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Peptide Folding in Cellular Environments: A Monte Carlo and Markov Modeling Approach

  • Daniel Nilsson
  • Sandipan Mohanty
  • Anders Irbäck
Chapter
Part of the Springer Series on Bio- and Neurosystems book series (SSBN, volume 8)

Abstract

Steric interactions with surrounding macromolecules tend to favor the compact native state of a globular protein over its unfolded state. However, in experiments conducted in cells and concentrated protein solutions, both stabilization and destabilization of proteins have been observed, compared to dilute-solution conditions. Therefore, in order to understand the effects of surrounding macromolecules on protein properties such as stability, there is a need for computational modeling beyond the level of hard-sphere crowders. Here, we discuss some recent exploratory studies of peptide folding in the presence of explicit protein crowders, carried out by us using an all-atom Monte Carlo-based approach along with an implicit solvent force field. For interpreting the simulation data, time-lagged independent component analysis and Markov state modeling are used.

Notes

Acknowledgements

The work discussed in this article was in part supported by the Swedish Research Council (Grant no. 621-2014-4522) and the Swedish strategic research program eSSENCE. The simulations were performed on resources provided by the Swedish National Infrastructure for Computing (SNIC) at LUNARC, Lund University, Sweden, and Jülich Supercomputing Centre, Forschungszentrum Jülich, Germany.

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© Springer Nature Switzerland AG 2019

Authors and Affiliations

  • Daniel Nilsson
    • 1
  • Sandipan Mohanty
    • 2
  • Anders Irbäck
    • 1
  1. 1.Department of Astronomy and Theoretical PhysicsLund UniversityLundSweden
  2. 2.Institute for Advanced Simulation, Jülich Supercomputing Centre, Forschungszentrum JülichJülichGermany

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