Kingshuk Ghosh

  • Biographical Description

    • Kingshuk Ghosh

      Associate Professor                                                                                         Department of Physics and  Astronomy, 2112 E Wesley Avenue,     University of Denver, Denver CO 80208                                  

  • Research Interest

    • I am interested in applying theoretical and computational methods to model fundamental problems in biology. Some of the specific research projects are listed below.

      Protein stability:  We are interested in understanding enhanced thermal tolerance in thermophilic proteins. These are a class of proteins generally extracted from thermophilic organisms that denature at significantly higher temperatures compared to mesophilic proteins extracted from organisms that live at room temperature. We are combining different theoretical approaches to probe multiple scales to better understand how evolution played its tricks to achieve such unusal thermal tolerance at a large scale.

      Proteome modeling: We have been recently interested in understanding many statistical properties to carry out large scale modeling of the entire proteome, the collection of all the proteins inside an organism. This is in contrary to the usual approach in protein science where majority of studies focus on one single, specific or a class of proteins.

      Proteins in diseases: In collaboration with our experimental colleagues in Biology, Chemistry and Physics, we are carrying out biophysical studies of disease causing proteins. One such protein is the enzyme ADSL, responsible for a disease called ADSL deficiency syndrome sharing similar phenotypic features as autism. We are probing stability, structure, function relation of different disease causing mutatnts of the enzyme ADSL. Our approach uses a combination of experimental and modeling techniques in collaboration with Prof David Patterson, Prof Scott Pegan and Prof Sean Shaheen. We believe these fundamental studies will help us detect different mechanisms that underlie different levels of severity in patients.

      Statistical mechanics of proteins and biopolymers: Besides projects mentioned above, we are in general interested in many interesting problems in protein kinetics, protein aggregation using principles of protein science and polymer physics. Some of the interesting questions are: Why proteins fold in a cooperative manner ? What governs folding speed and what is the ultimate speed limit ? How well can a homopolymer model describe protein ? 

      Formulating non-equilibrium statistical mechanics: Biology has a small number problem. Furthermore, life is out of equilibrium. This has prompted us to better understand fluctuations and noise in non-equilibrium biological problems. We are developing a new formalism called Maximum Caliber, a dynamical analog of Maximum Entropy method in equilibrium statistical mechanics. In collaboration with Prof Rob Phillips at Caltech, we have tested this principle in colloidal and single molecule systems. We are currently trying to establish the connection between this and other methods in Non equilibrium statistical mechanics and extend the formalism to derive several novel relations in statistical physics. This and the work below are in collaboration with Prof Ken Dill at the Stony Brook University.

      Synthetic biology: We are extending application of Maximum Caliber in modeling several biological problems as well. One of the areas of prime interest for us is modeling genetic networks. Simple examples are biological switches, clocks, timers that dictate biology. Maximum Caliber formalism allows us to quantify noise in such complex systems that lead to bistability, oscillation and cooperativity. We are actively collaborating with our experimental colleagues across the country to model natural and synthetic circuits. Our goal is to not only analyze data but make testable predictions and motivate new circuirts and experiments to advance design principles that will be of interest to synthetic biologists.

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  • Recent Publications

    • 1. Proteome folding kinetics is limited by protein halflife. T. Zou, N. Williams, S.B. Ozkan and K. Ghosh PLOS ONE: DOI: 10.1371/journal.pone.0112701 (2014).

      2. Nonadditive Entropies Yield Probability Distributions with Biases not Warranted by the Data. S Presse, K. Ghosh, J. Lee and K.A. Dill Phys. Rev. Lett. 111: 180604 (2013).

      3. Competition enhances stochasticity in biochemical reactions. T Firman and K. Ghosh J. Chem. Phys. 139: 121915 (2013) (invited contribution).

      4. Principles of maximum entropy and maximum caliber. S. Presse, K. Ghosh, J. Lee and K.A Dill Rev. Mod. Phys. 85: 1115-1141 (2013) (invited contribution).

      5. Inhrent properties of adenylosuccinate lyase could explain S-Ado/SAICAr ratio due to homozygous R426H and R303C mutations S.P. Ray, N. Duval, T.G. Wilkinson II, S.E. Shaheen, K. Ghosh and D. Patterson Biochemica et Biophysica Acta Proteins and Proteomics 1834: 1510 (2013).

      6. Why and how does native topology dictate the folding speed of a protein? M. Rustad and K. Ghosh J. Chem. Phys. 137:205104 (2012).

      7. Structural and Biochemical Characterization of Human Adenylosuccinate Lyase (ADSL) and the R303C ADSL Deficiency-Associated Mutation. S. P. Ray, M. K. Deaton, G. C. Capodagli, L.A.F. Calkins, L. Sawle, K. Ghosh, D. Patterson, and S. D. Pegan Biochemistry 51: 6731 (2012)

      8. Markov processes follow from the principle of Maximum Caliber. H. Ge, S Presse, K. Ghosh and K. Dill J. Chem. Phys. 136: 064108 (2012).

      9. Evidence of Multiple Folding Pathways for the Villin Headpiece Subdomain. L. Zhu, K. Ghosh, M. King, T. Cellmer, O. Bakajin, L. Lapidus J. Phys. Chem B 115:12632 (2011).

      10. Physical limits of cells and proteomes. K. A. Dill, K. Ghosh, J. Schmit Proc. Natl. Acad. Sci. 108: 17876 (2011).

      11. How do thermophilic proteins and proteomes withstand high temperature ? L. Sawle, K. Ghosh Biophys J 101, 217 (2011).

      12. Stochastic dynamics of complexation reaction in the limit of small numbers. K. Ghosh J. Chem. Phys. 134, 195101 (2011).

      13. Modeling Stochastic Dynamics in Biochemical Systems with Feedback using Maximum Caliber: S. Presse, K. Ghosh, K.A. Dill J Phys Chem B 115, 6202-6212  (2011).

      14. What drives amyloid molecules to assemble into oligomers and fibrils ? J. Schmit, K. Ghosh and K. A. Dill Biophys J 100, 450-458 (2011).

      15. Cellular proteomes have broad distributions of protein stability: K. Ghosh and K.A. Dill Biophys J 99, 3996-4002 (2010).

      16. Dynamical fluctuations in biochemical reactions and cycles: S. Presse, K. Ghosh, R. Phillips and K. A. Dill. Phys Rev E 82, 031905 (2010).

      17. Trajectory approach to two-state kinetics of single particles on sculpted energy landscapes: D. Wu, K. Ghosh, M. Inamdar, H. J. Lee, S. Fraser, K. A. Dill and R. Phillips. Phys. Rev. Lett. 103, 050603 (2009).

      18. Computing protein stabilities from their chain lengths: K. Ghosh and K. A. Dill. Proc. Natl. Acad. Sci. 106(26), 10649-10654 (2009).

      19. Theory for protein folding cooperativity: helix-bundles. K. Ghosh and K. A. Dill, J. Am. Chem. Soc. 131(6), 2306 (2009).

  • Awards

This portfolio last updated: Mar 24, 2015 10:19:19 AM