Testing and Optimizing the Drude Polarizable Force Field for Blocked Amino Acids Based on High-Level Quantum-Mechanical Energy Surfaces

The correct reproduction of conformational substates of amino acids was tested for the CHARMM Drude polarizable force field. This was achieved by evaluating the reorganization energies for all low lying energy minima occurring in all 15 neutral blocked amino acids on a quantum-mechanical (QM) energy surface at the MP2/cc-pVDZ level. The results indicate that the bonded parameters of the N-acetyl (ACE) and N-Methylamide (CT3) blocking groups lead to significant discrepancies. A reparametrization of five bond angles significantly improved the agreement with the QM energy surface. The corrected Drude force field exhibits almost the same average reorganization energies relative to the MP2 energy surface as the AM1 and PM3 semi-empirical methods.

Ion Transport, Selectivity, and Electronic Polarization in Fluoride Channels

Fluoride channels (Fluc) export toxic F- from the cytoplasm. Crystallography and mutagenesis have identified several conserved residues crucial for fluoride transport, but the transport mechanism at the molecular level has remained elusive. Herein we have applied constant-pH molecular dynamics and free energy sampling methods to investigate fluoride transfer through a Fluc protein from Escherichia coli. We find that fluoride is facile to transfer in its charged form, i.e., F-, by traversing through a non-bonded network. The extraordinary F- selectivity is gained by the hydrogen-bonding capability of the central binding site and the Coulombic filter at the channel entrance. The F- transfer rate calculated using an electronically polarizable force field is significantly more accurate compared to the experimental value than that calculated using a more standard additive force field, suggesting an essential role for electronic polarization in the F- - Fluc interactions.

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.

Conformational Flexibilities and Solvation Properties of Insulin in Aromatic Amino Acid Solutions: A Molecular Dynamics Study Using CHARMM Drude Polarizable Model

Aromatic amino acids (AAA) play a crucial role in the structure and function of proteins. A higher level of AAA causes several diseases, controls insulin levels. In this work, we carried out atomistic molecular dynamics simulations by using CHARMM Drude polarizable force field to investigate the conformational properties of insulin monomer in 2M phe, tyr, trp solutions as well as in pure aqueous solution to compare the relative changes of protein conformations, its solvation properties and the interactions of the free AAA with insulin. Although insulin’s native folded form was intact in all the solutions within the simulation length scale, we observed that the protein is a little more flexible and less compact in phe solution than in tyr/trp solutions. The free AAAs identified to self-aggregate around the protein surface and form clusters of different sizes. They interacted with insulin, significantly through cation/anion–[Formula: see text] and [Formula: see text]–[Formula: see text] stacking, and partly through hydrogen bonded interactions. Among the three, trp was prone to interact through cation–[Formula: see text] interactions while phe and tyr interacted through [Formula: see text]–[Formula: see text] stacking with insulin. Despite a significant number of free AAA molecules in the solvation shell, insulin was observed to be sufficiently hydrated and formed hydrogen bonds with water. Some of our findings agreed with the available experimental results that establish the reliability of the chosen force field. Our findings would interpret the interactions between the free AAA and insulin in solution, helpful to recognize the microscopic details of AAA governed biological processes in living organisms.

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.