Biochemistry & Biophysics | Structural & Computational Biology
Computational Biophysics of Macromolecules
The function of biomolecules arises from the interplay between their structure, dynamics and interactions with the environment. We explore this principle through the use of computational and theoretical methods, such as molecular dynamics (MD) simulations, in close collaboration with experimentalists. Specifically, we are interested in...more
The function of biomolecules arises from the interplay between their structure, dynamics and interactions with the environment. We explore this principle through the use of computational and theoretical methods, such as molecular dynamics (MD) simulations, in close collaboration with experimentalists. Specifically, we are interested in the role of dynamics and conformational entropy in non-covalent protein interactions. Frequently, a change in conformational entropy of binding partners may be enough to alter their functional state without any associated rearrangement of their average structures. We develop new methods for calculating conformational entropy of biomolecules from computer simulations and for measuring it experimentally. In addition to function, dynamics also affects the very process of biomolecular structure determination. Namely, biomolecular structures are typically static models derived from X-ray or NMR experiments performed on many dynamic copies of the same molecule. We use MD simulations to help interpret such time- and ensemble-averaged experiments and analyze the impact of conformational averaging on the derived structures.
Second, all biomolecular processes occur in crowded, dynamic, constantly changing environments. We study how crowding affects protein-protein interactions and other basic processes such as protein folding or post-translational modifications of proteins. In particular, we are interested in studying how binding partners find each other in the crowded cell and employ MD and Brownian dynamics simulations and structural bioinformatics methods to address this question.
Finally, we have recently discovered a remarkably robust correspondence between the nucleobase content of mRNAs and the propensity of their cognate protein sequences to interact with nucleobases. We believe this supports and extends the stereo-chemical hypothesis concerning the origin of the genetic code and suggests that cognate mRNAs and proteins may be physico-chemically complementary to each other and bind, especially if unstructured. We use different methods of computational biophysics including MD simulations, structural bioinformatics techniques, free energy calculations and in vitro experiments to further explore this hypothesis.
Polyansky AA & Zagrovic B (2013). Evidence of direct complementary interactions between messenger RNAs and their cognate proteins. NUCLEIC ACIDS RES;41(18):8434-8443. PMID: 23868089
Polyansky AA, Hlevnjak M & Zagrovic B. (2013). Analogue encoding of physiochemical properties of proteins in their cognate messenger RNAs. NAT COMMUN(4):2784. PMID: 24253588
Petrov D, Margreitter C, Grandits M, Oostenbrink C, Zagrovic B (2013). A systematic framework for molecular dynamics simulations of protein post-translational modifications PLOS COMPUT BIOL;9(7):e1003154. PMID: 23874192
ERC Starting Grant 2011
Awardee of a "Starting Independent Researcher Grant" from the European Research Council ERC
START Prize 2010, Austrian Science Fund (FWF)
Project title: "Specific and global aspects of protein interactions"