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Dataset on the DFT-QSAR, and docking approaches for anticancer activities of 1, 2, 3-triazole-pyrimidine derivatives against human esophageal carcinoma (EC-109)
The investigation of the novel hybrid, 1, 2, 3-triazole moiety combined with pyrimidine derivatives against human esophageal carcinoma is an unexplored field of theoretical/computational chemistry. Also, the development of new drugs still remains a major challenge, cost-intensive and time-consuming,...
Autores principales: | , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Elsevier
2020
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7365971/ https://www.ncbi.nlm.nih.gov/pubmed/32695851 http://dx.doi.org/10.1016/j.dib.2020.105963 |
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author | Adegoke, Rhoda Oyeladun Oyebamiji, Abel Kolawole Semire, Banjo |
author_facet | Adegoke, Rhoda Oyeladun Oyebamiji, Abel Kolawole Semire, Banjo |
author_sort | Adegoke, Rhoda Oyeladun |
collection | PubMed |
description | The investigation of the novel hybrid, 1, 2, 3-triazole moiety combined with pyrimidine derivatives against human esophageal carcinoma is an unexplored field of theoretical/computational chemistry. Also, the development of new drugs still remains a major challenge, cost-intensive and time-consuming, thus making the computational approach now a hot topic due to its ability to hasten up and aid the process of drug designs. Here, the use of the quantum chemical method via density functional theory (DFT) was employed in calculating molecular descriptors for developing the quantitative structure-activity relation (QSAR) model which predicts bioactivity of the selected 1, 2, 3-triazole-pyrimidine derivatives. Quantum chemical method implemented in Spartan 14, was used in calculating the molecular descriptors. The obtained results were imputed into Gretl and SPSS (software package for social sciences) to generate a novel QSAR model equation for human esophageal carcinoma (EC-109) through multiple linear regression. The relationship between the experimental and predicted inhibition efficiency (IC(50)) of 1,2,3-triazole-pyrimidine with EC-109 was calculated which gives good correlation results. QSAR was validated using CV.R(2) [Formula: see text]. Fitting value (R(2)) of 0.999 with an adjusted fitting value [Formula: see text] of 0.995 was obtained and the result of validating QSAR performance gave CV.R(2) and [Formula: see text] value that is greater than 0.6, signifying its appropriateness and dependability. Molecular docking through simulation using Discovery Studio 4.1, Autodock Tool 1.5.6 and AutodockVina 1.1.2 was also carried out to calculate the free energy of ligand-receptor interactions as well as ligand conformation in the receptor-binding site. The results obtained revealed the presence of hydrogen bond interaction of the ligands with the amino acids residue in the binding sites of the receptor. Conformation of the ligands was essential property for binding ligand with the receptor. Critical examination and the correlations between the IC(50) and binding energy showed the activeness of ligand conformation in the gouge of the receptor with binding energy greater than the 5-fluorouracil (5- Fu) that was used as the standard compound. |
format | Online Article Text |
id | pubmed-7365971 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | Elsevier |
record_format | MEDLINE/PubMed |
spelling | pubmed-73659712020-07-20 Dataset on the DFT-QSAR, and docking approaches for anticancer activities of 1, 2, 3-triazole-pyrimidine derivatives against human esophageal carcinoma (EC-109) Adegoke, Rhoda Oyeladun Oyebamiji, Abel Kolawole Semire, Banjo Data Brief Chemistry The investigation of the novel hybrid, 1, 2, 3-triazole moiety combined with pyrimidine derivatives against human esophageal carcinoma is an unexplored field of theoretical/computational chemistry. Also, the development of new drugs still remains a major challenge, cost-intensive and time-consuming, thus making the computational approach now a hot topic due to its ability to hasten up and aid the process of drug designs. Here, the use of the quantum chemical method via density functional theory (DFT) was employed in calculating molecular descriptors for developing the quantitative structure-activity relation (QSAR) model which predicts bioactivity of the selected 1, 2, 3-triazole-pyrimidine derivatives. Quantum chemical method implemented in Spartan 14, was used in calculating the molecular descriptors. The obtained results were imputed into Gretl and SPSS (software package for social sciences) to generate a novel QSAR model equation for human esophageal carcinoma (EC-109) through multiple linear regression. The relationship between the experimental and predicted inhibition efficiency (IC(50)) of 1,2,3-triazole-pyrimidine with EC-109 was calculated which gives good correlation results. QSAR was validated using CV.R(2) [Formula: see text]. Fitting value (R(2)) of 0.999 with an adjusted fitting value [Formula: see text] of 0.995 was obtained and the result of validating QSAR performance gave CV.R(2) and [Formula: see text] value that is greater than 0.6, signifying its appropriateness and dependability. Molecular docking through simulation using Discovery Studio 4.1, Autodock Tool 1.5.6 and AutodockVina 1.1.2 was also carried out to calculate the free energy of ligand-receptor interactions as well as ligand conformation in the receptor-binding site. The results obtained revealed the presence of hydrogen bond interaction of the ligands with the amino acids residue in the binding sites of the receptor. Conformation of the ligands was essential property for binding ligand with the receptor. Critical examination and the correlations between the IC(50) and binding energy showed the activeness of ligand conformation in the gouge of the receptor with binding energy greater than the 5-fluorouracil (5- Fu) that was used as the standard compound. Elsevier 2020-07-03 /pmc/articles/PMC7365971/ /pubmed/32695851 http://dx.doi.org/10.1016/j.dib.2020.105963 Text en © 2020 Published by Elsevier Inc. http://creativecommons.org/licenses/by-nc-nd/4.0/ This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/). |
spellingShingle | Chemistry Adegoke, Rhoda Oyeladun Oyebamiji, Abel Kolawole Semire, Banjo Dataset on the DFT-QSAR, and docking approaches for anticancer activities of 1, 2, 3-triazole-pyrimidine derivatives against human esophageal carcinoma (EC-109) |
title | Dataset on the DFT-QSAR, and docking approaches for anticancer activities of 1, 2, 3-triazole-pyrimidine derivatives against human esophageal carcinoma (EC-109) |
title_full | Dataset on the DFT-QSAR, and docking approaches for anticancer activities of 1, 2, 3-triazole-pyrimidine derivatives against human esophageal carcinoma (EC-109) |
title_fullStr | Dataset on the DFT-QSAR, and docking approaches for anticancer activities of 1, 2, 3-triazole-pyrimidine derivatives against human esophageal carcinoma (EC-109) |
title_full_unstemmed | Dataset on the DFT-QSAR, and docking approaches for anticancer activities of 1, 2, 3-triazole-pyrimidine derivatives against human esophageal carcinoma (EC-109) |
title_short | Dataset on the DFT-QSAR, and docking approaches for anticancer activities of 1, 2, 3-triazole-pyrimidine derivatives against human esophageal carcinoma (EC-109) |
title_sort | dataset on the dft-qsar, and docking approaches for anticancer activities of 1, 2, 3-triazole-pyrimidine derivatives against human esophageal carcinoma (ec-109) |
topic | Chemistry |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7365971/ https://www.ncbi.nlm.nih.gov/pubmed/32695851 http://dx.doi.org/10.1016/j.dib.2020.105963 |
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