Engineering Protein-Protein Interactions in DNA Repair for Cancer Therapeutics

Advisor: Wei Zhang, Molecular Cell Biology

Introduction: The recent clinical success of inhibitors against poly(ADP-ribose) polymerase (PARP), important for DNA base excision repair, in treating ovarian cancer patients with BRCA1/2 mutations highlights the significance of exploiting "synthetic lethality" for cancer therapy in patients with existing DNA damage response (DDR) deficiencies. While research on DDR continues to grow, there is paucity of development of efficient drug-targeting and therapeutic lead platforms encompassing probes that modulate DDR protein function. To tackle this problem, we will leverage our established protein rational design and engineering platform to target WD40 domain-mediated
protein-protein interactions (PPIs) important for DDR for cancer therapeutics.

Proposal: Through protein engineering approaches, we have now obtained potent and specific protein-based inhibitors for a couple of WD40 domain-containing proteins. We are in the process of validating and characterizing such synthetic molecules in vitro and in cells. We want to recruit a Master of Bioinformatics student to conduct extensive computational analysis to establish the molecular determinants for high-affinity binding and selectivity with tools and methodologies developed by a protein therapeutics and quantum computing company (our industry partner).

Specifically, we will pursue the following aims:
1. Qualitative analysis of protein structures in 3D molecular viewers and quantitative analysis through the use of programmed scripts
2. Conformational sampling of inhibitor-target complex proteins using molecular simulation with OpenMM
3. Biophysical modelling of PPI through global docking with ROSETTA
4. Inhibitor optimization of binding affinity, stability, and selectivity through structureguided sequence variations using ROSETTA design

Significance: We expect that the developed synthetic molecules can probe DDR signaling with unprecedented precision, and delineate elusive DNA repair mechanisms. Moreover, protein structural insight from experimental data and computational modeling will further guide rational design and facilitate screening of small molecule inhibitors, particularly for allosteric sites that traditional compound screen assays have failed to reach. Thus, our project will shed light on novel cancer therapeutic design, and most importantly, result in a proof-of-concept pipeline where computational modeling and phage display seamlessly integrate to guide self-directed evolution in drug discovery.