Shobhit S. Chaturvedi
Postdoctoral Scholar | Department of Chemistry and Applied Biosciences, ETH Zürich
Department of Chemistry and Applied Biosciences
ETH Zürich
Zurich, Switzerland
Computational Chemist · Enzyme Catalysis · Enzyme Engineering
I am a computational chemist investigating how protein scaffolds control enzyme catalysis — and how these principles can be harnessed to engineer enzymes with new functions. My research combines multiscale simulations (QM/MM, molecular dynamics), machine learning, and emerging quantum computing methods to discover novel reaction mechanisms, develop predictive computational tools, and design enzymes for applications in health, energy, and sustainability.
Currently a Postdoctoral Scholar at ETH Zürich with Prof. Markus Reiher, I work on quantum computing pipelines for biological applications, rational metalloenzyme engineering, and the catalytic mechanism of nitrogenase for biological nitrogen fixation. Previously at UCLA with Prof. Anastassia N. Alexandrova (2023–2025), I developed computational frameworks mapping dynamic 3D electric field landscapes in enzyme active sites and built ML models that predict enzymatic function from electrostatic signatures. I received my Ph.D. from Michigan Technological University (2022), where I elucidated metalloenzyme mechanisms with Prof. Christo Z. Christov — including novel pathways later validated experimentally in Science.
Understanding Catalysis — Why?
Discovering how electrostatics, dynamics, and electronic structure within protein scaffolds govern enzymatic precision — and uncovering previously unknown chemistry.
Predicting & Engineering — How?
Building ML models, open-source tools, and electric-field frameworks that predict enzyme function and guide rational design of new catalytic capabilities.
Frontier Applications — What for?
Translating mechanistic insights into quantum computing for biology, sustainable catalysis, and drug discovery for real-world impact.
News
| Apr 15, 2026 | Awarded the ETH Zürich Focus Grant (CHF 10,106) — a two-month fellowship from the ETH Grants Office supporting preparation of an ERC Starting Grant application. |
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| Aug 01, 2025 | Joined ETH Zürich as a Postdoctoral Scholar in the Department of Chemistry and Applied Biosciences. Working on quantum computing for biology, metalloenzyme engineering, and the catalytic mechanism of nitrogenase! |
| Apr 15, 2025 | PyCPET — our open-source Python toolbox for computing heterogeneous 3D protein electric fields — has been published in the Journal of Chemical Theory and Computation (JCTC 2025). |
| Jan 15, 2025 | Our comprehensive review on electric fields in enzyme catalysis has been published in Chemical Reviews (2025). This review covers the theory, computational methods, and experimental measurements of electric fields in enzymatic systems. |
| Oct 01, 2024 | New paper in JACS: Our machine learning framework interprets 3D electric fields across heme-iron oxidoreductases to predict enzymatic function. Published in J. Am. Chem. Soc. 2024, 146, 28375–28383. |