Bruno Correia

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bruno.correia@epfl.ch https://www.epfl.ch/labs/lpdi/

Citizenship: Portuguese

Birth date: 23.05.1980

https://orcid.org/0000-0002-7377-8636

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Linkedin ID

EPFL STI IBI-STI LPDI
AAB 0 44 (Bâtiment AAB)
Station 19
1015 Lausanne

Office: AAB 0 44
EPFL > STI > IBI-STI > LPDI

Web site: Web site: https://lpdi.epfl.ch

EPFL > SV > SV-SSV > SSV-ENS

Web site: Web site: https://sv.epfl.ch/education

EPFL > VPA-AVP-DLE > AVP-DLE-EDOC > EDBB-GE

Web site: Web site: https://go.epfl.ch/phd-edbb

EPFL > VPA-AVP-DLE > AVP-DLE-EDOC > CDOCT

EPFL > VPA-AVP-DLE > AVP-DLE-EDOC > EDBB-ENS

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Fields of expertise

Protein engineering, Computational design, Immunoengineering, Synthetic biology

Biography

Throughout my PhD and postdoctoral studies I was trained in world-renowned laboratories and institutions in the United States of America (University of Washington and The Scripps Research Institute). Very early in my scientific career I found out my fascination about protein structure and function. My PhD studies evolved in the direction of immunogen design and vaccine engineering which sparked my interest in the many needs and opportunities in vaccinology and translational research. My efforts resulted in an enlightening piece of work where for the first time, computationally designed immunogens elicited potent neutralizing antibodies. During my postdoctoral studies I joined a chemical biology laboratory at the Scripps Research Institute. In this stage I developed novel chemoproteomics methods for the identification of protein-small molecule interaction sites in complex proteomes. In March 2015, I joined the École Polytechnique Fédérale de Lausanne (EPFL) – Switzerland as a tenure track assistant professor. The focus of my research group is to develop computational tools for protein design with particular emphasis in applying these strategies to immunoengineering (e.g. vaccine and cancer immunotherapy). The activities in my laboratory focus on computational design methods development and experimental characterization of the designed proteins. Our laboratory has been awarded with 2 prestigious research grants from the European Research Council. Lastly, I have been awarded the prize for best teacher of Life sciences in 2019.

Current work

Featuring molecular surface fingerprints to decipher protein functional properties
Bottom-up de novo design of functional proteins
Computational design of synthetic components for CAR T-cells
Computational Design of Precision Vaccines

Professional course

Assistant professor

Bioengineering

Institute of Bioengineering - EPFL

2015

Post-doctoral researcher

Chemical Biology

The Scripps Research Institute

2011

Education

PhD

Computational Biology

Universidade Nova de Lisboa

2010

B. S.

Chemistry

Universidade de Coimbra

2004

Awards

2021 : Protein Science Young Investigator Award from Protein Society

2019 : Teaching award : EPFL - SV

2018 : Visiting scientist : Radcliffe Institute - Harvard

2016 : ERC Starting grant : European Research Council

2006 : PhD scholarship : Fundação para a Ciência e Tecnologia

Publications

Infoscience publications

Laboratory of Protein Design and Immunoengineering

Leveraging protein representations to explore uncharted fold spaces with generative models

B. Correia; Y. Miao; M. Pacesa; S. Georgeon; J. Schmidt et al.

2025

Sesterhenn F, Yang C, Cramer JT, Bonet J, Wen X, Abriata LA, Kucharska I, Chiang CI, Wang Y, Castoro G, Vollers SS, Galloux M, Dheilly E, Richard CA, Rosset S, Corthesy P, Georgeon S, Villard M, Richard CA, Descamps D, Delgado T, Oricchio E, Rameix-Welti MA, Mas V, Ervin S, Eleouet JF, Riffault S, Bates JT, Julien JP, Li Y, Jardetzky T, Krey T, Correia BE Science, 2020	De novo protein design enables precise induction of functional antibodies in vivo
Mathony J, Harteveld Z, Schmelas C, Belzen JU, Aschenbrenner S, Hoffmann MD, Stengl C, Scheck A, Rosset S, Grimm D, Eils R, Correia BE, Niopek D* Nature Chemical Biology, 2020	Computational design of anti-CRISPR proteins with improved inhibition potency and expanded specificity
Leman JK, Weitzner BD, Lewis SM, Adolf-Bryfogle J, Alam N, Alford RF, Aprahamian M, Baker D, Barlow KA, Barth P, Basanta B, Bender BJ, Blacklock K, Bonet J, Boyken SE, Bradley P, Bystroff C, Conway P, Cooper S, Correia BE, Coventry B, Das R, De Jong RM, DiMaio F, Dsilva L, Dunbrack R, Ford AS, Frenz B, Fu DY, Geniesse C, Goldschmidt L, Gowthaman R, Gray JJ, Gront D, Guffy S, Horowitz S, Huang PS, Huber T, Jacobs TM, Jeliazkov JR, Johnson DK, Kappel K, Karanicolas J, Khakzad H, Khar KR, Khare SD, Khatib F, Khramushin A, King IC, Kleffner R, Koepnick B, Kortemme T, Kuenze G, Kuhlman B, Kuroda D, Labonte JW, Lai JK, Lapidoth G, Leaver-Fay A, Lindert S, Linsky T, London N, Lubin JH, Lyskov S, Maguire J, Malmström L, Marcos E, Marcu O, Marze NA, Meiler J, Moretti R, Mulligan VK, Nerli S, Norn C, Ó'Conchúir S, Ollikainen N, Ovchinnikov S, Pacella MS, Pan X, Park H, Pavlovicz RE, Pethe M, Pierce BG, Pilla KB, Raveh B, Renfrew PD, Burman SSR, Rubenstein A, Sauer MF, Scheck A, Schief W, Schueler-Furman O, Sedan Y, Sevy AM, Sgourakis NG, Shi L, Siegel JB, Silva DA, Smith S, Song Y, Stein A, Szegedy M, Teets FD, Thyme SB, Wang RY, Watkins A, Zimmerman L, Bonneau R Nature Methods, 2020	Macromolecular modeling and design in Rosetta: recent methods and frameworks
Giordano-Attianese G, Gainza P, Gray-Gaillard E, Cribioli E, Shui S, Kim S, Kwak M, Vollers S, Osorio A, Reichenbach P, Bonet J, Oh B, Irving M, Coukos G, Correia BE Nature Biotechnology, 2020	Computationally designed STOP-CAR disrupted by small molecule confers on-command regulation of T-cell therapy
Gainza P, Sverrisson F, Monti F, Rodola E, Bronstein MM, Correia BE Nature Methods, 2020	Deciphering interaction fingerprints from protein molecular surfaces using geometric deep learning
Bonet J, Harteveld Z, Sesterhenn F, Scheck A, Correia BE BMC Bioinformatics, 2019	rstoolbox - a Python library for large-scale analysis of computational protein design data and structural bioinformatics
Sesterhenn F, Galloux M, Vollers S, Cspregi L, Yang C, Descamps D, Bonet J, Friedensohn S, Gainza P, Corthesy P, Chen M, Rosset S, Rameix-Welti MA, Elouet JF, Reddy ST, Graham B, Riffault S, Correia BE Plos Biology, 2019	Boosting subdominant neutralizing antibody responses with a computationally designed epitope-focused immunogen
*Bonet J, Wehrle S, Schriever K, Yang C, Billet A, Sesterhenn F, Scheck A, Sverrisson F, Veselkova B, Vollers S, Lourman R, Villard M, Rosset S, Krey T, Correia BE* Plos Computational Biology, 2018	Rosetta FunFolDes - a general framework for the computational design of functional proteins
Bubeck F, Hoffmann M, Harteveld Z, Aschenbrenner S, Bietz A, Waldhauer MC, Boerner K, Fakhiri J, Schmelas C, Dietz L, Grimm D, Correia BE, Eils R, Niopek D Nature Methods, 2018	Engineered anti-CRISPR proteins for optogenetic control of CRISPR/Cas9

Bruno Correia

Fields of expertise

Biography

Current work

Professional course

Education

Awards

Publications

Infoscience publications

Laboratory of Protein Design and Immunoengineering

Leveraging protein representations to explore uncharted fold spaces with generative models

Structure-based Design of Chimeric Influenza Hemagglutinins to Elicit Cross-group Immunity

Structures of a synthetic antibody selected against and bound to the C‐terminal domain of <i>Clostridium perfringens</i> enterotoxin

De novo design of phosphorylation-induced protein switches for synthetic signaling in cells

One-shot Design of Functional Protein Binders with Bindcraft

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

Computationally designed stem-epitope mimetics elicit broadly reactive antibodies

Targeting protein-ligand neosurfaces with a generalizable deep learning tool

Boosting Protein Graph Representations through Static-Dynamic Fusion

Computational Design of Protein Switches

Computational design of complex protein folds and soluble analogs of membrane proteins

Towards Conformational Targeting of Alpha-Synuclein Fibrils

The physiological landscape and specificity of antibody repertoires are consolidated by multiple immunizations

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

Structure-based drug design with equivariant diffusion models

Epitope-focused immunogens targeting the hepatitis C virus glycoproteins induce broadly neutralizing antibodies

FSscore: A Personalized Machine Learning-Based Synthetic Feasibility Score

Dual ON/OFF-switch chimeric antigen receptor controlled by two clinically approved drugs

Exploring “dark-matter” protein folds using deep learning

Structures of the Foamy virus fusion protein reveal an unexpected link with the F protein of paramyxo- and pneumoviruses

An evolved artificial radical cyclase enables the construction of bicyclic terpenoid scaffolds via an H-atom transfer pathway

Computational design of soluble and functional membrane protein analogues

Antibody-peptide conjugates deliver covalent inhibitors blocking oncogenic cathepsins

Opportunities and challenges in design and optimization of protein function

Equivariant 3D-conditional diffusion model for molecular linker design

A Synthetic Multivalent Lipopeptide Derived from Pam3CSK4 with Irreversible Influenza Inhibition and Immuno-Stimulating Effects

An atlas of protein homo-oligomerization across domains of life

Predicting protein interactions using geometric deep learning on protein surfaces

Multi-motif scaffolding for de novo pathogen antigen mimetics by deep generative learning

Chemically disruptable molecule switch and use thereof

Engineering novel protein interactions with therapeutic potential using deep learning-guided surface design

A new age in protein design empowered by deep learning

Protein-based bandpass filters for controlling cellular signaling with chemical inputs

Rational design of small-molecule responsive protein switches

Rules and mechanisms governing G protein coupling selectivity of GPCRs

Discriminating physiological from non‐physiological interfaces in structures of protein complexes: A community‐wide study

Rational Design of Chemically Controlled Antibodies and Protein Therapeutics

De novo protein design by inversion of the AlphaFold structure prediction network

De novo design of protein interactions with learned surface fingerprints

De novo designed proteins: a study in engineering novel folds and functions

Computational design of vaccine immunogens

A generic framework for hierarchical de novo protein design

Assessing and enhancing foldability in designed proteins

Antibodies to combat viral infections: development strategies and progress

Computational design of novel protein–protein interactions – An overview on methodological approaches and applications

Targeting molecular surfaces to engineer novel protein-based immunogens and inhibitors

Rational design of protein switches: applications in synthetic biology and cancer immunotherapy

Towards automating de novo protein design for novel functionalities: controlling protein folds and protein-protein interactions

A method and system for fast end-to-end learning on protein surfaces

Novel chemically controlled cellular switches

Computational design of bioactive protein switches with multi-logics for cell-based therapeutics

A Nanoscaffolded Spike-RBD Vaccine Provides Protection against SARS-CoV-2 with Minimal Anti-Scaffold Response

Optimization of therapeutic antibodies by predicting antigen specificity from antibody sequence via deep learning

Modeling Immunity with Rosetta: Methods for Antibody and Antigen Design

Optogenetic control of Neisseria meningitidis Cas9 genome editing using an engineered, light-switchable anti-CRISPR protein

Bottom-up de novo design of functional proteins with complex structural features

On the exploration of novel methodological approaches for immunogen design: case studies in influenza and hepatitis C

Fast end-to-end learning on protein surfaces

Oligomerization Profile of Human Transthyretin Variants with Distinct Amyloidogenicity

Macromolecular modeling and design in Rosetta: recent methods and frameworks

De novo protein design enables the precise induction of RSV-neutralizing antibodies

Computational design of anti-CRISPR proteins with improved inhibition potency

Epitope Mapping and Fine Specificity of Human T and B Cell Responses for Novel Candidate Blood-Stage Malaria Vaccine P27A

A computationally designed chimeric antigen receptor provides a small-molecule safety switch for T-cell therapy

Immunogen

Functional de novo Protein Design for Targeted Vaccines and Synthetic Biology Applications

Immunogen

Deciphering interaction fingerprints from protein molecular surfaces using geometric deep learning

Decrypting interaction fingerprints in protein molecular surfaces

rstoolbox - a Python library for large-scale analysis of computational protein design data and structural bioinformatics