Determination of drug solubility in supercritical solvents such as CO2 has been of great importance for preparation of nanomedicines. This study implements and tunes several machine learning models ...to describe the solubility of medicine and density of solvent at various pressure and temperature. The dataset used in this study consisted of the input variables, temperature, and pressure. The methods of AdaBoost algorithm to boost the performance of base regression models for predicting the mole fractions of rivaroxaban and the density of SC-CO2 were developed. The base models used include Theil-Sen Regression (TSR), Gaussian Process Regression (GPR), Automatic Relevance Determination Regression (ARD), and Linear Regression (LR). We employ the Hunter-Prey Optimization technique to tune the hyper-parameters of these models. The results indicated that the boosted models outperform their base counterparts. For the mole fraction predictions, AdaBoost with ARD achieves an R2 value of 0.95986, while AdaBoost with GPR obtains an R2 score of 0.99817. For the SC-CO2 density predictions, AdaBoost with GPR achieves an impressive R2 of 0.99906. Accordingly, the AdaBoost with GPR is the best model for both outputs. These results demonstrate AdaBoost strength and Hunter-Prey algorithm in enhancing the predictive accuracy of regression models for these chemical properties.
This study presents a comparative analysis of three different models, namely Deep Neural Network (DNN), Quantile Regression (QR), and K-Nearest Neighbors (KNN) for the prediction of SC-CO2 density ...and solubility of rivaroxaban. The models were tuned using the Fireworks Algorithm (FWA) to optimize their hyperparameters. The dataset used in this analysis consisted of temperature (T), pressure (P), SC-CO2 density, and mole fractions of rivaroxaban. The results indicate that the DNN model exhibited outstanding performance in both prediction tasks. For the prediction of SC-CO2 density, the DNN model achieved an impressive R2 score of 0.99667, with a mean absolute error (MAE) of 7.61812E+00. Similarly, for the prediction of mole fractions of rivaroxaban, the DNN model achieved an excellent R2 score of 0.99831, with a very low MAE of 2.49870E-02. The KNN model also demonstrated good performance, with R2 scores of 0.9799 and 0.98029 for SC-CO2 density and mole fractions, respectively. However, it exhibited slightly higher MAE values compared to the DNN model. On the other hand, the QR model showed relatively lower accuracy in both prediction tasks, with R2 scores of 0.90873 and 0.87362 for SC-CO2 density and mole fractions, respectively. The QR model had higher MAE values, indicating larger average deviations from the true values. Overall, the DNN model outperformed both the KNN and QR models in predicting SC-CO2 density and mole fractions of rivaroxaban. These findings highlight the effectiveness of DNN models in accurately modeling and predicting complex chemical properties.
Chlorothiazide is a well-known diuretic and an antihypertensive drug with poor solubility and permeability and thus low bioavailability. Producing nanoparticles of this drug via a suitable ...supercritical method can enhance its therapeutic efficiency. For this purpose, supercritical solubility of Chlorothiazide must be known. At 308- 338 K and 130- 290 bar, Majrashi obtained this parameter between the mole fraction of 0.417×10-5 to 1.012×10-5. The poor supercritical solubility of Chlorothiazide can be enhanced by adding a little polar co-solvent to scCO2.
In the current study, the solubility of this drug in the ternary systems of Chlorothiazide, scCO2, and different co-solvents of ethanol, DMSO, and acetone was measured. Also, the obtained experimental data were correlated by some empirical models presented by the research teams of González, Mendez-Santiago-Teja, Li, Soltani-Mazloumi, and Jouyban.
The supercritical solubility of Chlorothiazide in the presence of ethanol, DMSO, and acetone was found in the mole fraction range of 1.115×10-5 to 11.895×10-5, 0.778×10-5 to 9.25×10-5, and 0.668 ×10-5 to 9.04×10-5, respectively. It has been shown that addition of these co-solvents can improve the supercritical solubility of Chlorothiazide, and in the meantime, ethanol with the greatest effect can increase it by about 2.02-11.75 times. Furthermore, the Joyban model has the most accuracy for the correlation of the obtained solubility data, and the data calculated by this model are more consistent with the experimental data.
For the first time at this work, the effect of three different co-solvents of ethanol, DMSO, and acetone on the solubility of Chlorothiazide in scCO2 was studied both experimentally and theoretically.
Vascular endothelial growth factor receptor-2 (VEGFR-2) plays a critical role in cancer angiogenesis. Inhibition of VEGFR-2 activity proved effective suppression of tumour propagation. Accordingly, ...two series of new 3-methylquinoxaline derivatives have been designed and synthesised as VEGFR-2 inhibitors. The synthesised derivatives were evaluated in vitro for their cytotoxic activities against MCF-7and HepG2 cell lines. In addition, the VEGFR-2 inhibitory activities of the target compounds were estimated to indicate the potential mechanism of their cytotoxicity. To a great extent, the results of VEGFR-2 inhibition were highly correlated with that of cytotoxicity. Compound 27a was the most potent VEGFR-2 inhibitor with IC
50
of 3.2 nM very close to positive control sorafenib (IC
50
= 3.12 nM). Such compound exhibited a strong cytotoxic effect against MCF-7 and HepG2, respectively with IC
50
of 7.7 and 4.5 µM in comparison to sorafenib (IC
50
= 3.51 and 2.17 µM). In addition, compounds 28, 30f, 30i, and 31b exhibited excellent VEGFR-2 inhibition activities (IC
50
range from 4.2 to 6.1 nM) with promising cytotoxic activity. Cell cycle progression and apoptosis induction were investigated for the most active member 27a. Also, the effect of 27a on the level of caspase-3, caspase-9, and BAX/Bcl-2 ratio was determined. Molecular docking studies were implemented to interpret the binding mode of the target compounds with the VEGFR-2 pocket. Furthermore, toxicity and ADMET calculations were performed for the synthesised compounds to study their pharmacokinetic profiles
Piper betle L. is widely distributed and commonly used medicinally important herb. It can also be used as a medication for type 2 diabetes patients. In this study, compounds of P. betle were screened ...to investigate the inhibitory action of alpha-amylase and alpha-glucosidase against type 2 diabetes through molecular docking, molecular dynamics simulation, and ADMET (absorption, distribution, metabolism, excretion, and toxicity) analysis. The molecule apigenin-7-O-glucoside showed the highest binding affinity among 123 (one hundred twenty-three) tested compounds. This compound simultaneously bound with the two-target proteins alpha-amylase and alpha-glucosidase, with high molecular mechanics-generalized born surface area (MM/GBSA) values (ΔG Bind = −45.02 kcal mol−1 for alpha-amylase and −38.288 for alpha-glucosidase) compared with control inhibitor acarbose, which had binding affinities of −36.796 kcal mol−1 for alpha-amylase and −29.622 kcal mol−1 for alpha-glucosidase. The apigenin-7-O-glucoside was revealed to be the most stable molecule with the highest binding free energy through molecular dynamics simulation, indicating that it could compete with the inhibitors’ native ligand. Based on ADMET analysis, this phytochemical exhibited a wide range of physicochemical, pharmacokinetic, and drug-like qualities and had no significant side effects, making them prospective drug candidates for type 2 diabetes. Additional in vitro, in vivo, and clinical investigations are needed to determine the precise efficacy of drugs.
Coronavirus disease 2019 (COVID-19) is caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), resulting in a contagious respiratory tract infection that has become a global burden ...since the end of 2019. Notably, fewer patients infected with SARS-CoV-2 progress from acute disease onset to death compared with the progression rate associated with two other coronaviruses, SARS-CoV and Middle East respiratory syndrome coronavirus (MERS-CoV). Several research organizations and pharmaceutical industries have attempted to develop successful vaccine candidates for the prevention of COVID-19. However, increasing evidence indicates that the SARS-CoV-2 genome undergoes frequent mutation; thus, an adequate analysis of the viral strain remains necessary to construct effective vaccines. The current study attempted to design a multi-epitope vaccine by utilizing an approach based on the SARS-CoV-2 structural proteins. We predicted the antigenic T- and B-lymphocyte responses to four structural proteins after screening all structural proteins according to specific characteristics. The predicted epitopes were combined using suitable adjuvants and linkers, and a secondary structure profile indicated that the vaccine shared similar properties with the native protein. Importantly, the molecular docking analysis and molecular dynamics simulations revealed that the constructed vaccine possessed a high affinity for toll-like receptor 4 (TLR4). In addition, multiple descriptors were obtained from the simulation trajectories, including the root-mean-square deviation (RMSD), root-mean-square fluctuation (RMSF), solvent-accessible surface area (SASA), and radius of gyration (
R
g
), demonstrating the rigid nature and inflexibility of the vaccine and receptor molecules. In addition, codon optimization, based on
Escherichia coli
K12, was used to determine the GC content and the codon adaptation index (CAI) value, which further followed for the incorporation into the cloning vector pET28+(a). Collectively, these findings suggested that the constructed vaccine could be used to modulate the immune reaction against SARS-CoV-2.
COVID-19 is caused by SARS-CoV-2, resulting in a contagious respiratory tract infection. For designing a multi-epitope vaccine, we utilized the four structural proteins from the SARS-CoV-2 by using bioinformatics and immunoinformatics analysis.
Pseudomonas aeruginosa is an opportunistic bacterium causing several health problems and having many virulence factors like biofilm formation on different surfaces. There is a significant need to ...develop new antimicrobials due to the spreading resistance to the commonly used antibiotics, partly attributed to biofilm formation. Consequently, this study aimed to investigate the anti-biofilm and anti-quorum sensing activities of Dioon spinulosum, Dyer Ex Eichler extract (DSE), against Pseudomonas aeruginosa clinical isolates. DSE exhibited a reduction in the biofilm formation by P. aeruginosa isolates both in vitro and in vivo rat models. It also resulted in a decrease in cell surface hydrophobicity and exopolysaccharide quantity of P. aeruginosa isolates. Both bright field and scanning electron microscopes provided evidence for the inhibiting ability of DSE on biofilm formation. Moreover, it reduced violacein production by Chromobacterium violaceum (ATCC 12,472). It decreased the relative expression of 4 quorum sensing genes (lasI, lasR, rhlI, rhlR) and the biofilm gene (ndvB) using qRT-PCR. Furthermore, DSE presented a cytotoxic activity with IC
of 4.36 ± 0.52 µg/ml against human skin fibroblast cell lines. For the first time, this study reports that DSE is a promising resource of anti-biofilm and anti-quorum sensing agents.
Vandetanib (Caprelsa
; VNB) is a prescription medicine that is used for the treatment of medullary thyroid cancer that has disrupted other body parts or that cannot be removed by surgery. It is ...considered a tyrosine kinase inhibitor (TKI). Fast, sensitive and validated HPLC-UV was established for VNB quantification in pure human biological fluids (urine and plasma) and human liver microsomes (HLMs). This analytical methodology was applied also to the metabolic stability assessment of VNB. This method was performed using a phenyl column (250 mm × 4.6 mm id, 5 µm particle size). A sodium dodecyl sulphate solution (0.05 M, pH 3.0 using 0.02 M orthophosphoric acid) containing 0.3% triethylamine and 10% n-butanol was used as a mobile phase and was pumped isocratically at a flow rate of 0.7 mL/min and at a 260 nm detection wavelength. The total elution time was 6 min with an injection volume of 20 μL. The linearity of the established methodology ranged from 30 to 500 ng/mL in pure form and 50 to 500 ng/mL (r
≥ 0.9994) in human biological fluids and HLMs. No significant interference from the matrix components was observed. The proposed methodology revealed the benefits of being green, reliable and economic.
Alkaloids are a complex class of biologically active compounds with a broad spectrum of health-related applications. Particularly the alkaloids of indole, steroidal, terpenoids, isoquinoline, and ...bisbenzylisoquinoline have been extensively investigated. Ultimately, substantial advancement has been highlighted in the investigation of chemical constituents and the therapeutic benefits of plant alkaloids, particularly during the last ten years. A total of 386 alkaloids have been isolated from over 40 families, including Apocynaceae, Annonaceae, Rubiaceae, Menispermaceae, Ranunculaceae, Buxaceae, Papaveraceae, Magnoliaceae, Rutaceae and Phyllanthaceae. This paper will investigate several alkaloids that have been isolated from botanical medicines as well as offer an in-depth analysis of their cytotoxic properties.
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