초록

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Abstract ▼ AI-Helper

It is no exaggeration to say that the productivity of a research using computer simulations on complex molecular systems like biomolecules depends on the ability of the sampling algorithm to explore the relevant parts of configuration space. In this study, we investigate the properties on the mutien...

It is no exaggeration to say that the productivity of a research using computer simulations on complex molecular systems like biomolecules depends on the ability of the sampling algorithm to explore the relevant parts of configuration space. In this study, we investigate the properties on the mutiensemble sampling (MES) which is one of the solutions that surmount limitations of conventional sampling algorithms. Works for finding out practical systematic ways of using the MES efficiently to explore distantly separated regions in configuration space are performed. In this work, the more generalized form of weighting function for MES is used and 'cavity formation in water' is simulated using Monte Carlo. investigating the correlation of simulation parameters and the efficiency of the method, we propose a practical way of maximizing the power of the MES. We applied the way to 'cavity formation in water' and were able to explore the parts of configuration space relevant to cavities of radius from 0 to 5.6A in a single simulation.