Gwo-Yu Chuang

Associate VP and Global Head, Computational Antigen Design @ Sanofi

About

Computational protein design expert with 15+ years of research experience and 7+ years of experience in team building/management. Primary focus is in vaccine design with experience in engineering both viral and bacteria antigens compatible with the mRNA platform. 100+ peer-reviewed journal articles (10+ first/co-first/corresponding, https://scholar.google.com/citations?user=rczIBLMAAAAJ&hl=en) and 5+ patents. Other research interests include antibody design, epitope prediction, epitope specific probe design, binding hotspot identification, ligand docking, fragment-based drug discovery, pharmacophore design and compound screening.

Country

United States

City

Rockville

Industry

Biotechnology

Skill

Protein Design, Immunogen Design, Antibody Design, Small Molecule Design, Pharmacophore Modeling, Molecular Modeling, Computational Chemistry, Homology Modeling, Protein docking, Cheminformatics, Virtual Screening, Ligand Docking, Protein Engineering, Drug Discovery, Docking, GPCR modeling, Lead Optimization, Library Design, C++, Linux

Experience

Associate VP and Global Head, Computational Antigen Design

Sanofi

2024-12 - Present · 1 yr 10 mos

Waltham, MA

- Leading an international team of ~25 scientists to design vaccine sequences - Activities: Structural Biology, AI-based Protein Design, OMICs, Variant Surveillance, AI/ML

Senior Director and Global Head, Computational Antigen Design

Sanofi

2023-3 - 2024-12 · 1 yr 10 mos

Cambridge, Massachusetts, United States

Associate Scientific Director, Bioinformatics, Antigen Design and Selection, Infectious Disease

Moderna

2021-5 - 2023-3 · 1 yr 11 mos

Cambridge, Massachusetts, United States

- Leading a computational team to support the scientific needs of infectious disease research - Computational structure-based design of bacterial and viral antigens compatible with the mRNA platform

Co-head and Staff Scientist, Structural Bioinformatics Core Section, Vaccine Research Center

National Institute of Allergy and Infectious Diseases (NIAID)

2015-11 - 2021-5 · 5 yrs 7 mos

- Applying computational protein modeling to the development of a number of vaccine immunogens (e.g. HIV-1, RSV, and PIVs) - Applying bioinformatics methods to improve potent neutralizing antibodies against HIV-1 - Applying machine learning to predict protein properties - Supervising postdoctoral fellows and students, managing budgets, and applying for external fundings

Postdoctoral Research Fellow

National Institute of Allergy and Infectious Diseases (NIAID)

2011-5 - 2015-10 · 4 yrs 6 mos

Bethesda, MD

Designed mutations aiming at improving the interactions between CD4-binding-site antibodies and HIV-1 gp120. Designed HIV-1 gp120 based immunogens to improve the binding to CD4-binding-site germline antibodies. Developed N-linked glycosylation prediction algorithm using structural and pattern information. Antibody optimization, including improving potency, stability, solubility, and reducing autoreactivity. Provided computational supports to experimentalists at VRC. Advisor: Peter Kwong/Ivelin Georgiev

Postdoctoral Fellow

AstraZeneca

2009-6 - 2011-4 · 1 yr 11 mos

Developed a structure-based pharmacophore generation tool which identifies the hot spot atoms in binding cavities using a knowledge-based classification model and places the pharmacophore features near the hot spot atoms using topological rules. Built and refined homology models for intractable GPCRs related to metabolism and derived pharmacophore models. Screened and selected compounds from in-house library using the models. Advisor: Didier Rognan (University of Strasbourg)

Graduate Research Assistant

Boston University

2006-5 - 2009-5 · 3 yrs 1 mo

Developed a grid based computational fragment mapping algorithm FTMAP to identify the important functional and ligand binding sites of proteins by looking at the consensus sites where different types of small molecule fragments bind. Applications include identification of potential inhibitor binding sites on influenza M2 proton channel, targeting druggable hot spots on protein-protein interfaces, and analysis of CYP3A4 plasticity, Developed a statistical pairwise potential DARS (Decoys As Reference State) which significantly increased the docking accuracy of enzyme-inhibitor complexes. Formulated and implemented an asymmetric potential focusing on the hydrophobicity of the antibody CDR regions which greatly increased the docking accuracy of antibody-antigen complexes. Generated asymmetric small molecule mapping potentials for FTMAP. Advisor: Sandor Vajda