Ho-Leung Ng, Ph.D., Adjunct Associate Professor

Image of Ho Ng

Contact Information

Office: 34 Chalmers Hall
Phone: 785-532-2518
Fax: 785-532-7278
Email: hng@ksu.edu
Lab Website


A.B. 1994, Harvard University
Ph.D. 2001, University of California at Los Angeles

Areas of Speciality

  • Structure based drug discovery for cancer and immunology
  • Computational structural biology and chemistry
  • Protein photonics for imaging

1. Structure based drug discovery for cancer and immunology

Our lab uses X-ray crystallography and computational chemistry to discover new drugs for cancer and immunology. Our most advanced projects involve the 1) characterization and development of T-cell receptor mimic antibodies for immuno-oncology, 2) developing allosteric inhibitors against the estrogen producing enzyme, aromatase, for treating breast cancer, and 3) developing agonists and antagonists against the immunoregulatory receptor, RORgamma, for treating autoimmune disorders and cancer. We collaborate closely with researchers in clinical research, medicinal chemistry, and industry. A strength of our lab is the ability to perform cutting edge research in both experimental and computational science.

2. Computational structural biology and chemistry

We develop new computational methods to address challenges in interpreting crystallographic data, characterizing protein structural flexibility, and predicting drug binding affinity and selectivity. In our lead project, we are developing a new computational method, HyPO (Hydrogen atom Prediction and Observation) for analyzing protein X-ray crystallography maps to detect hydrogen atoms. Hydrogen atoms, having only one electron, scatter X-rays very weakly and are often invisible in X-ray maps. HyPO locates hydrogen atoms, which play critical roles in protein function such as enzyme mechanism and ligand binding. We are developing HyPO to work with x-ray crystallography maps of modest resolution and weak neutron crystallography maps. A new project is developing machine learning methods for problems in computational drug discovery.

3. Protein photonics for imaging

Atomic-level understanding of proteins allows us to re-engineer natural proteins to adopt new, useful functions. The design of new structures and functions is also the ultimate experimental test of the limits of our knowledge and technology. Our lab collaborates with leading researchers to develop new fluorescent protein probes for biological imaging. We use crystallographic and computational methods to develop the physical chemistry basis for improved optical and spectral properties. We are especially interested in chemical probes for deep imaging.

Selected Publications

Vidad AR, Macaspac S, Ng HL. (2016). Locating the ligand binding sites for the G-protein coupled estrogen receptor (GPER) using combined information from docking and sequence conservation.

Ng HL. (2016). Simulations reveal increased fluctuations in estrogen receptor-alpha conformation upon antagonist binding. J. Molec.Graphics Modelling. 69, 72.

Ng HL, Lin, M.Z. (2016). Structural-guided wavelength tuning in far-red fluorescent proteins. Current Opin. Struct. Biol. 39, 124.

Chu J, Oh Y, Sens A, Ataie N, Dana H, Macklin JJ, Laviv T, Welf ES, Dean KM, Zhang F, Kim BB, Tang CT, Hu M, Baird MA, Davidson MW, Kay MA, Fiolka R, Yasuda R, Kim DS, Ng HL, Lin MZ. (2016). A bright cyan-excitable orange fluorescent protein facilitates dual-emission microscopy and enhances bioluminescence imaging in vivo. Nature Biotechnol. 34, 760.

Ataie N, Xiang J, Cheng N, Brea EJ, Lu W, Scheinberg DA, Liu C, Ng HL. (2016). Structure of a TCR-mimic antibody with target predicts pharmacogenetics. J. Mol. Biol. 428, 194.

Kim J, Kagawa A, Kurasaki K, Ataie N, Cho IK, Li QX, Ng HL. (2015). Large scale identification of membrane proteins with properties favorable for crystallization. Protein Sci. 24, 1756.

Chu J, Haynes R, Corbel SY, Li P, González-González E, Burg JS, Ataie NJ, Lam AJ, Cranfill PJ, Baird MA, Davidson MW, Ng HL, Garcia KC ,Contag CH, Shen K, Blau HM, Lin MZ. (2014). Non-invasive intravital imaging of cellular differentiation with a bright red-excitable fluorescent protein. Nature Methods. 11, 572.

Lang PT, Ng HL, Fraser JS, Corn J, Echols N, Sales M, Holton JM, Alber T. (2010). Automated electron-density sampling reveals widespread conformational polymorphism in proteins. Protein Sci. 19, 1420.

Lin MZ, McKeown MR, Ng HL, Aguilera T, Shaner NC, Adams SR, Ma W, Alber T, Tsien RY. (2009). Autofluorescent proteins with excitation in the optical window for intravital imaging in mammals. Chemistry & Biology 16, 1169.

Complete Publications List