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BROMOCEA Code: An Improved Grand Canonical Monte Carlo/Brownian Dynamics Algorithm Including Explicit Atoms
- Source :
- Journal of chemical theory and computation. 12(5)
- Publication Year :
- 2016
-
Abstract
- All-atom molecular dynamics simulations have a long history of applications studying ion and substrate permeation across biological and artificial pores. While offering unprecedented insights into the underpinning transport processes, MD simulations are limited in time-scales and ability to simulate physiological membrane potentials or asymmetric salt solutions and require substantial computational power. While several approaches to circumvent all of these limitations were developed, Brownian dynamics simulations remain an attractive option to the field. The main limitation, however, is an apparent lack of protein flexibility important for the accurate description of permeation events. In the present contribution, we report an extension of the Brownian dynamics scheme which includes conformational dynamics. To achieve this goal, the dynamics of amino-acid residues was incorporated into the many-body potential of mean force and into the Langevin equations of motion. The developed software solution, called BROMOCEA, was applied to ion transport through OmpC as a test case. Compared to fully atomistic simulations, the results show a clear improvement in the ratio of permeating anions and cations. The present tests strongly indicate that pore flexibility can enhance permeation properties which will become even more important in future applications to substrate translocation.
- Subjects :
- 0301 basic medicine
Flexibility (engineering)
Quantitative Biology::Biomolecules
Field (physics)
Chemistry
Monte Carlo method
Dynamics (mechanics)
Equations of motion
Molecular Dynamics Simulation
Protein Structure, Secondary
Computer Science Applications
Protein Structure, Tertiary
03 medical and health sciences
Molecular dynamics
030104 developmental biology
Brownian dynamics
Statistical physics
Physical and Theoretical Chemistry
Potential of mean force
Monte Carlo Method
Algorithms
Subjects
Details
- ISSN :
- 15499626
- Volume :
- 12
- Issue :
- 5
- Database :
- OpenAIRE
- Journal :
- Journal of chemical theory and computation
- Accession number :
- edsair.doi.dedup.....076f28435ae52b962cb32954ab9029fc