A Practical Introduction to Martini 3 and its Application to Protein-Ligand Binding Simulations

Author:

Alessandri Riccardo1,Thallmair Sebastian2,Herrero Cristina Gil2,Mera-Adasme Raúl3,Marrink Siewert J.4,Souza Paulo C. T.5

Affiliation:

1. University of Chicago Pritzker School of Molecular Engineering, , Chicago, Illinois 60637, USA

2. Frankfurt Institute for Advanced Studies , Ruth-Moufang-Str. 1, 60438 Frankfurt am Main, Germany

3. Universidad de Santiago de Chile (USACH) Departamento de Ciencias del Ambiente, Facultad de Qúímica y Biología, , Chile

4. University of Groningen Groningen Biomolecular Sciences and Biotechnology Institute and Zernike Institute for Advanced Materials, , Groningen, The Netherlands

5. UMR 5086 CNRS and University of Lyon Molecular Microbiology and Structural Biochemistry, , Lyon, France

Abstract

Martini 3 is the new version of a widely used coarse-grained (CG) model that have been extensively parameterized to reproduce experimental and thermodynamic data. Based on a building-block approach, the new version shows a better coverage of the chemical space and more accurate predictions of interactions and molecular packing in general. Given these improvements, the Martini 3 model allows new applications such as studies involving protein–ligand interactions. In this chapter, a summary of the key elements of the new Martini version is presented, followed by an example of a practical application: a simulation of caffeine binding to the buried pocket of the adenosine A2A receptor, which is part of the GPCR family. Formulated as a hands-on tutorial, this chapter contains guidelines to build CG models of important systems, such as small drug-like molecules, transmembrane proteins, and lipid membranes. Finally, the last sections contain an outlook of possible future developments and notes describing useful information, limitations, and tips about Martini.

Publisher

AIP Publishing LLCMelville, New York

Cited by 1 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. Pragmatic Coarse-Graining of Proteins: Models and Applications;Journal of Chemical Theory and Computation;2023-10-03

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