Abstract
The MArtini Database (MAD) web server (www.mad.ens-lyon.fr) has been updated with new tools, models, and capabilities to support a broader range of molecular sys- tems for the Martini coarse grained (CG) force field. The most notable addition is the MAD:Polymer Builder, enabling the automated construction of CG polymer models with varying architectures and complexities. The server now incorporates the latest developments in Martini 3, providing enhanced control within the MAD:Molecule Builder over the conversion of all-atom structures into CG representations, including the implementation of GoMartini 3 for protein complexes and water protein interaction biases. The MAD:Polymer Builder and MAD:Molecule Builder are both adapted to work with intrinsically disordered proteins and domains. Substantial progress has been made in expanding the MAD:Database, making a growing library of Martini-ready compounds readily accessible across the entire MAD ecosystem. These advances position MAD as a comprehensive and evolving platform for the preparation of diverse systems in CG molecular simulations.
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Abstract
The MArtini Database (MAD) web server (https://mad.ens-lyon.fr/) has been updated with new tools, models, and capabilities to support a broader range of molecular systems for the Martini coarse-grained (CG) force field. The most notable addition is the MAD:Polymer Builder, enabling the automated construction of CG polymer models with varying architectures and complexities. The server now incorporates the latest developments in Martini 3, providing enhanced control within the MAD:Molecule Builder over the conversion of all-atom structures into CG representations, including the implementation of GōMartini 3 for protein complexes and water–protein interaction biases. The MAD:Polymer Builder and MAD:Molecule Builder are both adapted to work with intrinsically disordered proteins and domains. Substantial progress has been made in expanding the MAD:Database, making a growing library of Martini-ready compounds readily accessible across the entire MAD ecosystem. These advances position MAD as a comprehensive and evolving platform for the preparation of diverse systems in CG molecular simulations.
Competing Interest Statement
The authors have declared no competing interest.
Footnotes
E-mail: paulo.telles_de_souza{at}ens-lyon.fr;
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