SMASH Postdoctoral Research Fellow, University of Nova Gorica
I am a Computational Biologist with extensive wet-lab expertise, working for over 8 years
in the
characterization of novel proteins/enzymes and studying structure-function interconnections during
evolution. I specialize in integrating wet-lab and computational methods.
Currently, I am focusing on Protein Design, developing custom workflows that integrate AI-
and
physics-based methods to generate binders for folded and unfolded epitopes of medically relevant biomarkers.
I am developing a computational pipeline to design binders for studying the biology of challenging
biomarkers like CDKL5 kinase, which is poorly immunogenic/druggable, as different isoforms and closely
related paralogue kinases exist. In this project we need to target specific epitopes, both in folded
and unfolded regions, and find binders that, prior to have great affinity, are also specific and
developable for cell-based studies.
The key challenge to address is achieving both binding and developability success while keep
the experimental screening at minimum (<20 characterized designs). This will be done by
efficiently leveraging multiple AI-based and physics-based agents to filter out and optimize several
thousands of epitope-specific candidates. This will allow to bypass the severe high-throughput
experimental bottleneck that exists for making reagents suitable to target functional regions of
this biomarker in cell studies.