Publications related to Molecular design software

Machine learning-aided generative molecular design

Machine learning has provided a means to accelerate early-stage drug discovery by combining molecule generation and filtering steps in a single architecture that leverages the experience and design preferences of medicinal chemists. However, designing mach ...

Nature Portfolio2024

Augmented Memory: Sample-Efficient Generative Molecular Design with Reinforcement Learning

Philippe Schwaller, Jeff Guo

Sample efficiency is a fundamental challenge in de novo molecular design. Ideally, molecular generative models should learn to satisfy a desired objective under minimal calls to oracles (computational property predictors). This problem becomes more apparen ...

Amer Chemical Soc2024

Solvation Free Energies from Machine Learning Molecular Dynamics

Nicola Marzari, Nicéphore Arthur François Bonnet

The present work proposes an extension to the approach of [Xi, C; et al. J. Chem. Theory Comput. 2022, 18, 6878] to calculate ion solvation free energies from first-principles (FP) molecular dynamics (MD) simulations of a hybrid solvation model. The approa ...

Amer Chemical Soc2024

Exciton migration in two-dimensional materials

Excitons play an essential role in the optical response of two-dimensional materials. These are bound states showing up in the band gaps of many-body systems and are conceived as quasiparticles formed by an electron and a hole. By performing real-time simu ...

Nature Portfolio2024

The OpenMolcas Web: A Community-Driven Approach to Advancing Computational Chemistry

Francesco Aquilante

The developments of the open-source OpenMolcas chemistry software environment since spring 2020 are described, with a focus on novel functionalities accessible in the stable branch of the package or via interfaces with other packages. These developments sp ...

Washington2023

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

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

Inferring free-energy barriers and kinetic rates from molecular dynamics via underdamped Langevin models

Sara Bonella, Fabio Pietrucci, David Daniel Girardier

Rare events include many of the most interesting transformation processes in condensed matter, from phase transitions to biomolecular conformational changes to chemical reactions. Access to the corresponding mechanisms, free-energy landscapes and kinetic r ...

Aip Publishing2023

Advancing first principle-based molecular dynamics of biological systems with machine learning

François Louis Mouvet

Molecular dynamics (MD) simulations have emerged as a transformative approach to analyse molecular systems at the atomic level, offering valuable insights into complex biological processes. Many biological phenomena can only accurately be described by inco ...

EPFL2023

Computational Studies for the Design of Metalloenzyme Mimics

Guido Frisari

At present, there is no general standard automated method for engineering metalloenzymes, industrially-relevant systems able to catalyze environmentally friendly reactions. One of the most studied natural metalloenzymes is the second isoform of human carbo ...

EPFL2023

The role of Zn in C-S-H atomic structure, nucleation and growth

Anna Morales Melgares

The most promising solution towards cementitious materials with a lower carbon footprint is the partial substitution of the clinker by supplementary cementitious materials (SCMs) such as fly ash, blast furnace slag, limestone and calcined clays. The produc ...

EPFL2023

De novo design of protein interactions with learned surface fingerprints

Didier Trono, Henning Paul-Julius Stahlberg, Beat Fierz, Priscilla Turelli, Bruno Emanuel Ferreira De Sousa Correia, Elisa Oricchio, Sandrine Madeleine Suzanne Georgeon, Dongchun Ni, Andreas Scheck, Michael Bronstein, Charlène Mireille Raymonde Raclot, Anthony Marchand, Alexandra Teslenko, Casper Alexander Goverde, Aaron Simone Petruzzella, Stephen Michael Buckley, Martin Pacesa, Pablo Gainza Cirauqui, Stéphane Rosset, Zander Harteveld, Sarah Wehrle, Freyr Sverrisson, Alexandra Krina Van Hall-Beauvais, Jane Marsden

Physical interactions between proteins are essential for most biological processes governing life. However, the molecular determinants of such interactions have been challenging to understand, even as genomic, proteomic and structural data increase. This k ...

2023

Coupled Rotary and Oscillatory Motion in a Second-Generation Molecular Motor Pd Complex

Lukas Pfeifer

Molecular machines offer many opportunities for the development of responsive materials and introduce autono-mous motion in molecular systems. While basic molecular switches and motors carry out one type of motion upon being exposed to an external stimulus ...

AMER CHEMICAL SOC2023

A data-driven interpretation of the stability of organic molecular crystals

Michele Ceriotti, Edgar Albert Engel, Maria Pakhnova

Due to the subtle balance of intermolecular interactions that govern structure-property relations, predicting the stability of crystal structures formed from molecular building blocks is a highly non-trivial scientific problem. A particularly active and fr ...

ROYAL SOC CHEMISTRY2023

Artificial intelligence for natural product drug discovery

Philippe Schwaller, Florian Huber, Albert Hofstetter, Michael Alexander Skinnider

Developments in computational omics technologies have provided new means to access the hidden diversity of natural products, unearthing new potential for drug discovery. In parallel, artificial intelligence approaches such as machine learning have led to e ...

Nature Portfolio2023

Systems and methods for de novo design of protein interactions with learned surface fingerprints

Andreas Scheck, Michael Bronstein, Anthony Marchand, Pablo Gainza Cirauqui, Zander Harteveld, Sarah Wehrle, Freyr Sverrisson, Alexandra Krina Van Hall-Beauvais

The present application relates to a computer-implemented systems and methods for protein interaction design using surface fingerprints. The method comprises predicting at least one target interface site with high binding propensity, wherein, optionally, t ...

2023

Atomic-level structure determination of amorphous molecular solids by NMR

David Lyndon Emsley, Arthur César Pinon, Pinelopi Moutzouri, Manuel Cordova

Structure determination of amorphous materials remains challenging, owing to the disorder inherent to these materials. Nuclear magnetic resonance (NMR) powder crystallography is a powerful method to determine the structure of molecular solids, but disorder ...

Nature Portfolio2023

Visualization, Interactive Handling and Simulation of Molecules in Commodity Augmented Reality in Web Browsers Using moleculARweb's Virtual Modeling Kits

Matteo Dal Peraro, Luciano Andres Abriata, Fabio Jose Cortes Rodriguez, Lucien Fabrice Krapp

moleculARweb (https://molecularweb.epfl.ch) began as a website for education and outreach in chemistry and structural biology through augmented reality (AR) content that runs in the web browsers of regular devices like smartphones, tablets, and computers. ...

SWISS CHEMICAL SOC2022

Adhesive wear with a coarse-grained discrete element model

Jean-François Molinari, Son-Jonathan Pham-Ba

The use of molecular dynamics (MD) simulations has led to promising results to unravel the atomistic origins of adhesive wear, and in particular for the onset of wear at nanoscale surface asperities. However, MD simulations come with a high computational c ...

ELSEVIER SCIENCE SA2022

Modeling non-covalent interactions in condensed phase

Veronika Juraskova

The modeling of non-covalent interactions, solvation effects, and chemical reactions in complex molecular environment is a challenging task. Current state-of-the-art approaches often rely on static computations using implicit solvent models and harmonic ap ...

EPFL2022