Biomedical subjects

K K Koretke

Publications and source records attributed to K K Koretke.

3 recordsLinked to original sources

PubMed1998

Self-consistently optimized energy functions for protein structure prediction by molecular dynamics.

The protein energy landscape theory is used to obtain optimal energy functions for protein structure prediction via simulated annealing. The analysis here takes advantage of a more complete statistical characterization of the protein energy landscape and thereby improves on previous approximations. This schema partially takes into account correlations in the energy landscape. It also incorporates the relationships between folding dynamics and characteristic energy scales that control the collapse of the proteins and modulate rigidity of short-range interactions. Simulated annealing for the optimal energy functions, which are associative memory hamiltonians using a database of folding patterns, generally leads to quantitatively correct structures. In some cases the algorithm achieves "creativity," i.e., structures result that are better than any homolog in the database.

Artificial Intelligence↗

PubMed1997

Structural basis for thermostability and identification of potential active site residues for adenylate kinases from the archaeal genus Methanococcus.

Sequence comparisons of highly related archaeal adenylate kinases (AKs) from the mesophilic Methanococcus voltae, the moderate thermophile Methanococcus thermolithotrophicus, and two extreme thermophiles Methanococcus igneus and Methanococcus jannaschii, allow identification of interactions responsible for the large variation in temperatures for optimal catalytic activity and thermostabilities observed for these proteins. The tertiary structures of the methanococcal AKs have been predicted by using homology modeling to further investigate the potential role of specific interactions on thermal stability and activity. The alignments for the methanococcal AKs have been generated by using an energy-based sequence-structure threading procedure against high-resolution crystal structures of eukaryotic, eubacterial, and mitochondrial adenylate and uridylate (UK) kinases. From these alignments, full atomic model structures have been produced using the program MODELLER. The final structures allow identification of potential active site interactions and place a polyproline region near the active site, both of which are unique to the archaeal AKs. Based on these model structures, the additional polar residues present in the thermophiles could contribute four additional salt bridges and a higher negative surface charge. Since only one of these possible salt bridges is interior, they do not appear significantly to the thermal stability. Instead, our model structures indicate that a larger and more hydrophobic core, due to a specific increase in aliphatic amino acid content and aliphatic side chain volume, in the thermophilic AKs is responsible for increased thermal stability.

Adenylate Kinase↗

PubMed1996

Self-consistently optimized statistical mechanical energy functions for sequence structure alignment.

A quantitative form of the principle of minimal frustration is used to obtain from a database analysis statistical mechanical energy functions and gap parameters for aligning sequences to three-dimensional structures. The analysis that partially takes into account correlations in the energy landscape improves upon the previous approximations of Goldstein et al. (1994, 1995) (Goldstein R, Luthey-Schulten Z, Wolynes P, 1994, Proceedings of the 27th Hawaii International Conference on System Sciences. Los Alamitos, California: IEEE Computer Society Press. pp 306-315; Goldstein R, Luthey-Schulten Z, Wolynes P, 1995, In: Elber R, ed. New developments in theoretical studies of proteins. Singapore: World Scientific). The energy function allows for ordering of alignments based on the compatibility of a sequence to be in a given structure (i.e., lowest energy) and therefore removes the necessity of using percent identity or similarity as scoring parameters. The alignments produced by the energy function on distant homologues with low percent identity (less than 21%) are generally better than those generated with evolutionary information. The lowest energy alignment generated with the energy function for sequences containing prosite signatures but unknown structures is a structure containing the same prosite signature, providing a check on the robustness of the algorithm. Finally, the energy function can make use of known experimental evidence as constraints within the alignment algorithm to aid in finding the correct structural alignment.

Data Interpretation, Statistical↗