Chenglong Li

Research Description:

My long-standing scientific interest is to understand the structure and dynamics of matter at the atomic/molecular level (the jigglings and wigglings of atoms from the wonderful Feynman Lectures on Physics), and their relationship to the functions and properties of our physical and biological macro-world (the spatial-temporal collective behavior). My research domains span from X-ray macromolecular crystallography, molecular docking, molecular dynamics, quantum chemistry to statistical mechanics and non-equilibrium and equilibrium thermodynamics. Since the underlying complexity makes most of the research problems analytically intractable, computational approaches have to be adopted (the so-called third science of computation/simulation after theory and experiment).

Specifically, I would start with the study of molecular recognition because molecular recognition between biomolecules like proteins, DNAs, RNAs and small ligands is of central importance in biological and pharmacological processes like signal transduction, DNA transcription, enzymatic reaction and drug action. Whether two molecules bind to each other or not and how strong that binding is depend on the binding free energy differences. Therefore, predicting absolute and relative binding free energies of molecular associations is of great scientific and practical value. In fact, free energy calculation remains one of the most challenging issues in current computational sciences, even though great progress has been made and creative approaches have been developed over the past few decades.

Projects:

1) Structure-based/computer-aided drug design (SBDD/CADD)

* Anti-cancer drug design targeting BCL-2/BCL-xL, DNA methyltransferase (DNMT), thymidine kinase (TK), STAT3 and tubulin.
* Anti-diabetic (type 2) and anti-metabolic syndrome (MS) drug design targeting 11-HSD type 1.

2) Molecular docking and free energy simulation

* Molecular docking. Both sampling and scoring need to be improved.
* Free energy simulation. Both better end-point evaluation and fast and efficient phase-mapping are to be explored.

3) X-ray macromolecular crystallography

* The determination of 3D structures of biologically important proteins/DNAs/RNAs or their complexes (molecular machines).
* The development of crystallographic computing methods for both phase solution (reciprocal space) and structure refinement (real space).