Daniel Woldring
Assistant Professor
Chemical Engineering and Materials Science (ChEMS), College of Engineering
Institute For Quantitative Health Sciences and Engineering
775 Woodlot Dr Rm 4116
Biography
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.
Education
Ph.D., University of Minnesota, Chemical Engineering, 2017
B.S., Michigan Technological University, Chemical Engineering, 2011
Publications
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)