinases (ALK2 with LDN-193189 and LDN-212854), ion channels (Cav1.1 with nifedipine and amlodipine), G-protein coupled receptors (5-HT2B with LSD), cytochrome P450 oxygenases (CYP19A1 with letrozole), an RNA riboswitch (FMN-riboswitch with flavin mononucleotide), toll-like receptor 8 (TLR8 with ligand C08), and the opioid receptor (MOR with PZM21). OpenMMDL is publicly available on GitHub.

Study at a glance

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.