Building Kinetic Models with Complex Drug-Protein Interactions: application to
the targeted inhibition of MAPK signaling in cancer
Luca Gerosa, PhD, Postdoctoral Fellow, Laboratory of Systems Pharmacology,
Harvard Medical School
Wednesday January 20, 2021, 12:00 to 1:00 pm EDT
Register at https://www.rosaandco.com/webinars
Abstract:
A key goal in the field of Quantitative Systems Pharmacology (QSP) is the
construction of mechanistic models able to predict drug efficacy. A major
challenge in building such models is the necessity to properly describe highly
cooperative drug-protein and protein-protein interactions that govern the
functioning of biochemical networks. In this seminar, I will show how Ordinary
Differential Equations (ODEs) models comprising large numbers of drug-protein
and protein-protein interactions can be efficiently built using rule-based
modelling and energy-based descriptions of molecular cooperativity.
The modelling framework I will present is based on an extension of the Python
Systems Biology (PySB) toolbox to incorporate energy-based specifications
supported by BioNetGen (eBNG). The resulting framework allows modelers to write
large ODEs models as compact Python programs in which molecular cooperativity
is specified as free energy contributions and detailed balance is satisfied by
construction. As a case study, I will show that the framework allows the
accurate description of high-order cooperativity interactions between
components of the MAPK signaling pathway and targeted kinase inhibitors and
that the inclusion of such interactions predicts clinically-relevant drug
resistance mechanisms in skin and colorectal cancers.