研究领域
Theoretical Chemical Biology/Physics
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; 5) Bioinformatics; and 6) Protein engineering.
With the sequencing of the human genome and the genomes of hundreds of species of interest, Structural Genomics (SG) projects have now reported over 13,000 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. This is a very important question for enzyme design.
With the many very active programs in Medicinal Chemistry in this Department, the Ondrechen group also provides computational collaboration for multiple different drug discovery efforts.
近期论文
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“Design and evaluation of xanthine based adenosine receptor antagonists: Potential hypoxia targeted immunotherapies,” R. Thomas, J. Lee, V. Chevalier, S. Sadler, K. Selesniemi, S. Hatfield, M. Sitkovsky, M.J. Ondrechen, and G.B. Jones, Bioorganic and Medicinal Chemistry 21, 7453-7464 (2013). (Contact us for reprint)
“Protein function annotation with Structurally Aligned Local Sites of Activity (SALSAs),” Zhouxi Wang, Pengcheng Yin, Joslynn S Lee, Ramya Parasuram, Srinivas Somarowthu, Mary Jo Ondrechen, BMC Bioinformatics, 2013, 14(Suppl 3):S13. http://www.biomedcentral.com/1471-2105/14/S3/S13
“Effects of non-catalytic, distal amino acid residues on activity of E. coliDinB (DNA Polymerase IV),” Jason M. Walsh, Ramya Parasuram, Pradyumna R. Rajput, Eriks Rozners, Mary Jo Ondrechen, and Penny J. Beuning, Environmental and Molecular Mutagenesis 53(9), 766-776 (2013). (Contact us for a reprint) http://onlinelibrary.wiley.com/doi/10.1002/em.21730/full
“The human Aurora kinase inhibitor danusertib is a lead compound for anti-trypanosomal drug discovery via target repurposing,” Stefan O. Ochiana, Vidya Pandarinath, Zhouxi Wang, Rishika Kapoor, Mary Jo Ondrechen, Larry Ruben, and Michael P. Pollastri, European Journal Medicinal Chemistry, (2012). (PMID: 22889561) (Contact us for a preprint) http://dx.doi.org/10.101/j.ejmech.2012.07.038
“POOL server: Machine learning application for functional site prediction in proteins,” Srinivas Somarowthu and Mary Jo Ondrechen, Bioinformatics 28(15), 2078-2079 (2012). http://bioinformatics.oxfordjournals.org/content/28/15/2078.long
“Pharmacological Validation of Trypanosoma brucei Phosphodiesterases B1 and B2 as Druggable Targets for African Sleeping Sickness,” Nicholas D. Bland, Cuihua Wang, Craig Tallman, Alden E. Gustafson, Zhouxi Wang, Trent D. Ashton, Stefan Ochiana, Gregory McAllister, Kristina Cotter, Anna P. Fang, Lara Gechijian, Norman Garceau, Rajiv Gangurde, Ron Ortenberg, Mary Jo Ondrechen, Robert K. Campbell, and Michael P. Pollastri, J. Medicinal Chemistry, 54(23) 8188-8194 (2011). PMID:22023548 (Contact us for a pdf version) http://pubs.acs.org/doi/abs/10.1021/jm201148s
“A Tale of Two Isomerases: Compact versus Extended Active Sites in Ketosteroid Isomerase and Phosphoglucose Isomerase,” Srinivas Somarowthu, Heather R. Brodkin, J. Alejandro D’Aquino, Dagmar Ringe, Mary Jo Ondrechen*, and Penny J. Beuning*, Biochemistry 50(43) 9283-9295 (2011). (Contact us for a pdf version)
“High Performance Prediction of Functional Residues in Proteins with Machine Learning and Computed Input Features,” S. Somarowthu, H. Yang, D.G.C. Hildebrand, and M.J. Ondrechen, Biopolymers 95(6), 390-400 (2011). (Contact us for a pdf version) http://onlinelibrary.wiley.com/doi/10.1002/bip.21589/full
“Electrostatic Properties for Protein Functional Site Prediction,” J.S. Lee and M.J.Ondrechen, in Protein Function Prediction for Omics Era, D. Kihara, Ed., Springer, Dordrecht, pp. 183-196 (2011). (Contact us for a pdf version)
“Crystal structure of a metal-dependent phosphoesterase (YP_910028.1) from Bifidobacterium adolescentis: Computational prediction and experimental validation of phosphoesterase activity,” G.W. Han, J. Ko, C.L. Farr, M.C. Deller, Q. Xu, H.-J. Chiu, M.D. Miller, J. Sefcikova, S. Somarowthu, P.J. Beuning, M.-A.´ Elsliger, A.M. Deacon, A. Godzik, S.A. Lesley, I.A. Wilson,* and M.J. Ondrechen*, Proteins 79(7), 2146-2160 (2011). (Contact us for a pdf version) http://dx.doi.org/10.1002/prot.23035
“Evidence of the Participation of Remote Residues in the Catalytic Activity of Co-Type Nitrile Hydratase from Pseudomonas putida,” Heather R. Brodkin, Walter R. P. Novak, Amy C. Milne, J. Alejandro D’Aquino, N. M. Karabacak, Ilana G. Goldberg, Jeffrey N. Agar, Mark S. Payne, Gregory A. Petsko, Mary Jo Ondrechen, Dagmar Ringe, Biochemistry 50(22), 4923-4935 (2011). (Contact us for a pdf version) http://pubs.acs.org/doi/abs/10.1021/bi101761e
“Functional Classification of Protein 3D Structures from Predicted Local Interaction Sites,” R. Parasuram, J.S. Lee, P. Yin, S. Somarowthu, M.J. Ondrechen, Journal of Bioinformatics and Computational Biology, 8, 1-15 (2010).
“High Conservation of Amino Acids with Anomalous Protonation Behavior,” D.G.C. Hildebrand, H. Yang, M.J. Ondrechen, and R.J. Williams, Current Bioinformatics, 5(2), 134-140 (2010). Please contact us for a pdf reprint.
“Partial Order Optimum Likelihood (POOL): Maximum Likelihood Prediction of Active Site Residues Using 3D Structure and Sequence Properties,” W. Tong, Y. Wei, L.F. Murga, M.J. Ondrechen, and R.J. Williams, PLoS Computational Biology, 5(1): e1000266 (2009)
“Prediction of Interaction Sites from Apo 3D Structures When the Holo Conformation is Different,” L.F. Murga, M.J. Ondrechen, and D. Ringe, Proteins: Structure Function Bioinformatics 72:3, 980-992 (2008). Please contact us for a pdf reprint
“Selective Prediction of Interaction Sites in Protein Structures with THEMATICS,” Y. Wei, J. Ko, L.F. Murga, and M.J. Ondrechen, BMC Bioinformatics 8:119, (2007)
“Identification of Functional Subclasses in the DJ-1 Superfamily Proteins,” Y. Wei, D. Ringe, M.A. Wilson, and M.J. Ondrechen, PloS Computational Biology 3, e10, 120-126 (2007)
“Statistical Criteria for Protein Active Site Prediction with THEMATICS,” J. Ko, L.F. Murga, P. Andre, H. Yang, M.J. Ondrechen, R.J. Williams, A. Agunwamba, and D.E. Budil, Proteins: Structure Function Bioinformatics 59, 183-195 (2005)
“THEMATICS: A Simple Computational Predictor of Enzyme Function from Structure,” M.J. Ondrechen, J.G. Clifton & D. Ringe, Proc. Nat. Acad. Sci. USA 98, 12473-12478 (2001)
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