Education :

2007.9-2013.7	Xiamen University	Ph.D. Theoretical physics
2003.9-2007.7	Minnan Normal University	B.S. Physics

Work :

2019.10-	Jimei University	Associate professor
2019.10-2020.04	University of Maryland, Baltimore	Visiting scholar
2017.08 - 2019.10	Jimei University	Assistant professor
2013.12 - 2017.08	University of Maryland School of Pharmacy, Baltimore	PostDoc fellow

Publications :

• Anti-cross-correlation between the adjacent open and closed durations of Markovian channels.

• Understanding the pH-dependent reaction mechanism of a glycoside hydrolase using high resolution X-ray and neutron crystallography.

• Predicting catalytic proton donors and nucleophiles in enzymes: how adding dynamics help elucidate the structure-function relationships.

• Generalized Born based continuous constant pH molecular dynamics in Amber: Implementation, benchmarking and analysis.

• Mechanism of pH-dependent activation of the sodium-proton antiporter NhaA.

• All-atom continuous constant pH molecular dynamics with particle mesh Ewald and titratable water.

• Alternative proton-binding site and long-distance coupling in Escherichia coli sodium–proton antiporter NhaA

• Continuous constant pH molecular dynamics simulations of transmembrane proteins

• Conformational activation of a transmembrane proton channel from constant pH molecular dynamics.

• Channel based generating function approach to the stochastic Hodgkin-Huxley neuronal system.

• Accurate Langevin approaches to simulate Markovian channel dynamics.

• Langevin approach with scaled noise for stochastic channel dynamics in Hodgkin-Huxley neuron.

• Frequency and relative prevalence of calcium blips and puffs transition in a model of small IP3R clusters.

• Induced dipoles incorporated into all-atom Zn protein simulations with multiscale modeling.

• Channel-based Langevin approach for the stochastic Hodgkin-Huxley neuron.

• Langevin approach for stochastic Hodgkin-Huxley dynamics with discretization of channel open fraction.

• Modified langevin approach for a stochastic calcium puff model.

• Puff-wave transition in an inhomogeneous model for calcium signals.

• AMBER 2019

• A Guide to the Continuous Constant pH Molecular Dynamics Methods in Amber and CHARMM [Article v1.0]

• Protein secondary structure prediction with a reductive deep learning method

• CHARMM at 45: Enhancements in accessibility, functionality, and speed

• Basis for accurate protein pKa prediction with machine learning

• Progress in protein pKa prediction

• Protein pKa prediction with machine learning

• DeepKa Web Server: High-Throughput Protein pKa Prediction

• Interior pH Sensing Residue of Human Voltage-Gated Proton Channel Hv1 is Histidine 168