Publications de Arne Schneuing

Targeting protein-ligand neosurfaces with a generalizable deep learning tool

Luc Reymond, Sebastian Maerkl, Philippe Schwaller, Sandrine Madeleine Suzanne Georgeon, Anthony Marchand, Bruno Emanuel Ferreira De Sousa Correia, Pablo Gainza Cirauqui, Leo Scheller, Stephen Michael Buckley, Arne Schneuing, Martin Pacesa

Molecular recognition events between proteins drive biological processes in living systems1. However, higher levels of mechanistic regulation have emerged, in which protein-protein interactions are conditioned to small molecules2, 3, 4-5. Despite recent ad ...

NATURE PORTFOLIO2025

Equivariant 3D-conditional diffusion model for molecular linker design

Pascal Frossard, Bruno Emanuel Ferreira De Sousa Correia, Clément Arthur Yvon Vignac, Ilia Igashov, Arne Schneuing

Fragment-based drug discovery has been an effective paradigm in early-stage drug development. An open challenge in this area is designing linkers between disconnected molecular fragments of interest to obtain chemically relevant candidate drug molecules. I ...

2024

Structure-based drug design with equivariant diffusion models

Bruno Emanuel Ferreira De Sousa Correia, Ilia Igashov, Arne Schneuing

Structure-based drug design (SBDD) aims to design small-molecule ligands that bind with high affinity and specificity to pre-determined protein targets. Generative SBDD methods leverage structural data of drugs with their protein targets to propose new dru ...

SPRINGERNATURE2024

Joint host-pathogen genomic analysis identifies hepatitis B virus mutations associated with human NTCP and HLA class I variation

Jacques Fellay, Dylan Lawless, Olivier Noël Marie Naret, Andreas Scheck, Zhi Ming Xu, Arne Schneuing

Evolutionary changes in the hepatitis B virus (HBV) genome could reflect its adaptation to host -induced selective pressure. Leveraging paired human exome and ultra -deep HBV genome-sequencing data from 567 affected individuals with chronic hepatitis B, we ...

Cell Press2024

A new age in protein design empowered by deep learning

Bruno Emanuel Ferreira De Sousa Correia, Michael Bronstein, Casper Alexander Goverde, Ilia Igashov, Arne Schneuing, Hamed Khakzad

The rapid progress in the field of deep learning has had a significant impact on protein design. Deep learning methods have recently produced a breakthrough in protein structure prediction, leading to the availability of high-quality models for millions of ...

Cell Press2023