Design, synthesis, and bioevaluation of novel unsaturated cyanoacetamide derivatives: In vitro and in silico exploration

In this study, we synthesized novel α,β-unsaturated 2-cyanoacetamide derivatives (1-5) using microwave-assisted Knoevenagel condensation. Characterization of these compounds was carried out using FTIR and 1H NMR spectroscopy. We then evaluated their in vitro antibacterial activity against both gram-positive and gram-negative pathogenic bacteria. Additionally, we employed in silico methods, including ADMET prediction and density functional theory (DFT) calculations of molecular orbital properties, to investigate these cyanoacetamide derivatives (1-5). Molecular docking was used to assess the binding interactions of these derivatives (1-5) with seven target proteins (5MM8, 4NZZ, 7FEQ, 5NIJ, ITM2, 6SE1, and 5GVZ) and compared them to the reference standard tyrphostin AG99. Notably, derivative 5 exhibited the most favorable binding affinity, with a binding energy of -7.7 kcal mol-1 when interacting with the staphylococcus aureus (PDB:5MM8), while also meeting all drug-likeness criteria. Additionally, molecular dynamics simulations were carried out to evaluate the stability of the interaction between the protein and ligand, utilizing parameters such as Root-Mean-Square Deviation (RMSD), Root-Mean-Square Fluctuation (RMSF), Radius of Gyration (Rg), and Principal Component Analysis (PCA). A 50 nanosecond molecular dynamics (MD) simulation was performed to investigate stability further, incorporating RMSD and RMSF analyses on compound 5 within the active binding site of the modeled protein across different temperatures (300, 305, 310, and 320 K). Among these temperatures, compound 5 exhibited an RMSD value ranging from approximately 0.2 to 0.3 nm at 310 K (body temperature) with the 5MM8 target, which differed from the other temperature conditions. The in silico results suggest that compound 5 maintained significant conformational stability throughout the 50 ns simulation period. It is consistent with its low docking energy and in vitro findings concerning α,β-unsaturated cyanoacetamides. Key insights from this study include:•The creation of innovative α,β-unsaturated 2-cyanoacetamide derivatives (1-5) employing cost-effective, licensed, versatile, and efficient software for both in silico and in vitro assessment of antibacterial activity.•Utilization of FTIR and NMR techniques for characterizing compounds 1-5.

Detection of Aromatic Hydrocarbons in Aqueous Solutions Using Quartz Tuning Fork Sensors Modified with Calix[4]arene Methoxy Ester Self-Assembled Monolayers: Experimental and Density Functional Theory Study

Quartz tuning forks (QTFs), which were coated with gold and with self-assembled monolayers (SAM) of a lower-rim functionalized calix[4]arene methoxy ester (CME), were used for the detection of benzene, toluene, and ethylbenzene in water samples. The QTF device was tested by measuring the respective frequency shifts obtained using small (100 µL) samples of aqueous benzene, toluene, and ethylbenzene at four different concentrations (10-12, 10-10, 10-8, and 10-6 M). The QTFs had lower limits of detection for all three aromatic hydrocarbons in the 10-14 M range, with the highest resonance frequency shifts (±5%) being shown for the corresponding 10-6 M solutions in the following order: benzene (199 Hz) > toluene (191 Hz) > ethylbenzene (149 Hz). The frequency shifts measured with the QTFs relative to that in deionized water were inversely proportional to the concentration/mass of the analytes. Insights into the effects of the alkyl groups of the aromatic hydrocarbons on the electronic interaction energies for their hypothetical 1:1 supramolecular host-guest binding with the CME sensing layer were obtained through density functional theory (DFT) calculations of the electronic interaction energies (ΔIEs) using B3LYP-D3/GenECP with a mixed basis set: LANL2DZ and 6-311++g(d,p), CAM-B3LYP/LANL2DZ, and PBE/LANL2DZ. The magnitudes of the ΔIEs were in the following order: [Au4-CME⊃[benzene] > [Au4-CME]⊃[toluene] > [Au4-CME]⊃[ethylbenzene]. The gas-phase BSSE-uncorrected ΔIE values for these complexes were higher, with values of -96.86, -87.80, and -79.33 kJ mol-1, respectively, and -86.39, -77.23, and -67.63 kJ mol-1, respectively, for the corresponding BSSE-corrected values using B3LYP-D3/GenECP with LANL2dZ and 6-311++g(d,p). The computational findings strongly support the experimental results, revealing the same trend in the ΔIEs for the proposed hypothetical binding modes between the tested analytes with the CME SAMs on the Au-QTF sensing surfaces.

Viable remediation techniques to cleansing wastewaters comprising endocrine-disrupting compounds

Endocrine-disrupting chemicals (EDCs) have recently gained prominence as emerging pollutants due to their significant negative impacts on diverse living forms in ecosystems, including humans, by altering their endocrine systems. EDCs are a prominent category of emerging contaminants in various aquatic settings. Given the growing population and limited access to freshwater resources, their expulsion from aquatic systems is also a severe issue. EDC removal from wastewater depends on the physicochemical properties of the specific EDCs found in each wastewater type and various aquatic environments. Due to these components' chemical, physical, and physicochemical diversity, various approaches based on physical, biological, electrochemical, and chemical procedures have been developed to eliminate them. The objective of this review is to provide the comprehensive overview by selecting recent approaches that showed significant impact on the best available methods for removing EDCs from various aquatic matrices. It is suggested that adsorption by carbon-based materials or bioresources is effective at higher EDC concentrations. Electrochemical mechanization works, but it requires expensive electrodes, continual energy, and chemicals. Due to the lack of chemicals and hazardous byproducts, adsorption and biodegradation are considered environmentally friendly. When combined with synthetic biology and an AI system, biodegradation can efficiently remove EDCs and replace conventional water treatment technologies in the near future. Hybrid in-house methods may reduce EDCs best, depending on the EDC and resources.