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Anders Bergkvist,
Department of Molecular Biology. Project background: Göbel et al developed an algorithm to mine sequence alignments for covariations between positions in the alignments in 1994. Subsequently Pazos et al developed an application of Göbel's algorithm to predict neighbouring pairs of amino acids in the interface between two interacting proteins. Inspired by these advances Dr Bergkvist started to design an alternative algorithm to satisfy the purpose of Göbel et al and Pazos et al. In contrast to the previous papers this algorithm is based on a statistical analysis of relevant biophysical properties of the amino acids in the sequence alignments. The result shows good promise. However, since the statistical analysis assumes no general previous interdependences of the protein sequences - evolutionary relationships between the sequences may give rise to artefacts in the analysis. Specific plan and suitable previous knowledge: The aim of the project is to continue to develop the algorithm by Dr Bergkvist. A compensation factor is necessary to take into account evolutionary relationships between the protein sequences and alleviate corresponding artefacts in the results. This compensation factor should be incorporated into the code. The algorithm has been developed in Java so far, but a transfer to C may be advantageous. In any case, the more advanced statistical analysis probably needs to be developed in C. Besides familiarity with these programming languages, experiences with any of the following may be advantageous: protein sequence alignment algorithms, phylogenetic relationships, DNA replication and repair, incorporation of genetic mutations, and evolution. References: Göbel et al., Proteins: Structure, Function and Genetics 18 (1994), 309-317 Pazos et al., Journal of Molecular Biology 271 (1997), 511-523 Keywords: Bioinformatics, Computer programming, Protein
sequence alignments, Evolution, Phylogenetic relationships, Covariances,
C, C++, Java, Statistics. ===================================================================
Analysis of the correlation of NMR chemical shifts to protein dihedral
angles Project background: It is well-known in the field of NMR (nuclear
magnetic resonance), since quite some time ago, that chemical shift
is related to the electromagnetic environment of the measured nucleus.
For example is the chemical shift of a nucleus in a protein molecule
affected by the relative positions of electronic orbitals of neighbouring
atoms. This fact has been used to qualitatively determine the secondary
structure type of small peptide chains in proteins with unknown molecular
structure (see for example Wishart et al and Cornilescu et al). A more
recent publication (Wang and Jardetsky) reports an extension of previous
studies by presenting a quantification of the correlation using a statistical
approach. Finding an accurate quantification of the correlation between
the chemical shift and structure geometries have important implications
for protein structure determination, and have a potential to extend
current capabilities of NMR into analysis of protein folding and protein
interactions. Specific plan and suitable previous knowledge: The student
will analyze a database of chemical shifts and relate the chemical shifts
to corresponding protein structures in other databases. The aim is to
make a statistical quantification (analogously to Wang and Jardetsky)
of the relationship between chemical shifts and associated peptide dihedral
torsion angles. Using dihedral torsion angles rather than classifications
of secondary structure elements is believed to improve the correlations
(and thus structure predictions based on the chemical shift) significantly.
Data may be collected from the databases by writing program scripts
in for example Perl (or any other suitable programming language). Subsequent
statistical analysis is probably best developed in C. Besides familiarity
with these programming languages, experiences with any of the following
may be advantageous: protein structures, NMR, database programming,
and statistics. References: Wishart, Sykes and Richards, Biochemistry
31, 1647-1651 (1992) Cornilescu, Delaglio and Bax, J. Biomol. NMR 13,
289-302 (1999) Wang and Jardetsky, Protein Science 11, 852-861 (2002)
Keywords: NMR chemical shifts, Protein secondary structure, Dihedral
torsion angles, Statistics, Database, Computer programming, C, Perl.
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Molecular docking program and molecular structure visualisation on
the web References: Berman, Goodsell and Bourne, American Scientist 90 (4), 350 - 359 (2002) Halperin et al, Proteins 47, 409-443 (2002) Keywords: Molecular docking, protein structure, web design,
computer graphics, php, mysql, rational drug design. ===================================================================
Cloning and expression of the DNA repair and cell-cycle associated
protein Mus81 References: Haber and Heyer, Cell 107 (2001), 551-554 Ho et al., Nature 415 (2002), 180-183 Nishino et al, Structure 11 (2003), 445-457 Keywords: Protein interaction, NMR, gene cloning, protein purification, DNA metabolism, biochemistry. =================================================================== |