Investigations on Inhibitors of Hedgehog Signal Pathway: A Quantitative Structure-Activity Relationship Study

Zhu, Ruixin; Liu, Qi; Tang, Jian; Li, Hui‐Liang; Cao, Zhiwei

doi:10.3390/ijms12053018

Cited by 6 publications

(13 citation statements)

References 41 publications

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“…93 cyclopamine derivatives with their activities against four different cell lines (BxPC-3, NCI-H446, SW1990 and NCI-H157) were obtained from our previous work [7]. The compound activity is measured by PK i , as defined in the following Cheng-Prusoff equation [16]:…”

Section: Methodsmentioning

confidence: 99%

“…Similar to our previous study [7], two different molecule descriptors, general descriptor [17] and drug-like index (DLI) [18] will be used for compound representation.…”

Section: Methodsmentioning

confidence: 99%

“…This is one of the small chemical compounds that specifically inhibit Smoothened in the Hedgehog Signaling Pathway[2]. In our previous study [7], we have performed several quantitatively structure-activity relationship (QSAR) studies for cyclopamine derivatives in multiple cell lines, and such study could reveal useful clues in developing clinically effective drugs and modifications of parent lead compounds for cancer therapy.…”

Section: Introductionmentioning

confidence: 99%

“…Recently, our partners have synthesized 93 cyclopamine derivatives and their activities were tested against four different cell lines (BxPC-3, NCI-H446, SW1990 and NCI-H157) respectively [7][8]. Based on these experimental data, a systematical QSAR investigation was carried out by incorporation of various statistic modelings and different molecular descriptors [7].…”

Section: Introductionmentioning

confidence: 99%

“…Based on these experimental data, a systematical QSAR investigation was carried out by incorporation of various statistic modelings and different molecular descriptors [7]. However, there are still several issues remain to be solved, which we believe that solving such problems will greatly enhance the understanding of inhibitors on Hedgehog Signaling Pathway, as well as the development of novel QSAR methodology.…”

Section: Introductionmentioning

confidence: 99%

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Integrated QSAR study for inhibitors of hedgehog signal pathway against multiple cell lines:a collaborative filtering method

et al. 2012

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BackgroundThe Hedgehog Signaling Pathway is one of signaling pathways that are very important to embryonic development. The participation of inhibitors in the Hedgehog Signal Pathway can control cell growth and death, and searching novel inhibitors to the functioning of the pathway are in a great demand. As the matter of fact, effective inhibitors could provide efficient therapies for a wide range of malignancies, and targeting such pathway in cells represents a promising new paradigm for cell growth and death control. Current research mainly focuses on the syntheses of the inhibitors of cyclopamine derivatives, which bind specifically to the Smo protein, and can be used for cancer therapy. While quantitatively structure-activity relationship (QSAR) studies have been performed for these compounds among different cell lines, none of them have achieved acceptable results in the prediction of activity values of new compounds. In this study, we proposed a novel collaborative QSAR model for inhibitors of the Hedgehog Signaling Pathway by integration the information from multiple cell lines. Such a model is expected to substantially improve the QSAR ability from single cell lines, and provide useful clues in developing clinically effective inhibitors and modifications of parent lead compounds for target on the Hedgehog Signaling Pathway.ResultsIn this study, we have presented: (1) a collaborative QSAR model, which is used to integrate information among multiple cell lines to boost the QSAR results, rather than only a single cell line QSAR modeling. Our experiments have shown that the performance of our model is significantly better than single cell line QSAR methods; and (2) an efficient feature selection strategy under such collaborative environment, which can derive the commonly important features related to the entire given cell lines, while simultaneously showing their specific contributions to a specific cell-line. Based on feature selection results, we have proposed several possible chemical modifications to improve the inhibitor affinity towards multiple targets in the Hedgehog Signaling Pathway.ConclusionsOur model with the feature selection strategy presented here is efficient, robust, and flexible, and can be easily extended to model large-scale multiple cell line/QSAR data. The data and scripts for collaborative QSAR modeling are available in the Additional file 1.

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Section: Methodsmentioning

confidence: 99%

“…Similar to our previous study [7], two different molecule descriptors, general descriptor [17] and drug-like index (DLI) [18] will be used for compound representation.…”

Section: Methodsmentioning

confidence: 99%