Special Issue "Nonequilibrium Dynamics and Molecular Simulation in Living Systems"
Deadline for manuscript submissions: closed (7 December 2021).
Living organisms use energy to drive physicochemical processes uphill, against energy gradients, escaping from the corresponding minima. Thus, many biophysical and biochemical processes of interest in biology, ranging from protein–ligand binding or protein unfolding to electron transfer or enzymatic reactivity, are activated events. This nonequilibrium nature manifests at the nanoscale, at the molecular level. Therefore, to interpret experimental findings and assist rational design, these so-called rare events are commonly investigated using molecular dynamics simulations, relying on the use of enhanced sampling techniques.
Many methodological advances, including the use of machine and deep learning to increase the performance of computational protocols, have been made in the last few years. This Special Issue, dedicated to the computational study of out-of-equilibrium processes occurring in complex systems, aims to collect both novel theoretical developments in the field of nonequilibrium molecular simulations as well as applications of well-established techniques to sample rare events occurring in biologically relevant systems in order to shed light on their physicochemical mechanisms and dynamics. To this end, both unpublished original papers and comprehensive reviews focused on, but not restricted to, the research areas listed below will be considered.
- Novel applications of enhanced sampling techniques to protein folding/unfolding and aggregation;
- Computational studies on active conduction in ion channels;
- Modeling and interpretation of single-molecule pulling experiments;
- Nonequilibrium molecular dynamics simulations on energy transport and protein allosteric communication;
- New developments and applications of Markov state models to describe activated events;
- Multiscale modeling studies on electron transfer and enzymatic reactivity;
- Computational modeling of photoinduced conformational changes and intramolecular signaling in biomolecules;
- Applications of machine and deep learning to predict nonequilibrium structures and properties;
- Approaches to learn Markov models from data;
- Novel computational techniques to investigate rare events.
Dr. Pablo Campomanes
Manuscript Submission Information
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- nonequilibrium processes
- rare events
- molecular dynamics
- enhance sampling
- machine learning
- deep learning
- multiscale modeling