Multi-body effects in a coarse-grained protein force field
Journal article, 2021

The use of coarse-grained (CG) models is a popular approach to study complex biomolecular systems. By reducing the number of degrees of freedom, a CG model can explore long time- and length-scales inaccessible to computational models at higher resolution. If a CG model is designed by formally integrating out some of the system’s degrees of freedom, one expects multi-body interactions to emerge in the effective CG model’s energy function. In practice, it has been shown that the inclusion of multi-body terms indeed improves the accuracy of a CG model. However, no general approach has been proposed to systematically construct a CG effective energy that includes arbitrary orders of multi-body terms. In this work, we propose a neural network based approach to address this point and construct a CG model as a multi-body expansion. By applying this approach to a small protein, we evaluate the relative importance of the different multi-body terms in the definition of an accurate model. We observe a slow convergence in the multi-body expansion, where up to five-body interactions are needed to reproduce the free energy of an atomistic model.


Jiang Wang

Rice University

Guizhou Institute of Technology

Nicholas Charron

Rice University

Freie Universität Berlin

Brooke Husic

Freie Universität Berlin

Simon Olsson

Freie Universität Berlin

Chalmers, Computer Science and Engineering (Chalmers), Data Science

Frank Noé

Rice University

Freie Universität Berlin

Cecilia Clementi

Rice University

Freie Universität Berlin

Journal of Chemical Physics

0021-9606 (ISSN) 1089-7690 (eISSN)

Vol. 154 16 164113

Subject Categories

Computational Mathematics

Other Physics Topics

Bioinformatics (Computational Biology)





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