Greater Philadelphia Professor of Biological Sciences
Publications | Research | Faculty
Background:
David Shalloway is the Greater Philadelphia Professor in the Department of Molecular Biology and Genetics. After receiving his Ph.D. in theoretical physics at the Massachusetts Institute of Technology in 1975, he became a Research Associate in the Newman Laboratory of Nuclear Studies at Cornell developing renormalization group methods in quantum field theory. In 1977 he switched research directions to focus on the molecular basis of oncogene-mediated carcinogenesis. The transition was supported by Postdoctoral Fellowships from the National Institutes of Health and the American Cancer Society at the Dana-Farber Cancer Institute of the Harvard Medical School. From 1982-90, he was on the faculty of the Department of Molecular and Cell Biology at The Pennsylvania State University conducting research on src and other oncogenes and on computer applications in molecular biology. From 1988-89 he was Visiting Professor in the Department of Pharmaceutical Chemistry at the University of California, San Francisco Medical School, developing a new theoretical approach to the protein folding problem. Dr. Shalloway has received an American Cancer Society Junior Faculty Research Award, a National Institutes of Health Research Career Development Award, and has served on a number of National Institutes of Health grant review committees. He has been at Cornell since 1990.
Courses Taught:
BioMG8380 - Scientific Communication in BMCB
BioMG8340 - Quantitative Biology for MBG
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Links:
- QMOL An OpenGL based molecular viewer for Windows 95/NT/00 and X Windows (free software)
- PrestoPlot A 2D plotting tool for Win32 Platforms (free software)
Our research is focused in two areas:
- Role of Protein Tyrosine Phosphatase a in Cancer
- Macrostates in Computational Biology
Role of Protein Tyrosine Phosphatase a in Cancer
The Src proto-oncoprotein is activated in more than half of human breast and colon cancers but, unlike many other oncoproteins, its gene is not mutated. This suggests that aberrant regulation of Src in involved. We and others have shown that Src is regulated by a sophisticated network of phosphorylation and dephosphorylation reactions and that a key activator (responsible for the activation of Src during the cell cycle) is Protein Tyrosine Phosphatase (PTP)α. This suggested the possibility that abnormal activation of PTPα could play a role in Src-dependent cancer. We confirmed this hypothesis by showing that suppressing PTPα expression deactivated Src and induced apoptosis (programmed cell death) in human colon and estrogen-receptor-negative tumor cell lines but not in normal breast-derived cell lines (Zheng et al., 2008). Recently, in collaboration with Prof. Xinmin Zheng, we have found that aberrantly-spliced forms of PTPα are often found in human colon, breast and liver tumor cells and that these activate the normal PTPα and Src proteins in these cells. This indicates that screening for PTPα mutations it will contribute to molecular diagnosis and that PTPα may be an important therapeutic target in these cancer types. We are currently investigating attempting to determine the mechanism that is responsible for the splicing aberrations, so as to provide additional leads for therapeutic approaches.
Proposed model for the activation of wild-type PTPα by a truncated PTPα mutant generated by aberrant splicing in human colon and breast cancer cells. (a) Homodimerization of wild-type PTPα leaves it in an inactive state where binding of the Grb2 protein blocks access of Src to phosphotyrosine 789 and the obligate phosphotyrosine-displacement mechanism. (b) Heterodimerization with mutant PTPα abrogates binding of wild-type PTPα to Grb2 and enhances its ability to activate Src. (from Huang et al., submitted)
Many problems arising in computational molecular biology involve so many degrees-of-freedom that brute-force analysis is impossible. For example, protein dynamics typically involves the motions of > 104 atoms, each having three spatial coordinates, and even the fastest computers are unable to simulate their motions using straightforward approaches (e.g., molecular dynamics) for adequately long times; hierarchical dynamical analysis is needed. The analysis of high-throughput data (e.g., gene expression level analysis using DNA microarrays) provides another example: the raw data is so voluminous as to be unintelligible, and data clustering methods that segregate the results into groups are essential. Coarse-graining is a general approach for addressing such problems in which the original large number of fine-grained degrees-of-freedom are replaced with a much smaller number of coarse-grained effective degrees-of-freedom, much in the same way that the motions of leaves on a tree may be hierarchically described in terms of motions of trunk, branches and twigs. Our computational research focuses on developing methods for identifying the intrinsic, but hidden, hierarchical structures that can best be used to analyze such problems. The unifying idea is to map these problems into the context of stochastic dynamics and to identify the macrostates of the corresponding dynamical system—the subregions that have internal equilibration rates that are fast relative to their rates of external equilibration. We have applied this approach to analyzing protein structure and dynamics and are currently focusing on its application to “fuzzy” data clustering—clustering which provides a measure of the certainty of assignments. 
[from White and Shalloway (2009) Phys. Rev. E. 80:056705]
Research group:
Xin-Min Zheng
Brian White
Recent publications (including theoretical papers not listed in PubMed)
Click here to view Dr. Shalloway's PubMed listings.
Shalloway, D. and A.K. Faradjian (2006) Efficiently computing the first passage time generating function by steady-state relaxation. J. Chem. Phys. 124:054112.
West, M.A., R. Elber, and D. Shalloway (2007) Extending molecular dynamics timescales with milestoning: Example of complex kinetics in a solvated peptide. J. Chem. Phys. 126:145104.
Zheng, X.M, R.J. Resnick and D. Shalloway (2008) Selective apoptosis of estrogen receptor-negative breast and colon cancer cell lines by PTPα and Src RNAi. Intl. J. Cancer., 122:1999-2007.
Herrera Abreu, M.T.H., P.C. Penton, V. Kwok, D. Shalloway, L. Vidali, W. Lee, C.A. McCulloch, and G. P. Downey (2008) Tyrosine phosphatase PTPa regulates focal adhesion remodeling through Rac1 activation. Am. J. Physiol Cell Physiol. 294:C931-944.
Shalloway, D. (2008) Packet annealing. In Encyclopedia of Global Optimization (2nd Edition),
White, B. and D. Shalloway (2009) Efficient uncertainty minimization for fuzzy spectral clustering. Phys. Rev. E. 80:056705.
Zhang, Y.V., White, B.S., Shalloway, D., and T. Tumbar (2010) Stem cell dynamics in mouse hair follicles: a story from cell division counting and single cell lineage tracing, Cell Cycle 9:1504-1510.
Tremper-Wells, B., R.J. Resnick, X.M. Zheng, L.J. Holsinger, and D. Shalloway (2010) Extracellular domain dependence of PTPα transforming activity. Genes Cells 15: 711-724.