Dissection of Factors Affecting the Variability of the Peptide Bond Geometry and Planarity(71 visite) Balasco N, Esposito L, Thind AS, Guarracino MR, Vitagliano L
Biomed Res Int (ISSN: 2314-6133, 2314-6141), 2017; 2017: 2617629-2617629.
Tipo di articolo: Journal Article,
Impact factor: 2.583, Impact factor a 5 anni: 2.931
Parole chiave: Peptide, Amino Acid, Protein, Alpha Helix, Article, Hybridization, Hydrogen Bond, Protein Binding, Protein Conformation, Protein Expression, Protein Motif, Protein Secondary Structure, Protein Stability, Protein Structure, Chemistry, Protein Folding, Theoretical Model, Hydrogen Bonding,
Affiliazioni:
*** IBB - CNR *** Istituto di Biostrutture e Bioimmagini, CNR, Napoli, Italy., Istituto di Calcolo e Reti ad Alte Prestazioni, CNR, Napoli, Italy.,
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Proteins frequently assume complex three-dimensional structures characterized by marginal thermodynamic stabilities. In this scenario, deciphering the folding code of these molecular giants with clay feet is a cumbersome task. Studies performed in last years have shown that the interplay between backbone geometry and local conformation has an important impact on protein structures. Although the variability of several geometrical parameters of protein backbone has been established, the role of the structural context in determining these effects has been hitherto limited to the valence bond angle tau (NC (alpha) C). We here investigated the impact of different factors on the observed variability of backbone geometry and peptide bond planarity. These analyses corroborate the notion that the local conformation expressed in terms of (varphi, psi) dihedrals plays a predominant role in dictating the variability of these parameters. The impact of secondary structure is limited to bond angles which involve atoms that are usually engaged in H-bonds and, therefore, more susceptible to the structural context. Present data also show that the nature of the side chain has a significant impact on angles such as NC (alpha) C (beta) and C (beta) C (alpha) C. In conclusion, our analyses strongly support the use of variability of protein backbone geometry in structure refinement, validation, and prediction.
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