Li, Pengfei
Assistant Professor
Education
07/2011 B.S. in Chemistry, Xiamen University
08/2016 Ph.D. in Chemistry, Michigan State University
09/2016-12/2017 Postdoctoral Research Associate, University of Illinois at Urbana-Champaign
01/2018-08/2020 Postdoctoral Associate, Yale University
Research Interests
Metal ions are crucial to many biological processes such as enzymatic catalysis, electron transfer, and signal transduction. Computational modeling plays a more and more active role in scientific research nowadays. However, the mechanisms of many metal containing biomolecules are poorly understood and, furthermore, modeling metal ions in such systems is quite challenging. The Li research group will perform theoretical and computational studies at the interface of biochemistry and inorganic chemistry. The goals of my research group are to gain fundamental mechanistic insights on important metalloproteins and to apply our understanding to molecular design for catalytic, material, and biomedical purposes. To achieve these goals, we will develop accurate and efficient models as computational tools.
Metallodrugs and metalloenzyme inhibitors are two important types of medicines whose operations are dictated by metal-ligand interactions. However, it is challenging to model metal-ligand interactions both accurately and efficiently. We aim to develop an artificial intelligence assisted polarizable model for predicting the energetic properties of metal ion containing systems with high accuracy, cheap computational cost, and excellent transferability. This model will be used in mechanistic studies of metallodrugs and metalloenzymes as well as the design of metallodrugs and metalloenzyme inhibitors.
Moreover, through using theoretical and computational tools, we will investigate fundamental mechanisms of important metalloproteins, such as Ca2+ binding proteins and nitrogenase, and perform relevant molecular design for different purposes. For example, we are interested in investigating the ion-binding and ligand-binding mechanisms of Ca2+ binding proteins. Based on the obtained knowledge we will optimize ligand affinity and specificity for Ca2+ binding proteins, in order to provide biomedical solutions for relevant diseases.
Publications/Research Listings
Li, P.; Merz Jr, K. M., Taking into Account the Ion-Induced Dipole Interaction in the Nonbonded Model of Ions. J. Chem. Theory Comput. 2014, 10, 289-297.
Li, P.; Merz Jr, K. M., MCPB.py: A Python Based Metal Center Parameter Builder. J. Chem. Inf. Model. 2016, 56, 599-604.
Li, P.; Merz Jr, K. M., Metal ion modeling using classical mechanics. Chem. Rev. 2017, 117, 1564-1686.
Li, P.; Soudackov, A. V.; Hammes-Schiffer, S., Fundamental Insights into Proton-Coupled Electron Transfer in Soybean Lipoxygenase from Quantum Mechanical/Molecular Mechanical Free Energy Simulations. J. Am. Chem. Soc. 2018, 140, 3068-3076.
Li, P.; Hammes-Schiffer, S., Substrate-to-Product Conversion Facilitates Active Site Loop Opening in Yeast Enolase: A Molecular Dynamics Study. ACS Catal. 2019, 9, 8985-8990.
Li, P.; Rangadurai, A.; Al-Hashimi, H. M.; Hammes-Schiffer, S., Environmental Effects on Guanine-Thymine Mispair Tautomerization Explored with Quantum Mechanical/Molecular Mechanical Free Energy Simulations. J. Am. Chem. Soc. 2020, 142, 11183-11191.
Publication list via Google Scholar
Awards
2012 First Year Physical Chemist Award, University of Florida