enzyme catalysis; functional genomics; modeling of enzyme substrate interactions; drug discovery; bioinformatics; protein design
Prof. Ondrechen’s research group specializes in theoretical and computational chemistry and computational biology. Areas of interest include: 1) Understanding the fundamental basis for enzyme catalysis; 2) Functional genomics – prediction of the functional roles of gene products (proteins); 3) Modeling of enzyme-substrate interactions; 4) Drug discovery; and 5) Bioinformatics.
With the sequencing of the human genome and the genomes of hundreds of species of interest, Structural Genomics (SG) projects have now reported over 12,000 new protein structures. The next question is: What do these structures actually do? Prof. Ondrechen’s group is developing methods to predict protein function from structure. Our THEMATICS (see Ondrechen et al., Proc. Natl. Acad. Sci. USA 98, 12473, 2001) and POOL (see Tong, Wei, Murga, Ondrechen and Williams, PLoS Computational Biology, 2009) methods predict the residues involved in biochemical function, require only the structure of the query protein, and thus work for proteins that bear no resemblance to previously characterized proteins. Our SALSA method (see Wang, Yin, et al. 2013) uses these predicted functional residues to determine biochemical function.
Another current project explores the multilayer nature of enzyme active sites – we are able to predict when remote amino acid residues are involved in catalysis. We work in collaboration with experimentalists to test and verify our predictions pertaining to multilayer active sites.
1978 Ph.D., Northwestern University
1974 B.A., Reed College
- C.L. Mills, R. Garg, J.S. Lee, L. Tian, A. Suciu, G. Cooperman, P.J. Beuning, M.J. Ondrechen, Functional Classification of Protein Structures by Local Structure Matching in Graph Representation, Protein Science, 27, 2018, 1125-1135
- R. Parasuram, T.A. Coulther, J.M. Hollander, E. Keston-Smith, M.J. Ondrechen, P.J. Beuning, Prediction of Active Site and Distal Residues in E. coli DNA Polymerase III Alpha Polymerase Activity, Biochemistry 57(7), 2018, 1063-1072
- R. Cheng, W. Mori, L. Ma, M. Alhouayek, A. Hatori, Y. Zhang, D. Ogasawara, G. Yuan, Z. Chen, X. Zhang, H. Shi, T. Yamasaki, L. Xie, K. Kumata, M. Fujinaga, Y.Nagai, T.Minamimoto, M. Svensson, L. Wang, Y. Du, M.J. Ondrechen, N. Vasdev, B. Cravatt, C. Fowler, M. Zhang. S.H. Liang, In Vitro and in Vivo Evaluation of C-11-Labeled Azetidine-Carboxylates for Imaging Monoacylglycerol Lipase by PET Imaging Studies, J. Med. Chem. 61, 2018, 2278-2291
- E. Mongeau, G. Yuan, Z. Minden, S. Waldron, R. Booth, D. Felsing, M.J. Ondrechen, G.B. Jones, Homology Modeling Inspired Synthesis of 5-HT2A Inhibitors: A Diazepine Analogue of the Atypical Antipsychotic JL13, Central Nervous System Agents in Medicinal Chemistry, 2017
- R. Parasuram, C.L. Mills, Z. Wang, S. Somasundaram, P.J. Beuning, M.J. Ondrechen, Local Structure Based Method for Prediction of the Biochemical Function of Proteins: Application to Glycoside Hydrolases, Methods, 93, 2016, 51-63
Jun 27, 2019
ECE Professor Deniz Erdogmus (co-PI) and affiliated BioE Professors Mary Jo Ondrechen (PI) and Penny Beuning (co-PI) were awarded a $600K NSF grant for “Mining for mechanistic information to predict protein function”.
Apr 04, 2012
27 COE faculty and affiliates were recipients of FY13 TIER 1 Interdisciplinary Research Seed Grants for 21 different research projects.