NDLI: A novel strategy for the structure-based drug design of heat shock protein 90 inhibitors

Content Provider	IEEE Xplore Digital Library
Author	Chen, O.Y.-C. Guan-Wen Chen Chen, W.Y.-C.
Copyright Year	2008
Description	Author affiliation: Dept. of Biol. Sci. & Technol., China Med. Univ., Taichung (Chen, O.Y.-C.)
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 $(r^{2})$ between each scoring function and the biological activity were used to determine the accurate scoring function for virtual screening. The $r^{2}$ 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.
Starting Page	1199
Ending Page	1206
File Size	352343
Page Count	8
File Format	PDF
ISBN	9781424418206
ISSN	10987576
DOI	10.1109/IJCNN.2008.4633952
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2008-06-01
Publisher Place	China
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Compounds Proteins Inhibitors Correlation Crystals Artificial neural networks Joints
Content Type	Text
Resource Type	Article

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