Theoretical calculations of molecular descriptors for anticancer activities of 1, 2, 3-triazole-pyrimidine derivatives against gastric cancer cell line (MGC-803): DFT, QSAR and docking approaches
Abstract:This work used quantum chemical method via DFT to calculate molecular descriptors for the development of QSAR model to predict bioactivity (IC 50 -50% inhibition concentration) of the selected 1, 2, 3-triazole-pyrimidine derivatives against receptor (human gastric cancer cell line, MGC-803). The selected molecular parameters were obtained by B3LYP/6-31G**. QSAR model linked the molecular parameters of the studied compounds to their cytotoxicity and reproduced their observed bioactivities against MGC-803. The c… Show more
“…In this study, the role of dipole moment as one of the molecular non-bonded interaction in drug design cannot be over emphasized [35,36]. As reported by Oyewole et al [37], as well as Oyebamiji et al [38], molecular compound with high dipole moment value is expected to have anomalous property. As shown in Table 2, all the studied compounds can act as potential and fungal and antibacterial agent.…”
The menace caused by fungi amidst human being and in the world at large is colossal. Their increasing rate of causing havoc has drawn the attention of scientist to developing efficient drug-molecules in order to cure these diseases. In this work, sixteen molecular compounds were studied with aim of investigating the non-bonding interaction between the studied compounds and the receptors using the following software Spartan 14 (optimization), Pymol (for treating downloaded protein), Autodock Tool (for locating binding site in the downloaded protein and for converting ligand and receptor to.pdbqt format from.pdb format), Auto dock vina (for docking calculation) and discovery studio (for viewing the non-bonding interaction between the docked complexes) so as to observe anti-e-coli and anti-1,4α-demethylase properties of 3,4-dihydropyrimidin-2(1H)-one urea derivatives. The calculated parameters such as E HOMO energy, E LUMO energy, Dipole moment, log P, HBD and HBA which described anti-e-coli and anti-1,4α-demethylase properties of 3,4-dihydropyrimidin-2(1H)-one Urea Derivatives were observed. This showed that all the studied compounds have potential anti-e-coli and anti-1,4α-demethylase activities. Also, the calculated binding affinity showed that compound 4 and 3 possess better ability to inhibit e-coli and 1,4α-demethylase better than other studied compounds. More so, ADMET properties of five selected compounds were determined and it was observed that the ADMET properties obtained for the selected compounds were similar to the ADMET properties of the standards used in this work.
“…In this study, the role of dipole moment as one of the molecular non-bonded interaction in drug design cannot be over emphasized [35,36]. As reported by Oyewole et al [37], as well as Oyebamiji et al [38], molecular compound with high dipole moment value is expected to have anomalous property. As shown in Table 2, all the studied compounds can act as potential and fungal and antibacterial agent.…”
The menace caused by fungi amidst human being and in the world at large is colossal. Their increasing rate of causing havoc has drawn the attention of scientist to developing efficient drug-molecules in order to cure these diseases. In this work, sixteen molecular compounds were studied with aim of investigating the non-bonding interaction between the studied compounds and the receptors using the following software Spartan 14 (optimization), Pymol (for treating downloaded protein), Autodock Tool (for locating binding site in the downloaded protein and for converting ligand and receptor to.pdbqt format from.pdb format), Auto dock vina (for docking calculation) and discovery studio (for viewing the non-bonding interaction between the docked complexes) so as to observe anti-e-coli and anti-1,4α-demethylase properties of 3,4-dihydropyrimidin-2(1H)-one urea derivatives. The calculated parameters such as E HOMO energy, E LUMO energy, Dipole moment, log P, HBD and HBA which described anti-e-coli and anti-1,4α-demethylase properties of 3,4-dihydropyrimidin-2(1H)-one Urea Derivatives were observed. This showed that all the studied compounds have potential anti-e-coli and anti-1,4α-demethylase activities. Also, the calculated binding affinity showed that compound 4 and 3 possess better ability to inhibit e-coli and 1,4α-demethylase better than other studied compounds. More so, ADMET properties of five selected compounds were determined and it was observed that the ADMET properties obtained for the selected compounds were similar to the ADMET properties of the standards used in this work.
“…Also, 2D descriptors were used to develop another set of QSAR model using Material studio software and the predicted IC 50 were reported. The use of correlation coefficient in ascertaining the efficiency of develop model in QSAR study is not enough; this need validation of QSAR model where dependability and predicting ability of developed QSAR model can be confirmed [8] ; therefore, internal and external validation via training set and the test set were calculated respectively. The docking study was investigated on 1,2,4-Thiadiazole-1,2,4-Triazole and epidermal growth factor receptor kinase with PDB ID: 1m17 downloaded from protein data bank ( www.rcsb.org ).…”
Section: Experimental Design Materials and Methodsmentioning
Data from eight 1,2,4-thiadiazole-1,2,4-triazole derivatives were used to observe the anti-epidermal growth factor receptor kinase activities of 1,2,4-thiadiazole-1,2,4-triazole analogues thereby reducing human lung cancer. The software used to achieve this work were Spartan 14, Pymol, mgltools_win32_1.5.6, Auto dock vina and biovia2019.ds2019client. Also, the developed QSAR model was developed using the screened descriptors so as to inspect the closeness between the experimental IC
50
and the predicted IC
50
. More so, the binding affinity from 1,2,4-thiadiazole-1,2,4-triazole derivatives - epidermal growth factor receptor kinase complexes using molecular docking approach were reported. Also, the ADMET properties for selected compounds and proposed compounds with better binding affinity were reported.
“…The calculated cross-validation (CV.R 2 ) was 0.999 which shows its reliability and acceptability because the value obtained is greater than 0.5 [ 3 , 4 ]. Also, the predicting power of the QSAR model developed was believed to be enhanced, since adjusted correlation coefficient ( ) was calculated to be 0.995 which is greater than 0.6 [2] as presented in Table 3 . Fig.…”
Section: Data Descriptionmentioning
confidence: 99%
“…Tables SI 1 and 2 (in the supporting information) present the datasets of the selected molecular parameters obtained by B3LYP/6–31G** using DFT [2] . The molecular descriptors extracted were based on the electronic properties of the investigated compounds.…”
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
. Fitting value (R
2
) of 0.999 with an adjusted fitting value
of 0.995 was obtained and the result of validating QSAR performance gave CV.R
2
and
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.
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