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Dehydron: a structurally encoded signal for protein interaction.

ABSTRACT: We introduce a quantifiable structural motif, called dehydron, that is shown to be central to protein-protein interactions. A dehydron is a defectively packed backbone hydrogen bond suggesting preformed monomeric structure whose Coulomb energy is highly sensitive to binding-induced water exclusion. Such preformed hydrogen bonds are effectively adhesive, since water removal from their vicinity contributes to their stability. At the structural level, a significant correlation is established between dehydrons and sites for protein complexation, with the HIV-1 capsid protein P24 complexed with antibody light-chain FAB25.3 providing the most dramatic correlation. Furthermore, the number of dehydrons in homologous similar-fold proteins from different species is shown to be a signature of proteomic complexity. The techniques are then applied to higher levels of organization: The formation of the capsid and its organization in picornaviruses correlates strongly with the distribution of dehydrons on the rim of the virus unit. Furthermore, antibody contacts and crystal contacts may be assigned to dehydrons still prevalent after the capsid has been assembled. The implications of the dehydron as an encoded signal in proteomics, bioinformatics, and inhibitor drug design are emphasized.

SUBMITTER: Fernandez A

PROVIDER: S-EPMC1303363 | biostudies-literature | 2003 Sep

REPOSITORIES: biostudies-literature

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Dehydron: a structurally encoded signal for protein interaction.

Fernández Ariel A Scott Ridgway R

Biophysical journal 20030901 3

We introduce a quantifiable structural motif, called dehydron, that is shown to be central to protein-protein interactions. A dehydron is a defectively packed backbone hydrogen bond suggesting preformed monomeric structure whose Coulomb energy is highly sensitive to binding-induced water exclusion. Such preformed hydrogen bonds are effectively adhesive, since water removal from their vicinity contributes to their stability. At the structural level, a significant correlation is established betwee ...[more]

PMID: 12944304

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Project description:BackgroundThe recently emerged protein interaction network paradigm can provide novel and important insights into the innerworkings of a cell. Yet, the heavy burden of both false positive and false negative protein-protein interaction data casts doubt on the broader usefulness of these interaction sets. Approaches focusing on one-protein-at-a-time have been powerfully employed to demonstrate the high degree of conservation of proteins participating in numerous interactions; here, we expand his 'node' focused paradigm to investigate the relative persistence of 'link' based evolutionary signals in a protein interaction network of S. cerevisiae and point out the value of this relatively untapped source of information.ResultsThe trend for highly connected proteins to be preferably conserved in evolution is stable, even in the context of tremendous noise in the underlying protein interactions as well as in the assignment of orthology among five higher eukaryotes. We find that local clustering around interactions correlates with preferred evolutionary conservation of the participating proteins; furthermore the correlation between high local clustering and evolutionary conservation is accompanied by a stable elevated degree of coexpression of the interacting proteins. We use this conserved interaction data, combined with P. falciparum/Yeast orthologs, as proof-of-principle that high-order network topology can be used comparatively to deduce local network structure in non-model organisms.ConclusionHigh local clustering is a criterion for the reliability of an interaction and coincides with preferred evolutionary conservation and significant coexpression. These strong and stable correlations indicate that evolutionary units go beyond a single protein to include the interactions among them. In particular, the stability of these signals in the face of extreme noise suggests that empirical protein interaction data can be integrated with orthologous clustering around these protein interactions to reliably infer local network structures in non-model organisms.

Dataset Information

Dehydron: a structurally encoded signal for protein interaction.

Publications

Dehydron: a structurally encoded signal for protein interaction.

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