DocumentCode
2956695
Title
A novel strategy for the structure-based drug design of heat shock protein 90 inhibitors
Author
Chen, Omix Yu-Chian ; Chen, Guan-Wen ; Chen, WinstonYu-Chen
Author_Institution
Dept. of Biol. Sci. & Technol., China Med. Univ., Taichung
fYear
2008
fDate
1-8 June 2008
Firstpage
1199
Lastpage
1206
Abstract
Heat shock protein 90 (HSP90) regulates the correct folding of nascent protein in tumor cells. Through the ATPase domain of HSP90, inhibition of its activity is a manipulation for anticancer treatment. Two series of anticancer compounds, flavonoids and YC-1 derivatives, were employed in this study. The reference ligand in the docking simulation showed the significant RMSD of 0.87 with respect to the template (PDB code: 1uy7). Six scoring functions (DockScore, PLP1, PLP2, LigScore1, LigScore2, and PMF) were employed to evaluate the binding affinity. The correlation coefficients (r2) between each scoring function and the biological activity were used to determine the accurate scoring function for virtual screening. The r2 values were 0.878, 0.696, 0.395, 0.276, 0.050, and 0.187 for DockScore, LigScore1, LigScore2, PLP1, PLP2, and PMF, respectively. According to the accurate DockScore, most of flavonoids and YC-1 derivatives had the higher binding affinities to HSP90 than controls and built the important hydrogen bond with the key residue ASP93. The structure-based de novo design by using Ludi program was performed to increase the binding affinity. Final thirteen potential compounds had higher binding affinity than the original ones. These candidates might guide drug design for novel HSP90 inhibitors in the future.
Keywords
biochemistry; cancer; cellular biophysics; drugs; hydrogen bonds; patient treatment; proteins; tumours; ATPase domain; HSP90; Ludi program; YC-1 derivatives; anticancer compounds; anticancer treatment; binding affinity; biological activity; correlation coefficients; docking simulation; flavonoids; heat shock protein 90 inhibitors; hydrogen bond; nascent protein; scoring function; structure-based drug design; tumor cells; virtual screening; Biological information theory; Biological system modeling; Cancer; Chemical compounds; Drugs; Electric shock; Hydrogen; Inhibitors; Proteins; Tumors;
fLanguage
English
Publisher
ieee
Conference_Titel
Neural Networks, 2008. IJCNN 2008. (IEEE World Congress on Computational Intelligence). IEEE International Joint Conference on
Conference_Location
Hong Kong
ISSN
1098-7576
Print_ISBN
978-1-4244-1820-6
Electronic_ISBN
1098-7576
Type
conf
DOI
10.1109/IJCNN.2008.4633952
Filename
4633952
Link To Document