Welcome to the MAD Tutorial

What is MAD ?

The Martini Database (MAD) is a web server dedicated to (a) sharing structures and topologies of molecules parameterized with the Martini coarse-grained (CG) force field [1-3]; (b) converting atomistic structures into CG structures; (c) preparing complex systems (including proteins, nucleic acids, lipids etc.) for molecular dynamics (MD) simulations at the CG level. Specifically, the MAD server currently includes tools to: (a) submit or retrieve CG representations of a wide range of molecules (lipids, sugars, nanoparticles, etc.); (b) transform all-atom protein structures into CG structures and topologies, with fine control on the process; (c) assemble biomolecules into large systems and deliver all files necessary to start molecular dynamics simulations.
We will guide you during your first tour on the MAD server through the three following sections:

MAD:Database where you access/retrieve or submit to our database of compounds
MAD:Molecule Builder where you coarse grain all atom PDB structure into their Martini versions
MAD:System Builder which combines your coarse grained protein structure with lipid component from MAD database to create large system
MAD:Polymer Editor where you design or transform molecules. Powered by polyply.
MAD:API Download molecules in different formats.
A registration is required in order to use the MAD:Molecule Builder, MAD:Polymer Editor and the MAD:System Builder
Account access and registration are available here

References

  1. SJ Marrink, HJ Risselada, S Yefimov, DP Tieleman, AH De Vries. The MARTINI force field: coarse grained model for biomolecular simulations. J Phys Chem B (2007) 111, 7812-7824. Doi: 10.1021/jp071097f
  2. L Monticelli, SK Kandasamy, X Periole, RG Larson, DP Tieleman, SJ Marrink. The MARTINI coarse-grained force field: extension to proteins. J Chem Theory Comput (2008) 4, 819-834. Doi: 10.1021/ct700324x
  3. Souza, P.C.T., Alessandri, R., Barnoud, J. et al. Martini 3: a general-purpose force field for coarse-grained molecular dynamics. Nat Methods (2021) 18, 382–388. Doi : 10.1038/s41592-021-01098-3