Florent HédinQubit Pharmaceuticals
Florent Hédin
PhD in Physical Chemistry
Senior HPC Engineer @ Qubit Pharmaceuticals
About
41
Publications
5,753
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137
Citations
Introduction
Additional affiliations
November 2020 - present
Qubit Pharmaceuticals
Position
- Engineer
December 2018 - October 2020
INRIA Paris
Position
- Engineer
September 2017 - December 2017
Position
- Researcher
Description
- "Complex High-Dimensional Energy Landscapes" Long program September 11 - December 15, 2017 http://www.ipam.ucla.edu/programs/long-programs/complex-high-dimensional-energy-landscapes/?tab=overview
Education
October 2011 - October 2016
September 2009 - September 2011
September 2006 - June 2009
Publications
Publications (41)
![Figure 1: Diagram view of the generalized ParRep [43] algorithm. After...](profile/Florent-Hedin/publication/330641884/figure/fig1/AS:720015632392200@1548676512768/Diagram-view-of-the-generalized-ParRep-43-algorithm-After-setup-the-first-step_Q320.jpg)
Metastability is one of the major encountered obstacle when performing long molecular dynamics simulations, and many methods were developed to address this challenge. The “Parallel Replica”(ParRep) dynamics is known for allowing to simulate very long trajectories of metastable Langevin dynamics in the materials science community, but it relies on a...
Recent molecular dynamics (MD) simulations of human hemoglobin (Hb) give results in disagreement with experiment. Although it is known that the unliganded (T0) and liganded (R4) tetramers are stable in solution, the published MD simulations of T0 undergo a rapid quaternary transition to an R-like structure. We show that T0 is stable only when the p...
Partial infinite swapping (PINS) is a powerful enhanced sampling method for complex systems. In the present work thermodynamic observables are determined from reweighting at the post-processing stage for folding of (Ala) 10 in implicit and explicit solvent and for Xenon migration in myoglobin. In every case free energy surfaces are determined using...
We report a fast-track computationally-driven discovery of new SARS-CoV2 Main Protease Mpro inhibitors whose potency range from mM for initial non-covalent ligands to sub-μM for the final covalent compound (IC50=830 ± 50 nM). The project extensively relied on high-resolution all-atom molecular dynamics simulations and absolute binding free energy c...
We report a fast-track computationally driven discovery of new SARS-CoV-2 main protease (Mpro) inhibitors whose potency ranges from mM for the initial non-covalent ligands to sub-μM for the final covalent compound (IC50 = 830 ± 50 nM). The project extensively relied on high-resolution all-atom molecular dynamics simulations and absolute binding fre...
We investigate the computational performance of hybrid high-order methods applied to flow simulations in extremely large discrete fracture networks (over one million of fractures). We study the choice of basis functions, the trade-off between increasing the polynomial order and refining the mesh, and how to take advantage of polygonal cells to redu...
We report a fast-track computationally-driven discovery of new SARS-CoV2 Main Protease (Mpro) inhibitors whose potency range from mM for initial non-covalent ligands to high nM for the final covalent compound (IC50=830 ± 50 nM). The project extensively relied on high-resolution all-atom molecular dynamics simulations and absolute binding free energ...
We are interested in solving flow in large tridimensional Discrete Fracture Networks (DFN) with the hybrid high-order (HHO) method. The objectives of this paper are: (1) to demonstrate the benefit of using a high-order method for computing macroscopic quantities, like the equivalent permeability of fracture rocks; (2) to present the computational e...
We are interested in solving flow in large trimensional Discrete Fracture Networks (DFN) with the hybrid high-order (HHO) method. The objectives of this paper are: (1) to demonstrate the benefit of using a high-order method for computing macroscopic quantities, like the equivalent permeability of fracture rocks; (2) to present the computational eff...
We recently reported that molecular dynamics simulations for hemoglobin require a surprisingly large box size to stabilize the T(0) state relative to R(0), as observed in experiments (El Hage et al., 2018). Gapsys and de Groot have commented on this work but do not provide convincing evidence that the conclusions of El Hage et al., 2018 are incorre...
This presentation covers the content of the gen.parRep article (DOI: 10.1016/j.cpc.2019.01.005) plus some work in progress on a larger protein ligand system.
As it contains unpublished results, you are required to send a private message to Florent Hédin in order to request access.
Metastability is one of the major encountered obstacle when performing long molecular dynamics simulations, and many methods were developed to address this challenge. The "Parallel Replica" (ParRep) dynamics is known for allowing to simulate very long trajectories of metastable Langevin dynamics in the materials science community, but it relies on...
Metastability is one of the major encountered obstacle when performing long molecular dynamics simulations, and many methods were developed to address this challenge. The "Parallel Replica"(ParRep) dynamics is known for allowing to simulate very long trajectories of metastable Langevin dynamics in the materials science community, but it relies on a...
Metastability is one of the major encountered obstacle when performing long molecular dynamics simulations, and many methods were developed to address this challenge. The "Parallel Replica" (ParRep) dynamics is known for allowing to simulate very long trajectories of metastable Langevin dynamics in the materials science community, but it relies on...
Presentation given during the PINT workshop 7th edition
https://www.math.univ-paris13.fr/~japhet/PINT2018.htm
First figure comes from : https://sinews.siam.org/Details-Page/the-2013-nobel-prize-in-chemistry-celebrates-computations-in-chemistry-and-biology-1
Third figure comes from : https://chem.libretexts.org/Bookshelves/Physical_and_Theoretica...
This white paper was prepared by the participants of the fall 2017 long program Complex High-Dimensional Energy Landscapes.
Recent advances in computational resources and the development of high-throughput frameworks enable the efficient sampling of complicated multivariate functions. This includes energy and electronic property landscapes of inor...
French document : proposal for obtaining computing time on the OCCIGEN supercomputer.
In this PhD Thesis molecular systems off increasing size and complexity are investigated, using both standard sampling and advanced sampling methods.
The implementation and validation of two of those rare events
sampling methods is described, namely the SA-MC and PINS algorithm.
The development and use of a toolkit for fitting
force fields para...
PhD defense presentation, University of Basel, 22.09.2016
Presentation at HPC department of Universität Basel Florent Hédin
This performs MC or SA-MC simulations of Lennard-Jones clusters, as described in article http://pubs.acs.org/doi/abs/10.1021/ct500529w It was used for generating the LJ clusters results in the above linked article
Studies and structural analysis revealed
a gate-trapping mechanism for the uptake of O2 in truncated Haemoglobin.
This gate involves the Ile15, Ile19, Leu102, and Ile115 residues.
To further study the gate-trapping process, MD and MC simulations with O2 outside the protein but close to the gate are performed. O2 is constrained to remain around the...
Seminar presentation at University of Basel : overview of the efficiency of MC sampling, and discussion on the main sources of errors.
Spatial averaging algorithm is an efficient MC method which can be applied to problems where important regions (e.g. transition states) of the energy landscape may be difficult to sample with a standard random walk method, such as Metropolis sampling. At the heart of the method is the realization that from the equilibrium density a related, modifie...
Truncated hemoglobin (trHbN) is a protein involved in NO dioxygenation by converting nitric oxide to harmless nitrates: Fe(II)O2 + NO → Fe+(III) + NO− 3 . The tunnel system of trHbN plays an important role in determining and controlling ligand entrance, migration, and rebinding. Previous umbrella sampling studies and structural analysis of channel...
Spatial averaging algorithm: It is an efficient MC method which can be applied to problems where important regions (e.g. transition states) of the energy landscape may be difficult to sample with a standard random walk method, such as Metropolis sampling. At the heart of the method is the realization that from the equilibrium density a related, mod...
Basics of MC sampling in computational chemistry ; comparison of plain Metropolis MC and of Spatial Averaging MC sampling for alanine dipeptide and Villin headpiece.
![Figure C: Theoretical representation of LJ7 best minimum. Source: [14]](profile/Florent-Hedin/publication/282666134/figure/fig1/AS:282574099369984@1444382323646/Figure-C-Theoretical-representation-of-LJ7-best-minimum-Source-14_Q320.jpg)
Spatial Averaging is a Monte Carlo method introducing a new family of probability densities improving the sampling efficiency of the rare-event problems, while conserving the statistical properties of the original distribution. After a theoretical overview concerning Monte Carlo Methods, the principles of Spatial Averaging are introduced. After thi...
Ce dossier combine une étude bibliographique ainsi que les résultats d’une étude pratique sur le thème du Neighborhood Behavior, et plus particulièrement sur la valeur statistique de l’un de ses critères d’évaluation, le critère d’Optimalité.
Dans la première partie, le Neighborhood Behavior (NB) est présenté en détail : pour cela, il est égalemen...
But : étudier la valeur statistique du critère d'optimalité du Neighborhood Behavior, appliqué à une base de données de réactions organiques sous forme de Graphes Condensés de Réaction (GCRs).
Projects
Projects (9)
Neighborhood behavior : valeur statistique du critère d'optimalité
Travail de Master 2, Université de Strasbourg
The aim is to learn physicochemical properties of interest from simple structural representations, using deep neural networks: in particular I would like to investigate how much can be learned from molecular fingerprints generated by using the SMILES molecular representation.
This project was initiated in 0ctober 2017 during the IPAM's long program "Complex High-Dimensional Energy Landscapes"
