Kingshuk Ghosh

  • About us

    • Kingshuk Ghosh

      Associate Professor

      Department of Physics and Astronomy, Molecular and Cellular Biophyics, University of Denver, CO

      We are interested in applying theoretical and computational methods to understand complexity in biology. Some of the current research projects are listed below.

  • Research Interest

    • 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 (MaxCal), a dynamical analog of Maximum Entropy method in equilibrium statistical mechanics. In collaboration with Prof Ken Dill at the Stony Brook University, Prof Rob Phillips at Caltech, and Prof Steve Presse at IUPUI we have tested this principle in colloidal, single molecule systems.

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

      Fluctuations in genetic and signaling networks: We are extending application of MaxCal in modeling several biological problems as well. One of the areas of prime interest for us is modeling fluctuations in natural and synthetic genetic networks. Simple examples are biological switches, clocks, timers that dictate biology. MaxCal formalism allows us to quantify noise in such complex systems that lead to bistability, oscillation and cooperativity. The movie below shows stochastic expression of an antibiotic resistance gene using MaxCal model. The system behaves likes a stochastic genetic switch where noise helps flip the switch. This work is ongoing in collaboration with Prof Balazsi at Stony Brook University.

      We are also interested in investigating the role of noise in signaling networks where different molecules compete with each other to propagate signal.

      Reference:  Competition enhances stochasticity in biochemical networks, T. Firman, and K. Ghosh J. Chem. Phys 139: 121915 (2013)

    • Proteome modeling: We are 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. The ultimate goal is to build transferrable proteome level models to better understand cellular level behavior and evolutionary principles. 

      References:

      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).

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

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

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

      Protein stability:  We are interested in understanding enhanced thermal tolerance in thermophilic proteins. These are a class of proteins typically 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. 

      References:

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

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

      The video below obtained using molecular dynamics simulation demonstrates that thermophilic protein (in red) is more resilient to unfolding than mesophilic protein (in blue) at high temperature.

       

       

      Statistical mechanics of proteins and biopolymers: Besides projects mentioned above, we are in general interested in many interesting problems in protein kinetics, protein aggregation, ensembles of intrinsically disordered proteins using principles of protein science and polymer physics.

      References:

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

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

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

    • Biophysics of disease causing proteins: In collaboration with our colleagues in Biology (Prof David Patterson) we are interested in understanding 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.

      New opportunities in the biosynthesis of renewable energy carriers: We are also exploring the possibility of using thermophilic bacteria as a means to new opportunities in the biosynthesis of renewable energy carriers such as bio-hydrogen and lipid biodiesel at elevated temperatures. We are collaborating with Prof Sean Shaheen at the University of Colorado, Boulder on this project.

  • Awards and Honors

This portfolio last updated: May 9, 2015 10:11:05 AM