Speaker: Christina Bergonzo, Nist, USA

Abstract: Characterization of structure and dynamics is central to the development and assessment of monoclonal antibody-based therapeutics, which need to be effective, stable, and safe biopharmaceutical products. Molecular dynamics has become a central method to determine the higher order structure and structure ensembles of biotherapeutics. In this talk, I will discuss the application of molecular dynamics to two projects related to monoclonal antibodies: development of a measurement scheme to enable fast stability predictions of Fc domain truncations, and integration of molecular dynamics simulations with hydrogen deuterium exchange mass spectrometry to characterize the effect of glycans on Fc-Fcγ receptor binding.

Biography: Christina Bergonzo began her research career as an undergraduate at Manhattan College, studying transition state intermediates in cyclization reactions using high level quantum calculations. After graduating from Manhattan College with a Bachelor of Science in Chemistry, she went on to graduate school at Stony Brook University in Professor Carlos Simmerling’s Group. As a graduate student, she helped to develop the partial Nudged Elastic Band method and used it combined with molecular dynamics simulations to study the mechanism of repairing oxidative damage to DNA. She earned her Ph. D. in Chemistry in 2012 and became a post-doctoral researcher with Professor Tom Cheatham at the University of Utah. There she helped implement the multi-dimensional replica exchange method in the Amber MD software package and used it to perform in-depth assessments of the current state of nucleic acid force fields, ultimately revealing the importance of water models in reproducing experimental results with MD simulations of nucleic acids. In 2017 she received an NRCpost-doctoral fellowship from NIST, and in 2021 became a Research Chemist in the Biomolecular Structure and Function Group at NIST/IBBR. Her current work focuses on developing improved computational simulation methods and integrating data from experimental methods to address NIST priority areas in biomanufacturing.