TIGER2: An improved algorithm for temperature intervals with global exchange of replicas

Abstract

An empirical sampling method for molecular simulation based on "temperature intervals with global exchange of replicas" ͑TIGER2͒ has been developed to reduce the high demand for computational resources and the low computational efficiency of the conventional replica-exchange molecular dynamics ͑REMD͒ method. This new method overcomes the limitation of its previous version, called TIGER, which requires the assumption of constant heat capacity during quenching of replicas from elevated temperatures to the baseline temperature. The robustness of the TIGER2 method is examined by comparing it against a Metropolis Monte Carlo simulation for sampling the conformational distribution of a single butane molecule in vacuum, a REMD simulation for sampling the behavior of alanine dipeptide in explicit solvent, and REMD simulations for sampling the folding behavior of two peptides, ͑AAQAA͒ 3 and chignolin, in implicit solvent. The agreement between the results from these conventional sampling methods and the TIGER2 simulations indicates that the TIGER2 algorithm is able to closely approximate a Boltzmann-weighted ensemble of states for these systems but without the limiting assumptions that were required for the original TIGER algorithm. TIGER2 is an efficient replica-exchange sampling method that enables the number of replicas that are used for a replica-exchange simulation to be substantially reduced compared to the conventional REMD method.

TIGER2 with solvent energy averaging (TIGER2A): An accelerated sampling method for large molecular systems with explicit representation of solvent

“…The "temperature intervals with global exchange of replicas" (TIGER2) method 1,2 was recently developed to overcome some limitations of the conventional "replica exchange molecular dynamics" (REMD) method, 3 which becomes increasingly computationally expensive as the size of the molecular system being simulated increases. For complex systems with many degrees of freedom, the REMD method requires the use of a large number of replicas at closely spaced temperature levels in order that the overlap between potential energy distributions of adjacent replicas is sufficient to obtain an acceptable exchange rate.…”

Multiscale approach for the construction of equilibrated all-atom models of a poly(ethylene glycol)-based hydrogel

“…[54][55][56][57][58] Finally, the complete atomistic structure of the PEG-based hydrogel network was obtained by reverse mapping the equilibrated CG model to an all-atom model followed by adding explicit hydration and final further equilibration using molecular dynamics (MD), thus providing an all-atom representation of an equilibrated PEG-based hydrogel network.…”

“…For this process, we applied the TIGER2 advanced sampling method. 54,55 This method has two important characteristics: (1) using multiple replicas sampled at different temperature levels to help the system efficiently escape from local potential-energy minima, and (2) enabling the number of replicas used for this replica exchange simulation to be independent of the size of the molecular system. TIGER2 thus provides an accelerated sampling method that can be used to efficiently equilibrate systems that are too large for the application of conventional simulation techniques, such as standard MD or replica exchange molecular dynamics 82 methods.…”

“…TIGER2 thus provides an accelerated sampling method that can be used to efficiently equilibrate systems that are too large for the application of conventional simulation techniques, such as standard MD or replica exchange molecular dynamics 82 methods. The TIGER2 method has been successively applied in simulations of peptides and proteins in implicit solvent 54,55 as well as amorphous polymers.…”

Force fields for simulating the interaction of surfaces with biological molecules

“…First, Sun et al tried calculating the adsorption free energy of peptides using implicit water, but it became clear from this work that explicit water is necessary for accurately calculating the free energy of peptide adsorption [54]. The extra computational load of explicit water was addressed using a novel enhanced sampling method [55,56]. Since that work, computer power has increased and the need for enhanced sampling has diminished-longer periods of simulation can now adequately sample slower degrees of freedom [14].…”