Daniel R. Woldring


Daniel R. Woldring

Assistant Professor


We develop high performance therapeutics and diagnostics using novel protein engineering methods. Our lab combines directed evolution and high-throughput experiments with structural biology and bioinformatics to elucidate biological processes and their clinical relevance.


Research Area
PhD, University of Minnesota, Chemical Engineering, 2017
BS, Michigan Technological University, Chemical Engineering, 2011
M Mardikoraem, DR Woldring. “Machine Learning-Driven Protein Library Design: A Path Toward Smarter Libraries”, Methods in Molecular Biology, 2022;2491:87-104. doi: 10.1007/978-1-0716-2285-8_5.
H Komuro, S Aminova, K Lauro, DR Woldring and M Harada, “Design and Evaluation of Engineered Extracellular Vesicle (EV)-Based Targeting for EGFR-Overexpressing Tumor Cells Using Monobody Display.” Bioengineering 2022, 9(2), 56.
J VanAntwerp, P Finneran, DR Woldring. “Ancestral sequence reconstruction and alternate amino acid states guide protein library design”, Methods in Molecular Biology, 2022;2491:75-86. doi: 10.1007/978-1-0716-2285-8_4.
Z Wang, T Belecciu, J Eaves, M Bachmann, DR Woldring, “Phytochemical Drug Discovery for COVID-19 Using High-resolution Computational Docking and Machine Learning Assisted Binder Prediction.” 2022 (Accepted by Journal of Biomolecular Structure and Dynamics and currently available at ChemRxiv)