The Lab:

Our laboratory operates at the intersection of computational chemistry, machine learning, and enzymology. Enzymes are nature’s most sophisticated catalysts, driving complex chemical transformations with unparalleled efficiency and specificity. To understand, predict, and engineer these remarkable molecular machines, our group bridges the gap between physics-based simulations and data-driven machine learning methods. By teaching computers the underlying laws of physics and chemistry, we aim to accelerate molecular discovery and unlock predictive control over biological catalysts.

Core Pillars of Our Work
Enzymology & Biophysics: Deciphering the fundamental atomistic mechanisms, transition states, and catalytic pathways of complex enzymes.
Computational Chemistry: Utilizing electronic structure methods, molecular dynamics, and enhanced sampling workflows to model reactivity and molecular recognition.
Machine Learning: Developing and deploying next-generation machine learning methods that bridge and enhance conventional approaches for studying enzyme mechanisms and chemical reactivity.

News:

July 2026: We are officially setting up this Fall 2026! Are you excited about computational chemistry, biophysics, and machine learning? Our lab is actively looking for curious and motivated students to join our growing team. You do not need prior research experience—just a passion for discovery and a willingness to learn. Come by my office or drop me an email to chat about our upcoming projects!

Contact:

Steve Dajnowicz, Ph.D.
Department of Chemistry and Biochemistry
School of Interdisciplinary Data Science
University of Toledo
Toledo, Ohio 43606
WO 2231
steve.dajnowicz@rockets.utoledo.edu