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Computer-Aided Analysis of Oxino-bis-Pyrazolederivative as a Potential Breast Cancer Drug Based on DFT, Molecular Docking, and Pharmacokinetic Studies: Compared with the Standard Drug Tamoxifen

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Breast cancer is the most often diagnosed and deadliest type of cancer in the world. Thiophene derivatives are available with various biological and pharmacological properties. In the current study, Computer assisted toxicity and pharmacokinetics prediction has been considered by pharmaceutical industries as an efficient way of choosing the potential drug. This study aimed at evaluating the in-silico pharmacokinetic properties (ADME) and toxicity and drug likeness of eight drugs. This work applies SwissADME, Pro Tox II, molinspirastion, and ADMETlab web applications and a quantum chemical investigation using density function theory (DFT) was utilized to explore the structural characteristics of thiophene derivatives, and the breast cancer inhibitory properties were revealed through molecular docking simulation. The optimization of the lead molecule was initially performed using DFT/B3LYP approach with a 6-31++(d,p) base set. The simulated electrostatic potential was performed to evaluate the reactivity of the lead molecule, and the molecular reactivity and stability were evaluated through HOMO-LUMO analysis based on energy gap, chemical potential (μ), electronegativity (χ), hardness (η), and softness (S) values. Then molecular docking research was used to assess the interaction of thiophene derivatives against the breast cancer target proteins, and pharmacokinetic evaluation was used to evaluate the drug-likeness property of the lead molecule. The leading molecules showed no violation against Lipinski’s rule, and the highest binding affinity was observed against HER-2 (PDB ID: 2IOK) with a docking score of -9.45Kcal/mol.
Title: Computer-Aided Analysis of Oxino-bis-Pyrazolederivative as a Potential Breast Cancer Drug Based on DFT, Molecular Docking, and Pharmacokinetic Studies: Compared with the Standard Drug Tamoxifen
Description:
Breast cancer is the most often diagnosed and deadliest type of cancer in the world.
Thiophene derivatives are available with various biological and pharmacological properties.
In the current study, Computer assisted toxicity and pharmacokinetics prediction has been considered by pharmaceutical industries as an efficient way of choosing the potential drug.
This study aimed at evaluating the in-silico pharmacokinetic properties (ADME) and toxicity and drug likeness of eight drugs.
This work applies SwissADME, Pro Tox II, molinspirastion, and ADMETlab web applications and a quantum chemical investigation using density function theory (DFT) was utilized to explore the structural characteristics of thiophene derivatives, and the breast cancer inhibitory properties were revealed through molecular docking simulation.
The optimization of the lead molecule was initially performed using DFT/B3LYP approach with a 6-31++(d,p) base set.
The simulated electrostatic potential was performed to evaluate the reactivity of the lead molecule, and the molecular reactivity and stability were evaluated through HOMO-LUMO analysis based on energy gap, chemical potential (μ), electronegativity (χ), hardness (η), and softness (S) values.
Then molecular docking research was used to assess the interaction of thiophene derivatives against the breast cancer target proteins, and pharmacokinetic evaluation was used to evaluate the drug-likeness property of the lead molecule.
The leading molecules showed no violation against Lipinski’s rule, and the highest binding affinity was observed against HER-2 (PDB ID: 2IOK) with a docking score of -9.
45Kcal/mol.

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