Abstract

IntroductionWorldwide, cancer of the breast is the most commonly diagnosed disease and the second leading cause of cancer-related mortality amongst women yearly (Miller et al., 2016). Computer-aided drug discovery (CADD) is a fundamental shortcut in drug discovery arena. CADD tools ascertain key molecule for testing, predicting the effectiveness, the possible side effect, and also assist in upgrading drug-likeliness of drug molecules (Leelananda and Lindert, 2016). The propose of carrying out this research is to design new 2-anilinopyrimidine derivative compounds based on the interaction of the derivative compounds (ligand) and thyroid hormone receptor (TRβ1), and also analyze their pharmacokinetic properties as drug compounds that would be used by the pharmaceuticals against triple-negative breast cancer (MDA-MB-468 cell line).ResultsThree compounds (12, 17, and 18) had the highest docking score ranging from − 7.3 to − 7.4 kcal/mol. This showed that the compounds (ligands) bind tightly with the active site of the thyroid hormone receptor (TRβ1). Based on their tight interactions with the receptor, the compounds were chosen as lead compounds in the design of fourteen new compounds by incorporating some fragments found to bind intensely with the active site of the thyroid hormone receptor (TRβ1). All the newly designed compounds passed the pharmacokinetic analysis (adsorption, distribution, metabolism, excretion, and other physicochemical test) passed the drug-likeness test, and they also adhered to the Lipinski rule of five.ConclusionsNew derivative compounds of 2-anilinopyrimidine against MDA-MB-468 cell line were designed based on the information obtained from the molecular docking studies. Furthermore, the pharmacokinetics analysis (adsorption, distribution, metabolism, excretion (ADME) and other physicochemical properties) carried out on the newly designed compounds showed this compounds can be made into oral drugs for patients with triple-negative breast cancer (MBA-MD-468 cell line) as they serve as most promising inhibitors against thyroid hormone receptor (TRβ1).

Highlights

  • Worldwide, cancer of the breast is the most commonly diagnosed disease and the second leading cause of cancer-related mortality amongst women yearly (Miller et al, 2016)

  • Three compounds (12, 17, and 18) had the highest docking score ranging from − 7.3 to − 7.4 kcal/mol. This showed that the compounds bind tightly with the active site of the thyroid hormone receptor (TRβ1)

  • New derivative compounds of 2-anilinopyrimidine against MDA-MB-468 cell line were designed based on the information obtained from the molecular docking studies

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Summary

Introduction

Cancer of the breast is the most commonly diagnosed disease and the second leading cause of cancer-related mortality amongst women yearly (Miller et al, 2016). Computer-aided drug discovery (CADD) and design confirms the best potential compound; it reduces the cost related to discovering a drug, and it reduces the time taken for a drug to get to the consumer market. It is a fundamental shortcut in the drug discovery arena. CADD tools ascertain potential molecule to be tested, predicting the efficacy, the possible side effect, and aid to upgrade the drug-likeliness of drug molecules (Leelananda and Lindert, 2016). In SBDD, the therapeutics are designed based on the information of the crystalized macromolecule known as a receptor (Ferreira et al, 2015)

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