Biomedical subjects

Dmitry Korkin

Publications and source records attributed to Dmitry Korkin.

4 recordsLinked to original sources

PubMed2006

Structural modeling of protein interactions by analogy: application to PSD-95.

We describe comparative patch analysis for modeling the structures of multidomain proteins and protein complexes, and apply it to the PSD-95 protein. Comparative patch analysis is a hybrid of comparative modeling based on a template complex and protein docking, with a greater applicability than comparative modeling and a higher accuracy than docking. It relies on structurally defined interactions of each of the complex components, or their homologs, with any other protein, irrespective of its fold. For each component, its known binding modes with other proteins of any fold are collected and expanded by the known binding modes of its homologs. These modes are then used to restrain conventional molecular docking, resulting in a set of binary domain complexes that are subsequently ranked by geometric complementarity and a statistical potential. The method is evaluated by predicting 20 binary complexes of known structure. It is able to correctly identify the binding mode in 70% of the benchmark complexes compared with 30% for protein docking. We applied comparative patch analysis to model the complex of the third PSD-95, DLG, and ZO-1 (PDZ) domain and the SH3-GK domains in the PSD-95 protein, whose structure is unknown. In the first predicted configuration of the domains, PDZ interacts with SH3, leaving both the GMP-binding site of guanylate kinase (GK) and the C-terminus binding cleft of PDZ accessible, while in the second configuration PDZ interacts with GK, burying both binding sites. We suggest that the two alternate configurations correspond to the different functional forms of PSD-95 and provide a possible structural description for the experimentally observed cooperative folding transitions in PSD-95 and its homologs. More generally, we expect that comparative patch analysis will provide useful spatial restraints for the structural characterization of an increasing number of binary and higher-order protein complexes.

Amino Acid Sequence↗

PubMed2005

Localization of protein-binding sites within families of proteins.

We address the question of whether or not the positions of protein-binding sites on homologous protein structures are conserved irrespective of the identities of their binding partners. First, for each domain family in the Structural Classification of Proteins (SCOP), protein-binding sites are extracted from our comprehensive database of structurally defined binary domain interactions (PIBASE). Second, the binding sites within each family are superposed using a structural alignment of its members. Finally, the degree of localization of binding sites within each family is quantified by comparing it with localization expected by chance. We found that 72% of the 1847 SCOP domain families in PIBASE have binding sites with localization values greater than expected by chance. Moreover, 554 (30%) of these families have localizations that are statistically significant (i.e., more than four standard deviations away from the mean expected by chance). In contrast, only 144 (8%) families have significantly low localization. The absence of a significant correlation of the binding site localization with the average sequence and structural conservations in a family suggests that localization can be helpful for describing the functional diversity of protein-protein interactions, complementing measures of sequence and structural conservation. Consideration of the binding site localization may also result in spatial restraints for the modeling of protein assembly structures.

Acyl-CoA Dehydrogenase↗

PubMed2004

A structural perspective on protein-protein interactions.

Structures of macromolecular complexes are necessary for a mechanistic description of biochemical and cellular processes. They can be solved by experimental methods, such as X-ray crystallography, NMR spectroscopy and electron microscopy, as well as by computational protein structure prediction, docking and bioinformatics. Recent advances and applications of these methods emphasize the need for hybrid approaches that combine a variety of data to achieve better efficiency, accuracy, resolution and completeness.

Animals↗

PubMed2002

Multiple genome rearrangement: a general approach via the evolutionary genome graph.

MOTIVATION: In spite of a well-known fact that genome rearrangements are supposed to be viewed in the light of the evolutionary relationships within and between the species involved, no formal underlying framework based on the evolutionary considerations for treating the questions arising in the area has been proposed. If such an underlying framework is provided, all the basic questions in the area can be posed in a biologically more appropriate and useful form: e.g., the similarity between two genomes can then be computed via the nearest ancestor, rather than 'directly', ignoring the evolutionary connections. RESULTS: We outline an evolution-based general framework for answering questions related to the multiple genome rearrangement. In the proposed model, the evolutionary genome graph (EG-graph) encapsulates an evolutionary history of a genome family. For a set of all EG-graphs, we introduce a family of similarity measures, each defined via a fixed set of genome transformations. Given a set of genomes and restricting ourselves to the transpositions, an algorithm for constructing an EG-graph is presented. We also present the experimental results in the form of an EG-graph for a set of concrete genomes (for several species). This EG-graph turns out to be very close to the corresponding known phylogenetic tree.

Algorithms↗