Computational prediction and analysis of breast cancer targets for 6-methyl-1, 3, 8-trichlorodibenzofuran.
Breast cancer is one of the most known cancer types caused to the women around the world. Dioxins on the other hand are a wide range of chemical compounds known to cause the effects on human health. Among them, 6-Methyl-1,3,8-trichlorodibenzofuran (MCDF) is a relatively non toxic prototypical alkyl...
| Main Authors: | , |
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| Format: | Article |
| Language: | English |
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Public Library of Science (PLoS)
2014-01-01
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| Series: | PLoS ONE |
| Online Access: | http://europepmc.org/articles/PMC4217716?pdf=render |
| _version_ | 1818042513529765888 |
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| author | Kumaraswamy Naidu Chitrala Suneetha Yeguvapalli |
| author_facet | Kumaraswamy Naidu Chitrala Suneetha Yeguvapalli |
| author_sort | Kumaraswamy Naidu Chitrala |
| collection | DOAJ |
| description | Breast cancer is one of the most known cancer types caused to the women around the world. Dioxins on the other hand are a wide range of chemical compounds known to cause the effects on human health. Among them, 6-Methyl-1,3,8-trichlorodibenzofuran (MCDF) is a relatively non toxic prototypical alkyl polychlorinated dibenzofuran known to act as a highly effective agent for inhibiting hormone-responsive breast cancer growth in animal models. In this study, we have developed a multi-level computational approach to identify possible new breast cancer targets for MCDF. We used PharmMapper Server to predict breast cancer target proteins for MCDF. Search results showed crystal Structure of the Antagonist Form of Glucocorticoid Receptor with highest fit score and AutoLigand analysis showed two potential binding sites, site-A and site-B for MCDF. A molecular docking was performed on these two sites and based on binding energy site-B was selected. MD simulation studies on Glucocorticoid receptor-MCDF complex revealed that MCDF conformation was stable at site-B and the intermolecular interactions were maintained during the course of simulation. In conclusion, our approach couples reverse pharmacophore analysis, molecular docking and molecular dynamics simulations to identify possible new breast cancer targets for MCDF. |
| first_indexed | 2024-12-10T08:47:31Z |
| format | Article |
| id | doaj.art-a9aa0be0d1c1433d8a9c669992bb5ece |
| institution | Directory Open Access Journal |
| issn | 1932-6203 |
| language | English |
| last_indexed | 2024-12-10T08:47:31Z |
| publishDate | 2014-01-01 |
| publisher | Public Library of Science (PLoS) |
| record_format | Article |
| series | PLoS ONE |
| spelling | doaj.art-a9aa0be0d1c1433d8a9c669992bb5ece2022-12-22T01:55:41ZengPublic Library of Science (PLoS)PLoS ONE1932-62032014-01-01911e10918510.1371/journal.pone.0109185Computational prediction and analysis of breast cancer targets for 6-methyl-1, 3, 8-trichlorodibenzofuran.Kumaraswamy Naidu ChitralaSuneetha YeguvapalliBreast cancer is one of the most known cancer types caused to the women around the world. Dioxins on the other hand are a wide range of chemical compounds known to cause the effects on human health. Among them, 6-Methyl-1,3,8-trichlorodibenzofuran (MCDF) is a relatively non toxic prototypical alkyl polychlorinated dibenzofuran known to act as a highly effective agent for inhibiting hormone-responsive breast cancer growth in animal models. In this study, we have developed a multi-level computational approach to identify possible new breast cancer targets for MCDF. We used PharmMapper Server to predict breast cancer target proteins for MCDF. Search results showed crystal Structure of the Antagonist Form of Glucocorticoid Receptor with highest fit score and AutoLigand analysis showed two potential binding sites, site-A and site-B for MCDF. A molecular docking was performed on these two sites and based on binding energy site-B was selected. MD simulation studies on Glucocorticoid receptor-MCDF complex revealed that MCDF conformation was stable at site-B and the intermolecular interactions were maintained during the course of simulation. In conclusion, our approach couples reverse pharmacophore analysis, molecular docking and molecular dynamics simulations to identify possible new breast cancer targets for MCDF.http://europepmc.org/articles/PMC4217716?pdf=render |
| spellingShingle | Kumaraswamy Naidu Chitrala Suneetha Yeguvapalli Computational prediction and analysis of breast cancer targets for 6-methyl-1, 3, 8-trichlorodibenzofuran. PLoS ONE |
| title | Computational prediction and analysis of breast cancer targets for 6-methyl-1, 3, 8-trichlorodibenzofuran. |
| title_full | Computational prediction and analysis of breast cancer targets for 6-methyl-1, 3, 8-trichlorodibenzofuran. |
| title_fullStr | Computational prediction and analysis of breast cancer targets for 6-methyl-1, 3, 8-trichlorodibenzofuran. |
| title_full_unstemmed | Computational prediction and analysis of breast cancer targets for 6-methyl-1, 3, 8-trichlorodibenzofuran. |
| title_short | Computational prediction and analysis of breast cancer targets for 6-methyl-1, 3, 8-trichlorodibenzofuran. |
| title_sort | computational prediction and analysis of breast cancer targets for 6 methyl 1 3 8 trichlorodibenzofuran |
| url | http://europepmc.org/articles/PMC4217716?pdf=render |
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