Literature DB >> 26851906

Variational tensor approach for approximating the rare-event kinetics of macromolecular systems.

Feliks Nüske1, Reinhold Schneider2, Francesca Vitalini3, Frank Noé1.   

Abstract

Essential information about the stationary and slow kinetic properties of macromolecules is contained in the eigenvalues and eigenfunctions of the dynamical operator of the molecular dynamics. A recent variational formulation allows to optimally approximate these eigenvalues and eigenfunctions when a basis set for the eigenfunctions is provided. In this study, we propose that a suitable choice of basis functions is given by products of one-coordinate basis functions, which describe changes along internal molecular coordinates, such as dihedral angles or distances. A sparse tensor product approach is employed in order to avoid a combinatorial explosion of products, i.e., of the basis set size. Our results suggest that the high-dimensional eigenfunctions can be well approximated with relatively small basis set sizes.

Year:  2016        PMID: 26851906     DOI: 10.1063/1.4940774

Source DB:  PubMed          Journal:  J Chem Phys        ISSN: 0021-9606            Impact factor:   3.488


  7 in total

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6.  VAMPnets for deep learning of molecular kinetics.

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Journal:  Nat Commun       Date:  2018-01-02       Impact factor: 14.919

7.  Deep learning for universal linear embeddings of nonlinear dynamics.

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  7 in total

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