Dataset Information

Three-dimensional structure of human protein kinase C interacting protein 1, a member of the HIT family of proteins.

ABSTRACT: The three-dimensional structure of protein kinase C interacting protein 1 (PKCI-1) has been solved to high resolution by x-ray crystallography using single isomorphous replacement with anomalous scattering. The gene encoding human PKCI-1 was cloned from a cDNA library by using a partial sequence obtained from interactions identified in the yeast two-hybrid system between PKCI-1 and the regulatory domain of protein kinase C-beta. The PKCI-1 protein was expressed in Pichia pastoris as a dimer of two 13.7-kDa polypeptides. PKCI-1 is a member of the HIT family of proteins, shown by sequence identity to be conserved in a broad range of organisms including mycoplasma, plants, and humans. Despite the ubiquity of this protein sequence in nature, no distinct function has been shown for the protein product in vitro or in vivo. The PKCI-1 protomer has an alpha+beta meander fold containing a five-stranded antiparallel sheet and two helices. Two protomers come together to form a 10-stranded antiparallel sheet with extensive contacts between a helix and carboxy terminal amino acids of a protomer with the corresponding amino acids in the other protomer. PKCI-1 has been shown to interact specifically with zinc. The three-dimensional structure has been solved in the presence and absence of zinc and in two crystal forms. The structure of human PKCI-1 provides a model of this family of proteins which suggests a stable fold conserved throughout nature.

SUBMITTER: Lima CD

PROVIDER: S-EPMC39250 | biostudies-other | 1996 May

REPOSITORIES: biostudies-other

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Three-dimensional structure of human protein kinase C interacting protein 1, a member of the HIT family of proteins.

Lima C D CD Klein M G MG Weinstein I B IB Hendrickson W A WA

Proceedings of the National Academy of Sciences of the United States of America 19960501 11

The three-dimensional structure of protein kinase C interacting protein 1 (PKCI-1) has been solved to high resolution by x-ray crystallography using single isomorphous replacement with anomalous scattering. The gene encoding human PKCI-1 was cloned from a cDNA library by using a partial sequence obtained from interactions identified in the yeast two-hybrid system between PKCI-1 and the regulatory domain of protein kinase C-beta. The PKCI-1 protein was expressed in Pichia pastoris as a dimer of t ...[more]

PMID: 8643579

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Project description:Protein-protein interactions are key to many biological processes. Computational methodologies devised to predict protein-protein interaction (PPI) sites on protein surfaces are important tools in providing insights into the biological functions of proteins and in developing therapeutics targeting the protein-protein interaction sites. One of the general features of PPI sites is that the core regions from the two interacting protein surfaces are complementary to each other, similar to the interior of proteins in packing density and in the physicochemical nature of the amino acid composition. In this work, we simulated the physicochemical complementarities by constructing three-dimensional probability density maps of non-covalent interacting atoms on the protein surfaces. The interacting probabilities were derived from the interior of known structures. Machine learning algorithms were applied to learn the characteristic patterns of the probability density maps specific to the PPI sites. The trained predictors for PPI sites were cross-validated with the training cases (consisting of 432 proteins) and were tested on an independent dataset (consisting of 142 proteins). The residue-based Matthews correlation coefficient for the independent test set was 0.423; the accuracy, precision, sensitivity, specificity were 0.753, 0.519, 0.677, and 0.779 respectively. The benchmark results indicate that the optimized machine learning models are among the best predictors in identifying PPI sites on protein surfaces. In particular, the PPI site prediction accuracy increases with increasing size of the PPI site and with increasing hydrophobicity in amino acid composition of the PPI interface; the core interface regions are more likely to be recognized with high prediction confidence. The results indicate that the physicochemical complementarity patterns on protein surfaces are important determinants in PPIs, and a substantial portion of the PPI sites can be predicted correctly with the physicochemical complementarity features based on the non-covalent interaction data derived from protein interiors.

Dataset Information

Three-dimensional structure of human protein kinase C interacting protein 1, a member of the HIT family of proteins.

Publications

Three-dimensional structure of human protein kinase C interacting protein 1, a member of the HIT family of proteins.

Similar Datasets

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