Sai Sanjana Prakash
Sai Sanjana Prakash is an R&D scientist with training in Computer Science and Biomedical Engineering from Georgia Tech. She is passionate about tackling challenges at the intersection of computation, science, and engineering. Her work and interests span the foundations of intelligence, protein design and engineering, and the development of computational tools to advance scientific discovery. Driven by a deep curiosity for complex systems, Sanju focuses on translating insights into innovative, practical solutions.
Session
Engineering enzymes with improved catalytic activity remains a central challenge in biotechnology. In this research, we focus on engineering PETase, a plastic-degrading enzyme, as a testbed for developing a simulation-informed machine learning workflow. We present a Python framework that integrates molecular simulations, docking, and structural analysis with modern machine learning methods to predict enzyme activity from sequence and structure. By combining simulation-derived descriptors—including active-site geometry, electrostatics, stability metrics, dynamics, and docking scores—with sequence embeddings, we generate interpretable predictions that guide rational mutation strategies. While developed for PETase engineering, the workflow is extensible to broader de novo enzyme design efforts.