RNA Structure Prediction

nderstanding the function of biomolecules requires knowledge of their structures. Some of these structures are experimentally difficult to measure. An intriguing alternative is applying maximum-entropy based methods from theoretical physics to analyze the abundantly available sequential information for biomolecules. We can accurately predict spatial contacts within biomolecules (1), which then guides their structure prediction (1-4). This provides reliable predictions with resolutions comparable with experimental measurements.
In this thesis, we want to improve the present statistical methods for detect-ing spatial contacts (4) towards higher accuracy and improve the quality of structure prediction methods for RNA. Then, we want to apply these im-proved structure prediction methods on a large scale for all biomolecules with sufficient sequential information. As a biomolecule’s conformation is inherently linked to its function, this insight goes far beyond basic research: Given the importance of such interactions for diseases, we also expect significant impact on pharmacological and medical research and applica-tions.

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1.) Weigt, M., White, R. A., Szurmant, H., Hoch, J. A. & Hwa, T. Identification of direct residue contacts in protein-protein interaction by message passing. Proc Natl Acad Sci U S A 106, 67-72, doi:10.1073/pnas.0805923106 (2009).
2.) Dago, A. E. et al. Structural basis of histidine kinase autophosphorylation deduced by integrating genomics, molecular dynamics, and mutagenesis. Proc. Natl. Acad. Sci. U. S. A. 109, E1733-1742, doi:10.1073/pnas.1201301109 (2012).
3.) Schug, A., Weigt, M., Onuchic, J. N., Hwa, T. & Szurmant, H. High-resolution protein complexes from integrating genomic information with molecular simulation. Proc. Natl. Acad. Sci. U. S. A. 106, 22124-22129, doi:10.1073/pnas.0912100106 (2009).
4.) De Leonardis, E. et al. Direct-Coupling Analysis of nucleotide coevolution facilitates RNA secondary and tertiary structure prediction. Nucleic Acids Res, doi:10.1093/nar/gkv932 (2015).

Weitere Informationen

Unternehmen

Helmholtz Gemeinschaft

Bereich/Abteilung

Steinbuch Centre for Computing (SCC)

Abschlussart

Dissertation

Ansprechpartner/in

Name: Herr Dr. Alexander Schug

Branche

Forschung und Entwicklung

Anforderungen

We expect motivated individuals who have a diploma or master in physics or related fields and are interested in an interdisciplinary topic in the field of computational simulation and modeling. The successful candidate should have profound knowledge in statistical physics/ thermodynamics, good programming knowledge and interest in molecular biology.

Zusatzinformationen

Karlsruher Institut für Technologie

Vertragsdauer: befristet up to 3 years
Eintrittstermin: ASAP
Bewerbung bis: 23.12.2015
Stellenausschreibung Nr. 25-2015/SCC

Bei entsprechender Eignung werden schwerbehinderte Bewerber/innen bevorzugt berücksichtigt.