GPU-Enhanced DFTB Metadynamics for Efficiently Predicting Free Energies of Biochemical Systems

Abstract

Metadynamics calculations of large chemical systems with ab initio methods are computationally prohibitive due to the extensive sampling required to simulate the large degrees of freedom in these systems. To address this computational bottleneck, we utilized a GPU-enhanced density functional tight binding (DFTB) approach on a massively parallelized cloud computing platform to efficiently calculate the thermodynamics and metadynamics of biochemical systems. To first validate our approach, we calculated the free-energy surfaces of alanine dipeptide and showed that our GPU-enhanced DFTB calculations qualitatively agree with computationally-intensive hybrid DFT benchmarks, whereas classical force fields give significant errors. Most importantly, we show that our GPU-accelerated DFTB calculations are significantly faster than previous approaches by up to two orders of magnitude. To further extend our GPU-enhanced DFTB approach, we also carried out a 10 ns metadynamics simulation of remdesivir, which is prohibitively out of reach for routine DFT-based metadynamics calculations. We find that the free-energy surfaces of remdesivir obtained from DFTB and classical force fields differ significantly, where the latter overestimates the internal energy contribution of high free-energy states. Taken together, our benchmark tests, analyses, and extensions to large biochemical systems highlight the use of GPU-enhanced DFTB simulations for efficiently predicting the free-energy surfaces/thermodynamics of large biochemical systems.

Velocity-Gauge Real-Time Time-Dependent Density Functional Tight-Binding for Large-Scale Condensed Matter Systems

“…We anticipate that our VG-rtTDDFTB approach could find broad usage for large periodic systems, particularly for material systems that are too large to handle with rtTDDFT. Further extensions to accelerate these calculations with specialized hardware accelerators ,, are currently underway in our group.…”

“…To address this need, we present the first velocity-gauge real-time time-dependent density functional tight-binding (VG-rtTDDFTB) implementation in the open-source DFTB+ software package (https://dftbplus.org) for large-scale and long-time electron dynamics simulations with periodic boundary conditions. Our VG-rtTDDFTB implementation makes use of the density functional tight-binding (DFTB) formalism, , which is computationally efficient, relatively accurate, and scales extremely well with system size compared to full density functional theory (DFT). − …”

“…Our VG-rtTDDFTB implementation makes use of the density functional tight-binding (DFTB) formalism, 22 , 23 which is computationally efficient, relatively accurate, and scales extremely well with system size compared to full density functional theory (DFT). 24 − 29 …”

Beyond Conventional Density Functional Theory: Advanced Quantum Dynamical Methods for Understanding Degradation of Per- and Polyfluoroalkyl Substances

“…Consequently, extending both the length and time scales of these calculations would allow more realistic simulations that capture the spatial and temporal dynamics probed in PFAS degradation experiments. Progress on both these fronts is currently being tackled in our research group using excited-state semiempirical methods − and advanced hardware accelerators − to simulate large systems that cannot be easily obtained with conventional DFT. As algorithmic developments and computational resources improve, we recommend that these advanced quantum dynamics simulations be more widely used by the environmental research community to directly probe PFAS degradation dynamics and other environmental processes.…”