Ming-Hong is responsible for creating and implementing Ensem's core technologies on simulating protein/RNA structural dynamics and conformational ensemble and translating these insights into innovative therapeutics. He will guide the team to integrate proprietary experimental protein structural and dynamic data into predictive theoretical models; unleash the combined power of sophisticated peptide sampling methods, advance AI-based protein 3D structure and ligand-binding pocket recognition algorithms and multi-level molecular dynamics simulations.
Ming-Hong is a highly successful and well-recognized computational chemist with 23 years of experience in drug discovery in the pharmaceutical industry. He has made key contributions based on computational approaches to create four clinical drug candidates in Oncology. Before Joining Ensem Therapeutics, he worked at Boehringer Ingelheim, H3 Biomedicine, Eisai and Agios with increasing responsibilities. Ming-Hong received a PhD from Rutgers University and did postdoctoral research at Cornell University, where he built deep and broad expertise in structural biology and MM/QM computational sciences. He has authored/co-authored more than 50 peer-reviewed scientific papers. He is also co-inventor of 20 issued patents.