NAMD is a highly scalable molecular dynamics (MD) software, used for all-atom simulations of biomolecular systems with dozens of millions of atoms. Despite its great success, MD simulations are still limited in two regards: inaccuracy of classical force fields and high computational cost. Even employing petascale supercomputers, it may be impractical to adequately sample conformational states, which in turn limits the ability to analyze and reveal functional properties of the systems being examined. To address the high computational cost, a range of enhanced sampling techniques have been integrated to NAMD, leading to intelligent conformational exploration. Addressing the classical force field limitations, NAMD recently gained a powerful and flexible quantum-mechanics/molecular-mechanics (QM/MM) interface, while VMD’s QwikMD interface was also enhanced to significantly accelerate the process of setting up hybrid simulations (Nature Methods, 2018). Combining enhanced sampling with QM/MM techniques allows for the study of nanosecond timescale biological processes that rely on, for instance, chemical reactions or charge redistribution. For a simple reaction, the overall mechanism and free energy can be obtained in a single day using a state-of-the-art desktop computer. Due to the largely parallel nature of NAMD and its enhanced sampling and free energy calculation tools, large and complex reaction mechanisms can be tackled in a few days using a local cluster or supercomputer. We applied a combination of string method and adaptive biasing force to investigate the reaction mechanism of relevant biomolecular complexes, such as the aminoacylation of tRNA molecules by their cognate tRNA synthetase, and the decarboxylation of orotidine monophosphate (OMP). The jupyter notebook framework was employed for automation of key steps in the preparation and analysis of simulations of large and complex reaction mechanisms. Our protocol provides a practical and precise description of the energetics of enzymatic mechanisms.

NAMD’s enhanced sampling techniques applied to QM/MM simulations

256th National Meeting (2018)

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