Bartender: Martini 3 Bonded Terms via Quantum Mechanics-based Molecular Dynamics

Pre-print
Methods
Parametrization
Multi-scale
Author

Gilberto P Pereira, Riccardo Alessandri, Moisés Domínguez, Rocío Araya-Osorio, Linus Grünewald, Luís Borges-Araújo, Sangwook Wu, Siewert J Marrink, Paulo Cesar Telles de Souza, and Raul Mera-Adasme

Doi

https://doi.org/10.26434/chemrxiv-2024-62kh1-v2

Citation (APA 7)

Pereira, G. P., Alessandri, R., Domínguez, M., Araya-Osorio, R., Grünewald, L., Borges-Araújo, L., … & Mera-Adasme, R. (2024). Bartender: Martini 3 Bonded Terms via Quantum Mechanics-based Molecular Dynamics.

Abstract

Coarse-grained (CG) molecular dynamics (MD) simulations have grown in applicability over the years. The recently released version of the Martini CG force field (Martini 3) has been successfully applied to simulate many processes, including protein-ligand binding. However, the current ligand parameterization scheme is manual and requires an a priori reference all-atom (AA) simulation for benchmarking. For systems with suboptimal AA parameters, which are often unknown, this translates into a CG model which does not reproduce the true dynamical behavior of the underlying molecule. Here we present Bartender, a quantum mechanics (QM)/MD-based parameterization tool written in Go. Bartender harnesses the power of QM simulations and produces reasonable bonded terms for Martini 3 CG models of small molecules in an efficient and user-friendly manner. For small, ring-like molecules, Bartender generates models whose properties are indistinguishable from the human-made models. For more complex, drug-like ligands, it is able to fit functional forms beyond simple harmonic dihedrals, and thus better captures their dynamical behavior. Bartender has the power to both increase the efficiency and the accuracy of Martini 3-based high-throughput applications by producing stable and physically realistic CG models.