Zobrazeno 1 - 10 of 81 pro vyhledávání: '"Louis Lagardère"'
1
Scalable Hybrid Deep Neural Networks/Polarizable Potentials Biomolecular Simulations including Long-range Effects
Autor: Théo Jaffrelot Inizan, Thomas Plé, Olivier Adjoua, Pengyu Ren, Hatice Gökcan, Olexandr Isayev, Louis Lagardère, Jean-Philip Piquemal
Publikováno v: Chemical Science
Chemical Science, 2023, ⟨10.1039/D2SC04815A⟩
International audience; Deep-HP is a scalable extension of the Tinker-HP multi-GPUs molecular dynamics (MD) package enabling the use of Pytorch/TensorFlow Deep Neural Networks (DNNs) models. Deep-HP increases DNNs MD capabilities by orders of magnitu
Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::e3204c37f45afbf96b891d166d560cc0
https://hal.science/hal-03738403
Zobrazit plný text záznamu
2
Actin-AMOEBA
Autor: Adrien Schahl, Louis Lagardère, Brandon Walker, Pengyu Ren, Antoine Jégou, Matthieu Chavent, Jean-Philip Piquemal
Depository gathering all the relevant data for the work published in the following preprint: β-actin plasticity is modulated by coordinated actions of histidine 73 methylation, nucleotide type, and ions (https://doi.org/10.1101/2022.12.16.520803) Th
Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::e6ad2a38c8830d22e3d22daad1d63b43
Zobrazit plný text záznamu
3
Improving Condensed-Phase Water Dynamics with Explicit Nuclear Quantum Effects: The Polarizable Q-AMOEBA Force Field
Autor: Nastasia Mauger, Thomas Plé, Louis Lagardère, Simon Huppert, Jean-Philip Piquemal
Publikováno v: Journal of Physical Chemistry B
Journal of Physical Chemistry B, 2022, ⟨10.1021/acs.jpcb.2c04454⟩
International audience; 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
Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::989977a9c57ba3498377313029468b15
https://pubmed.ncbi.nlm.nih.gov/36270033
Zobrazit plný text záznamu
4
Generalized Many-Body Dispersion Correction through Random-phase Approximation for Chemically Accurate Density Functional Theory
Autor: Pier Paolo Poier, Olivier Adjoua, Louis Lagardère, Jean-Philip Piquemal
Publikováno v: Journal of Physical Chemistry Letters
Journal of Physical Chemistry Letters, 2023, pp.1609-1617. ⟨10.1021/acs.jpclett.2c03722⟩
International audience; We extend our recently proposed Deep Learning-aided many-body dispersion (DNN-MBD) model to quadrupole polarizability (Q) terms using a generalized Random Phase Approximation (RPA) formalism enabling to include van der Waals c
Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::cb1658f9c758dce95a07393482dd4d82
http://arxiv.org/abs/2210.09784
Zobrazit plný text záznamu
5
Targeting the Major Groove of the Palindromic d(GGCGCC)
Autor: Krystel, El Hage, Giovanni, Ribaudo, Louis, Lagardère, Alberto, Ongaro, Philippe H, Kahn, Luc, Demange, Jean-Philip, Piquemal, Giuseppe, Zagotto, Nohad, Gresh
Publikováno v: Journal of chemical information and modeling. 62(24)
GC-rich sequences are recurring motifs in oncogenes and retroviruses and could be targeted by noncovalent major-groove therapeutic ligands. We considered the palindromic sequence d(G
Externí odkaz: https://explore.openaire.eu/search/publication?articleId=pmid________::c74b4f59a98b9a603af159c2faddd87c
https://pubmed.ncbi.nlm.nih.gov/35895094
Zobrazit plný text záznamu
6
Development of the Quantum-Inspired SIBFA Many-Body Polarizable Force Field: Enabling Condensed-Phase Molecular Dynamics Simulations
Autor: Sehr Naseem-Khan, Louis Lagardère, Christophe Narth, G. Andrés Cisneros, Pengyu Ren, Nohad Gresh, Jean-Philip Piquemal
Publikováno v: Journal of Chemical Theory and Computation
Journal of Chemical Theory and Computation, 2022, 18 (6), pp.3607-3621. ⟨10.1021/acs.jctc.2c00029⟩
We present the extension of the SIBFA (Sum of Interactions Between Fragments Ab initio Computed many-body polarizable force field to condensed phase Molecular Dynamics (MD) simulations. The Quantum-Inspired SIBFA procedure is grounded on simplified i
Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::b01f96b7f6040160e27fc8424264e4df
https://pubmed.ncbi.nlm.nih.gov/35575306
Zobrazit plný text záznamu
8
An Efficient Gaussian-Accelerated Molecular Dynamics (GaMD) Multilevel Enhanced Sampling Strategy: Application to Polarizable Force Fields Simulations of Large Biological Systems
Autor: Frédéric Célerse, Théo Jaffrelot Inizan, Louis Lagardère, Olivier Adjoua, Pierre Monmarché, Yinglong Miao, Etienne Derat, Jean-Philip Piquemal
Publikováno v: Journal of Chemical Theory and Computation
Journal of Chemical Theory and Computation, 2022, 18 (2), pp.968-977. ⟨10.1021/acs.jctc.1c01024⟩
We introduce a novel multilevel 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 ne
Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::15687d14160af574ed9c81bf22929bb9
https://hal.science/hal-03360596
Zobrazit plný text záznamu
9
Accurate Deep Learning-aided Density-free Strategy for Many-Body Dispersion-corrected Density Functional Theory
Autor: Pier Paolo Poier, Théo Jaffrelot Inizan, Olivier Adjoua, Louis Lagardère, Jean-Philip Piquemal
Publikováno v: Journal of Physical Chemistry Letters
Journal of Physical Chemistry Letters, 2022, 13 (19), pp.4381-4388. ⟨10.1021/acs.jpclett.2c00936⟩
International audience; Using a Deep Neuronal Network model (DNN) trained on the large ANI-1 data set of small organic molecules, we propose a transferable density-free many-body dispersion model (DNN-MBD). The DNN strategy bypasses the explicit Hirs
Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::175f74cb9826f9aabd221ec4fb84524e
Zobrazit plný text záznamu
10
Routine Molecular Dynamics Simulations Including Nuclear Quantum Effects: from Force Fields to Machine Learning Potentials
Autor: Thomas Plé, Nastasia Mauger, Olivier Adjoua, Théo Jaffrelot Inizan, Louis Lagardère, Simon Huppert, Jean-Philip Piquemal
Publikováno v: Journal of Chemical Theory and Computation
Journal of Chemical Theory and Computation, 2023, ⟨10.1021/acs.jctc.2c01233⟩
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 t
Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::1ab761d06976e5b1f44ee4c592521672
Zobrazit plný text záznamu

Vyhledávací nástroje:

Upřesnit hledání

Omezení vyhledávání
Plný text Recenzováno Digitální knihovna AV ČR
Zdroje