Lee-Ping Wang

About

Lee-Ping Wang is a professor specializing in physical chemistry at the University of California, Davis. He completed his B.A. in Physics at U.C. Berkeley from 2002 to 2006, followed by a Ph.D. in Physical Chemistry at MIT from 2006 to 2011. After his doctoral studies, he conducted postdoctoral research in physical chemistry at Stanford University from 2011 to 2015. He joined U.C. Davis as an assistant professor in physical chemistry in 2015 and was promoted to associate professor in 2020. His group focuses on theoretical chemistry, with research interests that include bio-molecular simulations, quantum chemistry calculations, and the development of computational methods to study chemical reactions and protein conformational changes. Professor Wang's work involves the use of ab initio nanoreactors to develop mechanistic knowledge of chemical processes, such as C-C bond formation and enzyme catalytic reactions, as well as the simulation of molecular dynamics to improve mass spectrometry libraries. He also contributes to the development of software tools for exploring potential energy surfaces, supporting advances in theoretical and computational chemistry.

Research topics

• Computer Science
• Chemistry
• Physics
• Quantum mechanics
• Physical chemistry
• Statistical physics
• Classical mechanics
• Computational chemistry
• Mathematics
• Computational science

Selected publications

• <scp>TeraChem</scp>: A graphical processing unit<scp>‐accelerated</scp> electronic structure package for <scp>large‐scale</scp> ab initio molecular dynamics

  Wiley Interdisciplinary Reviews Computational Molecular Science · 2020 · 305 citations

  Abstract TeraChem was born in 2008 with the goal of providing fast on‐the‐fly electronic structure calculations to facilitate ab initio molecular dynamics studies of large biochemical systems such as photoswitchable proteins and multichromophoric antenna complexes. Originally developed for videogaming applications, graphics processing units (GPUs) offered a low‐cost parallel computer architecture that became more accessible for general‐purpose GPU computing with the release of CUDA in 2007. The…

  DOI

• Non-bonded force field model with advanced restrained electrostatic potential charges (RESP2)

  Communications Chemistry · 2020 · 295 citations

  The restrained electrostatic potential (RESP) approach is a highly regarded and widely used method of assigning partial charges to molecules for simulations. RESP uses a quantum-mechanical method that yields fortuitous overpolarization and thereby accounts only approximately for self-polarization of molecules in the condensed phase. Here we present RESP2, a next generation of this approach, where the polarity of the charges is tuned by a parameter, δ, which scales the contributions from gas- and…

  DOI

• Development and Benchmarking of Open Force Field v1.0.0—the Parsley Small-Molecule Force Field

  Journal of Chemical Theory and Computation · 2021 · 167 citations

  Senior authorCorresponding

  We present a methodology for defining and optimizing a general force field for classical molecular simulations, and we describe its use to derive the Open Force Field 1.0.0 small-molecule force field, codenamed Parsley. Rather than using traditional atom typing, our approach is built on the SMIRKS-native Open Force Field (SMIRNOFF) parameter assignment formalism, which handles increases in the diversity and specificity of the force field definition without needlessly increasing the complexity of…

  DOI

• Predicting Collision-Induced-Dissociation Tandem Mass Spectra (CID-MS/MS) Using Ab Initio Molecular Dynamics

  Journal of Chemical Information and Modeling · 2024-09-27 · 13 citations

  articleOpen accessCorresponding

  Compound identification is at the center of metabolomics, usually by comparing experimental mass spectra against library spectra. However, most compounds are not commercially available to generate library spectra. Hence, for such compounds, MS/MS spectra need to be predicted. Machine learning and heuristic models have largely failed except for lipids. Here, quantum chemistry software can be used to predict mass spectra. However, quantum chemistry predictions for collision induced dissociation (C…

  PublisherOA PDFDOI

• Benchmarking Quantum Mechanical Levels of Theory for Valence Parametrization in Force Fields

  The Journal of Physical Chemistry B · 2024-08-01 · 11 citations

  articleOpen access

  A wide range of density functional methods and basis sets are available to derive the electronic structure and properties of molecules. Quantum mechanical calculations are too computationally intensive for routine simulation of molecules in the condensed phase, prompting the development of computationally efficient force fields based on quantum mechanical data. Parametrizing general force fields, which cover a vast chemical space, necessitates the generation of sizable quantum mechanical data se…

  PublisherOA PDFDOI

Frequent coauthors

• John D. Chodera

  42 shared

• David L. Mobley

  University of California, Irvine

  41 shared

• Simon Boothroyd

  35 shared

• Michael K. Gilson

  34 shared

• Michael R. Shirts

  University of Colorado Boulder

  32 shared

• Hyesu Jang

  University of California, Davis

  30 shared

• Christopher I. Bayly

  27 shared

• Todd J. Martı́nez

  Stanford University

  26 shared

Labs

• L-P. Wang Theoretical Chemistry GroupPI

Education

• Ph.D., Physical Chemistry, Chemistry

  Massachusetts Institute of Technology

  2011

• B.A., Physics

  University of California Berkeley

  2006

Awards & honors

• ACS-PRF Doctoral New Investigator (2017)
• Promoted to Associate Professor (2020)

Similar researchers at University of California, Davis

• Chenchen Songh-29
• Cody Ross Pittsh-28
• Elizabeth Neumannh-24