Application of QSAR Method in the Design of Enhanced Antimalarial Derivatives of Azetidine-2-carbonitriles, their Molecular Docking, Drug-likeness, and SwissADME Properties

Exploring the potential of 2-arylbenzimidazole scaffolds as novel α-amylase inhibitors: QSAR, molecular docking, simulation and pharmacokinetic studies

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.

Least Absolute Shrinkage and Selection Operator-Based Prediction of the Binding Constant of p-Sulfonatocalix[6]/[8]arenes with Alkaloids

p-Sulfonatocalix[n]arenes (SCnA) have demonstrated great potential for drug encapsulation through host-guest complexation to improve solubility, stability, and bioavailability. In this study, the solubilization effect of SCnA (n = 4, 6, 8) on 95 active compounds derived from traditional Chinese medicine (TCM) was investigated. Based on the significant solubilization effect on alkaloids, SC6A/SC8A and 76 alkaloids were selected as the host and guest, respectively, to determine the binding constant by competitive fluorescence titration. LASSO regression was adopted to investigate the mechanism of the complex of SCnA with alkaloids. The binding constant of alkaloids-SC6A and alkaloids-SC8A was related to the alkaloid alkalinity. Also, the electronegativity, polarization, first ionization potential, hydrogen bond potential, the molecular size, and shape of alkaloids are critical properties to determine alkaloids-SC6A binding constant as well as electronegativity, polarization, hydrophobicity, and the molecular size and shape of alkaloids play an important role for the alkaloids-SC8A binding constant.

Anti-angiogenic Potential of Trans-chalcone in an In Vivo Chick Chorioallantoic Membrane Model: An ATP Antagonist to VEGFR with Predicted Blood-brain Barrier Permeability

BACKGROUND

Glioblastoma multiforme (GBM) is characterized by massive tumorinduced angiogenesis aiding tumorigenesis. Vascular endothelial growth factor A (VEGF-A) via VEGF receptor 2 (VEGFR-2) constitutes majorly to drive this process. Putting a halt to tumordriven angiogenesis is a major clinical challenge, and the blood-brain barrier (BBB) is the prime bottleneck in GBM treatment. Several phytochemicals show promising antiangiogenic activity across different models, but their ability to cross BBB remains unexplored.

METHODS

We screened over 99 phytochemicals having anti-angiogenic properties reported in the literature and evaluated them for their BBB permeability, molecular interaction with VEGFR-2 domains, ECD2-3 (extracellular domains 2-3) and TKD (tyrosine kinase domain) at VEGF-A and ATP binding site, cell membrane permeability, and hepatotoxicity using in silico tools. Furthermore, the anti-angiogenic activity of predicted lead Trans-Chalcone (TC) was evaluated in the chick chorioallantoic membrane.

RESULTS

Out of 99 phytochemicals, 35 showed an efficient ability to cross BBB with a probability score of > 0.8. Docking studies revealed 30 phytochemicals crossing benchmark binding affinity < -6.4 kcal/mol of TKD with the native ligand ATP alone. Out of 30 phytochemicals, 12 showed moderate to low hepatotoxicity, and 5 showed a violation of Lipinski's rule of five. Our in silico analysis predicted TC as a BBB permeable anti-angiogenic compound for use in GBM therapy. TC reduced vascularization in the CAM model, which was associated with the downregulation of VEGFR-2 transcript expression.

CONCLUSION

The present study showed TC to possess anti-angiogenic potential via the inhibition of VEGFR-2. In addition, the study predicted TC to cross BBB as well as a safe alternative for GBM therapy, which needs further investigation.

Homology modeling, docking, and ADMET studies of benzoheterocyclic 4-aminoquinolines analogs as inhibitors of Plasmodiumfalciparum

Objectives

The ongoing fight against endemic diseases is necessary due to the growing resistance of malarial parasites to widely accessible medications. Thus, there has been an ongoing search for antimalarial medications with improved efficacy. The goal of this study was to develop derivatives of benzoheterocyclic 4-aminoquinolines with enhanced activities and better binding affinities than the original compounds.

Methods

Thirty-four derivatives of benzoheterocyclic 4-aminoquinolines were docked (using a model of dihydrofolate reductase-thymidylate synthase [DRTS] protein) with Molegro software to identify the compound with the minimum docking score as a design template. The generated quantitative structure-activity model was employed to estimate the activity of the designed derivatives. The derivatives were also docked to determine the most stable derivatives. Furthermore, the designed derivatives were tested for their drug-likeness and pharmacokinetic properties using SwissADME software and pkCSM web application, respectively.

Results

Compound H-014, (N-(7-chloroquinolin-4-yl)-2-(4-methylpiperazin-1-yl)-1,3-benzoxazol-5-amine) with the lowest re-rank score of -115.423 was employed as the design template. Then 10 derivatives were further designed by substituting -OH, -OCH₃, -CHO, -F, and -Cl groups at various positions of the template. We found that the designed derivatives had improved activities compared to the template. The docking scores of the designed derivatives were lower than those of the original derivatives. Derivative h-06 (7-methoxy-4-((2-(4-methylpiperazin-1-yl)benzo[d]oxazol-5-yl)amino)quinolin-6-ol) with four hydrogen bonds was identified as the most stable due to its lowest re-rank score (-163.607). While all of the designed derivatives satisfied both the Lipinski and Verber rules, some derivatives such as h-10 (cytochrome P450 1A2 [CYP1A2]); h-05, h-08, h-09, and h-10 [CYP2C19]; and h-03, h-07, h-08, and h-10 [renal organic cation transporter 2 substrate]) showed poor absorption, distribution, metabolism, excretion, and toxicity (ADMET) properties.

Conclusion

Ten derivatives of benzoheterocyclic 4-aminoquinolines were designed with improved efficacies. Derivatives that follow Lipinski and Verber rules and are mostly non-toxic and non-sensitive to the skin can be utilized in the development of effective antimalarial medications.

Rhamnetin, a nutraceutical flavonoid arrests cell cycle progression of human ovarian cancer (SKOV3) cells by inhibiting the histone deacetylase 2 protein

Overexpression of HDAC 2 promotes cell proliferation in ovarian cancer. HDAC 2 is involved in chromatin remodeling, transcriptional repression, and the formation of condensed chromatin structures. Targeting HDAC 2 presents a promising therapeutic approach for correcting cancer-associated epigenetic abnormalities. Consequently, HDAC 2 inhibitors have evolved as an attractive class of anti-cancer agents. This work intended to investigate the anti-cancer abilities and underlying molecular mechanisms of Rhamnetin in human epithelial ovarian carcinoma cells (SKOV3), which remain largely unexplored. We employed various in vitro methods, including MTT, apoptosis study, cell cycle analysis, fluorescence microscopy imaging, and in vitro enzymatic HDAC 2 protein inhibition, to examine the chemotherapeutic sensitivity of Rhamnetin in SKOV3 cells. Additionally, we conducted in silico studies using molecular docking, MD simulation, MM-GBSA, DFT, and pharmacokinetic analysis to investigate the binding interaction mechanism within Rhamnetin and HDAC 2, alongside the compound's prospective as a lead candidate. The in vitro assay confirmed the cytotoxic effects of Rhamnetin on SKOV3 cells, through its inhibition of HDAC 2 activity. Rhamnetin, a nutraceutical flavonoid, halted at the G1 phase of the cell cycle and triggered apoptosis in SKOV3 cells. Furthermore, computational studies provided additional evidence of its stable binding to the HDAC 2 protein's binding site cavity. Based on our findings, we conclude that Rhamnetin effectively promotes apoptosis and mitigates the proliferation of SKOV3 cells through HDAC 2 inhibition. These results highlight Rhamnetin as a potential lead compound, opening a new therapeutic strategy for human epithelial ovarian cancer.Communicated by Ramaswamy H. Sarma.

Ligand-Based Virtual Screening and Molecular Docking of Benzimidazoles as Potential Inhibitors of Triosephosphate Isomerase Identified New Trypanocidal Agents

Trypanosoma cruzi (T. cruzi) is a parasite that affects humans and other mammals. T. cruzi depends on glycolysis as a source of adenosine triphosphate (ATP) supply, and triosephosphate isomerase (TIM) plays a key role in this metabolic pathway. This enzyme is an attractive target for the design of new trypanocidal drugs. In this study, a ligand-based virtual screening (LBVS) from the ZINC15 database using benzimidazole as a scaffold was accomplished. Later, a molecular docking on the interface of T. cruzi TIM (TcTIM) was performed and the compounds were grouped by interaction profiles. Subsequently, a selection of compounds was made based on cost and availability for in vitro evaluation against blood trypomastigotes. Finally, the compounds were analyzed by molecular dynamics simulation, and physicochemical and pharmacokinetic properties were determined using SwissADME software. A total of 1604 molecules were obtained as potential TcTIM inhibitors. BP2 and BP5 showed trypanocidal activity with half-maximal lytic concentration (LC₅₀) values of 155.86 and 226.30 µM, respectively. Molecular docking and molecular dynamics simulation analyzes showed a favorable docking score of BP5 compound on TcTIM. Additionally, BP5 showed a low docking score (−5.9 Kcal/mol) on human TIM compared to the control ligand (−7.2 Kcal/mol). Both compounds BP2 and BP5 showed good physicochemical and pharmacokinetic properties as new anti-T. cruzi agents.

Identifications of good and bad structural fragments of hydrazone/2,5-disubstituted-1,3,4-oxadiazole hybrids with correlation intensity index and consensus modelling using Monte Carlo based QSAR studies, their molecular docking and ADME analysis

The application of QSAR along with other in silico tools like molecular docking, and molecular dynamics provide a lot of promise for finding new treatments for life-threatening diseases like Type 2 diabetes mellitus (T2DM). The present study is an attempt to develop Monte Carlo algorithm-based QSAR models using freely available CORAL software. The experimental data on the α-amylase inhibition by a series of benzothiazole-linked hydrazone/2,5-disubstituted-1,3,4-oxadiazole hybrids were selected as endpoint for the model generation. Initially, a total of eight QSAR models were built using correlation intensity index (CII) as a criterion of predictive potential. The model developed from split 6 using CII was the most reliable because of the highest numerical value of the determination coefficient of the validation set (r²_VAL = 0.8739). The important structural fragments responsible for altering the endpoint were also extracted from the best-built model. With the goal of improved prediction quality and lower prediction errors, the validated models were used to build consensus models. Molecular docking was used to know the binding mode and pose of the selected derivatives. Further, to get insight into their metabolism by living beings, ADME studies were investigated using internet freeware, SwissADME.