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Temperature replica exchange molecular dynamics (T-REM) has been successfully used to improve the conformational search for model peptides and small proteins. However, for larger and more complicated systems, the use of T-REM is computationally intensive since the complexity of the free energy landscape and number of replicas required increase with system size. Achieving convergence of systems with slow transition kinetics is often difficult. Several methods have been proposed to overcome the size and convergence speed issues of standard T-REM. One of these is the Reservoir Replica Exchange Method (R-REM), in which the conformational search and temperature equilibration are separated by exchanging with a pre-existing reservoir of structures. This approach allows the integration of computationally efficient search algorithms with replica exchange. The Conformational Space Annealing (CSA) method has been shown to be able to determine the global energy minimum of proteins efficiently and has been used in structure prediction successfully. CSA uses a genetic algorithm to generate a diverse set of conformations to determine the minimum energy structure. We combine these methods by using conformations generated by the CSA method to build a reservoir. R-REM is then used to seed the top replica with the structures from the reservoir; fast convergence at every temperature is observed. The efficiency of this method is then demonstrated with model peptides and small proteins, and significant improvement of efficiency is observed while maintaining the overall shape of the free energy landscape.

Generating Reservoir Conformations for Replica Exchange through the Use of the Conformational Space Annealing Method