Brian Pierce

Assistant Professor

Pierce Group

Contact

Email: pierce@umd.edu

Call: (240) 314-6271

Education

  • Ph.D., Bioinformatics, Boston University, 2008
  • B.S., Physics and Computer Science, Duke University, 2000

Profile

Dr. Brian Pierce’s laboratory develops and applies computer algorithms to better understand how the immune system recognizes pathogens and cancer, and his lab is particularly interested in antibodies, T cell receptors, and vaccine design. For more information on the Pierce Lab, visit the lab web site at: https://piercelab.ibbr.umd.edu.

CURRENT RESEARCH

Recent efforts have focused on studying the structure of the hepatitis C virus (HCV) to inform the design of novel vaccine candidates. This work includes the development of a pioneering epitope-based vaccine for HCV that elicits neutralizing antibodies. The Pierce lab is also modeling how HCV can escape antibody neutralization, and this can be used toward developing new vaccine candidates.

Crystallographic structure of a broadly neutralizing hepatitis C virus antibody in complex with a vaccine immunogen designed by the Pierce laboratory.

The Pierce group is working on understanding and predicting how antibodies recognize viruses and other pathogens. Through a collaboration with researchers at Stanford University, they now have an unprecedented view of the structure and key antibody recognition features of HCV. This provides a roadmap for improved HCV vaccine candidates, as well as insights into antibody recognition of viral envelope proteins in general.

Global mapping recognition determinants for a panel of 16 human monoclonal antibodies targeting hepatitis C virus.  Color representing binding level of mutants, and mutants are clustered based on binding profile similarity.

A longstanding area of focus in the lab has been understanding how T cells recognize specific antigens, and work in the Pierce lab includes modeling how T cell receptors (TCR) can be engineered to target cancer cells. The group has developed a therapeutic TCR that targets melanoma, and ongoing work includes developing algorithms to improve and optimize TCR structures for immunotherapeutic applications.  

The Pierce lab has developed a number of predictive protein modeling and design algorithms to carry out their research, including Rosetta, TCRFlexDock, RosettaTCR, ZRANK, and ZDOCK. The lab is a member of the RosettaCommons community, which is a global network of developers of the Rosetta modeling and design software. 

Structure of a T cell receptor for melanoma immune-therapy that was designed for 400-fold affinity improvement in binding to the tumor antigen.
Publications
2022
Benchmarking AlphaFold for protein complex modeling reveals accuracy determinants.
Structural Features of Antibody-Peptide Recognition.
Induction of broadly neutralizing antibodies using a secreted form of the hepatitis C virus E1E2 heterodimer as a vaccine candidate.
An extended motif in the SARS-CoV-2 spike modulates binding and release of host coatomer in retrograde trafficking.
T cell receptors (TCRs) employ diverse strategies to target a p53 cancer neoantigen.
Structural assessment of HLA-A2-restricted SARS-CoV-2 spike epitopes recognized by public and private T-cell receptors.
2021
Molecular Determinants of Filament Capping Proteins Required for the Formation of Functional Flagella in Gram-Negative Bacteria.
An Antigenically Diverse, Representative Panel of Envelope Glycoproteins for Hepatitis C Virus Vaccine Development.
Structural and energetic profiling of SARS-CoV-2 receptor binding domain antibody recognition and the impact of circulating variants.
Prediction of protein assemblies, the next frontier: The CASP14-CAPRI experiment.
T Cell Receptor Genotype and Ubash3a Determine Susceptibility to Rat Autoimmune Diabetes.
Structural and Biophysical Characterization of the HCV E1E2 Heterodimer for Vaccine Development.
Structure-Based and Rational Design of a Hepatitis C Virus Vaccine.
An expanded benchmark for antibody-antigen docking and affinity prediction reveals insights into antibody recognition determinants.
Anti-CfaE nanobodies provide broad cross-protection against major pathogenic enterotoxigenic Escherichia coli strains, with implications for vaccine design.
Design of a native-like secreted form of the hepatitis C virus E1E2 heterodimer.
2020
High-throughput modeling and scoring of TCR-pMHC complexes to predict cross-reactive peptides.
CoV3D: a database of high resolution coronavirus protein structures.
Structure-Based Design of Hepatitis C Virus E2 Glycoprotein Improves Serum Binding and Cross-Neutralization.
CoV3D: A database and resource for high resolution coronavirus protein structures.