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Previous studies have shown that 2-arylbenzimidazole derivatives have a strong anti-diabetic effect. To further explore this potential, we develop new analogues of the compound using ligand-based drug design and tested their inhibitory and binding properties through QSAR analyses, molecular docking, dynamic simulations and pharmacokinetic studies. By using quantitative structure activity relationship and ligand-based modification, a highly precise predictive model and design of potent compounds was developed from the derivatives of 2-arylbenzimidazoles. Molecular docking and simulation studies were then conducted to identify the optimal binding poses and pharmacokinetic profiles of the newly generated therapeutic drugs. DFT was employed to optimize the chemical structures of 2-arylbenzimidazole derivatives using B3LYP/6-31G* as the basis set. The model with the highest R2trng set, R2adj, Q2cv, and R2test sets (0.926, 0.912, 0.903, and 0.709 respectively) was chosen to predict the inhibitory activities of the derivatives. Five analogues designed using ligand-based strategy had higher activity than the hit molecule. Additionally, the designed molecules had more favorable MolDock scores than the hit molecule and acarbose and simulation studies confirm on their stability and binding affinities towards the protein. The ADME and druglikeness properties of the analogues indicated that they are safe to consume orally and have a high potential for total clearance. The results of this study showed that the suggested analogues could act as α-amylase inhibitors, which could be used as a basis for the creation of new drugs to treat type 2 diabetes mellitus. [ABSTRACT FROM AUTHOR]

Background: Breast cancer is the most common tumor among females globally. Its prevalence is growing around the world, and it is alleged to be the leading cause of cancer death. Approved anti-breast cancer drugs display several side effects and resistance during the early treatment stage. Hence, there is a need for the development of more effective and safer drugs. This research was aimed at designing more potent quinazolin-4(3H)-one molecules as breast cancer inhibitors using a ligand-based design approach, studying their modes of interaction with the target enzyme using molecular docking simulation, and predicting their pharmacological properties. Methods: The QSAR model was developed using a series of quinazoline-4(3H)-one derivatives by utilizing Material Studio v8.0 software and validated both internally and externally. Applicability domain virtual screening was utilized in selecting the template molecule, which was structurally modified to design more potent molecules. The inhibitive capacities of the design molecules were predicted using the developed model. Furthermore, molecular docking was performed with the EGFR target active site residues, which were obtained from the protein data bank online server (PDB ID: 2ITO) using Molegro Virtual Docker (MVD) software. SwissADME and pkCSM online sites were utilized in predicting the pharmacological properties of the designed molecules. Results: Four QSAR models were generated, and the first model was selected due to its excellent internal and external statistical parameters as follows: R2 = 0.919, R2adj = 0.898, Q2cv = 0.819, and R2pred = 0.7907. The robustness of the model was also confirmed by the result of the Y-scrambling test performed with cR2p = 0.7049. The selected model was employed to design seven molecules, with compound 4 (pIC50 = 5.18) adopted as the template. All the designed compounds exhibit better activities ranging from pIC50 = 5.43 to 5.91 compared to the template and Doruxybucin (pIC50 = 5.35). The results of molecular docking revealed better binding with the EGFR target compared with the template and Doruxybucin. The designed compounds exhibit encouraging therapeutic applicability, as evidenced by the findings of pharmacological property prediction. Conclusions: The designed derivatives could be utilized as novel anti-breast cancer agents. [ABSTRACT FROM AUTHOR]

Background: In spite of the significant escalation in the depth of our conception and regulation of breast cancer over the past decades, the malady is still a serious community health challenge globally and poses a substantial tasks. Selective estrogen modulators (SERMs) such as Tamoxifen are approved for the therapy of this illness but developed drug resistance and unwanted side effects such as endometrial cancer caused by the long-term Tamoxifen chemotherapy limit their therapeutic applicability. Hence, developing new ER+ drugs with better therapeutic effect is strongly needed. In an attempt to overcome this challenge, this research is aimed at designing novel chromen-2-one analogues with better inhibition capacity against MCF-7 breast cancer cell line via structural modification of the reference compound and predict their activities using a developed QSAR model. Results: Four models were developed, and the first was selected for the design as it has the highest statistical parameters such as: coefficient of determination (R2 = 0.950), cross-validation coefficient (Qcv2 = 0.912), adjusted R2 (Radj2 = 0.935), and external validation R2 (Rpred2 = 0.7485). Twelve (12) new novel chromen-2-one analogs were designed through structural modification of the reference compound. Their activities was predicted using the selected model, and their pIC50 was found to be better than that of the reference compound and standard drug (Tamoxifen) used in the research. Results of pharmacokinetic study of the designed compounds revealed that they possess drug-likeness properties as none of them violated the Lipinski's rule of five while ADMET studies confirmed designed compounds 6, 8, 11 and 12 as orally safe and non-toxic. Furthermore, molecular docking analysis was performed between these orally safe designed compounds and the active site of the ER+ receptor and the result showed that they have higher binding affinities than the reference compound and the standard drug used for this research. Conclusion: Hence, designed compounds 6, 8, 11 and 12 can be used as novel ER+ breast cancer drug candidates after performing in vivo and in vitro studies. [ABSTRACT FROM AUTHOR]

Background: Diabetes mellitus (DM) is one of the most defying health risk in the twenty-first century promoting a high rate of morbidity and mortality that could possibly increase if no intervention is in place. However, drugs for curing DM are available but are associated with adverse side effect necessitating the pursuit for a safe antidiabetic drugs. The present study was conducted in order to develop a QSAR model that would be used to predict the activities of salicylic acid derivatives, as well as to determine the binding interactions of the compounds with α-glucosidase using molecular docking studies. Results: Model one was selected and reported as the best model based on its fitness with the following validation keys: R2(trng set) = 0.968, R2(adj) = 0.957, Q2(cv) = 0.932, LOF = 0.085 and R2(test set) = 0.864. Five potent analogues were designed using the ligand-based method with their predicted activities been calculated and found to be higher compared to the lead compound. Furthermore, binding interactions of the designed analogues within the active site of α-glucosidase (pdb id:3L4V) illustrate a good binding affinities than kotalanol and acarbose. However, the ADMET and drug-likeness properties predicted the design analogues to be pharmacologically and orally safe by not having more than one violation of Lipinski's (Ro5) criteria. Conclusions: The present findings therefore showed that the salicylic acid derivatives could serve as α-glucosidase inhibitors. The compounds can be studied further for a hunts of promising drug candidates against diabetes mellitus. [ABSTRACT FROM AUTHOR]

Background: Cancer is a major health threat especially in unindustrialized nations. It surpasses coronary diseases and takes the number one killer position as a result of different global wide influences. Among many breast cancer substrates, triple-negative breast cancer (TNBC) is particularly devastating because it rapidly metastasize to other parts of the body, with a high risk of earlier recession and mortality. Result: In this research work, four (4) quantitative structure activity relationship (QSAR) models were developed using a series of quinazoline derivatives with activities against triple negative breast cancer cell line (MDA-MB231), model 1 was selected due to its statistical fitness with the following validation parameters: R2 = 0.875, Q2 = 0.837, R2 − Q2 = 0.038, Next test set = 5, and R2ext = 0.655. Molecular docking studies was performed for the quinazoline series as well as the reference drug (Gefitinib) and the active site of the epidermal growth factor receptor (EGFR) (pdb id = 3ug2). Eight compounds (6, 10, 13, 16, 17, 18, 19 and 20) were observed to have better docking score docking scores relative to Gefitinib. Compound number nineteen from the training set (pred pIC50 = 5.67, Residual = − 0.04 and MolDock score = − 123.238) was identified as the best compound since it has the best Moldock score and was excellently predicted by the selected model with least residual value, Hence was adopted as template for the design of Ten (10) new novel compounds with better activities and better docking scores. The inhibitive activities of the designed compounds were predicted by the selected model and most of them possess an improved activity relative to the template compound (19). The designed compounds were also redocked on to active pocket of the EGFR receptor and it was observed that they displayed better docking scores compared to the Template and the reference drug (Gefitinib) utilized in the design. Furthermore, the designed compounds were subjected to ADMET and drug-likeness studies using SWISSADME and pkCSM online web tools and they were observed to be pharmacologically active, easily synthesized and do not violate the Lipinski's rule of five. Conclusion: Hence, the designed compounds can be employed as inhibitors of MDA-MB231 cell line after passing through in vivo and in vitro evaluation. [ABSTRACT FROM AUTHOR]

Background: The most well-known cause of cancer deaths identified in female is breast cancer. Several drugs approved by the food and drug administration (FDA) for the treatment of breast cancer may have adverse health effects. This research is aimed at developing a QSAR model and utilize it to predict the inhibitive activities of newly designed novel compounds, examine their ADMET and drug-likeness properties and carry out molecular docking studies between the designed compounds and the VEGFR-2 receptors in order to identify the essential amino acid residues involved in protein–ligand interactions and possible mechanism of action of the designed compounds. Results: The first model was selected as the best because of its fitness statistically with the following assessment parameters: R2train = 0.832, R2adj = 0.79, R2ext = 0.62, Q2 = 0.68, and LOF = 0.14509. Compound 11 was selected as a template to design new powerful compounds based on its low residual and high pIC50 values. Majority of the designed compounds has predicted pIC50 greater than that of the lead compound and the standard drug (Sunitinib) used as reference. Molecular docking studies results of the designed compounds revealed that they have higher docking scores than the template and the reference drug (Sunitinib) and are found to bind to the VEGFR-2 receptor in a similar manner to the reference drug. Pharmacokinetics and ADMET properties revealed that the designed compounds passed drug-likeness criteria because they did not violate more than 1 Lipinski's rule of Five, They are uniformly distributed to the brain and are assumed to penetrate the central nervous system and finally they are all found to non-toxic and orally bioavailable. Conclusion: The developed model was therefore found to be efficient in predicting the pIC50 of Anti breast cancer compounds that are yet to be synthesized and it also help in reducing the cost and synthetic duration the compounds. The result of this research confirmed that the designed compounds may be developed as novel VEGFR-2 inhibitors. [ABSTRACT FROM AUTHOR]

Background: Melanoma cancer causes serious health problem worldwide because of its rapid invasion to other organs and lack of satisfactory chemotherapy. The pGI50 anticancer activity values of 70 compounds from the NCI (National Cancer Institute) on MALME-3M cell line was modeled to describe the quantitative structure-activity relationships (QSARs) of the compounds, and some selected compounds were docked. Results: The generated QSAR model was found to be statistically significant based on the obtained values of the validation keys such as R2 (0.885), R adjusted 2 (0.868), Q2cv (0.842), and R pred 2 (0.738) required to evaluate the strength and robustness of QSAR model. Compound 39 was selected as a template due to its good pGI50 (9.205) and was modified to design new potent compounds. The predicted pGI50 activity of the designed compounds by the built model was N1 (9.836), N2 (12.876), N3 (10.901), and N4 (11.263) respectively. These proposed compounds were docked with V600E-BRAF receptor and the result shows that, N1, N2, N3, and N4 with free binding energy (FBE) of − 11.7 kcal mol−1, − 12.8 kcal mol−1, − 12.7 kcal mol−1, and − 12.9 kcal mol−1 respectively were better than the parent structure of the template (compound 39, FBE = − 7.0 kcal mol−1) and the standard V600E-BRAF inhibitor (Vemurafenib, FBE = − 11.3 kcal mol−1). Additionally, these compounds passed the drug-likeness criteria successfully to be orally bioavailable. Conclusion: The proposed compounds were considered optimal as their performances are comparable to vemurafenib and possessed enhanced physicochemical properties. Thus recommends further research such as synthesis, in vivo, and ex-vivo evaluation. [ABSTRACT FROM AUTHOR]