Predictive quantum simulations for the atomistic understanding of oncogenic GTPase mutantions, DNA polymerase function and nucleoside analogue drug side effects
témavezető: Nagy Péter
helyszín (magyar oldal): BME Fizikai Kémia és Anyagtudományi Tanszék helyszín rövidítés: BME
A kutatási téma leírása:
Computational enzyme catalysis is at the interface of structural biology, electronic structure theory and enhanced sampling approaches. We will exploit the reduced-cost and local DFT, multilevel quantum embedding and CCSD(T) methods developed in our group to guide free energy simulations at the QM/MM level with sufficient predictive power for the exploration of reaction mechanisms. [1,2]
We will model biomolecular processes, in particular, enzyme reactions of key biomedically important systems which are not accessible at the atomic scale via experiments, thus having unknown mechanisms and require the higher accuracy of our state-of-the-art methods due to their complexity:
1) We will calculate the free energy profiles of oncogenic Ras GTPase mutants and study the molecular origin of catalytic impairment occurring in about a third of cancerous cells lines [3].
2) We will discern the nucleotide selectivity and incorporation into the mitochondrial DNA catalysed by DNA polymerase γ.
3) We will study the origin of unwanted polymerase inhibition by nucleoside analogue drugs (often prescribed to treat viral infections), resulting in side effects.
Successful candidates will learn and employ biomolecular simulations, especially cutting-edge QM and MM methods, as well as free energy simulation schemes like Free Energy Perturbation and enhanced sampling methods (e.g., the finite temperature string method).
These computational studies are carried out as part of competitive research grants (such as our ERC Starting grant) using our (MRCC [4]) and other quantum chemistry and molecular dynamics program suites, in collaboration with the MRCC developer team and international research groups.
Requirements: introductory skills/experience in theoretical/computational chemistry or biology. Participation in additional PhD talent support or scholarship programs is encouraged and supported.
[1] Journal of Chemical Theory and Computation 15, 5275 (2019) & 17, 860 (2021)
[2] Nature Communications 12, 3927 (2021), J. Am. Chem. Soc. 139, 17052 (2017)
[3] Journal of the American Chemical Society 145, 20302 (2023)
[4] Journal of Chemical Physics 152, 074107 (2020), http://www.mrcc.hu
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