Abstract
The coarse-grained Martini force field is widely used in biomolecular simulations. Here we present the refined model, Martini 3 (http://cgmartini.nl), with an improved interaction balance, new bead types and expanded ability to include specific interactions representing, for example, hydrogen bonding and electronic polarizability. The updated model allows more accurate predictions of molecular packing and interactions in general, which is exemplified with a vast and diverse set of applications, ranging from oil/water partitioning and miscibility data to complex molecular systems, involving protein–protein and protein–lipid interactions and material science applications as ionic liquids and aedamers.
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Data availability
Force-field parameters and procedures (for example, tutorials) are publicly available at http://cgmartini.nl. Simulation data (for example, trajectories) supporting the results of this paper are available from the corresponding authors upon reasonable request.
Code availability
Martinize2 (for which the manuscript is in preparation) and Martinate codes used in this work are publicly available at https://github.com/marrink-lab/. For more detailed information, see Supplementary Codes.
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Acknowledgements
We thank all members of the S.J.M. group and also external users for testing Martini 3 in its open-beta version. In particular, we thank C. F. E. Schroer, P. W. J. M. Frederix, W. Pezeshkian, M. N. Melo, H. I. Ingólfsson, M. Tsanai, M. König, P. A. Vainikka, T. Zijp, L. Gaifas, J. H. van der Woude, M. Espinoza Cangahuala, M. Scharte, J. Cruiming, L. M. van der Sleen, V. Verduijn, A. H. Beck Frederiksen, B. Schiøtt, M. Sikora, P. Schmalhorst, R. A. Moreira, A. B. Poma, K. Pluhackova, C. Arnarez, C. A. López, E. Jefferys and M. S. P. Sansom for their preliminary tests with a lot of different systems including aedamers, sugars, amino acids, deep eutectic solvents, lipids, peptides and proteins. We also thank the Center for Information Technology of the University of Groningen for providing access to the Peregrine high-performance computing cluster. We acknowledge the National Computing Facilities Foundation of The Netherlands Organization for Scientific Research (NWO), CSC–IT Center for Science Ltd (Espoo, Finland) and CINES (France) for providing computing time. Work in the S.J.M. group was supported by an European Research Council advanced grant no. ‘COMP-MICR-CROW-MEM’. R.A. thanks the NWO (Graduate Programme Advanced Materials, no. 022.005.006) for financial support. L.M. acknowledges the Institut National de la Santé et de la Recherche Medicale and the Agence Nationale de la Recherche for funding (grant no. ANR-17-CE11-0003) and GENCI-CINES for computing time (grant no. A0060710138). S.T. acknowledges the support from the European Commission via a Marie Skłodowska-Curie Actions individual fellowship (MicroMod-PSII, grant agreement no. 748895). M.J. thanks the Emil Aaltonen foundation for financial support. I.V. thanks the Academy of Finland (Center of Excellence program (grant no. 307415)), Sigrid Juselius Foundation, the Helsinki Institute of Life Science fellow program and the HFSP (research grant no. RGP0059/2019). R.B.B. and J.D. were supported by the intramural research program of the NIDDK, NIH. Their work used the computational resources of the NIH HPC Biowulf cluster (http://hpc.nih.gov). H.M.-S. acknowledges the Czech Science Foundation (grant no. 19-19561S). J.B. acknowledges funding from the TOP grant from S.J.M. (NWO) and the EPSRC program grant no. EP/P021123/1. Work in D.P.T.’s group is supported by the Natural Sciences and Engineering Research Council (Canada) and Compute Canada, funded by the Canada Foundation for Innovation. D.P.T. acknowledges further support from the Canada Research Chairs program. N.R. acknowledges funding from the Norwegian Research Council (FRIMEDBIO nos. 251247 and 288008) and computational resources from UNINETT SIGMA2 AS (grant no. NN4700K). H.M.K. acknowledges funding from the University of Calgary through the ‘Eyes High Postdoctoral Fellowship’ program.
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P.C.T.S. and S.J.M. conceived the project with suggestions from R.A., A.H.V., J.B. and S.T. P.C.T.S. generated and optimized all bead parameters. P.C.T.S., R.A. and J.B. generated the topology and bonded parameters of all CG models with suggestions from S.T. and I.F. P.C.T.S., R.A., A.H.V. and F.G. performed the simulations and analysis involving transfer free energies, solvent and polymer properties. P.C.T.S., S.T., J.B. and J.M. performed the simulations and analysis involving lipid bilayers. P.C.T.S., I.F. and R.A. performed the simulations and analysis involving nucleobases. P.C.T.S., I.P. and A.H.V. generated the models and performed the simulations and analysis involving aedamers. P.C.T.S. and F.G. generated the models and performed the simulations and analysis involving ionic liquids and ionic water solutions. R.A. generated the models and performed the simulations and analysis involving bulk heterojunctions, with suggestions from L.M. regarding the fullerene model. P.C.T.S., J.B., H.A., R.A., B.M.H.B., S.T., J.M., V.N., X.P., M.J., H.M.K., J.D., V.C. and H.M.-S. performed the simulations and analysis involving amino acids, peptides and proteins. J.B., T.A.W., P.C.K. and S.T. developed some tools and scripts used to generate the CG models and to run the molecular dynamics simulations. L.M., R.B.B., P.T., N.R., I.V., A.H.V. and S.J.M. provided guidance and supervision in the studies performed by their respective group members and collaborators. P.C.T.S. and S.J.M. wrote the main manuscript, with contributions from all the authors. P.C.T.S. prepared the figures with contributions from R.A., B.M.H.B., H.M.K. and A.H.V. P.C.T.S. wrote the Methods with contributions from all the authors. P.C.T.S. wrote the Supplementary Information, with contributions from all the authors. All the authors revised and approved the final version of the manuscript, Methods and Supplementary Information.
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Souza, P.C.T., Alessandri, R., Barnoud, J. et al. Martini 3: a general purpose force field for coarse-grained molecular dynamics. Nat Methods 18, 382–388 (2021). https://doi.org/10.1038/s41592-021-01098-3
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DOI: https://doi.org/10.1038/s41592-021-01098-3
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