Publications by Bruno Emanuel Ferreira De Sousa Correia

Custom CRISPR—Cas9 PAM variants via scalable engineering and machine learning

Bruno Emanuel Ferreira De Sousa Correia, Martin Pacesa

Engineering and characterizing proteins can be time-consuming and cumbersome, motivating the development of generalist CRISPR-Cas enzymes1–4 to enable diverse genome editing applications. However, such enzymes have caveats such as an increased risk of off- ...

Springer Science and Business Media LLC2025

Targeting protein-ligand neosurfaces with a generalizable deep learning tool

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

Boosting Protein Graph Representations through Static-Dynamic Fusion

Pierre Vandergheynst, Bruno Emanuel Ferreira De Sousa Correia, Daniel Probst

Machine learning for protein modeling faces significant challenges due to proteins' inherently dynamic nature, yet most graph-based machine learning methods rely solely on static structural information. Recently, the growing availability of molecular dynam ...

2025

Equivariant 3D-conditional diffusion model for molecular linker design

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

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

An atlas of protein homo-oligomerization across domains of life

Bruno Emanuel Ferreira De Sousa Correia, Sandrine Madeleine Suzanne Georgeon, Casper Alexander Goverde, Martin Pacesa, Yoan Désiré Duhoo

Protein structures are essential to understanding cellular processes in molecular detail. While advances in artificial intelligence revealed the tertiary structure of proteins at scale, their quaternary structure remains mostly unknown. We devise a scalabl ...

2024

Chemically disruptable molecule switch and use thereof

Bruno Emanuel Ferreira De Sousa Correia, Pablo Gainza Cirauqui

The invention relates to chemically disruptable molecule (CDM) switch, their use in controlling cell signaling components, and their use for treatments and therapies. Further disclosed are methods of treating and/or preventing a disease, such as e.g. a can ...

2024

Isoperimetry in Finitely Generated Groups

Marc Troyanov, Bruno Emanuel Ferreira De Sousa Correia

We revisit the isoperimetric inequalities for finitely generated groups introduced and studied by N. Varopoulos, T. Coulhon and L. Saloff-Coste. Namely we show that a lower bound on the isoperimetric quotient of finite subsets in a finitely generated group ...

Springer2024

Antibody-peptide conjugates deliver covalent inhibitors blocking oncogenic cathepsins

Bruno Emanuel Ferreira De Sousa Correia, Luc Reymond, Florence Pojer, Elisa Oricchio, Sandrine Madeleine Suzanne Georgeon, Albert Santamaria Martinez, Kelvin Ka Ching Lau, Natalya Katanayeva, Aaron Simone Petruzzella, Sarah Wehrle

Cysteine cathepsins are a family of proteases that are relevant therapeutic targets for the treatment of different cancers and other diseases. However, no clinically approved drugs for these proteins exist, as their systemic inhibition can induce deleterio ...

Nature Portfolio2024

Exploring “dark-matter” protein folds using deep learning

Pierre Vandergheynst, Bruno Emanuel Ferreira De Sousa Correia, Sandrine Madeleine Suzanne Georgeon, Casper Alexander Goverde, Andreas Loukas, Stéphane Rosset, Zander Harteveld, Alexandra Krina Van Hall-Beauvais

De novo protein design explores uncharted sequence and structure space to generate novel proteins not sampled by evolution. A main challenge in de novo design involves crafting “designable” structural templates to guide the sequence searches toward adoptin ...

2024

A deep mutational scanning platform to characterize the fitness landscape of anti-CRISPR proteins

Bruno Emanuel Ferreira De Sousa Correia, Stéphane Rosset

Deep mutational scanning is a powerful method for exploring the mutational fitness landscape of proteins. Its adaptation to anti-CRISPR proteins, which are natural CRISPR-Cas inhibitors and key players in the co-evolution of microbes and phages, facilitate ...

2024