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Virtual Screening of Specific Insulin-Like Growth Factor 1 Receptor (IGF1R) Inhibitors from the National Cancer Institute (NCI) Molecular Database

1
National Engineering Laboratory for Druggable Gene and Protein Screening, Northeast Normal University, Changchun 130024, China
2
Research Center of Agriculture and Medicine Gene Engineering of Ministry of Education, Northeast Normal University, Changchun 130024, China
*
Authors to whom correspondence should be addressed.
Int. J. Mol. Sci. 2012, 13(12), 17185-17209; https://0-doi-org.brum.beds.ac.uk/10.3390/ijms131217185
Received: 10 October 2012 / Revised: 21 November 2012 / Accepted: 11 December 2012 / Published: 14 December 2012
(This article belongs to the Section Physical Chemistry, Theoretical and Computational Chemistry)
Insulin-like growth factor 1 receptor (IGF1R) is an attractive drug target for cancer therapy and research on IGF1R inhibitors has had success in clinical trials. A particular challenge in the development of specific IGF1R inhibitors is interference from insulin receptor (IR), which has a nearly identical sequence. A few potent inhibitors that are selective for IGF1R have been discovered experimentally with the aid of computational methods. However, studies on the rapid identification of IGF1R-selective inhibitors using virtual screening and confidence-level inspections of ligands that show different interactions with IGF1R and IR in docking analysis are rare. In this study, we established virtual screening and binding-mode prediction workflows based on benchmark results of IGF1R and several kinase receptors with IGF1R-like structures. We used comprehensive analysis of the known complexes of IGF1R and IR with their binding ligands to screen specific IGF1R inhibitors. Using these workflows, 17 of 139,735 compounds in the NCI (National Cancer Institute) database were identified as potential specific inhibitors of IGF1R. Calculations of the potential of mean force (PMF) with GROMACS were further conducted for three of the identified compounds to assess their binding affinity differences towards IGF1R and IR. View Full-Text
Keywords: IGF1R; IR; virtual screening; binding mode prediction; selective inhibition IGF1R; IR; virtual screening; binding mode prediction; selective inhibition
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MDPI and ACS Style

Fan, C.; Huang, Y.-X.; Bao, Y.-L.; Sun, L.-G.; Wu, Y.; Yu, C.-L.; Zhang, Y.; Song, Z.-B.; Zheng, L.-H.; Sun, Y.; Wang, G.-N.; Li, Y.-X. Virtual Screening of Specific Insulin-Like Growth Factor 1 Receptor (IGF1R) Inhibitors from the National Cancer Institute (NCI) Molecular Database. Int. J. Mol. Sci. 2012, 13, 17185-17209. https://0-doi-org.brum.beds.ac.uk/10.3390/ijms131217185

AMA Style

Fan C, Huang Y-X, Bao Y-L, Sun L-G, Wu Y, Yu C-L, Zhang Y, Song Z-B, Zheng L-H, Sun Y, Wang G-N, Li Y-X. Virtual Screening of Specific Insulin-Like Growth Factor 1 Receptor (IGF1R) Inhibitors from the National Cancer Institute (NCI) Molecular Database. International Journal of Molecular Sciences. 2012; 13(12):17185-17209. https://0-doi-org.brum.beds.ac.uk/10.3390/ijms131217185

Chicago/Turabian Style

Fan, Cong, Yan-Xin Huang, Yong-Li Bao, Lu-Guo Sun, Yin Wu, Chun-Lei Yu, Yu Zhang, Zhen-Bo Song, Li-Hua Zheng, Ying Sun, Guan-Nan Wang, and Yu-Xin Li. 2012. "Virtual Screening of Specific Insulin-Like Growth Factor 1 Receptor (IGF1R) Inhibitors from the National Cancer Institute (NCI) Molecular Database" International Journal of Molecular Sciences 13, no. 12: 17185-17209. https://0-doi-org.brum.beds.ac.uk/10.3390/ijms131217185

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