Nature CommunicationsBiophysicsPeer-reviewed journal article
GoMartini 3: From large conformational changes in proteins to environmental bias corrections
Paulo C. T. SouzaiD, Luís Borges-AraújoiD, Christopher BrasnettiD, Rodrigo A. MoreiraiD, Fabian GrünewaldiD, Peter ParkiD, Liguo WangiD, Hafez RazmazmaiD, Ana C. Borges-AraújoiD, Luis Fernando Cofas‐VargasiD, Luca MonticelliiD, Raúl Mera‐AdasmeiD, Manuel N. MeloiD, Sangwook WuiD, Siewert J. MarrinkiD, Adolfo B. PomaiD, Sebastian ThallmairiD
Abstract
Coarse-grained modeling has become an important tool to supplement experimental measurements, allowing access to spatio-temporal scales beyond all-atom based approaches. The G[o]Martini model combines structure- and physics-based coarse-grained approaches, balancing computational efficiency and accurate representation of protein dynamics with the capabilities of studying proteins in different biological environments. This paper introduces an enhanced G[o]Martini model, which combines a virtual-site implementation of G[o] models with Martini 3. The implementation has been extensively tested by the community since the release of the new version of Martini. This work demonstrates the capabilities of the model in diverse case studies, ranging from protein-membrane binding to protein-ligand interactions and AFM force profile calculations. The model is also versatile, as it can address recent inaccuracies reported in the Martini protein model. Lastly, the paper discusses the advantages, limitations, and future perspectives of the Martini 3 protein model and its combination with G[o] models.
- assay: protein structure
- research focus: protein folding & dynamics
- research focus: benchmarking
- approach: deep learning
- approach: statistical model
- Citations
- 108
- FWCI
- 22.51
- Field percentile
- top 1%
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