期刊
PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA
卷 103, 期 26, 页码 9867-9872出版社
NATL ACAD SCIENCES
DOI: 10.1073/pnas.0600220103
关键词
binding energy; cooperativity; protein-protein interaction; surface plasmon resonance; T cell activity
资金
- NIAID NIH HHS [AI 55882, R21 AI055882, AI 064611, R01 AI064611] Funding Source: Medline
- NIGMS NIH HHS [GM 55767, T32 GM007283, R01 GM055767, T32 GM 07283] Funding Source: Medline
Although cellular processes depend on protein-protein interactions, our understanding of molecular recognition between proteins remains far from comprehensive. Protein-protein interfaces are structural and energetic mosaics in which a subset of interfacial residues, called hot spots, contributes disproportionately to the affinity of the complex. These hot-spot residues can be further clustered into hot regions. It has been proposed that binding energetics between residues within a hot region are cooperative, whereas those between hot regions are strictly additive. If this idea held true for all protein-protein interactions, then energetically significant long-range conformational effects would be unlikely to occur. In the present study, we show cooperative binding energetics between distinct hot regions that are separated by > 20 angstrom. Using combinatorial mutagenesis and surface plasmon resonance binding analysis to dissect additivity and cooperativity in a complex formed between a variable domain of a T cell receptor and a bacterial superantigen, we find that combinations of mutations from each of two hot regions exhibited significant cooperative energetics. Their connecting sequence is composed primarily of a single P-strand of the T cell receptor variable Ig domain, which has been observed to undergo a strand-switching event and does not form an integral part of the stabilizing core of this Ig domain. We propose that these cooperative effects are propagated through a dynamic structural network. Cooperativity between hot regions has significant implications for the prediction and inhibition of protein-protein interactions.
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