Agenda Highlights
Can Makya re-discover known inhibitors? In this validation use case, we challenge the platform’s 3D structure-based generative models to explore the chemical space of the complement C1s enzyme. Learn how Makya converges on known actives, what this reveals about the reliability of AI-generated designs, and how such analyses help scientists gain confidence in de novo design outcomes.
Speaker
Stefani Gamboa
Application Scientist, Iktos
Stefani Gamboa is a pharmaceutical and computational chemist by training. She holds a degree in Pharmaceutical Chemistry and a PhD in theoretical and bioinorganic chemistry, with a focus on quantum bioinorganic systems. Her doctoral research centered on the experimental design and theoretical modeling of polynuclear copper complexes, serving as bioinspired models for copper-containing enzymes with applications in catalysis and magnetic materials. Stefani gained industry experience at GlaxoSmithKline before moving into her current role as an Application Scientist at Iktos, where she works at the intersection of drug discovery, generative AI, and computational chemistry.
