Application of taguchi method for optimization of the peptide ligand structure
Matematičeskaâ biologiâ i bioinformatika, Tome 11 (2016) no. 2, pp. 385-393.

Voir la notice de l'article provenant de la source Math-Net.Ru

Taguchi method was used to optimize peptide ligand structure using the H-2/TCR complex (PDB ID 2Z31). This approach greatly reduces the number of experiments that are required to analyze the contribution of various amino acid residues for each position into ligand molecule. Taguchi matrix was used to design a set of peptide ligands for molecular docking and molecular mechanics energy minimization. This approach allowed creating a new peptide structure with lower molecular mechanics energy than native peptide and demonstrates the applicability of the Taguchi method for peptide ligand optimization.
@article{MBB_2016_11_2_a7,
     author = {A. V. Danilkovich and V. I. Turobov and E. V. Sobolev and I. P. Udovichenko},
     title = {Application of taguchi method for optimization of the peptide ligand structure},
     journal = {Matemati\v{c}eska\^a biologi\^a i bioinformatika},
     pages = {385--393},
     publisher = {mathdoc},
     volume = {11},
     number = {2},
     year = {2016},
     language = {ru},
     url = {http://geodesic.mathdoc.fr/item/MBB_2016_11_2_a7/}
}
TY  - JOUR
AU  - A. V. Danilkovich
AU  - V. I. Turobov
AU  - E. V. Sobolev
AU  - I. P. Udovichenko
TI  - Application of taguchi method for optimization of the peptide ligand structure
JO  - Matematičeskaâ biologiâ i bioinformatika
PY  - 2016
SP  - 385
EP  - 393
VL  - 11
IS  - 2
PB  - mathdoc
UR  - http://geodesic.mathdoc.fr/item/MBB_2016_11_2_a7/
LA  - ru
ID  - MBB_2016_11_2_a7
ER  - 
%0 Journal Article
%A A. V. Danilkovich
%A V. I. Turobov
%A E. V. Sobolev
%A I. P. Udovichenko
%T Application of taguchi method for optimization of the peptide ligand structure
%J Matematičeskaâ biologiâ i bioinformatika
%D 2016
%P 385-393
%V 11
%N 2
%I mathdoc
%U http://geodesic.mathdoc.fr/item/MBB_2016_11_2_a7/
%G ru
%F MBB_2016_11_2_a7
A. V. Danilkovich; V. I. Turobov; E. V. Sobolev; I. P. Udovichenko. Application of taguchi method for optimization of the peptide ligand structure. Matematičeskaâ biologiâ i bioinformatika, Tome 11 (2016) no. 2, pp. 385-393. http://geodesic.mathdoc.fr/item/MBB_2016_11_2_a7/

[1] Verma J., Khedkar V. M., Coutinho E. C., “3D-QSAR in drug design — a review”, Curr. Top. Med. Chem., 10 (2010), 95–115 | DOI

[2] Taguchi G., System of experimental design: engineering methods to optimize quality and minimize costs, v. 1, UNIPUB/Kraus International Publications, 1987

[3] Abbasian M. A., Moallem M., Fahimi B., “Double stator switched reluctance machines (DSSRM): fundamentals and magnetic force analysis”, IEEE Trans. on Energy Con., 25 (2010), 589–597 | DOI

[4] Chapman P. L., Sudhoff S. D., “Design and precise realization of optimized current waveform for switched reluctance drive”, IEEE Trans. Power Electronics, 17 (2002), 76–83 | DOI

[5] Feiz J., Finch J. W., Metwally H. M. B., “A novel switched reluctance motor with multiple teeth per stator pole and comparison of such motors”, Electric Power System Research, 34 (1995), 197–203 | DOI

[6] Cobb B. D., Clarkson J. M., “A simple procedure for optimising the polymerase chain reaction (PCR) using modified Taguchi methods”, Nucleic Acids Res., 22 (1994), 3801–3805 | DOI

[7] Burch G. J., Ferguson C. H., Cartwright G., Kwong F. Y., “Application of Taguchi experimental design to the optimisation of a baculovirus expression system”, Biochem. Soc. Trans., 23 (1995), 107S | DOI

[8] Jeney C., Dobay O., Lengyel A., Adam E., Nasz I., “Taguchi optimisation of ELISA procedures”, J. Immunol. Methods, 223 (1999), 137–146 | DOI

[9] Vijayasarathy S., Datta S., Method, U.S. Patent. No 20080200649

[10] Rogov S. I., Nekrasov A. N., “A numerical measure of amino acid residues similarity based on the analysis of their surroundings in natural protein sequences”, Protein Engineering, 14 (2001), 459–463 | DOI

[11] Guex N., Peitsch M. C., “SWISS-MODEL and the Swiss-PdbViewer: An environment for comparative protein modeling”, Electrophoresis, 18 (1997), 2714–2723 | DOI

[12] Danilkovich A. V., Sobolev E. V., Tikhonov D. A., Shadrina T. E., Udovichenko I. P., “Molekulyarnaya dinamika kompleksov samoorganizuyuschikhsya ionnykh peptidov (RADA)$_4$”, Mat. biol. i bioinf., 6 (2011), 92–101 | DOI

[13] Danilkovich A. V., Sobolev E. V., Tikhonov D. A., Udovichenko I. P., Lipkin V. M., “Distinctive H-(RLDL)$_4$-OH peptide complexes potentiate nanostructure self-assembling in water”, Dokl. Biochem. Biophys., 443 (2012), 96–99 | DOI

[14] van Gunsteren W. F., Billeter S. R., Eising A. A., Hünenberger P. H., Krüger P., Mark A. E., Scott W. R. P., Tironi I. G., Biomolecular Simulation: The GROMOS96 Manual and User Guide, Vdf Hochschulverlag AG an der ETH Zürich, Switzerland, Zürich, 1996, 1042 pp.

[15] Martenson R. E., “Myelin basic protein speciation”, Experimental Allergic Encephalomyelitis: A Useful Model for Multiple Sclerosis, Progress in Clinical and Biological Research, 146, eds. E. C. Alvord Jr., M. W. Kies, A. J. Suckling, Alan R. Liss, Inc, New York, 1983

[16] Stepaniak J. A., Gould K. E., Sun D., Swanborg R. H., “A comparative study of experimental autoimmune encephalomyelitis in Lewis and DA rats”, J. Immunol., 155 (1995), 2762–2769

[17] Burns F. R., Li X. B., Shen N., Offner H., Chou Y. K., Vandenbark A. A., Heber-Katz E., “Both rat and mouse T cell receptors specific for the encephalitogenic determinant of myelin basic protein use similar V$\alpha$ and V$\beta$ chain genes even though the major histocompatibility complex and encephalitogenic determinants being recognized are different”, J. Exp. Med., 169 (1989), 27–39 | DOI

[18] Lenschow D. J., Walunas T. L., Bluestone J. A., “CD28/B7 system of T cell costimulation”, Annu. Rev. Immunol., 14 (1996), 233–258 | DOI