David Kastner

David Kastner

Graduate Student

Massachusetts Institute of Technology

David is a graduate student in bioengineering jointly advised in the Kulik and Tidor labs. He graduated from Brigham Young University with a B.S. in biophysics and worked in an organic chemistry lab under the supervision of Dr. Steven Castle studying non-standard amino acids. David completed separate internships with Dr. Haribabu Arthanari at Dana-Farber on NMR and protein composition, and Dr. Nico Tjandra at the NIH studying protein-peptide interactions. After completing his bachelors, David worked as a cancer biologist at the Huntsman Cancer Institute studying network motifs in small-cell lung cancer with Dr. Trudy Oliver. His current research at MIT will focus on better understanding high-valent iron enzymes. David is an NSF fellow.

  • biochemistry
  • enzyme catalysis
  • non-heme iron
  • BS in Biophysics, 2019

    Brigham Young University


  1. Dynamic Charge Distribution as a Key Driver of Catalytic Reactivity in an Artificial Metalloenzyme (2024)
  2. Mechanistic basis for the emergence of EPS1 as a catalyst in salicylic acid biosynthesis of Brassicaceae (2024)
  3. Protein3D: Enabling analysis and extraction of metal-containing sites from the Protein Data Bank with molSimplify (2024)
  4. Enzymatic synthesis of azide by a promiscuous N-nitrosylase (2024)
  5. Emergence of a Proton Exchange-Based Isomerization and Lactonization Mechanism in the Plant Coumarin Synthase COSY (2023)
  6. Mechanistic Insights Into Substrate Positioning Across Non-heme Fe(II)/Alpha-Ketoglutarate-Dependent Halogenases and Hydroxylases (2023)
  7. Active Learning Exploration of Transition Metal Complexes to Discover Method-Insensitive and Synthetically Accessible Chromophores (2023)
  8. Using Computational Chemistry to Reveal Nature's Blueprints for Single-Site Catalysis of C–H Activation (2022)
  9. Influence of the Greater Protein Environment on the Electrostatic Potential in Metalloenzyme Active Sites: The Case of Formate Dehydrogenase (2022)
  10. MOFSimplify, machine learning models with extracted stability data of three thousand metal–organic frameworks (2022)
  11. Probing the mechanism of isonitrile formation by a non-heme iron(II)-dependent oxidase/decarboxylase (2022)