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Independent Markov Decomposition: Towards modeling kinetics of biomolecular complexes

View ORCID ProfileTim Hempel, View ORCID ProfileMauricio J. del Razo, View ORCID ProfileChristopher T. Lee, Bryn C. Taylor, Rommie E. Amaro, View ORCID ProfileFrank Noé
doi: https://doi.org/10.1101/2021.03.24.436806
Tim Hempel
aFreie Universität Berlin, Department of Mathematics and Computer Science, Berlin, Germany
bFreie Universität Berlin, Department of Physics, Berlin, Germany
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Mauricio J. del Razo
aFreie Universität Berlin, Department of Mathematics and Computer Science, Berlin, Germany
cUniversity of Amsterdam, Van’t Hoff Institute for Molecular Sciences and Korteweg-de Vries Institute for Mathematics, Amsterdam, The Netherlands
dDutch Institute for Emergent Phenomena, Amsterdam, The Netherlands
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Christopher T. Lee
eUniversity of California, San Diego, Department of Mechanical and Aerospace Engineering, San Diego, CA, USA
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Bryn C. Taylor
fUniversity of California, San Diego, Biomedical Sciences Graduate Program, San Diego, CA, USA
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Rommie E. Amaro
gUniversity of California, San Diego, Department of Chemistry & Biochemistry, San Diego, CA, USA
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  • For correspondence: ramaro@ucsd.edu frank.noe@fuberlin.de
Frank Noé
aFreie Universität Berlin, Department of Mathematics and Computer Science, Berlin, Germany
bFreie Universität Berlin, Department of Physics, Berlin, Germany
hRice University, Department of Chemistry, Houston, TX, USA
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  • For correspondence: ramaro@ucsd.edu frank.noe@fuberlin.de
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Abstract

In order to advance the mission of in silico cell biology, modeling the interactions of large and complex biological systems becomes increasingly relevant. The combination of molecular dynamics (MD) and Markov state models (MSMs) have enabled the construction of simplified models of molecular kinetics on long timescales. Despite its success, this approach is inherently limited by the size of the molecular system. With increasing size of macromolecular complexes, the number of independent or weakly coupled subsystems increases, and the number of global system states increase exponentially, making the sampling of all distinct global states unfeasible. In this work, we present a technique called Independent Markov Decomposition (IMD) that leverages weak coupling between subsystems in order to compute a global kinetic model without requiring to sample all combinatorial states of subsystems. We give a theoretical basis for IMD and propose an approach for finding and validating such a decomposition. Using empirical few-state MSMs of ion channel models that are well established in electrophysiology, we demonstrate that IMD can reproduce experimental conductance measurements with a major reduction in sampling compared with a standard MSM approach. We further show how to find the optimal partition of all-atom protein simulations into weakly coupled subunits.

Significance Statement Molecular simulations of proteins are often interpreted using Markov state models (MSMs), in which each protein configuration is assigned to a global state. As we explore larger and more complex biological systems, the size of this global state space will face a combinatorial explosion, rendering it impossible to gather sufficient sampling data. In this work, we introduce an approach to decompose a system of interest into separable subsystems. We show that MSMs built for each subsystem can be later coupled to reproduce the behaviors of the global system. To aid in the choice of decomposition we also describe a score to quantify its goodness. This decomposition strategy has the promise to enable robust modeling of complex biomolecular systems.

  • Markov state models
  • independent processes
  • molecular kinetics
  • molecular dynamics
  • ion channels
  • optimal partition

Competing Interest Statement

The authors have declared no competing interest.

Footnotes

  • T.H., B.C.T., M.J.R., C.T.L., R.E.A., F.N. designed research; T.H., B.C.T., M.J.R., C.T.L. performed research; T.H., B.C.T., C.T.L., F.N. analyzed data; T.H., B.C.T., M.J.R., C.T.L., R.E.A., F.N. wrote the paper.

  • Conflict of interest statement: The authors declare no conflict of interest.

Copyright 
The copyright holder for this preprint is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. All rights reserved. No reuse allowed without permission.
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Posted March 25, 2021.
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Independent Markov Decomposition: Towards modeling kinetics of biomolecular complexes
Tim Hempel, Mauricio J. del Razo, Christopher T. Lee, Bryn C. Taylor, Rommie E. Amaro, Frank Noé
bioRxiv 2021.03.24.436806; doi: https://doi.org/10.1101/2021.03.24.436806
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Independent Markov Decomposition: Towards modeling kinetics of biomolecular complexes
Tim Hempel, Mauricio J. del Razo, Christopher T. Lee, Bryn C. Taylor, Rommie E. Amaro, Frank Noé
bioRxiv 2021.03.24.436806; doi: https://doi.org/10.1101/2021.03.24.436806

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