Towards a better understanding of the specificity of protein-protein interaction
Jazyk angličtina Země Anglie, Velká Británie Médium print
Typ dokumentu časopisecké články, práce podpořená grantem
PubMed
23108620
DOI
10.1002/jmr.2219
Knihovny.cz E-zdroje
- MeSH
- aminokyseliny chemie MeSH
- databáze proteinů MeSH
- houby chemie MeSH
- interakční proteinové domény a motivy MeSH
- kinetika MeSH
- krystalografie rentgenová MeSH
- lidé MeSH
- mapování interakce mezi proteiny * MeSH
- prokaryotické buňky chemie MeSH
- proteiny chemie MeSH
- rostliny chemie MeSH
- sekundární struktura proteinů MeSH
- statická elektřina MeSH
- termodynamika MeSH
- vazba proteinů MeSH
- vazebná místa MeSH
- viry chemie MeSH
- zvířata MeSH
- Check Tag
- lidé MeSH
- zvířata MeSH
- Publikační typ
- časopisecké články MeSH
- práce podpořená grantem MeSH
- Názvy látek
- aminokyseliny MeSH
- proteiny MeSH
In order to predict interaction interface for proteins, it is crucial to identify their characteristic features controlling the interaction process. We present analysis of 69 crystal structures of dimer protein complexes that provides a basis for reasonable description of the phenomenon. Interaction interfaces of two proteins at amino acids level were localized and described in terms of their chemical composition, binding preferences, and residue interaction energies utilizing Amber empirical force field. The characteristic properties of the interaction interface were compared against set of corresponding intramolecular binding parameters for amino acids in proteins. It has been found that geometrically distinct clusters of large hydrophobic amino acids (leucine, valine, isoleucine, and phenylalanine) as well as polar tyrosines and charged arginines are signatures of the protein-protein interaction interface. At some extent, we can generalize that protein-protein interaction (seen through interaction between amino acids) is very similar to the intramolecular arrangement of amino acids, although intermolecular pairs have generally lower interaction energies with their neighbors. Interfaces, therefore, possess high degree of complementarity suggesting also high selectivity of the process. The utilization of our results can improve interface prediction algorithms and improve our understanding of protein-protein recognition.
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