Luiz Pedro Carvalho & Edina Rosta


Computational and experimental dissection of divergently evolved enzymes

Joint Crick/King's College London position

Functional diversification of enzymes by divergent evolution is essential for the development of complex life [1]. This project intends to explore a selected number of enzymes, which despite sharing a common ancestor, likely have distinct enzymatic activities. This divergence in function might encompass the use of different substrates and/or new catalysed reactions. Therefore, these related enzymes might belong to the same biochemical pathways as the common ancestor or might have diverse function unrelated to the original pathway to which the ancestor enzyme belong. The enzymes under investigation will be derived from the human pathogen Mycobacterium tuberculosis. These will be produced recombinatly in  E. coli.      

This project is a genuine collaboration between the Rosta group (KCL) and the Carvalho laboratory (TFCI). The successful student will employ a range of computational methods such as mixed quantum/classical molecular dynamics calculations and Markov-based analysis methods to investigate substrate specificity and reaction mechanisms derived from enzymes that diverged from a common ancestor. These computational methods are developed [2] and have well established applications [3] in the Rosta lab at KCL. Hypothesis generated by the computational work will then be tested experiementally by recombinant expression and purification of target enzymes, mutagenesis, activity-based metabolomic profiling, mechanistic enzymology (steady-state and pre-steady-state kinetics, pH studies, kinetic isotope effects, etc) and structural biology. The Carvalho lab is well resourced and has successfully overexpressed, purified and characterised a number of mycobacterial enzymes over the last 6 years [4,5].

The ideal candidate should have a background in chemistry or biochemistry and a sincere interest in carrying out extensive computational and experimental work on enzymes, to understand their substrate specificity and chemical mechanisms.

1. Galperin, M. Y. and Koonin, E. V. (2012)
Divergence and convergence in enzyme evolution.
Journal of Biological Chemistry 287: 21-28. PubMed abstract

2. Rosta, E. and Hummer, G. (2015)
Free energies from dynamic weighted histogram analysis using unbiased Markov state model.
Journal of Chemical Theory and Computation 11: 276-285. PubMed abstract

3. Nagy, G. N., Suardíaz, R., Lopata, A., Ozohanics, O., Vékey, K., Brooks, B. R., Leveles, I., Tóth, J., Vértessy, B. G. and Rosta, E. (2016)
Structural characterization of arginine fingers: Identification of an arginine finger for the pyrophosphatase dUTPases.
Journal of the American Chemical Society 138: 15035-15045. PubMed abstract

4. Larrouy-Maumus, G., Biswas, T., Hunt, D. M., Kelly, G., Tsodikov, O. V. and de Carvalho, L. P. S. (2013)
Discovery of a glycerol 3-phosphate phosphatase reveals glycerophospholipid polar head recycling in Mycobacterium tuberculosis.
Proceedings of the National Academy of Sciences of the United States of America 110: 11320-11325. PubMed abstract

5. Prosser, G. A., Larrouy-Maumus, G. and de Carvalho, L. P. S. (2014)
Metabolomic strategies for the identification of new enzyme functions and metabolic pathways.
EMBO Reports 15: 657-669. PubMed abstract