scholarly journals Does glycosyl transfer involve an oxacarbenium intermediate? Computational simulation of the lifetime of the methoxymethyl cation in water

2011 ◽  
Vol 83 (8) ◽  
pp. 1507-1514 ◽  
Author(s):  
Ian H. Williams ◽  
J. Javier Ruiz Pernía ◽  
Iñaki Tuñón
Keyword(s):  
Free Energy ◽  
Computational Simulation ◽  
Zero Point ◽  
Md Simulations ◽  
Quantum Corrections ◽  
Water Molecules ◽  
Point Energy ◽  
Classical Estimate ◽  
High Level ◽  
Energy Surfaces

2D free-energy surfaces for transfer of the methoxymethyl cation between two water molecules are constructed from molecular dynamics (MD) simulations in which these atoms are treated quantum-mechanically within a box of 1030 classical solvent water molecules at 300 K. This provides a simple model for glycosyl transfer in water. The AM1/TIP3P surfaces with 2D-spline corrections at either MPWB1K/6-31+G(d,p) or MP2/6-31+G(d,p) contain a shallow free-energy well corresponding to an oxacarbenium ion intermediate in a DN*AN mechanism. MD analysis at three temperatures leads to a classical estimate of the lifetime of the methoxymethyl cation in water; when quantum corrections for vibrational zero-point energy are included, the lifetime is estimated to be about 1 ps, in agreement with the best experimental estimate. This suggests that computational simulation, with appropriate high-level correction, is a reliable tool to obtain detailed and reliable mechanistic descriptions for glycosidases. In view of the importance of developing improved anti-influenza drugs, simulations of sialidases that considered both sialyl oxacarbenium ion and covalent sialyl-enzyme as possible intermediates could provide particular insight.

scholarly journals Dynamical strengthening of covalent and non-covalent molecular interactions by nuclear quantum effects at finite temperature

2021 ◽  
Vol 12 (1) ◽  
Author(s):  
Huziel E. Sauceda ◽  
Valentin Vassilev-Galindo ◽  
Stefan Chmiela ◽  
Klaus-Robert Müller ◽  
Alexandre Tkatchenko
Keyword(s):  
Finite Temperature ◽  
Electrostatic Interactions ◽  
Zero Point ◽  
Quantum Effects ◽  
Van Der Waals Interactions ◽  
Interatomic Distances ◽  
Point Energy ◽  
Molecular Bond ◽  
Energy Surfaces ◽  
Nuclear Quantum Effects

AbstractNuclear quantum effects (NQE) tend to generate delocalized molecular dynamics due to the inclusion of the zero point energy and its coupling with the anharmonicities in interatomic interactions. Here, we present evidence that NQE often enhance electronic interactions and, in turn, can result in dynamical molecular stabilization at finite temperature. The underlying physical mechanism promoted by NQE depends on the particular interaction under consideration. First, the effective reduction of interatomic distances between functional groups within a molecule can enhance the n → π* interaction by increasing the overlap between molecular orbitals or by strengthening electrostatic interactions between neighboring charge densities. Second, NQE can localize methyl rotors by temporarily changing molecular bond orders and leading to the emergence of localized transient rotor states. Third, for noncovalent van der Waals interactions the strengthening comes from the increase of the polarizability given the expanded average interatomic distances induced by NQE. The implications of these boosted interactions include counterintuitive hydroxyl–hydroxyl bonding, hindered methyl rotor dynamics, and molecular stiffening which generates smoother free-energy surfaces. Our findings yield new insights into the versatile role of nuclear quantum fluctuations in molecules and materials.

THE SURFACE TENSION OF LIQUID HELIUM

1953 ◽  
Vol 31 (7) ◽  
pp. 1165-1169 ◽  
Author(s):  
K. R. Atkins
Keyword(s):  
Surface Tension ◽  
Free Energy ◽  
Surface Energy ◽  
Liquid Helium ◽  
Normal Modes ◽  
Zero Point ◽  
Total Surface Energy ◽  
Helium Surface ◽  
Point Energy ◽  
Helium Ii

Following a suggestion due to Frenkel, the normal modes of a liquid helium surface are taken to be surface tension waves. The free energy associated with these modes is estimated and is found to give a major contribution to the temperature dependence of the surface tension of liquid helium II. The zero-point energy of the modes is shown to be an appreciable fraction of the total surface energy at 0°K.

scholarly journals Benchmarking Force Field and the ANI Neural Network Potentials for the Torsional Potential Energy Surface of Biaryl Drug Fragments

2020 ◽  
Author(s):  
Shae-Lynn Lahey ◽  
Từ Nguyễn Thiên Phúc ◽  
Christopher Rowley
Keyword(s):  
Neural Network ◽  
Potential Energy ◽  
Force Field ◽  
Potential Energy Surfaces ◽  
Md Simulations ◽  
Absolute Deviation ◽  
Torsional Potential ◽  
The Mean ◽  
High Level ◽  
Energy Surfaces

Many drug molecules contain biaryl fragments, resulting in a torsional barrier corresponding to rotation around the bond linking the aryls. The potential energy surfaces of these torsions vary significantly due to steric and electronic effects, ultimately affecting the relative stability of the molecular conformations in the protein-bound and solution states. Simulations of protein--ligand binding require accurate computational models to represent the intramolecular interactions to provide accurate predictions of the structure and dynamics of binding. In this paper, we compare four force fields (Generalized AMBER Force Field (GAFF), Open Force Field (OpenFF), CHARMM General Force Field (CGenFF), Optimized Potentials for Liquid Simulations (OPLS)) and two neural network potentials (ANI-2x, ANI-1ccx) in their ability to predict the torsional potential energy surfaces of 88 biaryls extracted from drug fragments. The mean of the absolute deviation over the full PES (MADF) and the mean absolute deviation of the torsion rotational barrier height (MADB) relative to high-level ab initio reference data was used as a measure of accuracy. In comparison to high-level ab-initio data, ANI-1ccx was most accurate for predicting the barrier height (MADF: 0.5~kcal/mol, MADB:~0.8~kcal/mol), followed closely by ANI-2x (MADF: 0.5~kcal/mol, MADB:~1.0~kcal/mol), then CGenFF (MADF: 0.8~kcal/mol, MADB: 1.3~kcal/mol), OpenFF (MADF: 1.5~kcal/mol, MADB: 1.4~kcal/mol), GAFF (MADF: 1.2~kcal/mol, MADB: 2.6~kcal/mol), and finally OPLS (MADF: 1.5~kcal/mol, MADB: 2.8~kcal/mol). Significantly, the NNPs are systematically more accurate and more reliable than any of the force fields. As a practical example, the neural network potential/molecular mechanics (NNP/MM) method was used to simulate the isomerization of ozanimod, a drug used for multiple sclerosis. Multi-nanosecond molecular dynamics (MD) simulations in an explicit aqueous solvent were performed, as well as umbrella sampling and adaptive biasing force enhanced sampling techniques. These theories predicted a rate of isomerization of $4.30 \times 10^{-1}$ ns$^{-1}$, which is consistent with direct MD simulations.

scholarly journals Astrophysically motivated laboratory measurements of deuterium reacting with isotopologues of H

2019 ◽  
Vol 15 (S350) ◽  
pp. 114-115
Author(s):  
K. P. Bowen ◽  
P.-M. Hillenbrand ◽  
J. Liévin ◽  
X. Urbain ◽  
D. W. Savin
Keyword(s):  
Cross Sections ◽  
Zero Point ◽  
Rate Coefficients ◽  
Laboratory Measurements ◽  
Exchange Reactions ◽  
Point Energy ◽  
Chemical Tracers ◽  
Prestellar Cores ◽  
Order Of Magnitude ◽  
High Level

AbstractH2D+ and D2H+ are important chemical tracers of prestellar cores due to their pure rotational spectra that can be excited at the ~20 K temperature of these environments. The use of these molecules as probes of prestellar cores requires understanding the chemistry that forms and destroys these molecules. Of the eight key reactions that have been identified (Albertssonet al. 2013), five are thought to be well understood. The remaining three are the isotope exchange reactions of atomic D with H $${ + \over 3}$$ , H2D+, and D2H+. Semi-classical results differ from the classical Langevin calculations by an order of magnitude (Moyano et al. 2004). To resolve this discrepancy, we have carried out laboratory measurements for these three reactions. Absolute cross sections were measured using a dual-source, merged fast-beams apparatus for relative collision energies between ~10 meV to ~10 eV (Hillenbrand et al. 2019). A semi-empirical model was developed incorporating high level quantum mechanical ab initio calculations for the zero-point-energy-corrected potential energy barrier in order to generate thermal rate coefficients for astrochemical models. Based on our studies, we find that these three reactions proceed too slowly at prestellar core temperatures to play a significant role in the deuteration of H $${ + \over 3}$$ isotopologues.

Benchmarking Force Field and the ANI Neural Network Potentials for the Torsional Potential Energy Surface of Biaryl Drug Fragments

2020 ◽  
Author(s):  
Shae-Lynn Lahey ◽  
Từ Nguyễn Thiên Phúc ◽  
Christopher Rowley
Keyword(s):  
Neural Network ◽  
Potential Energy ◽  
Force Field ◽  
Potential Energy Surfaces ◽  
Md Simulations ◽  
Absolute Deviation ◽  
Torsional Potential ◽  
The Mean ◽  
High Level ◽  
Energy Surfaces

Many drug molecules contain biaryl fragments, resulting in a torsional barrier corresponding to rotation around the bond linking the aryls. The potential energy surfaces of these torsions vary significantly due to steric and electronic effects, ultimately affecting the relative stability of the molecular conformations in the protein-bound and solution states. Simulations of protein--ligand binding require accurate computational models to represent the intramolecular interactions to provide accurate predictions of the structure and dynamics of binding. In this paper, we compare four force fields (Generalized AMBER Force Field (GAFF), Open Force Field (OpenFF), CHARMM General Force Field (CGenFF), Optimized Potentials for Liquid Simulations (OPLS)) and two neural network potentials (ANI-2x, ANI-1ccx) in their ability to predict the torsional potential energy surfaces of 88 biaryls extracted from drug fragments. The mean of the absolute deviation over the full PES (MADF) and the mean absolute deviation of the torsion rotational barrier height (MADB) relative to high-level ab initio reference data was used as a measure of accuracy. In comparison to high-level ab-initio data, ANI-1ccx was most accurate for predicting the barrier height (MADF: 0.5~kcal/mol, MADB:~0.8~kcal/mol), followed closely by ANI-2x (MADF: 0.5~kcal/mol, MADB:~1.0~kcal/mol), then CGenFF (MADF: 0.8~kcal/mol, MADB: 1.3~kcal/mol), OpenFF (MADF: 1.5~kcal/mol, MADB: 1.4~kcal/mol), GAFF (MADF: 1.2~kcal/mol, MADB: 2.6~kcal/mol), and finally OPLS (MADF: 1.5~kcal/mol, MADB: 2.8~kcal/mol). Significantly, the NNPs are systematically more accurate and more reliable than any of the force fields. As a practical example, the neural network potential/molecular mechanics (NNP/MM) method was used to simulate the isomerization of ozanimod, a drug used for multiple sclerosis. Multi-nanosecond molecular dynamics (MD) simulations in an explicit aqueous solvent were performed, as well as umbrella sampling and adaptive biasing force enhanced sampling techniques. These theories predicted a rate of isomerization of $4.30 \times 10^{-1}$ ns$^{-1}$, which is consistent with direct MD simulations.

scholarly journals Benchmarking Force Field and the ANI Neural Network Potentials for the Torsional Potential Energy Surface of Biaryl Drug Fragments

2020 ◽  
Author(s):  
Shae-Lynn Lahey ◽  
Từ Nguyễn Thiên Phúc ◽  
Christopher Rowley
Keyword(s):  
Neural Network ◽  
Potential Energy ◽  
Force Field ◽  
Potential Energy Surfaces ◽  
Md Simulations ◽  
Absolute Deviation ◽  
Torsional Potential ◽  
The Mean ◽  
High Level ◽  
Energy Surfaces

Many drug molecules contain biaryl fragments, resulting in a torsional barrier corresponding to rotation around the bond linking the aryls. The potential energy surfaces of these torsions vary significantly due to steric and electronic effects, ultimately affecting the relative stability of the molecular conformations in the protein-bound and solution states. Simulations of protein--ligand binding require accurate computational models to represent the intramolecular interactions to provide accurate predictions of the structure and dynamics of binding. In this paper, we compare four force fields (Generalized AMBER Force Field (GAFF), Open Force Field (OpenFF), CHARMM General Force Field (CGenFF), Optimized Potentials for Liquid Simulations (OPLS)) and two neural network potentials (ANI-2x, ANI-1ccx) in their ability to predict the torsional potential energy surfaces of 88 biaryls extracted from drug fragments. The mean of the absolute deviation over the full PES (MADF) and the mean absolute deviation of the torsion rotational barrier height (MADB) relative to high-level ab initio reference data was used as a measure of accuracy. In comparison to high-level ab-initio data, ANI-1ccx was most accurate for predicting the barrier height (MADF: 0.5~kcal/mol, MADB:~0.8~kcal/mol), followed closely by ANI-2x (MADF: 0.5~kcal/mol, MADB:~1.0~kcal/mol), then CGenFF (MADF: 0.8~kcal/mol, MADB: 1.3~kcal/mol), OpenFF (MADF: 1.5~kcal/mol, MADB: 1.4~kcal/mol), GAFF (MADF: 1.2~kcal/mol, MADB: 2.6~kcal/mol), and finally OPLS (MADF: 1.5~kcal/mol, MADB: 2.8~kcal/mol). Significantly, the NNPs are systematically more accurate and more reliable than any of the force fields. As a practical example, the neural network potential/molecular mechanics (NNP/MM) method was used to simulate the isomerization of ozanimod, a drug used for multiple sclerosis. Multi-nanosecond molecular dynamics (MD) simulations in an explicit aqueous solvent were performed, as well as umbrella sampling and adaptive biasing force enhanced sampling techniques. These theories predicted a rate of isomerization of $4.30 \times 10^{-1}$ ns$^{-1}$, which is consistent with direct MD simulations.

scholarly journals Accounting for the Central Role of Interfacial Water in Protein-Ligand Binding Free Energy Calculations

2020 ◽  
Author(s):  
Ido Ben-Shalom ◽  
Zhixiong Lin ◽  
Brian Radak ◽  
Charles Lin ◽  
Woody Sherman ◽  
...  
Keyword(s):  
Free Energy ◽  
Binding Site ◽  
Binding Free Energy ◽  
Md Simulations ◽  
Simulation Software ◽  
Free Energy Calculations ◽  
Computer Hardware ◽  
Water Molecules ◽  
Energy Calculations ◽  
Binding Free Energy Calculations

Rigorous binding free energy methods in drug discovery are growing in popularity due to a combination of methodological advances, improvements in computer hardware, and workflow automation. These calculations typically use molecular dynamics (MD) to sample from the Boltzmann distribution of conformational states. However, when part or all the binding site is inaccessible to bulk solvent, the time needed for water molecules to equilibrate between bulk solvent and the binding site can be well beyond what is practical with standard MD. This sampling limitation is problematic in relative binding free energy calculations, which compute the reversible work of converting Ligand 1 to Ligand 2 within the binding site. Thus, if Ligand 1 is smaller and/or more polar than Ligand 2, the perturbation may allow additional water molecules to occupy a region of the binding site. However, this change in hydration may not be captured by standard MD simulations and may therefore lead to errors in the computed free energy. We recently developed a hybrid Monte Carlo/MD (MC/MD) method, which speeds the equilibration of water between bulk solvent and buried cavities, while sampling from the intended distribution of states. Here, we report on the use of this approach in the context of alchemical binding free energy calculations. We find that using MC/MD markedly improves the accuracy of the calculations and also reduces hysteresis between the forward and reverse perturbations, relative to matched calculations using only MD with or without the crystallographic water molecules. The present method is available for use in the AMBER simulation software.<br>

scholarly journals Accounting for the Central Role of Interfacial Water in Protein-Ligand Binding Free Energy Calculations

2020 ◽  
Author(s):  
Ido Ben-Shalom ◽  
Zhixiong Lin ◽  
Brian Radak ◽  
Charles Lin ◽  
Woody Sherman ◽  
...  
Keyword(s):  
Free Energy ◽  
Binding Site ◽  
Binding Free Energy ◽  
Md Simulations ◽  
Simulation Software ◽  
Free Energy Calculations ◽  
Computer Hardware ◽  
Water Molecules ◽  
Energy Calculations ◽  
Binding Free Energy Calculations

Rigorous binding free energy methods in drug discovery are growing in popularity due to a combination of methodological advances, improvements in computer hardware, and workflow automation. These calculations typically use molecular dynamics (MD) to sample from the Boltzmann distribution of conformational states. However, when part or all the binding site is inaccessible to bulk solvent, the time needed for water molecules to equilibrate between bulk solvent and the binding site can be well beyond what is practical with standard MD. This sampling limitation is problematic in relative binding free energy calculations, which compute the reversible work of converting Ligand 1 to Ligand 2 within the binding site. Thus, if Ligand 1 is smaller and/or more polar than Ligand 2, the perturbation may allow additional water molecules to occupy a region of the binding site. However, this change in hydration may not be captured by standard MD simulations and may therefore lead to errors in the computed free energy. We recently developed a hybrid Monte Carlo/MD (MC/MD) method, which speeds the equilibration of water between bulk solvent and buried cavities, while sampling from the intended distribution of states. Here, we report on the use of this approach in the context of alchemical binding free energy calculations. We find that using MC/MD markedly improves the accuracy of the calculations and also reduces hysteresis between the forward and reverse perturbations, relative to matched calculations using only MD with or without the crystallographic water molecules. The present method is available for use in the AMBER simulation software.<br>

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