Computational insights into function and inhibition of fatty acid amide hydrolase

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Publications associées (31)

Hybrid ground-state quantum algorithms based on neural Schrödinger forging

Giuseppe Carleo, Sofia Vallecorsa

Entanglement forging based variational algorithms leverage the bipartition of quantum systems for addressing ground-state problems. The primary limitation of these approaches lies in the exponential summation required over the numerous potential basis stat ...

Amer Physical Soc2024

An explainability framework for deep learning on chemical reactions exemplified by enzyme-catalysed reaction classification

Daniel Probst

Assigning or proposing a catalysing enzyme given a chemical or biochemical reaction is of great interest to life sciences and chemistry alike. The exploration and design of metabolic pathways and the challenge of finding more sustainable enzyme-catalysed a ...

2023

Optimal enzyme utilization suggests that concentrations and thermodynamics determine binding mechanisms and enzyme saturations

Vassily Hatzimanikatis, Daniel Robert Weilandt, Asli Sahin

One of the main challenges hampering the development of kinetic models is the lack of kinetic parameters for many enzymatic reactions. Here, the authors introduce a framework to explore the catalytically optimal operating conditions of any complex enzyme m ...

Nature Portfolio2023

Emergence of Classical Magnetic Order from Anderson Towers: Quantum Darwinism in Action

Frédéric Mila

Environment is assumed to play a negative role in quantum mechanics, destroying the coherence in a quantum system and, thus, randomly changing its state. However, for a quantum system that is initially in a degenerate ground state, the situation could be d ...

American Physical Society2023

A recipe for cracking the quantum scaling limit with machine learned electron densities

Mario Geiger

A long-standing goal of science is to accurately simulate large molecular systems using quantum mechanics. The poor scaling of current quantum chemistry algorithms on classical computers, however, imposes an effective limit of about a few dozen atoms on tr ...

IOP Publishing Ltd2023

2023 Roadmap on molecular modelling of electrochemical energy materials

Alfredo Pasquarello, Chunmin Zhang, Assil Bouzid

New materials for electrochemical energy storage and conversion are the key to the electrification and sustainable development of our modern societies. Molecular modelling based on the principles of quantum mechanics and statistical mechanics as well as em ...

Iop Publishing Ltd2023

Bioaccumulation and molecular effects of carbamazepine and methylmercury co-exposure in males of Dreissena polymorpha

Florian Frédéric Vincent Breider, Dominique Grandjean, Nguyên Thiên Kim Lê, Claudia Cosio

Dreissena polymorpha is a bivalve promising for biomonitoring in freshwater ecosystems thanks to its abundance and high filtration activity allowing rapid uptake of toxicants and identification of their negative effects. Nonetheless, we still lack knowledg ...

2023

Machine-learning the electronic density of states: electronic properties without quantum mechanics

Chiheb Ben Mahmoud

The electronic density of states (DOS) quantifies the distribution of the energy levels that can be occupied by electrons in a quasiparticle picture and is central to modern electronic structure theory. It also underpins the computation and interpretation ...

EPFL2023

Mode-Specific Coupling of Nanoparticle-on-Mirror Cavities with Cylindrical Vector Beams

Christophe Marcel Georges Galland, Valeria Vento, Sachin Suresh Verlekar, Philippe Andreas Rölli

Nanocavities formed by ultrathin metallic gaps permitthe reproducibleengineering and enhancement of light-matter interaction, withmode volumes reaching the smallest values allowed by quantum mechanics.While the enhanced vacuum field in metallic nanogaps ha ...

2023

Advancing Computational Chemistry with Stochastic and Artificial Intelligence Approaches

Justin Villard

Computational chemistry aims to simulate reactions and molecular properties at the atomic scale, advancing the design of novel compounds and materials with economic, environmental, and societal implications. However, the field relies on approximate quantum ...

EPFL2023

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Hybrid ground-state quantum algorithms based on neural Schrödinger forging

Giuseppe Carleo, Sofia Vallecorsa

Amer Physical Soc2024

An explainability framework for deep learning on chemical reactions exemplified by enzyme-catalysed reaction classification

Daniel Probst

2023

Optimal enzyme utilization suggests that concentrations and thermodynamics determine binding mechanisms and enzyme saturations

Vassily Hatzimanikatis, Daniel Robert Weilandt, Asli Sahin

Nature Portfolio2023