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D-Index & Metrics

Chemistry

D-Index
54
Citations
13729
World Ranking
12464
National Ranking
3322

Overview

Yingkai Zhang is a researcher affiliated with New York University in the United States. Their work spans multiple disciplines with a significant focus on biochemistry, genetics, and molecular biology, as well as contributions to medicine and computer science.

The main fields of study for this scientist include:

  • Biochemistry, Genetics and Molecular Biology
  • Medicine
  • Computer Science

Within these broader areas, Zhang's research delves into several subfields, notably molecular biology, computational theory and mathematics, materials chemistry, oncology, and pharmacology.

  • Molecular Biology
  • Computational Theory and Mathematics
  • Materials Chemistry
  • Oncology
  • Pharmacology

Zhang has contributed to research on diverse topics, including computational drug discovery methods, protein structure and dynamics, machine learning applications in materials science, chemical synthesis and analysis, studies of protein tyrosine phosphatases, mechanisms of RNA and protein synthesis, and ubiquitin and proteasome pathways.

  • Computational Drug Discovery Methods
  • Protein Structure and Dynamics
  • Machine Learning in Materials Science
  • Chemical Synthesis and Analysis
  • Protein Tyrosine Phosphatases
  • RNA and protein synthesis mechanisms
  • Ubiquitin and proteasome pathways

Frequent co-authors collaborating with Zhang include:

  • Chao Yang
  • Xuben Hou
  • William M. Marsiglia
  • Jing Zhao
  • Xinyue Liu

Zhang's work has appeared in multiple publication venues, with the highest number of contributions to the Journal of Chemical Information and Modeling, followed by Nature Communications and the Journal of Chemical Theory and Computation. Zhang has also published in the Journal of Ethnopharmacology and archives such as arXiv (Cornell University).

  • Journal of Chemical Information and Modeling
  • Nature Communications
  • Journal of Chemical Theory and Computation
  • Journal of Ethnopharmacology
  • arXiv (Cornell University)

Notable recent papers authored or co-authored by Yingkai Zhang include:

  • "Targeting Amyloidogenic Processing of APP in Alzheimer's Disease" (2020), Frontiers in Molecular Neuroscience
  • "EGCG binds intrinsically disordered N-terminal domain of p53 and disrupts p53-MDM2 interaction" (2021), Nature Communications
  • "Protein-Ligand Docking in the Machine-Learning Era" (2022), Molecules
  • "Unified Deep Learning Model for Multitask Reaction Predictions with Explanation" (2022), Journal of Chemical Information and Modeling
  • "Selective and noncovalent targeting of RAS mutants for inhibition and degradation" (2021), Nature Communications

Best Publications

  • Comment on “Generalized Gradient Approximation Made Simple”

    Yingkai Zhang;Weitao Yang

  • A challenge for density functionals: Self-interaction error increases for systems with a noninteger number of electrons

    Yingkai Zhang;Weitao Yang

  • A pseudobond approach to combining quantum mechanical and molecular mechanical methods

    Yingkai Zhang;Tai Sung Lee;Weitao Yang

  • Free energy calculation on enzyme reactions with an efficient iterative procedure to determine minimum energy paths on a combined ab initio QM/MM potential energy surface

    Yingkai Zhang;Haiyan Liu;Weitao Yang

  • Degenerate Ground States and a Fractional Number of Electrons in Density and Reduced Density Matrix Functional Theory

    Weitao Yang;Yingkai Zhang;Paul W. Ayers

  • Describing van der Waals interaction in diatomic molecules with generalized gradient approximations: The role of the exchange functional

    Yingkai Zhang;Wei Pan;Weitao Yang;Weitao Yang

  • Role of the Catalytic Triad and Oxyanion Hole in Acetylcholinesterase Catalysis: An ab initio QM/MM Study

    Yingkai Zhang;Jeremy Kua;J. Andrew McCammon

  • Improving scoring-docking-screening powers of protein-ligand scoring functions using random forest.

    Cheng Wang;Yingkai Zhang;Yingkai Zhang

  • Reaction mechanism of monoethanolamine with CO2 in aqueous solution from molecular modeling

    Hong Bin Xie;Yanzi Zhou;Yingkai Zhang;J. Karl Johnson

  • Improved pseudobonds for combined ab initio quantum mechanical/molecular mechanical methods

    Yingkai Zhang

  • Polaron-to-Polaron Transitions in the Radio-Frequency Spectrum of a Quasi-Two-Dimensional Fermi Gas

    Y. Zhang;Y. Zhang;W. Ong;W. Ong;I. Arakelyan;I. Arakelyan;J. E. Thomas

  • Pseudobond ab initio QM/MM approach and its applications to enzyme reactions

    Yingkai Zhang

  • How does the cAMP-dependent protein kinase catalyze the phosphorylation reaction: an ab initio QM/MM study.

    Yuhui Cheng;Yingkai Zhang;J. Andrew McCammon

  • Density-based energy decomposition analysis for intermolecular interactions with variationally determined intermediate state energies

    Qin Wu;Paul W. Ayers;Yingkai Zhang

  • Protein–Ligand Docking in the Machine-Learning Era

    Unknown

  • A Proton-Shuttle Reaction Mechanism for Histone Deacetylase 8 and the Catalytic Role of Metal Ions

    Ruibo Wu;Shenglong Wang;Nengjie Zhou;Zexing Cao

  • Perspective on “Density-functional theory for fractional particle number: derivative discontinuities of the energy”

    Yingkai Zhang;Weitao Yang

  • Catalytic Reaction Mechanism of Acetylcholinesterase Determined by Born-Oppenheimer ab initio QM/MM Molecular Dynamics Simulations

    Yanzi Zhou;Shenglong Wang;Yingkai Zhang

  • Targeting Amyloidogenic Processing of APP in Alzheimer’s Disease

    Jing Zhao;Xinyue Liu;Weiming Xia;Weiming Xia;Yingkai Zhang

  • A Water-Mediated and Substrate-Assisted Catalytic Mechanism for Sulfolobus solfataricus DNA Polymerase IV

    Lihua Wang;Xinyun Yu;Po Hu;Suse Broyde

  • Studying enzyme binding specificity in acetylcholinesterase using a combined molecular dynamics and multiple docking approach.

    Jeremy Kua;Yingkai Zhang;J. Andrew McCammon

  • EGCG binds intrinsically disordered N-terminal domain of p53 and disrupts p53-MDM2 interaction

    Jing Zhao;Jing Zhao;Alan Blayney;Xiaorong Liu;Lauren Gandy

  • An efficient linear scaling method for ab initio calculation of electron density of proteins

    Ai M. Gao;Da W. Zhang;John Z.H. Zhang;Yingkai Zhang

Frequent Co-Authors

Suse Broyde
Suse Broyde New York University
Weitao Yang
Weitao Yang Duke University
Nicholas E. Geacintov
Nicholas E. Geacintov New York University
J. Andrew McCammon
J. Andrew McCammon University of California, San Diego
John Z. H. Zhang
John Z. H. Zhang New York University
Moosa Mohammadi
Moosa Mohammadi New York University Langone Medical Center
Daiqian Xie
Daiqian Xie Nanjing University
Hua Guo
Hua Guo University of New Mexico
Xin Gao
Xin Gao King Abdullah University of Science and Technology
Xuhui Huang
Xuhui Huang University of Wisconsin–Madison

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