Thesis supervisor: András Szilágyi
Location of studies (in Hungarian): Institute of Molecular Life Sciences, HUN-REN Research Centre for Natural Sciences Abbreviation of location of studies: H-REN
Description of the research topic:
"Genome-wide association studies have revealed thousands of gene variants associated with human diseases or influencing drug responses. Mutations arising in the body are particularly important as they can lead to various diseases including cancer. Understanding how mutations resulting in amino acid changes in proteins affect protein function can help us understand the pathogenesis of individual diseases. Mutations can interfere with protein folding, cause conformational changes, can prevent or promote the binding of ligands or other proteins. The effect can manifest itself largely through the conformational dynamics: a mutation can increase or decrease the flexibility of the protein or a portion of it, can shift the conformational equilibrium between states, can trigger an order-disorder transition, can alter the distribution of rigid and flexible regions, or can interfere with the allosteric communication network within the protein, thereby influencing protein function.
Our research project aims to use bioinformatics methods (e.g. modeling and simulation of protein structures) to reveal how mutations affect protein structure and dynamics, and use the results to interpret the role of mutations in diseases. We apply this approach to several protein families. Accurate understanding of the effect of the mutation can help develop therapeutic solutions, e.g. by drug design. Besides mutations, we also study the effect of post-translational modifications (e.g. phosphorylation). The research involves using artificial intelligence based tools, e.g. to predict structures or to predict the pathogenicity of mutations.
The candidate can join this research project. The research involves collecting and processing data on disease-associated protein variants from genomic databases, and the modeling and dynamics simulation of particular proteins. The research is done using bioinformatic techniques, thus some programming knowledge is required."
Required language skills: English Further requirements: Basic programming skills, e.g. Python
Number of students who can be accepted: 1
Deadline for application: 2024-05-31
2024. IV. 17. ODT ülés Az ODT következő ülésére 2024. június 14-én, pénteken 10.00 órakor kerül sor a Semmelweis Egyetem Szenátusi termében (Bp. Üllői út 26. I. emelet).
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