Projects per year
Abstract
pH dependence abounds in biochemical systems; however, many simulation methods used to investigate these systems do not consider this property. Using a modified version of the hybrid non-equilibrium molecular dynamics (MD)/Monte Carlo algorithm, we include a stochastic charge neutralization method, which is particularly suited to the MARTINI force field and enables artifact-free Ewald summation methods in electrostatic calculations. We demonstrate the efficacy of this method by reproducing pH-dependent self-assembly and self-organization behavior previously reported in experimental literature. In addition, we have carried out experimental oleic acid titrations where we report the results in a more relevant way for the comparison with computational methods than has previously been done.
Original language | English |
---|---|
Pages (from-to) | 4046−4051 |
Number of pages | 6 |
Journal | Journal of Physical Chemistry Letters |
Volume | 13 |
Issue number | 18 |
Early online date | 29 Apr 2022 |
DOIs | |
Publication status | Published - 12 May 2022 |
Keywords
- Constant pH
- CpHMD
- coarse grained molecular dynamics
- particle mesh Ewald
- Constant Charge
- titration
- Oleic acid
- Fmoc
- peptides
- self-assembly
Fingerprint
Dive into the research topics of 'Constant pH coarse-grained molecular dynamics with stochastic charge neutralization'. Together they form a unique fingerprint.Projects
- 1 Finished
-
E Infrastructure Bid - Capital Equipment Bid
Littlejohn, D. (Principal Investigator), Fedorov, M. (Co-investigator), Mulheran, P. (Co-investigator) & Reese, J. (Co-investigator)
EPSRC (Engineering and Physical Sciences Research Council)
20/01/12 → 31/03/12
Project: Research
Datasets
-
Data for: "Constant pH Coarse-Grained MolecularDynamics with Stochastic Charge Neutralization - Associated Data"
van Teijlingen, A. (Creator), Tuttle, T. (Supervisor), Swanson, H. W. A. (Creator) & Lau, K. H. A. (Supervisor), University of Strathclyde, 16 Feb 2022
DOI: 10.15129/f76ac245-0e38-40ca-ac3c-26c000510faf
Dataset