An Efficient GaMD Multi-Level Enhanced Sampling Strategy: Application to Polarizable Force Fields Simulations of Large Biological Systems

We introduce a novel multi-level enhanced sampling strategy grounded on Gaussian accelerated Molecular Dynamics (GaMD). First, we propose a GaMD multi-GPUs-accelerated implementation within the Tinker-HP molecular dynamics package. We introduce the new "dual-water" mode and its use with the flexible AMOEBA polarizable force field.By adding harmonic boosts to the water stretching and bonding terms, it accelerates the solvent-solute interactions while enabling speedups thanks to the use of fast multiple--timestep integrators. To further reduce time-to-solution, we couple GaMD to Umbrella Sampling (US). The GaMD—US/dual--water approach is tested on the 1D Potential of Mean Force (PMF) of the solvated CD2--CD58 system (168000 atoms) allowing the AMOEBA PMF to converge within 1 kcal/mol of the experimental value. Finally, Adaptive Sampling (AS) is added enabling AS-GaMD capabilities but also the introduction of the new Adaptive Sampling--US--GaMD (ASUS-GaMD) scheme. The highly parallel ASUS--GaMD setup decreases time to convergence by respectively 10 and 20 times compared to GaMD-US and US. Overall, beside the acceleration of PMF computations, Tinker-HP now allows for the simultaneous use of Adaptive Sampling and GaMD-"dual water" enhanced sampling approaches increasing the applicability of polarizable force fields to large scale simulations of biological systems.

An Efficient GaMD Multi-Level Enhanced Sampling Strategy: Application to Polarizable Force Fields Simulations of Large Biological Systems

We detail a novel multi-level enhanced sampling strategy grounded on Gaussian accelerated Molecular Dynamics (GaMD). First, we propose a GaMD multi-GPUs-accelerated implementation within the Tinker-HP molecular dynamics package. We then introduce the new "dual-water" mode and its use with the flexible AMOEBA polarizable force field. By adding harmonic boosts to the water stretching and bonding terms, it accelerates the solvent-solute interactions while enabling speedups thanks to the use of fast multiple--timestep integrators. To further reduce time-to-solution, we couple GaMD to Umbrella Sampling (US). The GaMD—US/dual-water approach is tested on the 1D Potential of Mean Force (PMF) of the CD2-CD58 system (168000 atoms) allowing the AMOEBA PMF to converge within 1 kcal/mol of the experimental value. Finally, Adaptive Sampling (AS) is added enabling AS-GaMD capabilities but also the introduction of the new Adaptive Sampling--US--GaMD (ASUS--GaMD) scheme. The highly parallel ASUS--GaMD setup decreases time to convergence by respectively 10 and 20 compared to GaMD--US and US.

An Efficient GaMD Multi-Level Enhanced Sampling Strategy: Application to Polarizable Force Fields Simulations of Large Biological Systems

We detail a novel multi-level enhanced sampling strategy grounded on Gaussian accelerated Molecular Dynamics (GaMD). First, we propose a GaMD multi-GPUs-accelerated implementation within the Tinker-HP molecular dynamics package. We then introduce the new "dual-water" mode and its use with the flexible AMOEBA polarizable force field. By adding harmonic boosts to the water stretching and bonding terms, it accelerates the solvent-solute interactions while enabling speedups thanks to the use of fast multiple--timestep integrators. To further reduce time-to-solution, we couple GaMD to Umbrella Sampling (US). The GaMD—US/dual-water approach is tested on the 1D Potential of Mean Force (PMF) of the CD2-CD58 system (168000 atoms) allowing the AMOEBA PMF to converge within 1 kcal/mol of the experimental value. Finally, Adaptive Sampling (AS) is added enabling AS-GaMD capabilities but also the introduction of the new Adaptive Sampling--US--GaMD (ASUS--GaMD) scheme. The highly parallel ASUS--GaMD setup decreases time to convergence by respectively 10 and 20 compared to GaMD--US and US.

An Efficient GaMD Multi-Level Enhanced Sampling Strategy for Polarizable Force Fields Simulations of Large Biological Systems

We introduce a novel multi-level enhanced sampling strategy grounded on Gaussian accelerated Molecular Dynamics (GaMD). First, we propose a GaMD multi-GPUs -accelerated implementation within Tinker-HP. For the specific use with the flexible AMOEBA polarizable force field (PFF), we introduce the new "dual–water" GaMD mode. By adding harmonic boosts to the water stretching and bonding terms, it accelerates the solvent-solute interactions while enabling speedups with fast multiple–timestep integrators. To further reduce time-to-solution, we couple GaMD to Umbrella Sampling (US). The GaMD—US/dual–water approach is tested on the 1D Potential of Mean Force (PMF) of the CD2–CD58 system (168000 atoms) allowing the AMOEBA PMF to converge within 1 kcal/mol of the experimental value. Finally, Adaptive Sampling (AS) is added enabling AS–GaMD capabilities but also the introduction of the new Adaptive Sampling–US–GaMD (ASUS–GaMD) scheme. The highly parallel ASUS–GaMD setup decreases time to convergence by respectively 10 and 20 compared to GaMD–US and US.

Improvement of the Gaussian Electrostatic Model by Separate Fitting of Coulomb and Exchange-Repulsion Densities and Implementation of a new Dispersion term

The description of each separable contribution of the intermolecular interaction is a useful approach to develop polarizable force fields (polFF). The Gaussian Electrostatic Model (GEM) is based on this approach, coupled with the use of density fitting techniques. In this work, we present the implementation and testing of two improvements of GEM: the Coulomb and Exchange-Repulsion energies are now computed with separate frozen molecular densities, and a new dispersion formulation inspired by the SIBFA polFF, which has been implemented to describe the dispersion and charge–transfer interactions. Thanks to the combination of GEM characteristics and these new features, we demonstrate a better agreement of the computed structural and condensed properties for water with experimental results, as well as binding energies in the gas phase with the ab initio reference compared with the previous GEM* potential. This work provides further improvements to GEM and the items that remain to be improved, and the importance of the accurate reproduction for each separate contribution.

Kinetic pathways of water exchange in the first hydration shell of magnesium: Influence of water model and ionic force field

Water exchange between the first and second hydration shell is essential for the role of Mg2+ in biochemical processes. In order to provide microscopic insights into the exchange mechanism, we resolve the exchange pathways by all-atom molecular dynamics simulations and transition path sampling. Since the exchange kinetics relies on the choice of the water model and the ionic force field, we systematically investigate the influence of seven different polarizable and non-polarizable water and three different Mg2+ models. In all cases, water exchange can occur either via an indirect or direct mechanism (exchanging molecules occupy different/same position on water octahedron). In addition, the results reveal a crossover from an interchange dissociative (Id) to an associative (Ia) reaction mechanism dependent on the range of the Mg2+-water interaction potential of the respective force field. Standard non-polarizable force fields follow the Id mechanism in agreement with experimental results. By contrast, polarizable and long-ranged non-polarizable force fields follow the Ia mechanism. Our results provide a comprehensive view on the influence of the water model and ionic force field on the exchange dynamics and the foundation to assess the choice of the force field in biomolecular simulations.

Ion Pairing and Dielectric Decrement in Glycosaminoglycan Brushes

<p>Cell-surface polysaccharides are essential to many aspects of physiology, serving as a highly-conserved evolutionary feature of life and as an important part of the innate immune system in mammals. Here, as simplified biophysical models of these sugar-coatings, we present results of molecular dynamics simulations of hyaluronic acid and heparin brushes that show important effects of ion-pairing, water dielectric decrease, and co-ion exclusion. As in prior studies of macromolecular crowding under physiologically-relevant salt concentrations, our results show equilibria with electroneutrality attained through screening and pairing of brush anionic charges by monovalent cations at atomistic detail. Most surprising is the reversal of the Donnan potential obtained from both nonpolarizable and Drude polarizable force fields, in contrast to what would be expected based on electrostatic Boltzmann partitioning alone. Water dielectric decrement within the brush domain is also associated with Born hydration-driven cation exclusion from the brush. We observe that the primary partition energy attracting cations to attain brush electroneutrality is the ion-pairing or salt-bridge energy. Potassium and sodium pairing to glycosaminoglycan carboxylates and sulfates show similar abundance of contact-pairing and solvent-separated pairing. We conclude that in these crowded macromolecular brushes, ion-pairing, Born-hydration, and electrostatic potential energies all contribute to attain electroneutrality and should therefore contribute in mean-field models to accurately represent brush electrostatics. </p>