Publications by Andrea Levy | EPFL Graph Search

Related publications (5)

Making Puzzle Pieces Fit or Reshaping MiMiC for Multiscale Simulations with CP2K and More

Ursula Röthlisberger, Sophia Kathryn Johnson, Andrea Levy, Andrej Antalik

MiMiC is a framework for modeling large-scale chemical processes that require treatment at multiple resolutions. It does not aim to implement single-handedly all methods required to treat individual subsystems, but instead, it relegates this task to specia ...

American Chemical Society (ACS)2025

MiMiCPy: An Efficient Toolkit for MiMiC-Based QM/MM Simulations

Ursula Röthlisberger, Sophia Kathryn Johnson, Andrea Levy

MiMiC is a highly flexible, extremely scalable multiscale modeling framework. It couples the CPMD (quantum mechanics, QM) and GROMACS (molecular mechanics, MM) codes. The code requires preparing separate input files for the two programs with a selection of ...

AMER CHEMICAL SOC2023

OpenMM–MiMiC Interface for Efficient and Flexible Multiscale Simulations

Ursula Röthlisberger, Andrea Levy, Andrej Antalik

MiMiC is a flexible and efficient framework for multiscale simulations in which different subsystems are treated by individual client programs. In this work, we present a new interface with OpenMM to be used as an MM client program and we demonstrate its e ...

American Chemical Society (ACS)2025

MiMiC: A high-performance framework for multiscale molecular dynamics simulations

Ursula Röthlisberger, Sophia Kathryn Johnson, François Louis Mouvet, Andrea Levy, Andrej Antalik

MiMiC is a framework for performing multiscale simulations in which loosely coupled external programs describe individual subsystems at different resolutions and levels of theory. To make it highly efficient and flexible, we adopt an interoperable approach ...

2024

Metal3D: a general deep learning framework for accurate metal ion location prediction in proteins

Ursula Röthlisberger, Andrea Levy, Simon Leonard Dürr

Zinc is an essential metal for many proteins. Here, the authors propose a model based on 3D convolutional networks to predict the location of zinc in experimental and computationally predicted structures within a framework readily extensible to other metal ...

Nature Portfolio2023