Journal
JOURNAL OF CHEMICAL THEORY AND COMPUTATION
Volume 14, Issue 6, Pages 2881-2888Publisher
AMER CHEMICAL SOC
DOI: 10.1021/acs.jctc.8b00192
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Funding
- MICCoM as part of the Computational Materials Sciences Program - U.S. Department of Energy (DOE), Office of Science, Basic Energy Sciences (BES), Materials Sciences and Engineering Division [5J-30161-0010A]
- National Science Foundation Graduate Fellowship Program (NSF-GRFP)
- University of Chicago Research Computing Center
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We present a seamless coupling of a suite of codes designed to perform advanced sampling simulations, with a first-principles molecular dynamics (MD) engine. As an illustrative example, we discuss results for the free energy and potential surfaces of the alanine dipeptide obtained using both local and hybrid density functionals (DFT), and we compare them with those of a widely used classical force field, Amber99sb. In our calculations, the efficiency of first-principles MD using hybrid functionals is augmented by hierarchical sampling, where hybrid free energy calculations are initiated using estimates obtained with local functionals. We find that the free energy surfaces obtained from classical and first-principles calculations differ. Compared to DFT results, the classical force field overestimates the internal energy contribution of high free energy states, and it underestimates the entropic contribution along the entire free energy profile. Using the string method, we illustrate how these differences lead to different transition pathways connecting the metastable minima of the alanine dipeptide. In larger peptides, those differences would lead to qualitatively different results for the equilibrium structure and conformation of these molecules.
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