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Istituto di scienza dell'alimentazione

Torna all'elenco Contributi in rivista anno 2006

Contributo in rivista

Tipo: Articolo in rivista

Titolo: Amino acid propensities for secondary structures are influenced by the protein structural class.

Anno di pubblicazione: 2006

Formato: Elettronico Cartaceo

Autori: Costantini S, Colonna G, Facchiano A.

Affiliazioni autori: Istituto di Scienza dell'Alimentazione, CNR, Avellino Seconda UniversitÓ di Napoli

Autori CNR:


Lingua: inglese

Abstract: Amino acid propensities for secondary structures were used since the 1970s, when Chou and Fasman evaluated them within datasets of few tens of proteins and developed a method to predict secondary structure of proteins, still in use despite prediction methods having evolved to very different approaches and higher reliability. Propensity for secondary structures represents an intrinsic property of amino acid, and it is used for generating new algorithms and prediction methods, therefore our work has been aimed to investigate what is the best protein dataset to evaluate the amino acid propensities, either larger but not homogeneous or smaller but homogeneous sets, i.e., all-alpha, all-beta, alpha-beta proteins. As a first analysis, we evaluated amino acid propensities for helix, beta-strand, and coil in more than 2000 proteins from the PDBselect dataset. With these propensities, secondary structure predictions performed with a method very similar to that of Chou and Fasman gave us results better than the original one, based on propensities derived from the few tens of X-ray protein structures available in the 1970s. In a refined analysis, we subdivided the PDBselect dataset of proteins in three secondary structural classes, i.e., all-alpha, all-beta, and alpha-beta proteins. For each class, the amino acid propensities for helix, beta-strand, and coil have been calculated and used to predict secondary structure elements for proteins belonging to the same class by using resubstitution and jackknife tests. This second round of predictions further improved the results of the first round. Therefore, amino acid propensities for secondary structures became more reliable depending on the degree of homogeneity of the protein dataset used to evaluate them. Indeed, our results indicate also that all algorithms using propensities for secondary structure can be still improved to obtain better predictive results.

Lingua abstract: inglese

Pagine da: 441

Pagine a: 451


Biochemical and biophysical research communications Elsevier [etc.]
Paese di pubblicazione: Stati Uniti d'America
Lingua: inglese
ISSN: 0006-291X

Numero volume: 342

DOI: 10.1016/j.bbrc.2006.01.159

Indicizzato da: PubMed [16487481]

URL: http://www.sciencedirect.com/science/article/pii/S0161589008001004

Altre informazioni: 4

Strutture CNR:


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