BMC Chemistry最新文献

Gliomas, particularly glioblastoma (GBM), are highly aggressive brain tumors with poor prognosis and high recurrence rates. This underscores the urgent need for novel therapeutic approaches. One promising target is Focal adhesion kinase (FAK), a key regulator of tumor progression currently in clinical trials for glioma treatment. Drug development, however, is both challenging and costly, necessitating efficient strategies. Computer-Aided Drug Design (CADD), especially when combined with machine learning (ML), streamlines the processes of virtual screening and optimization, significantly enhancing the efficiency and accuracy of drug discovery. Our study integrates ML, docking analysis, ADMET (absorption, distribution, metabolism, elimination, and toxicity) studies to identify novel FAK inhibitors specific to GBM. Predictive models showed strong performance, with an R² of 0.892, MAE of 0.331, and RMSE of 0.467 using protein-level IC₅₀ data in combined CDK, CDK extended fingerprints, and substructure fingerprint counts derived from 1280 FAK inhibitors. Another model, based on IC₅₀ data from 2608 compounds tested on U87-MG cells, achieved an R² of 0.789, MAE of 0.395, and RMSE of 0.536. Using these models, we efficiently identified 275 potentially active compounds out of 5107 candidates. Subsequent ADMET analysis narrowed this down to 16 potential FAK inhibitors that meet the established drug-likeness criteria. Moreover, molecular dynamics (MD) simulations validated the stable binding interactions between the selected compounds and the FAK protein. This study highlights the effectiveness of combining ML, docking analysis, and ADMET studies to rapidly identify potential FAK inhibitors from large databases, providing valuable insights for the systematic design of FAK inhibitors.

Novel univariate and chemometrics-aided UV spectrophotometric methods were tailored to undergo the fundamentals of green and white analytical chemistry for the simultaneous estimation of a ternary mixture of olanzapine (OLA), fluoxetine HCL (FLU), and its toxic impurity 4-(Trifluoromethyl) phenol (FMP) without any prior separation. The dual-wavelength ratio spectrum univariate method was used to determine OLA and FLU in the presence of FMP in the range of (4–20) and (5–50) μg/ml, respectively. In compliance with the International Conference on Harmonization (ICH) standards, the technique was validated and established Remarkable accuracy (98–102%) and precision (< 2%) with limits of quantification (LOQs) of 0.432 and 2.002 μg/ml, respectively. Partial least squares (PLS) and artificial neural networks (ANNs) are chemometric methodologies that have advantages over the univariate method and use significant innovations employing Latin hypercube sampling (LHS), allowing the generation of a reliable validation set to guarantee the effectiveness and sustainability of these models. The concentration ranges used were (2–20), (2–20), and (5–50) μg/ml; for PLS, the LOQs were 0.602, 0.508, and 1.429 μg/ml, and the root mean square errors of prediction (RMSEPs) were 0.087, 0.048, and 0.159 for OLA, FMP, and FLU, respectively; and for ANNs, the LOQs were 0.551, 0.465, and 0.965 μg/ml, with RMSEPs of 0.056, 0.047, and 0.087 for OLA, FMP, and FLU, respectively. The developed methods yield a greener National Environmental Methods Index (NEMI) with an eco-scale assessment (ESA) score of 90 and a complementary Green Analytical Procedure Index (complex GAPI) in quadrants with an analytical greenness metric (AGREE) score of 0.8. The Red‒Green–Blue 12 algorithm (RGB 12) scored 88.9, outperforming on reported methods and demonstrating widespread practical and environmental approval. Statistical analysis revealed no noteworthy differences (P > 0.05) among the proposed and published techniques. Both pure powders and pharmaceutical capsules were analyzed via these methods.

Arsenic species have been known for their toxic impact on human. Therefore, removal of such pollutant requires efficient and effective removal methodology from polluted water. In this study, bismuthene quantum dots (Bi-ene-QDs) were fabricated by a green and facile one pot-hydrothermal conversion reaction of Bi(NO₃)₃·5H₂O. Bi-ene-QDs exhibited semi-spherical crystalline providing 6.0 nm 157.78 m²/g. Consequently, As(V) capturing by Bi-ene-QDs revealed optimum practical conditions at pH 3, interaction duration time 40 min and 10 mg Bi-ene-QDs dosage. The interaction of As(V) ions with Bi-ene-QDs were confirmed by the appearance of As-O stretching vibration. Moreover, Bi-ene-QDs achieved excellent adsorptive capture percentages of Arsenic ions from sea, tap and wastewater providing 94.61, 95.21 and 94.38% from contaminated samples with 5 mg L⁻¹ Arsenic ions. Therefore, Bi-ene-QDs can be categorized as an unprecedented and efficient nanosorbent for the successful removal of Arsenic ions pollution from various wastewater matrices with > 90.0% efficiency.

The availability of well-established analytical methods is crucial to cope with the fast-ongoing research for the development of new drug delivery formulations. In this work, a rapid highly green chromatographic method was developed for the simultaneous determination of nicotine (NIC) and caffeine (CAF) to be applied for an in-vitro release study from a newly prepared quick mist mouth spray co-formula (QMS), as a complementary synergistic fast-onset relief of cravings during smoking cessation. The chromatographic resolution was accomplished on a cyano column using isocratically delivered (1.0 mL/ min) glycerol: orthophosphoric acid (OPA) (0.2 M) adjusted to pH 3.0 using 0.05 M triethylamine (5:95, v/v) and UV detection at 260 nm. Well resolved peaks of NIC and CAF were eluted at 2.1 and 3.9 min (Rs = 5.64), with linear responses between 0.1 and 20.0 µg/mL and 0.2–40.0 µg/mL, and detection limits of 0.03 and 0.07 µg/mL for NIC and CAF, respectively. The developed method showed good analytical performance (accuracy, precision, robustness, and selectivity) as well as superiority in practicality and ecological profile compared to reported methods applying GAPI, analytical eco-scale, AGREE, BAGI, and whiteness metric tool. The developed method was successfully applied for NIC and CAF determination in their pharmaceutical preparations, and artificial saliva with no significant differences from reported method results (F-test and t-test). Moreover, an in-vitro release study of NIC and CAF from QMS was performed employing the developed method that revealed diffusion-controlled release, compared to mixed diffusion/ polymer chain relaxation for marketed single component formulation, showing the superiority of QMS in reducing drug level fluctuations of NIC and CAF and improving their bioavailability.

Graphical Abstract

The process of removing sulfur compounds and aromatic compounds to produce clean fuel is an important and effective contribution to the processes of mitigating and adapting to climate change. In contrast, it is necessary to find an innovative way to remove sulfur and carcinogenic aromatic compounds because clean, low-sulfur diesel is commonly used in all countries of the world at the present time. Therefore, in this work, we have studied the effect of the microwave radiation power and the irradiation time with the use of more than one type of organic solvent; methanol, acetonitrile and ethyl acetoacetate; as an extractant and solvent to feed ratio impact on the removal of sulfur and aromatic compounds of a real diesel fuel feed which has 450 ppm sulfur content and 16 wt% aromatic Content. The results showed that the best solvent used during this work was ethyl acetoacetate. According to the results, high sulfur removal (≈ 92%) was accomplished with microwave-assisted extractive desulfurization technique under the following ideal conditions: the irradiation time is 7 min, the solvent feed ratio is 3:1 and the microwave intensity is 180 W. To reveal the mechanism of microwave-assisted extractive desulfurization via different organic solvents, a theoretical study including structural examination and interaction energy analysis on the interaction between dibenzothiophene (DBT) or dimethyl dibenzothiophene (DMDBT) and the different organic solvents was also conducted.

Melanin nanoparticles (MNPs) are a type of electronegative compound that can be used as photothermal agent for cancer treatment. Nevertheless, the agglomeration of MNP, which is one of the limitations in practice, contributes to the instability of MNP. Pristine layered double hydroxide (LDH), as a kind of positive inorganic material when there exist no other cargo between its layers, can accommodate electronegative molecules between its layers to endow them with stable properties. Hence, in this study, electronegative MNP was intercalated into LDH lamellas via ion-exchange method to obtain the stable original photothermal agent LDH/MNP, solving the tough problem of MNP’s agglomeration. The surface morphology, X-ray diffraction and fourier transform infrared spectra affirmed the successful intercalation of MNP between LDH lamellas. The Z-average particle sizes of LDH/MNP on day 0, 7 and 14 were measured as 221.8 nm, 227.6 nm and 230.5 nm without obvious fluctuation, while the particle sizes of MNP went through dramatic enlargement from 105.8 nm (day 0) to 856.1 nm (day 7), indicating the better stability of LDH/MNP than MNP. The typical polymer dispersity index (PDI) values on day 0, 7 and 14 verified the better stability of LDH/MNP, too. Photothermal properties of LDH/MNP were assessed and the results ensured the representative photothermal properties of LDH/MNP. The fine cytocompatibility of LDH/MNP was verified via cytotoxicity test. Results confirmed that the agglomeration of MNP disappeared after its intercalation into LDH and LDH/MNP possessed fine stability as well as typical photothermal property. The intercalation of MNP into LDH gave the photothermal agent MNP a promising way for its better stability and long-term availability in photothermal treatment.

The development of two eco-friendly analytical methods for the simultaneous determination of eight cardiovascular drugs; hydrochlorothiazide (HCT), captopril (CPL), lisinopril (LSP), valsartan (VAL), atorvastatin (ATR), bisoprolol (BSL), amlodipine (AML) and carvedilol (CVL); alongside with the nutraceutical vincamine (VIC) is essential for sustainable pharmaceutical analysis. This study explores the application of Micellar Electro Kinetic Chromatography (MEKC) and High-Performance Liquid Chromatography (HPLC) for this purpose. In MEKC method, the separation was done using fused silica capillary (41.5 cm × 50 µm id) and a back ground electrolyte consisting of 50 mM borate buffer (pH 9) containing 50 mM sodium lauryl sulphate (SLS) and 10% organic modifier (Acetonitrile). In HPLC method, separation was performed on a ZORBAX Extend-C18 (4.6 × 250 mm, 5 µm) column, using a gradient mobile phase consisting of 50 mM phosphate buffer pH 3 and methanol. Both methods attained good linearity (r ≥ 0.9996) with low values of LOD and LOQ. Both methods were successfully applied in the determination of co-administered single, binary and ternary dosage form of the studied drugs. Moreover, application of various combinations of co-administered dosage forms was achieved in rat plasma, confirming the applicability of these methods in different matrices. The use of micellar solutions in MEKC enhances separation efficiency while reducing the need for organic solvents, aligning with green chemistry principles. HPLC methods were optimized using environmentally benign solvents, ensuring reduced toxicity and waste production. The methodologies were evaluated through green, white, and blue metrics to ensure comprehensive sustainability, considering ecological impact, safety, and practical efficiency. These methods were not only cost-effective and time-saving but achieved high efficiency, sensitivity, and reproducibility making them ideal for routine use in pharmaceutical analysis.

Ectoine (ECT) has recently gained considerable interest in the healthcare sector due to its promising therapeutic benefits in a variety of human disorders. This research aimed to quantify the ECT plasma level in rats by creating and optimizing a sensitive and validated UPLC-MS/MS method. Prior to analysis, ECT extraction from the plasma samples was conducted via a protein precipitation procedure, using hydroxyectoine as an internal standard (IS). A 1.7 μm UPLC C8 column (100 mm × 2.1 mm) was selected for the chromatographic separation, using a gradient mobile phase consisting of acetonitrile and 0.05% formic acid. The electrospray ionization mass spectrometry (ESI-MS) was used to detect ECT in the positive ion mode. To determine the specific precursor and the product ions of ECT, multiple reaction monitoring (MRM) methods were carried out. The selected ion pair of ECT was 143.1 > 97 and 159.1 > 113.13 for the IS. The ECT’s linearity range in rat plasma was found to be 1-1000 ng/mL, with a recovery rate of 96.48–97.37%. Consistent with FDA guidelines for bio-analytical method validation, the suggested method was validated. The method was efficiently employed to quantify the studied drug in spiked rat plasma with good accuracy and precision with no significant matrix effects. Furthermore, it was effectively used to investigate the pharmacokinetic behavior of ECT in rats after a single oral dose of 30 mg/kg.

New generation of electrochemical energy storage devices (EESD) such as supercapattery is being intensively studied as it merges the ideal energy density of batteries and optimal power density of supercapacitors in a single device. A multitude of parameters such as the method of electrodes preparation can affect the performance of supercapattery. In this research, nickel doped tin sulfide /tin oxide (SnS@Ni/SnO₂) heterostructures were grown directly on the Ni foam and subjected to different calcination temperatures to study their effect on formation, properties, and electrochemical performance through X-ray diffraction (XRD), field emission scanning electron microscopy (FESEM), and electrochemical tests. The optimized SnS@Ni/SnO₂ electrode achieved a maximum specific capacity of 319 C g^− 1 while activated carbon based capacitive electrode exhibited maximum specific capacitance of 381.19 Fg^− 1. Besides, capacitive electrodes for the supercapattery were optimized by incorporating different conductive materials such as acetylene black (AB), carbon nanotubes (CNT) and graphene (GR). Assembling these optimized electrodes with the aid of charge balancing equation, the assembled supercapattery was able to achieve outstanding maximum energy density and power density of 36.04 Wh kg^− 1 and 12.48 kW kg^− 1 with capacity retention of 91% over 4,000 charge/discharge cycles.

Povidone-iodine is identified as one of the widely applicable antiseptic reagents for treatment of skin infection and wound healing. Controllable releasing of povidone-iodine is extensively required for healing of chronic wounds. The release of povidone-iodine was systematically studied from the composites based on carboxymethyl starch (CMS). Currently, different ratios from copper precursor and L-aspartic acid (L-AA) were interacted with CMS to obtain Cu-L-AA@CMS composites. Increment the percentage of L-AA was reflected in clustering of dense masses from the desirable composite with highly crystalline/stable structural network. Regardless to pH conditions, Cu-L-AA(30%)@CMS composite showed the highest efficiency for controllable release of povidone-iodine, whereas, the release percentages were estimated to be 58%, 32% and 18% at pH 5, 7 and 9, respectively. The kinetic results revealed the impossibility of povidone-iodine releasing via diffusion/erosion for further support of the hypothesis of releasing via swelling process. Moreover, the release of povidone-iodine using column technique showed that the lowest release was estimated at using high rate of 6 mL/min. Besides the biocompatibility and biodegradability of the prepared Cu-L-AA@CMS composites, it showed the superiority for controllable release of povidone-iodine antiseptic reagent to regulate its beneficial effect in curing of the skin.