Instytut Podstawowych Problemów Techniki
Polskiej Akademii Nauk

Partnerzy

Simón Poblete


Ostatnie publikacje
1.  Cofas Vargas L.F., Azevedo Rodrigo M., Poblete S., Chwastyk M., Poma Bernaola A.M., The GōMartini Approach: Revisiting the Concept of Contact Maps and the Modelling of Protein Complexes, ACTA PHYSICA POLONICA A, ISSN: 0587-4246, DOI: 10.12693/APhysPolA.145.S9, Vol.145, No.3, pp.S9-S20, 2024

Streszczenie:
We present a review of a series of contact maps for the determination of native interactions in proteins and nucleic acids based on a distance threshold. Such contact maps are mostly based on physical and chemical construction, and yet they are sensitive to some parameters (e.g., distances or atomic radii) and can neglect some key interactions. Furthermore, we also comment on a new class of contact maps that only requires geometric arguments. The contact map is a necessary ingredient to build a robust Gō-Martini model for proteins and their complexes in the Martini 3 force field. We present the extension of a popular structure-based Gō--like approach to the study of protein–sugar complexes, and the limitations of this approach are also discussed. The Gō-Martini approach was first introduced by Poma et al. (J. Chem. Theory Comput. 13, 1366 (2017)) in Martini 2 force field, and recently, it has gained the status of gold standard for protein simulation undergoing conformational changes in Martini 3 force field. We discuss several studies that have provided support for this approach in the context of the biophysical community.

Słowa kluczowe:
Martini 3,Structure-based coarse-graining,SMFS,biomolecules,GoMartini

Afiliacje autorów:
Cofas Vargas L.F. - inna afiliacja
Azevedo Rodrigo M. - inna afiliacja
Poblete S. - inna afiliacja
Chwastyk M. - Institute of Physics, Polish Academy of Sciences (PL)
Poma Bernaola A.M. - inna afiliacja
70p.
2.  Poblete S., Pantano S., Okazaki K., Liang Z., Kremer K., Poma Adolfo B., Editorial: Recent advances in computational modelling of biomolecular complexes, Frontiers in Chemistry, ISSN: 2296-2646, DOI: 10.3389/fchem.2023.1200409, Vol.11, pp.1200409-1-3, 2023, EDITORIAL

Słowa kluczowe:
coarse-grained method, machine learning, multiscale approach, biopolymers, aggregation, GōMartini approach, Martini 3, nanomechanics

Afiliacje autorów:
Poblete S. - inna afiliacja
Pantano S. - inna afiliacja
Okazaki K. - inna afiliacja
Liang Z. - inna afiliacja
Kremer K. - inna afiliacja
Poma Adolfo B. - IPPT PAN

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