Nastasia Mauger’s research while affiliated with French National Centre for Scientific Research and other places

We report the implementation of a multi-CPU and multi-GPU massively parallel platform dedicated to the explicit inclusion of nuclear quantum effects (NQEs) in the Tinker-HP molecular dynamics (MD) package. The platform, denoted Quantum-HP, exploits two simulation strategies: the Ring-Polymer Molecular Dynamics (RPMD) that provides exact structural properties at the cost of a MD simulation in an extended space of multiple replicas and the adaptive Quantum Thermal Bath (adQTB) that imposes the quantum distribution of energy on a classical system via a generalized Langevin thermostat and provides computationally affordable and accurate (though approximate) NQEs. We discuss some implementation details, efficient numerical schemes, and parallelization strategies and quickly review the GPU acceleration of our code. Our implementation allows an efficient inclusion of NQEs in MD simulations for very large systems, as demonstrated by scaling tests on water boxes with more than 200,000 atoms (simulated using the AMOEBA polarizable force field). We test the compatibility of the approach with Tinker-HP's recently introduced Deep-HP machine learning potentials module by computing water properties using the DeePMD potential with adQTB thermostatting. Finally, we show that the platform is also compatible with the alchemical free energy estimation capabilities of Tinker-HP and fast enough to perform simulations. Therefore, we study how NQEs affect the hydration free energy of small molecules solvated with the recently developed Q-AMOEBA water force field. Overall, the Quantum-HP platform allows users to perform routine quantum MD simulations of large condensed-phase systems and will help to shed new light on the quantum nature of important interactions in biological matter.

We report the implementation of a multi-CPU and multi-GPU massively parallel platform dedicated to the explicit inclusion of nuclear quantum effects (NQEs) in the Tinker-HP molecular dynamics (MD) package. The platform, denoted Quantum-HP, exploits two simulation strategies: the Ring-Polymer Molecular Dynamics (RPMD) that provides exact structural properties at the cost of a MD simulation in an extended space of multiple replicas, and the adaptive Quantum Thermal Bath (adQTB) that imposes the quantum distribution of energy on a classical system via a generalized Langevin thermostat and provides computationally affordable and accurate (though approximate) NQEs. We discuss some implementation details, efficient numerical schemes, parallelization strategies and quickly review the GPU acceleration of our code. Our implementation allows an efficient inclusion of NQEs in MD simulations for very large systems, as demonstrated by scaling tests on water boxes with more than 200,000 atoms (simulated using the AMOEBA polarizable force field). We test the compatibility of the approach with Tinker-HP's recently introduced Deep-HP machine learning potentials module by computing water properties using the DeePMD potential with adQTB thermostating. Finally, we show that the platform is also compatible with the alchemical free energy estimation capabilities of Tinker-HP and fast enough to perform simulations. Therefore, we study how the NQEs affect the hydration free energy of small molecules solvated with the recently developed Q-AMOEBA water force field. Overall, the Quantum-HP platform allows users to perform routine quantum MD simulations of large condensed-phase systems and will participate to shed a new light on the quantum nature of important interactions in biological matter.

We introduce a new parametrization of the AMOEBA polarizable force field for water denoted Q-AMOEBA, for use in simulations that explicitly account for nuclear quantum effects (NQEs). This study is made possible thanks to the recently introduced adaptive Quantum Thermal Bath (adQTB) simulation technique which computational cost is comparable to classical molecular dynamics. The flexible Q-AMOEBA model conserves the initial AMOEBA functional form, with an intermolecular potential including an atomic multipole description of electrostatic interactions (up to quadrupole), a polarization contribution based on the Thole interaction model and a buffered 14−7 potential to model van der Waals interactions. It has been obtained by using a ForceBalance fitting strategy including high-level quantum chemistry reference energies and selected condensed-phase properties targets. The final Q-AMOEBA model is shown to accurately reproduce both gas-phase and condensed-phase properties, notably improving the original AMOEBA water model. This development allows the fine study of NQEs on water liquid phase properties such as the average H−O−H angle compared to its gas-phase equilibrium value, isotope effects, and so on. Q-AMOEBA also provides improved infrared spectroscopy prediction capabilities compared to AMOEBA03. Overall, we show that the impact of NQEs depends on the underlying model functional form and on the associated strength of hydrogen bonds. Since adQTB simulations can be performed at near classical computational cost using the Tinker-HP package, Q-AMOEBA can be extended to organic molecules, proteins, and nucleic acids opening the possibility for the large-scale study of the importance of NQEs in biophysics.

Molecular dynamics (MD) is a powerful tool to study properties of complex systems. However, it treats particles as classical one by using Newton's equation of motion. Therefore, Nuclear Quantum Effects (NQEs), such as zero point energy or tunneling, are not taken into account, although they can have an influence on the different mechanisms of chemical reactivity that imply light atoms even at ambient temperatures. The reference method to include NQEs is the Path Integral Molecular Dynamics (PIMD) based on Feynman formalism of quantum mechanics applied to the quantum partition function. It relies on an isomorphism between a quantum particle and a chain of harmonic oscillators, called beads, coupled through harmonic springs. However, the number of beads needed to reach convergence (typically several tens) remains the limiting factor and then reduces the possibility to study NQEs on more complex systems. The Quantum Thermal Bath (QTB) is an interesting alternative. This method relies on the Langevin equation where the different classical degrees of freedom are coupled to a chain of quantum oscillators. In the classical case, the Langevin equation obeys to the classical Fluctuation-Dissipation Theorem (FDT), which corresponds to the equipartition of energy. The QTB aims to impose the quantum FDT which implies to inject more energy in the high frequency modes to reproduce the effects of the zero point energy. However, an energy leakage appears when the method is applied to realistic systems due to the coupling between high and low frequency modes. To correct this leakage, an adaptive method has been proposed where the FDT is used as a criterion to systematically correct this unphysical flow of energy. The work presented in this thesis focuses on water which is an important chemical compound made up of hydrogen atoms. Its low mass makes NQEs not negligible. These NQEs can have a major impact on the solvent dynamics. Moreover, it has been shown that NQEs should be included in the dynamics to correctly recover some thermodynamical properties such as the density or the enthalpy of vaporization. In order to validate the method on highly anharmonic system such as water, PIMD and adQTB methods were implemented inside the molecular dynamics software TINKER-HP (CPU and GPU). The different results obtained with the q-TIP4P/f water model were very promising for the adQTB and a new polarizable water model has been developed: Q-AMOEBA. This new model allowed to study NQEs on a more complex functional form which includes polarization. This study shows that the impact of NQEs can no longer be generalized to all water models. Therefore, with this new model and the classical cost of the adQTB method, NQEs can now be included in MD simulations to study more complex systems such as proteins opening the paths to new domains such as biology or pharmacology.

We introduce a new parametrization of the AMOEBA polarizable force field for water denoted Q-AMOEBA, for use in simulations that explicitly account for nuclear quantum effects (NQEs). This study is made possible thanks to the recently introduced adaptive Quantum Thermal Bath (adQTB) simulation technique which computational cost is comparable to classical molecular dynamics. The flexible Q-AMOEBA model conserves the initial AMOEBA functional form, with an intermolecular potential including an atomic multipole description of electrostatic interactions (up to quadrupole), a polarization contribution based on the Thole interaction model and a buffered 14-7 potential to model van der Waals interactions. It has been obtained by using a Force Balance fitting strategy including high-level quantum chemistry reference energies and selected condensed phase properties targets. The final Q-AMOEBA model is shown to accurately reproduce both gas phase and condensed phase properties, notably improving the original AMOEBA water model. This development allows the fine study of NQEs on water liquid phase properties such as the average H-O-H angle compared to its gas phase equilibrium value, isotope effects etc... Q-AMOEBA also provides improved infrared spectroscopy prediction capabilities compared to AMOEBA03. Overall, we show that the impact of NQEs depends on the underlying model functional form and on the associated strength of hydrogen bonds. Since adQTB simulations can be performed at near classical computational cost using the Tinker-HP package, Q-AMOEBA can be extended to organic molecules, proteins and nucleic acids opening the possibility for the large scale study of the importance of NQEs in biophysics.

We demonstrate the accuracy and efficiency of a recently introduced approach to account for nuclear quantum effects (NQE) in molecular simulations: the adaptive Quantum Thermal Bath (adQTB). In this method, zero point energy is introduced through a generalized Langevin thermostat designed to precisely enforce the quantum fluctuation-dissipation theorem. We propose a refined adQTB algorithm with improved accuracy and we report adQTB simulations of liquid water. Through extensive comparison with reference path integral calculations, we demonstrate that it provides excellent accuracy for a broad range of structural and thermodynamic observables as well as infrared vibrational spectra. The adQTB has a computational cost comparable to classical molecular dynamics, enabling simulations of up to millions of degrees of freedom.