Bruno Correia

bruno.correia@epfl.ch +41 21 693 61 66 https://www.epfl.ch/labs/lpdi/
Citizenship : Portuguese
Birth date : 23.05.1980
EPFL STI IBI-STI LPDI
AAB 2 44 (Bâtiment AAB)
Station 19
CH-1015 Lausanne
+41 21 693 61 66
+41 21 693 96 82
Office: AAB 2 44
EPFL > STI > IBI-STI > LPDI
Web site: Web site: https://lpdi.epfl.ch
+41 21 693 61 66
EPFL > SV > SV-SSV > SSV-ENS
Web site: Web site: https://sv.epfl.ch/education
Fields of expertise
Biography
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
Teaching award
EPFL - SV
2019
Visiting scientist
Radcliffe Institute - Harvard
2018
Starting grant
European Research Council
2016
PhD scholarship
Fundação para a Ciência e Tecnologia
2006
Publications
Infoscience publications
Laboratory of Protein Design and Immunoengineering
Designs and Characterization of Subunit Ebola GP Vaccine Candidates: Implications for Immunogenicity
Frontiers In Immunology. 2020-11-04. DOI : 10.3389/fimmu.2020.586595.De novo protein design enables the precise induction of RSV-neutralizing antibodies
Science. 2020-05-15. DOI : 10.1126/science.aay5051.A computationally designed chimeric antigen receptor provides a small-molecule safety switch for T-cell therapy
Nature Biotechnology. 2020-02-03. DOI : 10.1038/s41587-019-0403-9.Functional de novo Protein Design for Targeted Vaccines and Synthetic Biology Applications
Lausanne, EPFL, 2020. DOI : 10.5075/epfl-thesis-7545.Deciphering interaction fingerprints from protein molecular surfaces using geometric deep learning
Nature Methods. 2019-12-09. DOI : 10.1038/s41592-019-0666-6.rstoolbox - a Python library for large-scale analysis of computational protein design data and structural bioinformatics
BMC Bioinformatics. 2019-05-15. DOI : 10.1186/s12859-019-2796-3.Expanding beyond the natural protein repertoire to engineer targeted vaccines and diagnostics
Lausanne, EPFL, 2019. DOI : 10.5075/epfl-thesis-7515.Computational protein design - the next generation tool to expand synthetic biology applications
CURRENT OPINION IN BIOTECHNOLOGY. 2018. DOI : 10.1016/j.copbio.2018.04.001.Selected publications
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 |
Research
Deciphering functional fingerprints in protein surfaces
Computational design of functional de novo proteins
Computational design of chemical switches for synthetic biology
Teaching & PhD
Teaching
Life Sciences Engineering