Using artificially generated spectral data to improve protein secondary structure prediction from Fourier transform infrared spectra of proteins

Date

2004-09-15

Author

Severcan, M
Haris, PI
Severcan, Feride

Metadata

Show full item record

This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.

Item Usage Stats

358
views

0
downloads

Secondary structures of proteins have been predicted using neural networks from their Fourier transform infrared spectra. To improve the generalization ability of the neural networks, the training data set has been artificially increased by linear interpolation. The leave-one-out approach has been used to demonstrate the applicability of the method. Bayesian regularization has been used to train the neural networks and the predictions have been further improved by the maximum-likelihood estimation method. The networks have been tested and standard error of prediction (SEP) of 4.19% for alpha helix, 3.49% for beta sheet, and 3.15% for turns have been achieved. The results indicate that there is a significant decrease in the SEP for each type of structure parameter compared to previous works.

Subject Keywords

Biophysics, Cell Biology, Biochemistry, Molecular Biology

URI

https://hdl.handle.net/11511/56922

Journal

ANALYTICAL BIOCHEMISTRY

DOI

https://doi.org/10.1016/j.ab.2004.06.030

Collections

Department of Biology, Article

Suggestions

OpenMETU
Core

IR and turbidity studies of vitamin E-cholesterol-phospholipid membrane interactions Severcan, Feride; Kazanci, Nadide; Baykal, Ülkü; Süzer, Şefik (Portland Press Ltd., 1995-8-1) Binary and tertiary mixture of α-tocophenol, cholesterol and dimyristoylphosphatidylcholine in the form of multilamellar liposomes were investigated by Fourier Transform Infrared and visible spectroscopy. Results of the FTIR and turbidity experiments indicate that α T decreases or diminishes the effect of cholesterol on the frequency and the bandwidth of the C-H stretching, CH2 scissoring and C=O stretching bands in FTIR spectra and the turbidity measurements (recorded as absorbance values at 440 nm) in pho...
Effect of progesterone on DPPC membrane: Evidence for lateral phase separation and inverse action in lipid dynamics Korkmaz, F; Severcan, Feride (Elsevier BV, 2005-08-15) Interactions of progesterone with zwitterionic dipalmitoyl phosphatidylcholine (DPPC) triultilamellar liposomes were investigated as a function of temperature and progesterone concentration by using three non-invasive techniques namely Fourier transform infrared spectroscopy, turbidity at 440 nm, and differential scanning calorimetry. The results reveal that progesterone changes the physical properties of DPPC bilayers by decreasing the main phase-transition temperature, abolishing the pre-transition, broad...
Structural properties of an engineered outer membrane protein G mutant, OmpG-16SL, investigated with infrared spectroscopy Yilmaz, Irem; Yildiz, Ozkan; KORKMAZ ÖZKAN, FİLİZ (Informa UK Limited, 2019-05-31) The structural and functional differences between wild type (WT) outer membrane protein G and its two mutants are investigated with Fourier transform infrared spectroscopy. Both mutants have a long extension to the primary sequence to increase the number of beta-strands from 14 (wild type) to 16 in an attempt to enlarge the pore diameter. The comparison among proteins is made in terms of pH-dependent conformational changes and thermal stability. Results show that all proteins respond to pH change but at dif...
Estimation of protein secondary structure from FTIR spectra using neural networks Severcan, M; Severcan, Feride; Haris, PI (Elsevier BV, 2001-05-30) Secondary structure of proteins have been predicted using neural networks (NN) from their Fourier transform infrared spectra. Leave-one-out approach has been used to demonstrate the applicability of the method. A form of cross-validation is used to train NN to prevent the overfitting problem. Multiple neural network outputs are averaged to reduce the variance of predictions. The networks realized have been tested and rms errors of 7.7% for alpha -helix, 6.4% for beta -sheet and 4.8% for turns have been achi...
The effect of cysteine-43 mutation on thermostability and kinetic properties of citrate synthase from Thermoplasma acidophilum Kocabıyık, Semra; Russel, RJM; Danson, MJ; Hough, DW (Elsevier BV, 1996-07-05) In this study, we have substituted serine-43 by cysteine in the recombinant citrate synthase from a moderately thermophilic Archaeon Thermoplasma acidophilum, for site-specific attachment of labels and have investigated the effects of this mutation on the biochemical properties and thermal stability of the enzyme. Both wild-type and the mutant enzymes were purified to homogenity using affinity chromatography on Matrex Gel Red A. The mutant Thermoplasma citrate synthase is very similar to wild-type citrate s...

Citation Formats

M. Severcan, P. Haris, and F. Severcan, “Using artificially generated spectral data to improve protein secondary structure prediction from Fourier transform infrared spectra of proteins,” ANALYTICAL BIOCHEMISTRY, pp. 238–244, 2004, Accessed: 00, 2020. [Online]. Available: https://hdl.handle.net/11511/56922.