GōMartini 3: From large conformational changes in proteins to environmental bias corrections

Coarse-grained modeling has become an important tool to supplement experimental measurements, allowing access to spatio-temporal scales beyond all-atom based approaches. The GōMartini 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 GōMartini model, which combines a virtual-site implementation of Gō models with Martini 3. The implementation has been extensively tested by the community since the release of the reparametrized version of Martini. This work demonstrates the capabilities of the…

• EC
  European Commission

  Award: 748895
• IN
  Institut National de la Santé et de la Recherche Médicale
• RG
  Rijksuniversiteit Groningen
• FD
  Fundação de Amparo à Pesquisa do Estado de São Paulo

  Awards: 2019/, 2019/26557-8
• NO
  Nederlandse Organisatie voor Wetenschappelijk Onderzoek
• CN
  Centre National de la Recherche Scientifique
• GÉ
  Grand Équipement National De Calcul Intensif

  Awards: 2022-A0120713456, 2023-A0140713456
• IP
  Infrastruktura PL-Grid

  Award: PLG/2023/016519
• ÉN
  École Normale Supérieure de Lyon
• DR
  Dr. Rolf M. Schwiete Stiftung
• AN
  Agencia Nacional de Investigación y Desarrollo

  Award: 1200200
• FP
  Fundação para a Ciência e a Tecnologia

  Awards: CEECIND/04124/2017, /2017
• IN
  Institut National de Physique Nucléaire et de Physique des Particules
• AC
  Academic Computer Centre Cyfronet, AGH University of Science and Technology
• HM
  H2020 Marie Skłodowska-Curie Actions

  Award: 748895