Molecular Interactions Research Articles

A paradigm for natural eutectic solvents based on fatty acids: Molecular interactions and toxicological considerations

In this work, we present experimental and molecular modeling results on archetypal hydrophobic natural deep eutectic solvents (NADES) based on fatty acids (octanoic and dodecanoic acid) and menthol, a representative monoterpenoid. Our goal is to provide a multiscale characterization to enhance the understanding of this field by studying these selected archetypical mixtures. We examine their liquid state properties, intermolecular forces, nanoscopic arrangements, toxicity, and environmental impact.The computational study integrates quantum chemistry, molecular dynamics (both all-atom and coarse-grained approaches), and thermodynamic modeling (COSMO-RS approach) to analyze the fluids and their interactions with biological entities, such as proteins and plasma membranes. The experimental characterization focuses on elucidating intermolecular interactions and liquid phase dynamics using NMR spectroscopy, visible and UV resonance Raman spectroscopy (UVRR). Notably, this is the first report of UVRR data on NADES.Additionally, we simulate the effect of the molecular moieties forming the solvents on biological targets—specifically, protein and cell membrane models –. This in silico analysis aims to rationalize and predict their potential toxicity.Overall, our experimental findings and in silico simulations contribute to a deeper understanding of these novel solvents in terms of their network of interactions. Additionally, they highlight the potential impact on biological targets, providing new data to accurately define the eco-friendliness of type V DES and their suitability as sustainable alternatives to traditional molecular solvents.

Optimization of solvent cooling crystallization process for separating phenanthrene from 9-fluorenone by COSMO-RS and solubility calculation approach

Phenanthrene (Phe) and fluorene (Flu) are crucial chemical intermediates with applications in materials, medicine, and pesticides. However, conventional separation methods struggle to effectively isolate phenanthrene from fluorene due to their similar physical properties. To address this challenge, a reaction–separation coupling technique was employed to convert fluorene into 9-fluorenone (9-Fluo), followed by the separation of phenanthrene from 9-fluorenone using solvent-cooling crystallization. Initially, the relative solubilities of phenanthrene and 9-fluorenone in 2072 solvents were calculated using COSMO-RS for preliminary screening. Among various conventional short-chain aliphatic alcohols and low-carbon saturated hydrocarbons, methanol, and cyclohexane were identified as the most effective solvents based on their solubility selectivity (SS). The molecular interactions between phenanthrene or 9-fluorenone and these solvents were analyzed using theoretical methods such as σ-potential/profile, infinite dilution activity coefficients in COSMO-RS, and Hansen solubility parameters, with further confirmation from FTIR tests. The optimal liquid–solid ratios were determined using both phase diagram measurements and solubility calculations. The reaction conversion of fluorene to 9-fluorenone was complete regardless of the raw material used. phenanthrene and 9-fluorenone were effectively separated using methanol and cyclohexane with optimum liquid–solid mass ratios of 1.6:1 and 2.8:1, respectively. In the model mixture, the contents of phenanthrene and 9-fluorenone exceeded 98 wt%, with yields above 91 wt%. For anthracene residue, the content of 9-fluorenone reached 93.98 wt% with a yield of 84.52 wt%, while its content was only 76.58 wt% due to the accumulation of other components in phenanthrene.

Improved qualities of cod-rice dual-protein gel as affected by rice protein: Insight into molecular flexibility, protein interaction and gel properties

Blending plant-based proteins with animal-based proteins to achieve adequate dietary protein intake is a strategy to address dietary deficiencies in the elderly. This research systematically investigated the effect of the ratio of cod protein/rice protein (21:0, 21:1.5, 21:3, 21:4.5, 21:6, 21:7.5, and 21:9) on the gelation properties of dual-protein gels and the underlying dual-protein interaction mechanisms. The results indicated that the myosin heavy chain (MHC) of cod and the glutelin in rice protein are primarily linked by hydrogen bonds, particularly involving Tyr residues, as evidenced by molecular docking and fluorescence quenching results. The addition of rice protein in cod protein promoted α-helix transforming into β-sheet, β-turn and random coil of the original protein solution, which was significantly correlated with molecule flexibility increasing. The decrease in the dual-protein particle size, and rice protein uniformly distributed in a cod protein-based gel network, which promoted the compactness and density of the gel structure. It was found that the hardness and springiness of 21:6 cod-rice protein gel increased by 73.96% and 17.28% compared to single cod gel, respectively. This study provides theoretical basis to the mechanism of dual-protein interaction affecting gel properties from the molecular level.

Synthesis, structural studies and Hirshfeld surface analysis of the substituted isoindole-1,3-dione derivatives

In this study, we have performed the ring-opening reaction of 5-benzyl/ethyl-2-hydroxyhexahydro-4H-oxireno[2,3-e] isoindole-4,6(5H)-dione (10) with HBr to the corresponding bromodiols, regioselectively. Structures of the synthesized compounds are elucidated through spectral methods (1H-NMR,13C-NMR and HRMS) Afterwards, the racemic products 11a-b were purified and the absolute geometries of 5-bromo-2-ethyl-4,6-dihydroxyhexahydro-1H-isoindole 1,3(2H)-dione (11a) and 2-benzyl-5-bromo-4,6-dihydroxyhexahydro-1H-isoindole-1,3(2H)-dione (11b) was determined by X-ray diffraction analysis. Effective O−H∙∙∙O (2.738-2.874 Å) hydrogen bonds between diol and ketone units are important interactions between the molecules. Hirshfeld surface analyses of the compounds (11a-b) have provided further insights into molecular, crystal structure and intermolecular interactions. The results indicated that the most important contributions for the crystal packings are from H∙∙∙H, O∙∙∙H/H∙∙∙O, C∙∙∙H/H∙∙∙C and Br∙∙∙H/H∙∙∙Br interactions. Finally, energy frameworks were analyzed to a better understanding of the packing of crystal structure and the supramolecular rearrangements for the structures (11a-b).

Selective Detection of Picric Acid by Benzodiazepine Containing Enaminone Core as Receptor and Its Application to Real Water Sample Analysis.

Nitroaromatic compounds are highly explosive and illegitimate substances. Over a decade, chemists have been affianced in extensive research on the selective and sensitive detection of these nitroaromatic explosives for homeland security and environmental protection. The benzodiazepine-based enaminone (BDE) receptor has been synthesized by aqueous extract of onion catalyzed three-component reaction between o-phenylenediamine, dimedone with an aldehyde. The BDE probe is well analyzed and applied to a sensor that selectively detects picric acid (PA). UV-Vis and fluorescence spectroscopy were used to investigate the photophysical responses of the receptor (BDE). From the observed results BDE found turn-off fluorescence with the addition of picric acid and the lowest limit of detection and limit of quantification was achieved about 24.6 nM and 73.8 nM. The fluorescence quantum yield was attained about 0.28. The BDE-PA adduct formation was confirmed by 1H NMR titration analysis. The Job's plot analysis was performed through 1H NMR titrations and established the binding stoichiometry ratio of the BDE-PA adduct as 1:1 ratio. Further, DFT calculations supported the observed photophysical responses of BDE-PA adduct to confirm the molecular level interactions. The receptor was effectively applied to approximate level of picric acid in real water sample analysis.

The impact of host genetics on microbe assemblages in three types of mrigal carp (Cirrhinus mrigala)

Host–microbiota interactions are molecular and physical interactions between the microbiota and the host that play significant roles in the lifespan of animals. In the present study, two types of gynogenetic mrigal carp (GMCC and GMCW) and the original maternal mrigal carp (MC) were used as a models to investigate host–microbiota interactions. The two types of gynogenetic mrigal carps showed faster growth and better cold tolerance than the MC fish. Compared to those in MC, a large number of goblet cells and higher activity of cellulase and pepsin were detected in the intestine of gynogenetic fish. The composition and abundance of the microbial communities significantly differed among the three types of mrigal carp and water, with Proteobacteria, Firmicutes and Chloroflexi being the most dominant microbes in the GMCC, GMCW and MC fish, respectively. Pseudomonas, Lactococcus and Defluviicoccus were the biomarker genera in the GMCC, GMCW and MC fish. Network analysis revealed no relationships between fish and water, but the dominant genera was positively correlated with the abundance of certain enzymes. Functional analysis revealed the dominant genera associated with amino acid metabolism, fatty acid metabolism and bile acid biosynthesis. Our results suggested that host genetics may affected gut microbe assembly and that the specific metabolic functions of gut microbes may contribute to growth performance through the microbe-gut-liver axis.

Fish behavior recognition based on an audio-visual multimodal interactive fusion network

In light of the challenges imposed by fish behavior recognition, which arise from environmental noise and dim lighting in aquaculture environments and adversely affect the effectiveness of unimodal recognition methods based on either sound or visual cues, this paper proposes a fish behavior recognition model, Mul-SEResNet50, based on the fusion of audio and visual information. To address issues such as image blurring and indistinct sounds in aquaculture environments, which hinder the effectiveness of multimodal fusion and complementary modalities, a multimodal interaction fusion (MIF) module is introduced. This module integrates audio-visual modalities at multiple stages to achieve a more comprehensive joint feature representation. To enhance complementarity during the fusion process, we designed a U-shaped bilinear fusion structure to fully utilize multimodal information, capture cross-modal associations, and extract high-level features. Furthermore, to address the potential loss of key features, a temporal aggregation and pooling (TAP) layer is introduced to preserve more fine-grained features by extracting both the maximum and average values within pooling regions. To validate the effectiveness of the proposed model, both ablation experiments and comparative experiments are conducted. The results demonstrate that Mul-SEResNet50 achieves a 5.04% accuracy improvement over SEResNet50 without sacrificing detection speed. Compared to the state-of-the-art U-FusionNet-ResNet50+SENet model, Mul-SEResNet50 achieves accuracy and F1 score improvements of 0.47% and 1.32%, respectively. These findings confirm the efficacy of the proposed model in terms of accurately recognizing fish behavior, facilitating the precise monitoring of fish behavior.

Prolonged Skin Retention of Luliconazole from SLNs Based Topical Gel Formulation Contributing to Ameliorated Antifungal Activity.

The development of effective therapy is necessary because the patients have to contend with long-termtherapy as skin fungal infections usually relapse and are hardly treated. Despite being a potent antifungal agent, luliconazole (LCZ) has certainshortcomings such as limited skin penetration, low solubility in aqueous medium, and poor skin retention. Solid Lipid Nanoparticles (SLNs) were developed using biodegradable lipids by solvent injection method and were embodied into the gel base for topical administration. After in-vitro characterizations of the formulations, molecular interactions of the drug with excipients were analyzed using in-silico studies. Ex-vivo release was determined in contrast to the pure LCZ and the commercial formulation followed by in-vivo skin localization, skin irritation index, and antifungal activity. The prepared SLNs have an average particle size of 290.7nm with no aggregation of particles and homogenous gels containing SLNs with ideal rheology and smooth texture properties were successfully prepared. The ex-vivo LCZ release from the SLN gel was lower than the commercial formulation whereas its skin deposition and skin retention were higher as accessed by CLSM studies. The drug reaching the systemic circulation and the skin irritation potential were found to be negligible. Thesolubility and drug retention in the skin were both enhanced by the development of SLNs as a carrier. Thus, SLNs offer significant advantages by delivering long lasting concentrations of LCZ at the site of infection for a complete cure of the fungal load together with skin localization of the topical antifungal drug.

Elucidating molecular interaction leading to successful grafting of in vitro regenerated shoots of three chickpea (Cicer arietinum L.) cultivars

Elucidating molecular interaction leading to successful grafting of in vitro regenerated shoots of three chickpea (Cicer arietinum L.) cultivars

Integrated analysis of metabolomic and transcriptomic profiles elucidates the core role of glycerophospholipid metabolism in hypertension related to metabolic syndrome

BackgroundMetabolic syndrome (MetS) represents a comprehensive framework that encompasses conditions such as diabetes, hypertension (HBP), obesity, and dyslipidemia. MetS without hypertension significantly contributes to the development of refractory hypertension. However, the underlying molecular regulatory mechanisms of hypertension associated with MetS remain incompletely elucidated. The objective of this study was to identify differences in plasma metabolome and leukocyte transcriptome profiles between patients with MetS comorbid HBP compared to those with MetS with hypertension and HBP alone. MethodsIn this study, whole blood samples were collected from 104 participants, including patients with HBP, MetS without hypertension (MS), and MetS with hypertension (MS-HBP). Ultra-high-performance liquid chromatography was employed to perform metabolomic analysis of plasma samples. Comparative analysis was conducted to identify distinct metabolites among the three groups, while MetaboAnalyst 5.0 was utilized for enrichment and pathway analysis. Clinical correlation analysis and receiver operating characteristic analyses were applied to select biomarker metabolites for MS-HBP. Transcriptomic profiling of white blood cells was performed to identify dysregulated genes and KEGG/GO pathways. Integrative analysis of metabolomics and transcriptomics was used to construct molecular interaction networks. Finally, blood pressure was monitored every 2 weeks during the treatment period for experimental validation. ResultsThe metabolomic results indicated that lipid metabolic pathways, particularly glycerophospholipid metabolic pathways, played a crucial role in MS-HBP. The area under the curve of tryptophan-isoleucine for diagnosis in the MS-HBP group was 0.82. Tryptophyl-isoleucine demonstrated a negative correlation with both HbA1c and diastolic blood pressure. Transcriptomic analysis revealed the involvement of MS-HBP in numerous immune and inflammatory pathways. Furthermore, the integrated analysis of metabolomic and transcriptomic data emphasized the importance of glycerophospholipid metabolism in MS-HBP. PPC exhibited a comparable effect on lowering blood pressure in SHR rats. ConclusionThe findings of this study demonstrated that glycerophospholipid metabolism plays a pivotal role in the pathophysiological processes of MS-HBP, providing novel insights into early clinical diagnosis and the optimization of therapeutic strategies.

Chemical Composition, In vitro and In silico Evaluation of Essential Oil from Ocimum tenuiflorum and Coriandrum sativum Linn for Lung Cancer.

Medicinal plants play an essential role in everyday life; plants highly contain therapeutic phytoconstituents commonly used to treat various diseases. This paper discusses the Chemical composition, In vitro antiproliferative activity and In silico study of essential oil extracted from Ocimum tenuiflorum (family Lamiaceae) and Coriandrum sativum (family Apiaceae). In present study GC-MS was used to identify the chemical constituents from O. tenuiflorum and C. sativum. In vitro antiproliferative activity was performed on A549 cancer cell lines. In silico study was performed by Schrodinger's maestro software to identify chemical constituents in both plants as potential EGFR inhibitors for the treatment of lung cancer. The essential oil was extracted by hydro distillation from aerial parts of O. tenuiflorum and C. sativum. The volatile oil sample was analyzed by (GC-MS) Gas Chromatography- Mass Spectrometry. Different chemical constituents were identified based on the retention index and compared with the NIST library. The oil samples from O. tenuiflorum and C. sativum was also evaluated for antiproliferative activity against human lung cancer A549 cell lines. In silico study was performed by Schrodinger maestro software against EGFR (PDB ID 5HG8). O. tenuiflorum essential oil contains Eugenol (42.90%), 2-β-Elemene (25.98%), β- Caryophyllene (19.12%) are the major constituents. On the other side, C. sativum contains nnonadecanol- 1 (16.37%), decanal (12.37%), dodecanal (12.27%), 2-Dodecanal (9.67%), Phytol (8.81%) as the major constituents. Both the oils have shown in vitro antiproliferative activity against human lung cancer cell lines A549 having IC50 values of 38.281 μg/ml (O. tenuiflorum) and 74.536 μg/ml (C. sativum). Molecular interactions of constituents hydro distilled from two oils was analysed by schrodinger maestro software against EGFR (PDB ID 5HG8). The oil sample extracted from O. tenuiflorum showed more antiproliferative activity than C. sativum. In silico study showed that two chemical constituents, namely di-isobutyl phthalate (-7.542 kcal/mol) and dibutyl phthalate (-7.181 kcal/mol) from O. tenuiflorum and one diethyl phthalate (-7.224 kcal/mol) from C. sativum having more docking score than standard Osimertinib which indicates the effectiveness of oils for lung cancer.

Britannin inhibits hepatocellular carcinoma development and metastasis through the GSK-3β/β-catenin signaling pathway

BackgroundHepatocellular carcinoma (HCC) stands out as a significant contributor of cancer-related death. Traditional Chinese Medicine (TCM) presents numerous advantages in the treatment of HCC. Britannin, a pivotal compound found in Inulae Flos, demonstrates pharmacological effects against various cancers, yet research on its specific impact on anti-hepatocellular carcinoma remains limited. PurposeThis study aims to explore both the anti-hepatocellular carcinoma effects of britannin and its underlying mechanism of action. MethodsMTT assay, clone formation assay and flow cytometry were utilized to detect the cell activity, proliferation ability and apoptosis of britannin against HCC cell lines. Cell migration and invasion abilities of britannin on HCC cell lines were evaluated by wound-healing assay and transwell migration and invasion assay. H22 xenografted tumor mouse model was constructed and britannin treatment was performed to observe the effect of britannin on HCC tumor. The expression levels of liver cancer biomarkers AFP, AFP-L3, APT and TGF-β were detected by Elisa, and the histopathology was observed by HE staining. Network pharmacology and molecular docking were used to predict the possible signaling pathway of anti- hepatocellular carcinoma effect of britannin. The surface plasmon resonance (SPR) experiments was used to verify the interaction between britannin and proteins. The cell kinase activity function experiment was employed to detect the effect of britannin on enzyme activity. RT-qPCR and Western-Blot were used to verify the effect of britannin on the mRNA expressions of key genes and protein levels related to GSK-3β/β-catenin pathway in hepatocellular carcinoma cells and tumor tissues in mice. ResultsIn vitro experiments showed that britannin could inhibit the activity, proliferation, migration and invasion abilities of HCC cells, while promoting their apoptosis. In vivo experiments revealed that britannin exerted inhibitory effects on the growth of transplanted liver cancer tumors, reducing the inflammatory infiltration and the expression levels of AFP, AFP-L3, APT and TGF-β of liver cancer markers in transplanted mice. Network pharmacology and molecular docking predicted that cell adhesion factors and GSK-3β/β-catenin pathway might be the related signaling pathway and had potential docking activity with key proteins. The SPR experiments elucidated the molecular interaction between britannin and GSK-3β. Enzyme activity assays indicated that britannin could modulate the functional activity of GSK-3β kinase. RT-qPCR suggested britannin could regulate the mRNA expressions of β-catenin, GSK-3β, E-cadherin and N-Cadherin. Western-Blot further verified that britannin could significantly up-regulate the expression of GSK-3β and down-regulate the expression of p-GSK-3β and β-catenin. At the same time, the expression of E-cadherin increased and N-Cadherin decreased, thereby reducing the occurrence of EMT and inhibiting the metastasis of hepatocellular carcinoma. ConclusionIn conclusion, britannin could inhibit the growth, development and metastasis of HCC, and its mechanism may be related to the regulation of GSK-3β/β-catenin signaling pathway to inhibit epithelial-mesenchymal transition of HCC.

Large language models and their applications in bioinformatics

Recent advancements in Natural Language Processing (NLP) have been significantly driven by the development of Large Language Models (LLMs), representing a substantial leap in language-based technology capabilities. These models, built on sophisticated deep learning architectures, typically transformers, are characterized by billions of parameters and extensive training data, enabling them to achieve high accuracy across various tasks. The transformer architecture of LLMs allows them to effectively handle context and sequential information, which is crucial for understanding and generating human language. Beyond traditional NLP applications, LLMs have shown significant promise in bioinformatics, transforming the field by addressing challenges associated with large and complex biological datasets. In genomics, proteomics, and personalized medicine, LLMs facilitate identifying patterns, predicting protein structures, or understanding genetic variations. This capability is crucial, e.g., for advancing drug discovery, where accurate prediction of molecular interactions is essential. This review discusses the current trends in LLMs research and their potential to revolutionize the field of bioinformatics and accelerate novel discoveries in the life sciences.

Experimental and Modeling Molecular Interactions Between Ethyl Myristate and 2-Alkanol

Experimental and Modeling Molecular Interactions Between Ethyl Myristate and 2-Alkanol

Acoustic and spectroscopic characterization of glycol ethers in vitamin B7 over the range of temperatures (288.15, 293.15, 298.15, 303.15) K

Density (ρ) and ultrasonic speed (u) of butoxyethanol and phenoxyethanol in aqueous solution of biotin concentrations (0.0012, 0.0017, 0.0022) mol·kg−1 at varying temperature range (288.15, 293.15, 298.15 and 303.15) K at 0.1MPa were measured using Anton Paar DSA 5000M. The volumetric and acoustical properties such as apparent molar properties (V∅), partial molar volume (V∅0),partial molar volume of transfer (ΔV∅0),apparent molar isentropic compression (K∅),partial molar isentropic compression (K∅0),partial molar isentropic compression of transfer are computed using the experimental data of density (ρ) and ultrasonic speed (u). This investigation is useful to understand the solvation behavior of biotin. Additionally, partial molar expansibilities (E∅0) along with their first order derivatives (∂E∅0/∂T)pare determined using the obtained experimental data. These results are effective in understanding the nature of interaction occurring inside the solution. Further, pair and triplet coefficients are evaluated which determines the structure making and breaking ability of glycol ethers in aqueous solution of biotin. Also, spectroscopic study of solutions is mentioned in current research which reveals the nature and strength of bond formation and various interactions in the mixture. The present study suggests the molecular interaction between the solute and solvent present in aqueous solution of Biotin (Vitamin B7) as solvent, butoxyethanol (BE) and phenoxyethanol (PE) as solute.

Insights from volumetric, acoustic, conductance and spectroscopic studies to study the molecular interactions of drug Levocetirizine in aqueous and aqueous glucose solutions at varying temperatures

Levocetirizine, an antihistamine, has been analyzed in relation to temperature by volumetric, acoustic, and spectroscopic methods to investigate its interaction with glucose, the predominant carbohydrate. Density and ultrasonic velocity for LC (0 to 0.10 mol dm−3) at different temperature (298.15, 308.15 and 318.15 K) in water and in aqueous solution of glucose (0.05, 0.10 and 0.15 mol kg−1) have been recorded using Anton Paar DSA 5000 M. The apparent molar volume (Vϕ), limiting apparent molar volume (Vϕ0), apparent molar compressibility (Kϕ,S), limiting apparent molar compressibility (Kϕ,S0) were computed utilizing the experimental data. In addition, the transfer parameters of LC from water to aqueous glucose solutions were identified and elucidated using the co-sphere model. The transfer volumes have been utilized to estimate the interaction coefficients. Limiting apparent molar expansibility (ϕE0) and Hepler’s constant was obtained to throw light upon the structure-making or structure-breaking effect of solute. Multiple acoustical parameters like isentropic compressibility (KS), relaxation strength (r), intermolecular free length (Lf), specific acoustic impedance (Z), Wada’s constant (W), relative association (RA), Rao’s constant (Rm), molar volume (Vm), Van der Waals constant (b), and free volume (Vf) were determined to validate the thermodynamic results.

Updates in Microglial Research with Respect to Brain Cancer

Microglia resides in the microenvironment of the central nervous system (CNS) and is thought to play a key role in the development and progression of brain cancer. This is because it was shown that microglia comprised a large portion of the total brain tumour mass. Besides, the origin of microglia cells in brain tumours is worth understanding as it is important to distinguish the resident macrophages from the circulating macrophages when discussing the pathology of brain tumours. Activated microgliosis has been linked to increased inflammatory mediators like cytokines, growth factors, matrix metalloproteinases (MMPs) and many more, which would facilitate tumourigenesis. Brain tumour cells also proliferate under the influence of signalling pathways, such as the toll-like receptor 2 signals. Vascular endothelial growth factor (VEGF) which is an angiogenic factor aids in the growth of tumour cells. Brain cancer cells rely on suppressing the effector arm of immune system to evade attacks by downregulating major histocompatibility complexes (MHC) class II molecules and inducing the conversion of microglia to an immunosuppressive phenotype. Glioblastoma stem cells (GSCs) that give rise to brain cancers communicate with microglia cells, which determines their growth and invasion potential. Understanding the molecular interactions of brain cancer and microglia cells would help unlock novel treatments via means of immunotherapy, immunosuppressants and utilising microglia cells to deliver nanoparticle drugs to effectively target and treat brain cancer.

Feedstock recycling of single-use garment simultaneously using CO2 and MSW incinerator bottom ash

This study is aimed at proposing a feedstock recycling approach to make value-added monomer from single-use garment like stocking waste (SW) using incinerator bottom ash catalyst (IBAC). SW is made mainly of nylon 6 (>80 wt%) with minor components such as polyurethane. Thermochemical SW decomposition pathways are identified by evolved gas analysis and single-shot pyrolysis analysis, confirming that caprolactam (a value-added chemical re-used for manufacturing nylon 6) is the major product. IBAC is composed mainly of alkaline metal oxides (e.g., CaO). The use of IBAC in thermochemical SW conversion at 500 °C under CO2 atmosphere increases the yield of caprolactam reaching 70.8 wt% (20 % higher than non-catalytic SW conversion (59.2 wt%)). Moreover, the caprolactam yield corrected to the nylon 6 content of SW is 86.8 wt%. The enhancement of caprolactam production by IBAC in CO2 is most likely due to the synergistical effect of IBAC and CO2 on promoting the molecular interaction of amide groups present on SW. It is hoped that this study brings the idea of new applications of concurrently reusing textile waste (e.g., SW) and municipal solid waste-treatment byproduct (e.g., IBAC).

Computational investigation of Pluchea indica mechanism targeting peroxisome proliferator-activated receptor gamma

Introduction: Pluchea indica is known to have diverse pharmacological properties, including anti-inflammatory, antioxidant, antimicrobial, and anticancer activities. However, there is a pressing need to thoroughly investigate the molecular interactions between P. indica compounds and peroxisome proliferator-activated receptor gamma (PPARG). This study aimed to elucidate the molecular mechanisms behind P. indica and PPARG, and its potential implications for diabetes mellitus. Methods: The computational investigation employed Pharmacological Network pharmacology, homology modeling, deep learning docking, and molecular dynamics to explore the active compounds and targets within P. indica against the PPARG. Results: Three active compounds were identified namely pinoresinol, syringaresinol, and plucheoside A, all of which complied with the Lipinski rule of five. The deep learning-based pose scores were determined as follows: Pinoresinol 0.55, syringaresinol 0.32, and plucheoside A 0.44. Additionally, protein-protein interactions were observed with PPARG and associated with the PPAR signaling pathway. Molecular dynamics simulation analysis showed the stability of the three compounds over a 100 ns period. Free energy calculations using Molecular Mechanics-Generalized Born and Surface Area (MM-GBSA) yielded ΔG values of -44.39 kcal/mol, -51.83 kcal/mol, and -40.27 kcal/mol for pinoresinol, syringaresinol, and plucheoside A, respectively. Conclusion: Pluchea indica might be developed to treat various diseases, particularly those involving the PPARG signaling pathway. It suggests the possibility of being developed as a focused medication for diabetes.

Diabetic wound healing potentials of phenylethanoid glycosides from Clerodendrum glandulosum Lindl.: Connecting the dots by integrating network pharmacology, molecular docking, and molecular dynamics simulation

The diabetic wound is one of the severe complications of diabetes mellitus, accounting for 20 % of limb amputations in diabetic patients. This creates a need to search for newer natural compounds to target the different molecular pathways of diabetic wounds to accelerate the repair. The phenylethanoid glycosides (PhGs) isolated from Clerodendrum glandulosum (CG) have been shown to exhibit antioxidant, antimicrobial, and anti-inflammatory properties but have never been explored for diabetic wound healing. Thus, this study focuses on exploring the diabetic wound-repairing properties of PhGs through in-silico approaches. The PhGs present in CG were identified through extensive literature searching, which were further subjected to database searching in BindingDB, TargetNet, PharmMapper, Super-PRED, and Swiss Target Prediction to find the potential targets, which included PRKCA, PRKCG, PRKCZ, TDP1, and Pol. Subsequently, these targets were used to determine the disease IDs related to diabetic wounds from databases such as DisGeNET, Gene Expression Omnibus, GeneCards, and OMIM. A network was established using Cytoscape to study the relationship among the PhGs, the protein targets, and their associated disease IDs. The top twenty molecular pathways associated with the target proteins were determined using the ShinyGO database. Genetic enrichment analysis showed that the Sphingolipid signalling pathway included the maximum number of genes and had the lowest false discovery rate value, which concluded that this pathway is the potential target of the PhGs. PRKCA and PRKCZ were found to be the only two genes involved in this pathway, and thus, molecular docking was used to evaluate the binding affinity of the PhGs with the proteins. Docking scores were between -13.2859 and -5.10928, suggesting a strong molecular interaction between the PhGs and their targets. Thus, it is concluded that PhGs present in CG can be the potential compounds to treat diabetic wounds; however, further in-vitro and in-vivo investigations are necessary.