Nuno Bandeira, Ph.D.

Source: https://pharmacy.ucsd.edu/faculty/bandeira Parent: https://pharmacy.ucsd.edu/research/affiliate-research-centers-institutes-resources-and-training-programs

Associate Professor Skaggs School of Pharmacy and Pharmaceutical Sciences Executive Director Center for Computational Mass Spectrometry

bandeira@ucsd.edu

Phone

(858) 534-8666

Research Summary

The Bandeira laboratory aims to develop novel mass spectrometry algorithms for the discovery and characterization of novel biomarker proteins, post- translational modifications and protein-protein interactions. The research in my lab falls into 5 general areas: (1) De novo sequencing of complete proteins; our Shotgun Protein Sequencing paradigm yields the longest and most accurate de novo sequences, even on mixtures of unknown proteins. (2) Discovery and detailed characterization of post- translational modifications in signaling pathways and health/disease; our Spectral Networks paradigm enables the precise localization of modification sites and reveals novel modifications and highly modified peptides. (3) Sequencing and characterization of non-linear peptidic natural products, including cyclic and branched peptides; (4) Mass spectrometry algorithms for high-throughput analysis of in-vivo structural proteomics and protein-protein interactions; (5) New mass spectrometry approaches to the identification of neuropeptides and other endogenous peptides; biomarker and drug discovery pipelines are severely limited by only identifying 20-30% of all detectable peptide species – new combinations of algorithms and experimental protocols are needed to reveal this proteomics ‘dark matter’. Overall, this research aims to substantially improve the capabilities of proteomics discovery pipelines and could result in the development of novel drug therapeutics.

Academic Achievements

Education: B.S. in Computer Science (1997); New University of Lisbon, Portugal; M.Sc. in Applied Artificial Intelligence (2001); New University of Lisbon, Portugal; Ph. D. in Computer Science and Bioinformatics (2007); University of California, San Diego.

Awards and Honors:2006 Human Proteome Organization (HUPO) Young Investigator Award, 2007 Ph.D. Dissertation Award (CSE/UCSD), Member of the Molecular and Cellular Proteomics Publication Guidelines committee.

Leadership Experience: Executive Director of the NIH/NCRR Center for Computational Mass Spectrometry (http://proteomics.ucsd.edu), Program Committee chair for the 2010 RECOMB Satellite conference on Computational Proteomics (http://casb.ucsd.edu/cp2010/).

Teaching

Biostatistics (SPPS 206)
Proteomics and mass spectrometry for biologists (CMM264/SPPS 268)
Supramolecular Complex Characterization (BENG283/CHEM283/BIOM283)

Key Contributions

Shotgun Protein Sequencing paradigm has become the central tool at Genentech/Roche for de novo sequencing of monoclonal antibodies (including Herceptin® and Avastin®) and at the Broad Institute of MIT and Harvard for sequencing of toxins and potentially therapeutic venom proteins.
Algorithms for sequencing and identification of non-ribosomal cyclic peptides incorporating novel non-standard amino acids (e.g., Cyclosporine)
Peptidomics and Post-translational Modification Biomarkers in Human Diseases. Mass spectrometry algorithms continue to be developed for detailed characterization of disease markers, pathogen infection and drug response.

Selected Publications

Bandeira et al (2007). Protein Identification by Spectral Networks Analysis. Proc. Natl. Acad. Sci. 104:6140-6145.
Bandeira et al. (2007). Shotgun Protein Sequencing: Assembly of Peptide Tandem Mass spectra from Mixtures of Modified Proteins. Mol. Cell. Prot. 6:1123- 1134.
Bandeira et al. (2008). Automated de Novo Protein Sequencing of Monoclonal Antibodies. Nature Biotech. 26:1336-8.
Ng et al. (2009). Dereplication and de novo sequencing of nonribosomal peptides. Nature Methods. 6:596-599.

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Potential Collaborative Programs

Proteomics mass spectrometry algorithms related to therapeutic discovery, target identification and biomarker interactions/pathways.