Replica exchange molecular dynamics (REMD) is a popular method to accelerate conformational sampling of complex molecular systems. The idea is to run several replicas of the system in parallel at different temperatures that are swapped periodically. These swaps are typically attempted every few MD steps and accepted or rejected according to a Metropolis-Hastings criterion. This guarantees that the joint distribution of the composite system of replicas is the normalized sum of the symmetrized product of the canonical distributions of these replicas at the different temperatures. Here we propose a different implementation of REMD in which (i) the swaps obey a continuous-time Markov jump process implemented via Gillespie's stochastic simulation algorithm (SSA), which also samples exactly the aforementioned joint distribution and has the advantage of being rejection free, and (ii) this REMD-SSA is combined with the heterogeneous multiscale method to accelerate the rate of the swaps and reach the so-called infinite-swap limit that is known to optimize sampling efficiency. The method is easy to implement and can be trivially parallelized. Here we illustrate its accuracy and efficiency on the examples of alanine dipeptide in vacuum and C-terminal β-hairpin of protein G in explicit solvent. In this latter example, our results indicate that the landscape of the protein is a triple funnel with two folded structures and one misfolded structure that are stabilized by H-bonds.
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http://dx.doi.org/10.1073/pnas.1605089113 | DOI Listing |
Biophys Chem
December 2024
School of Biotechnology, Jawaharlal Nehru University, New Delhi 110067, India. Electronic address:
Parkinson's disease (PD) is a neurodegenerative disorder involving the progressive loss of dopaminergic neurons in the substantia nigra pars compacta triggered by the accumulation of amyloid aggregates of α-synuclein protein. This study investigates the potential of Salvianolic Acid B (SalB), a water-soluble polyphenol derived from Salvia miltiorrhiza Bunge, in modulating the aggregation of the A53T mutant of α-synuclein (A53T Syn). This mutation is associated with rapid aggregation and a higher rate of protofibril formation in early-onset familial PD.
View Article and Find Full Text PDFJ Phys Chem B
December 2024
Faculty of Chemistry, University of Gdańsk, Fahrenheit Union of Universities in Gdańsk, Wita Stwosza 63, 80-308 Gdańsk, Poland.
The association of 55 dipeptides extracted from aggregation-prone regions of selected proteins was studied by means of multiplexed replica-exchange molecular dynamics simulations with the coarse-grained UNRES model of polypeptide chains. Each simulation was carried out with 320 dipeptide molecules in a periodic box at 0.24 mol/dm concentration, in the 260-370 K temperature range.
View Article and Find Full Text PDFInt J Mol Sci
November 2024
Engelhardt Institute of Molecular Biology, Russian Academy of Sciences, 119991 Moscow, Russia.
Src kinase is one of the key regulators of cellular metabolism and is dysregulated in numerous diseases, including cancer, neurodegenerative diseases, and particularly Alzheimer's disease. Despite its therapeutic importance, its full-length structure has never been obtained before, as it contains an intrinsically disordered regulatory region, SH4UD. The SH4UD region is crucial for Src activation, functional dimerization, and regulation by other kinases.
View Article and Find Full Text PDFJ Pers Med
November 2024
3dmi Research Group, Department of Medical Physics, School of Medicine, University of Patras, 26504 Rion, Greece.
This review examines the significant influence of Digital Twins (DTs) and their variant, Digital Human Twins (DHTs), on the healthcare field. DTs represent virtual replicas that encapsulate both medical and physiological characteristics-such as tissues, organs, and biokinetic data-of patients. These virtual models facilitate a deeper understanding of disease progression and enhance the customization and optimization of treatment plans by modeling complex interactions between genetic factors and environmental influences.
View Article and Find Full Text PDFSci Technol Adv Mater
October 2024
Department of Materials, Faculty of Engineering, Kyushu University, Fukuok, Japan.
This review presents computational and machine learning methodologies developed during a 5-year research project on proton-conducting oxides. The main goal was to develop methodologies that could assist in materials discovery or provide new insights into complex proton-conducting oxides. Through these methodologies, three new proton-conducting oxides, including both perovskite and non-perovskites, have been discovered.
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