Jianhan Chen

Research in the Chen lab focuses on the development of theoretical and computational methods and application of these methods to advance our understanding of biophysical, biochemical and biomedical problems. The lab has made significant contributions to the field of molecular modeling and simulation, including advanced conformational sampling algorithms, balanced implicit solvent protein force fields, GPU-accelerated simulation algorithms, and multi-scale protein and RNA modeling. We are also interested in physics-informed machine learning strategies to overcome data scarcity and to generate dynamic conformation ensembles. These developments have been distributed in the widely available CHARMM/OpenMM and MMTSB packages, as well as GitHub and the CCP-SAS website.

Our method developments have been motivated by the need to study biomedically relevant problems, including intrinsically disordered proteins in biology and diseases, bimolecular condensates, protein amyloid formation in neurogenerative diseases, self-assembling peptides and polymers for drug delivery, nanopore tweeters for single molecule measurement of protein dynamics, and transmembrane ion channel protein structure, activation and regulation. To study these complex molecular systems, we collaborate extensively with experimental researchers. Integrated computational and experimental approaches deployed throughout these studies enable us to direct our computational method development efforts to critical areas for which advances are needed, while at the same time push and test our methods with tangible feedback.

Learn more at Jianhan Chen Research Group

Academic Background

• B.S. 1998, University of Science and Technology of China
• Ph.D. 2002, University of California at Irvine