Pregled bibliografske jedinice broj: 72013
New computational algorithm for the prediction of protein folding types
New computational algorithm for the prediction of protein folding types // International Journal of Quantum Chemistry, 84 (2001), 1; 13-22 (međunarodna recenzija, članak, znanstveni)
CROSBI ID: 72013 Za ispravke kontaktirajte CROSBI podršku putem web obrasca
Naslov
New computational algorithm for the prediction of
protein folding types
Autori
Štambuk, Nikola ; Konjevoda, Paško
Izvornik
International Journal of Quantum Chemistry (0020-7608) 84
(2001), 1;
13-22
Vrsta, podvrsta i kategorija rada
Radovi u časopisima, članak, znanstveni
Ključne riječi
protein folding; secondary structure prediction; genetic code; error-correcting; Gray code; minimization; sequences; model
Sažetak
We present a new computational algorithm for the
prediction of a secondary protein structure. The
method enables the evaluation of alpha- and
beta-protein folding types from the nucleotide
sequences. The procedure is based on the reflected
Gray code algorithm of nucleotide-amino acid
relationships, and represents the extension of
Swanson's procedure in Ref. [4]. It is shown that
six-digit binary notation of each codon enables
the prediction of alpha- and beta-protein folds
by means of the error-correcting linear block
triple-check code. We tested the validity of the
method on the test set of 140 proteins (70 alpha-
and 70 beta-folds). The test set consisted of
standard alpha- and beta-protein classes from
Jpred and SCOP databases, with nucleotide sequence
available in the GenBank database. 100% accurate
classification of alpha- and beta-protein folds,
based on 39 dipeptide addresses derived by the
error-correcting coding procedure was obtained by
means of the logistic regression analysis (p <
0.00000001). Classification tree and machine
learning sequential minimal optimization (SMO)
classifier confirmed the results by means 97.1%
and 90% accurate classification, respectively.
Protein fold prediction quality tested by means of
leave-one-out cross-validation was a satisfactory
82.1% for the logistic regression and 81.4% for
the SMO classifier. The presented procedure of
computational analysis can be helpful in detecting
the type of protein folding from the newly
sequenced exon regions. Tile method enables quick,
simple, and accurate prediction of alpha- and beta
-protein folds from the nucleotide sequence on a
personal computer.
Izvorni jezik
Engleski
Znanstvena područja
Temeljne medicinske znanosti
POVEZANOST RADA
Citiraj ovu publikaciju:
Časopis indeksira:
- Current Contents Connect (CCC)
- Web of Science Core Collection (WoSCC)
- Science Citation Index Expanded (SCI-EXP)
- SCI-EXP, SSCI i/ili A&HCI
- Scopus
Uključenost u ostale bibliografske baze podataka::
- Chemical Abstracts