The application of in silico drug-likeness predictions in pharmaceutical research

Integrating classic AI and agriculture: A novel model for predicting insecticide-likeness to enhance efficiency in insecticide development

The integration of artificial intelligence (AI) into smart agriculture boosts production and management efficiency, facilitating sustainable agricultural development. In intensive agricultural management, adopting eco-friendly and effective pesticides is crucial to promote green agricultural practices. However, exploring new insecticides species is a difficult and time-consuming task that involves significant risks. Enhancing compound druggability in the lead discovery phase could considerably shorten the discovery cycle, accelerating insecticides research and development. The Insecticide Activity Prediction (IAPred) model, a novel classic artificial intelligence-based method for evaluating the potential insecticidal activity of unknown functional compounds, is introduced in this study. The IAPred model utilized 27 insecticide-likeness features from PaDEL descriptors and employed an ensemble of Support Vector Machine (SVM) and Random Forest (RF) algorithms using the hard-vote mechanism, achieving an accuracy rate of 86 %. Notably, the IAPred model outperforms current models by accurately predicting the efficacy of novel insecticides such as nicofluprole, overcoming the limitations inherent in existing insecticide structures. Our research presents a practical approach for discovering and optimizing novel insecticide lead compounds quickly and efficiently.

QSAR modelling of enzyme inhibition toxicity of ionic liquid based on chaotic spotted hyena optimization algorithm

Ionic liquids (ILs) have attracted considerable interest due to their unique properties and prospective uses in various industries. However, their potential toxicity, particularly regarding enzyme inhibition, has become a growing concern. In this study, a QSAR model was proposed to predict the enzyme inhibition toxicity of ILs. A dataset of diverse ILs with corresponding toxicity data against three enzymes was compiled. Molecular descriptors that capture the physicochemical, structural, and topological properties of the ILs were calculated. To optimize the selection of descriptors and develop a robust QSAR model, the chaotic spotted hyena optimization algorithm, a novel nature-inspired metaheuristic, was employed. The proposed algorithm efficiently searches for an optimal subset of descriptors and model parameters, enhancing the predictive performance and interpretability of the QSAR model. The developed model exhibits excellent predictive capability, with high classification accuracy and low computation time. Sensitivity analysis and molecular interpretation of the selected descriptors provide insights into the critical structural features influencing the toxicity of ILs. This study showcases the successful application of the chaotic spotted hyena optimization algorithm in QSAR modelling and contributes to a better understanding of the toxicity mechanisms of ILs, aiding in the design of safer alternatives for industrial applications.

Evaluation of the Interaction between Carvacrol and Thymol, Major Compounds of Ptychotis verticillata Essential Oil: Antioxidant, Anti-Inflammatory and Anticancer Activities against Breast Cancer Lines

The objective of this study was to evaluate the antioxidant, anti-inflammatory, and anticancer properties of thymol, carvacrol, and their equimolar mixture. Antioxidant activities were assessed using the DPPH, ABTS, and ORAC methods. The thymol/carvacrol mixture exhibited significant synergism, surpassing the individual compounds and ascorbic acid in DPPH (IC50 = 43.82 ± 2.41 µg/mL) and ABTS (IC50 = 23.29 ± 0.71 µg/mL) assays. Anti-inflammatory activity was evaluated by inhibiting the 5-LOX, COX-1, and COX-2 enzymes. The equimolar mixture showed the strongest inhibition of 5-LOX (IC50 = 8.46 ± 0.92 µg/mL) and substantial inhibition of COX-1 (IC50 = 15.23 ± 2.34 µg/mL) and COX-2 (IC50 = 14.53 ± 2.42 µg/mL), indicating a synergistic effect. Anticancer activity was tested on MCF-7, MDA-MB-231, and MDA-MB-436 breast cancer cell lines using the MTT assay. The thymol/carvacrol mixture demonstrated superior cytotoxicity (IC50 = 0.92-1.70 µg/mL) and increased selectivity compared to cisplatin, with high selectivity indices (144.88-267.71). These results underscore the promising therapeutic potential of the thymol/carvacrol combination, particularly for its synergistic antioxidant, anti-inflammatory, and anticancer properties against breast cancer. This study paves the way for developing natural therapies against breast cancer and other conditions associated with oxidative stress and inflammation, leveraging the synergistic effects of natural compounds like thymol and carvacrol.

Antihypertensive and Antidiabetic Drug Candidates from Milkfish (Chanos chanos)-Identification and Characterization through an Integrated Bioinformatic Approach

Integrated bioinformatics tools have created more efficient and robust methods to overcome in vitro challenges and have been widely utilized for the investigation of food proteins and the generation of peptide sequences. This study aimed to analyze the physicochemical properties and bioactivities of novel peptides derived from hydrolyzed milkfish (Chanos chanos) protein sequences and to discover their potential angiotensin-converting enzyme (ACE)- and dipeptidyl peptidase-4 (DPPIV)-inhibitory activities using machine learning-based tools, including BIOPEP-UWM, PeptideRanker, and the molecular docking software HADDOCK 2.4. Nine and three peptides were predicted to have ACE- and DPPIV-inhibitory activities, respectively. The DPPIV-inhibitory peptides were predicted to inhibit the compound with no known specific mode. Meanwhile, two tetrapeptides (MVWH and PPPS) were predicted to possess a competitive mode of ACE inhibition by directly binding to the tetra-coordinated Zn ion. Among all nine discovered ACE-inhibitory peptides, only the PPPS peptide satisfied the drug-likeness analysis requirements with no violations of the Lipinski rule of five and should be further investigated in vitro.

Assessing anti oxidant, antidiabetic potential and GCMS profiling of ethanolic root bark extract of Zanthoxylum rhetsa (Roxb.) DC: Supported by in vitro, in vivo and in silico molecular modeling

Zanthoxylum rhetsa (ZR) is used traditionally to manage a variety of ailments, including diabetes. Oxidative stress may accelerate the diabetic condition. The available antidiabetic and antioxidant drugs have many shortcomings including resistance, inefficiency, higher dose, side effects and costs. The goal of the current investigation was to assess the antioxidant capacity and antidiabetic activity of an ethanolic extract of Zanthoxylum rhetsa root bark (ZRRB) through in vitro, in vivo, and in silico methods. The antioxidant capacity of the ZRRB extract was measured using both the DPPH radical assay and the total antioxidant activity test. The oral glucose tolerance test (OGTT) and alloxan-induced diabetic mice model were also used to examine in vivo antidiabetic efficacy. Phytochemicals identification was done by GCMS analysis. Additionally, computational methods such as molecular docking, ADMET analysis, and molecular dynamics (MD) modeling were performed to determine the above pharmacological effects. The extract demonstrated significant DPPH scavenging activity (IC50 = 42.65 μg/mL). In the OGTT test and alloxan-induced diabetes mice model, the extract effectively lowered blood glucose levels. Furthermore, in vitro inhibition of pancreatic α-amylase studies demonstrated the ZRRB extract as a good antidiabetic crude drug (IC50 = 81.45 μg/mL). GCMS investigation confirmed that the crude extract contains 16 major phytoconstituents, which were docked with human peroxiredoxin-5, α-amylase, and sulfonylurea receptor 1. Docking and pharmacokinetic studies demonstrated that among 16 phytoconstituents, 6H-indolo[3,2,1-de] [1,5]naphthyridin-6-one (CID: 97176) showed the highest binding affinity to targeted enzymes, and imitated Lipinski's rule of five. Furthermore, MD simulation data confirmed that the aforementioned compound is very steady to the binding site of α-amylase and sulfonylurea receptor 1 receptors. Findings from in vitro, in vivo and in silico investigation suggest that ZRRB extract contains a lead compound that could be a potent source of antidiabetic drug candidate.

Exploring Bryophyllum pinnatum compounds as potential inhibitors for Vespula vulgaris allergen proteins: A systematic computational approach

Vespula vulgaris (V. vulgaris), commonly known as the common wasp, poses a significant health threat due to its venom-induced allergic reactions. This research focused on the exploration of bioactive compounds from Bryophyllum pinnatum as potential inhibitors for V. vulgaris allergen proteins, including Phospholipase A1 (Ves V1), Hyaluronoglucosaminidase (Ves V2), and Antigen 5 (Ves V5). Through a multidisciplinary approach involving literature reviews, molecular docking analyses, ADMET assessments and Molecular Dynamics Simulations (MDS) of 100ns we identified two promising drug candidates from four bioactive compounds- Bryophyllin A, Bryophyllin B, Bryotoxin A, and Bryotoxin B of Bryophyllum pinnatum. Molecular docking results revealed strong binding interactions, with Bryophyllin B and Bryotoxin A consistently exhibiting the highest affinity (-9.6 kcal/mol and -10.0 kcal/mol) across the allergen proteins. ADMET analyses highlighted Bryophyllin B as a favorable candidate, showing high absorption (HIA: 92.1 %), minimal metabolic interactions (CYP1A2: No), and a low toxicity profile (LD50 (rat): 2.431). MDS analysis revealed Bryophyllin B and Bryotoxin A as promising drug inhibitors, exhibiting the highest binding stability with the allergen proteins of V. vulgaris, as indicated by the lowest Root Mean Square Deviation (RMSD), Root Mean Square Fluctuation (RMSF), Radius of Gyration (RG) values and highest protein-ligand contacts. Our study provides valuable insights into the therapeutic potential of Bryophyllum pinnatum compounds as inhibitors for V. vulgaris allergen proteins having two promising candidates- Bryophyllin B and Bryotoxin A.

Recent advances in the development of P2Y14R inhibitors: a patent and literature review (2018-present)

INTRODUCTION

The P2Y14 receptor (P2Y14R), a member of the G protein-coupled receptor family, is activated by extracellular nucleotides. Due to its involvement in inflammatory, immunological and other associated processes, P2Y14R has emerged as a promising therapeutic target. Despite lacking a determined three-dimensional crystal structure, the homology modeling technique based on closely related P2Y receptors' crystallography has been extensively utilized for developing active compounds targeting P2Y14R. Recent discoveries have unveiled numerous highly effective and subtype-specific P2Y14R inhibitors. This study presents an overview of the latest advancements in P2Y14R inhibitors.

AREAS COVERED

This review presents an overview of the advancements in P2Y14R inhibitor research over the past five years, encompassing new patents, journal articles, and highlighting the therapeutic prospects inherent in these compounds.

EXPERT OPINION

The recent revelation of the vast potential of P2Y14R inhibitors has led to the development of novel compounds that exhibit promising capabilities for the treatment of sterile inflammation of the kidney, potentially diabetes, and asthma. Despite being a relatively nascent class of compounds, certain members have already exhibited their capacity to surmount specific challenges posed by conventional P2Y14R inhibitors. Targeting P2Y14R through small molecules may present a promising therapeutic strategy for effectively managing diverse inflammatory diseases.

Structure-based pharmacophore modeling for precision inhibition of mutant ESR2 in breast cancer: A systematic computational approach

BACKGROUND

Breast cancer, a leading cause of female mortality, is closely linked to mutations in estrogen receptor beta (ESR2), particularly in the ligand-binding domain, which contributed to altered signaling pathways and uncontrolled cell growth.

OBJECTIVES/AIMS

This study investigates the molecular and structural aspects of ESR2 mutant proteins to identify shared pharmacophoric regions of ESR2 mutant proteins and potential therapeutic targets aligned within the pharmacophore model.

METHODS

This study was initiated by establishing a common pharmacophore model among three mutant ESR2 proteins (PDB ID: 2FSZ, 7XVZ, and 7XWR). The generated shared feature pharmacophore (SFP) includes four primary binding interactions: Hydrogen bond donors (HBD), hydrogen bond acceptors (HBA), hydrophobic interactions (HPho), and Aromatic interactions (Ar), along with halogen bond donors (XBD) and totalling 11 features (HBD: 2, HBA: 3, HPho: 3, Ar: 2, XBD: 1). By employing an in-house Python script, these 11 features distributed into 336 combinations, which were used as query to isolate a drug library of 41,248 compounds and subjected to virtual screening through the generated SFP.

RESULTS

The virtual screening demonstrated 33 hits showing potential pharmacophoric fit scores and low RMSD value. The top four compounds: ZINC94272748, ZINC79046938, ZINC05925939, and ZINC59928516 showed a fit score of more than 86% and satisfied the Lipinski rule of five. These four compounds and a control underwent molecular (XP Glide mode) docking analysis against wild-type ESR2 protein (PDB ID: 1QKM), resulting in binding affinity of -8.26, -5.73, -10.80, and -8.42 kcal/mol, respectively, along with the control -7.2 kcal/mol. Furthermore, the stability of the selected candidates was determined through molecular dynamics (MD) simulations of 200 ns and MM-GBSA analysis.

CONCLUSION

Based on MD simulations and MM-GBSA analysis, our study identified ZINC05925939 as a promising ESR2 inhibitor among the top four hits. However, it is essential to conduct further wet lab evaluation to assess its efficacy.

Prediction of Drug-Induced Liver Injury: From Molecular Physicochemical Properties and Scaffold Architectures to Machine Learning Approaches

The process of developing new drugs is widely acknowledged as being time-intensive and requiring substantial financial investment. Despite ongoing efforts to reduce time and expenses in drug development, ensuring medication safety remains an urgent problem. One of the major problems involved in drug development is hepatotoxicity, specifically known as drug-induced liver injury (DILI). The popularity of new drugs often poses a significant barrier during development and frequently leads to their recall after launch. In silico methods have many advantages compared with traditional in vivo and in vitro assays. To establish a more precise and reliable prediction model, it is necessary to utilize an extensive and high-quality database consisting of information on drug molecule properties and structural patterns. In addition, we should also carefully select appropriate molecular descriptors that can be used to accurately depict compound characteristics. The aim of this study was to conduct a comprehensive investigation into the prediction of DILI. First, we conducted a comparative analysis of the physicochemical properties of extensively well-prepared DILI-positive and DILI-negative compounds. Then, we used classic substructure dissection methods to identify structural pattern differences between these two different types of chemical molecules. These findings indicate that it is not feasible to establish property or substructure-based rules for distinguishing between DILI-positive and DILI-negative compounds. Finally, we developed quantitative classification models for predicting DILI using the naïve Bayes classifier (NBC) and recursive partitioning (RP) machine learning techniques. The optimal DILI prediction model was obtained using NBC, which combines 21 physicochemical properties, the VolSurf descriptors and the LCFP_10 fingerprint set. This model achieved a global accuracy (GA) of 0.855 and an area under the curve (AUC) of 0.704 for the training set, while the corresponding values were 0.619 and 0.674 for the test set, respectively. Moreover, indicative substructural fragments favorable or unfavorable for DILI were identified from the best naïve Bayesian classification model. These findings may help prioritize lead compounds in the early stage of drug development pipelines.

Discovery of novel FUT8 inhibitors with promising affinity and in vivo efficacy for colorectal cancer therapy

As a member of glycosyltransferases, fucosyltransferase 8 (FUT8) is essential to core fucosylation and has been considered as a potential therapeutic target for malignant tumors, including colorectal cancer (CRC). Based on the identification of key binding residues and probable conformation of FUT8, an integrated strategy that combines virtual screening and chemical optimization was carried out and compound 15 was identified as a potent FUT8 inhibitor with novel chemical structure and in vitro antitumor activity. Moreover, chemical pulldown experiments and binding assays confirmed that compound 15 selectively bound to FUT8. In vivo, compound 15 showed promising anti-CRC effects in SW480 xenografts. These data support that compound 15 is a potential FUT8 inhibitor for CRC treatment and deserve further optimization studies.

Probing Dual Covalent Irreversible Inhibition of EGFR/FGFR4 by Electrophilic-Based Natural Compounds to Overcome Resistance and Enhance Combination Therapeutic Potentials and Management of Hepatocellular Carcinoma (HCC)

Hepatocellular carcinoma (HCC) is one of the most prevalent cancer types in the world and accounts for the majority of cases of primary liver cancer. A crucial part of the carcinogenesis of HCC involves aberrant stimulation of the FGF19-FGFR4 signaling pathway. Therefore, FGFR4 inhibition has become a strategic therapeutic approach for the treatment of HCC. However, the clinical treatment procedure is significantly hampered by the prevalence of kinase inhibitors resistance. It was recently established that the activation of EGFR signaling was found to be one of the primary mechanisms mediating the acquired resistance to FGFR4 inhibitors, moreover, sensitivity to FGFR4 inhibitors was effectively restored by inhibiting EGFR. These results provide compelling evidence that dual inhibition of EGFR and FGFR4 could represent a viable therapeutic approach to overcome resistance, hence enhanced management of HCC. To this end, we proposed a dual irreversible inhibition strategy through covalent binding by naturally occurring electrophilic warhead-bearing compounds (curcumin, deoxyelephantopin, eupalmerin acetate, syringolin A and andrographolide) to covalently target both EGFR and FGFR4 through cysteine residues, Cys797 and Cys552, respectively. Covalent docking and covalent molecular dynamics (MM/MDcov) simulations combined with thermodynamic binding free energy calculations were performed, and the results were compared against known potent and selective covalent EGFR and FGFR4 inhibitors with available X-ray crystal structures, Afatinib and BLU9931, respectively. Curcumin, deoxyelephantopin, eupalmerin acetate, syringolin A, and andrographolide showed relative binding free energies of -22.85, -17.14, -12.98, -21.81, and - 19.00 kcal/mol against EGFR and - 41.06, -29.45, -24.76, -40.11, and - 37.55 kcal/mol against FGFR4, respectively. The mechanisms of binding were emphasized by hydrogen bonding and binding forces analysis as well as active site physicochemical profiling. The findings of this study identified that curcumin, syringolin A and andrographolide-but not eupalmerin acetate or deoxyelephantopin -could be viable dual EGFR and FGFR4 covalent irreversible inhibitors and could be implemented in HCC combination therapy protocols alone or in conjunction with other chemotherapeutic agents. Investigations of this study conclusively indicate dual blockade of EGFR and FGFR4 may be a promising future therapeutic strategy for enhanced management of HCC.

In silico insights into the design of novel NR2B-selective NMDA receptor antagonists: QSAR modeling, ADME-toxicity predictions, molecular docking, and molecular dynamics investigations

Based on a structural family of thirty-two NR2B-selective N-Methyl-D-Aspartate receptor (NMDAR) antagonists, two phenylpiperazine derivatives labeled C37 and C39 were conceived thanks to molecular modeling techniques, as novel NMDAR inhibitors exhibiting the highest analgesic activities (of pIC50 order) against neuropathic pain, with excellent ADME-toxicity profiles, and good levels of molecular stability towards the targeted protein of NMDA receptor. Initially, the quantitative structure-activity relationships (QSARs) models were developed using multiple linear regression (MLR), partial least square regression (PLSR), multiple non-linear regression (MNLR), and artificial neural network (ANN) techniques, revealing that analgesic activity was strongly correlated with dipole moment, octanol/water partition coefficient, Oxygen mass percentage, electronegativity, and energy of the lowest unoccupied molecular orbital, whose the correlation coefficients of generated models were: 0.860, 0.758, 0.885 and 0.977, respectively. The predictive capacity of each model was evaluated by an external validation with correlation coefficients of 0.703, 0.851, 0.778, and 0.981 respectively, followed by a cross-validation technique with the leave-one-out procedure (CVLOO) with Q2cv of 0.785, more than Y-randomization test, and applicability domain (AD), in addition to Fisher's and Student's statistical tests. Thereafter, ten novel molecules were designed based on MLR QSAR model, then predicted with their ADME-Toxicity profiles and subsequently examined for their similarity to the drug candidates. Finally, two of the most active compounds (C37 and C39) were chosen for molecular docking and molecular dynamics (MD) investigations during 100 ns of MD simulation time in complex with the targeted protein of NMDA receptor (5EWJ.pdb).

The active components of Erzhi wan and their anti-Alzheimer's disease mechanisms determined by an integrative approach of network pharmacology, bioinformatics, molecular docking, and molecular dynamics simulation

Erzhi Wan (EZW), a classic Traditional Chinese Medicine formula, has shown promise as a potential therapeutic option for Alzheimer's disease (AD), yet its mechanism remains elusive. Herein, we employed an integrative in-silico approach to investigate the active components and their mechanisms against AD. We screened four active components with blood-brain barrier permeabilities from TCMSP, along with 307 corresponding targets predicted by SwissTargetPrediction, PharmMapper, and TCMbank websites. Then, we retrieved 2260 AD-related targets from Genecards, OMIM, and NCBI databases. Furthermore, we constructed the protein-protein interaction (PPI) network of the intersected targets via the STRING database and performed the GO and KEGG enrichment analyses using the "clusterProfiler" R package. The results showed that the intersected targets were intimately related to the p53/PI3K/Akt signaling pathway, serotonergic synapse, and response to oxygen level. Subsequently, 25 core targets were found differentially expressed in brain regions by bioinformatics analyses of GEO datasets of clinical samples from the Alzdata database. The binding sites and stabilities between the active components and the core targets were investigated by the molecular docking approach using Autodock 4.2.6 software, followed by pocket detection and druggability assessment via the DoGSiteScorer server. The results showed that acacetin, β-sitosterol, and 3-O-acetyldammarenediol-II strongly interacted with the druggable pockets of AR, CASP8, POLB, and PREP. Eventually, the docking results were further cross-referenced with the literature research and validated by 100 ns of molecular dynamics simulations using GROMACS software. Binding free energies were calculated via MM/PBSA strategy combined with interaction entropy. The simulation results indicated stable bindings between four docking pairs including acacetin-AR, acacetin-CASP8, β-sitosterol-POLB, and 3-O-acetyldammarenediol-II-PREP. Overall, our study demonstrated a theoretical basis for how three active components of EZW confer efficacy against AD. It provides a promising reference for subsequent research regarding drug discoveries and clinical applications.

Prediction method of pharmacokinetic parameters of small molecule drugs based on GCN network model

CONTEXT

Accurately predicting plasma protein binding rate (PPBR) and oral bioavailability (OBA) helps to better reveal the absorption and distribution of drugs in the human body and subsequent drug design. Although machine learning models have achieved good results in prediction accuracy, they often suffer from insufficient accuracy when dealing with data with irregular topological structures.

METHODS

In view of this, this study proposes a pharmacokinetic parameter prediction framework based on graph convolutional networks (GCN), which predicts the PPBR and OBA of small molecule drugs. In the framework, GCN is first used to extract spatial feature information on the topological structure of drug molecules, in order to better learn node features and association information between nodes. Then, based on the principle of drug similarity, this study calculates the similarity between small molecule drugs, selects different thresholds to construct datasets, and establishes a prediction model centered on the GCN algorithm. The experimental results show that compared with traditional machine learning prediction models, the prediction model constructed based on the GCN method performs best on PPBR and OBA datasets with an inter-molecular similarity threshold of 0.25, with MAE of 0.155 and 0.167, respectively. In addition, in order to further improve the accuracy of the prediction model, GCN is combined with other algorithms. Compared to using a single GCN method, the distribution of the predicted values obtained by the combined model is highly consistent with the true values. In summary, this work provides a new method for improving the rate of early drug screening in the future.

The mechanism of Gejie Zhilao Pill in treating tuberculosis based on network pharmacology and molecular docking verification

Introduction

Gejie Zhilao Pill (GJZLP), a traditional Chinese medicine formula is known for its unique therapeutic effects in treating pulmonary tuberculosis. The aim of this study is to further investigate its underlying mechanisms by utilizing network pharmacology and molecular docking techniques.

Methods

Using TCMSP database the components, potential targets of GJZLP were identified. Animal-derived components were supplemented through the TCMID and BATMAN-TCM databases. Tuberculosis-related targets were collected from the TTD, OMIM, and GeneCards databases. The intersection target was imported into the String database to build the PPI network. The Metascape platform was employed to carry out Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis. Heatmaps were generated through an online platform (https://www.bioinformatics.com.cn). Molecular docking was conducted between the core targets and core compounds to explore their binding strengths and patterns at the molecular level.

Results

61 active ingredients and 118 therapeutic targets were identified. Quercetin, Luteolin, epigallocatechin gallate, and beta-sitosterol showed relatively high degrees in the network. IL6, TNF, JUN, TP53, IL1B, STAT3, AKT1, RELA, IFNG, and MAPK3 are important core targets. GO and KEGG revealed that the effects of GJZLP on tuberculosis mainly involve reactions to bacterial molecules, lipopolysaccharides, and cytokine stimulation. Key signaling pathways include TNF, IL-17, Toll-like receptor and C-type lectin receptor signaling. Molecular docking analysis demonstrated a robust binding affinity between the core compounds and the core proteins. Stigmasterol exhibited the lowest binding energy with AKT1, indicating the most stable binding interaction.

Discussion

This study has delved into the efficacious components and molecular mechanisms of GJZLP in treating tuberculosis, thereby highlighting its potential as a promising therapeutic candidate for the treatment of tuberculosis.

AC-ModNet: Molecular Reverse Design Network Based on Attribute Classification

Deep generative models are becoming a tool of choice for exploring the molecular space. One important application area of deep generative models is the reverse design of drug compounds for given attributes (solubility, ease of synthesis, etc.). Although there are many generative models, these models cannot generate specific intervals of attributes. This paper proposes a AC-ModNet model that effectively combines VAE with AC-GAN to generate molecular structures in specific attribute intervals. The AC-ModNet is trained and evaluated using the open 250K ZINC dataset. In comparison with related models, our method performs best in the FCD and Frag model evaluation indicators. Moreover, we prove the AC-ModNet created molecules have potential application value in drug design by comparing and analyzing them with medical records in the PubChem database. The results of this paper will provide a new method for machine learning drug reverse design.

An In Silico Study Based on QSAR and Molecular Docking and Molecular Dynamics Simulation for the Discovery of Novel Potent Inhibitor against AChE

Acetylcholinesterase (AChE) is one of the main drug targets for treating Alzheimer's disease. This current study relies on multiple molecular modeling approaches to develop new potent inhibitors of AChE. We explored a 2D QSAR study using the statistical method of multiple linear regression based on a set of substituted 5-phenyl-1,3,4-oxadiazole and N-benzylpiperidine analogs, which were recently synthesized and proved their inhibitory activities against acetylcholinesterase (AChE). The molecular descriptors, polar surface area, dipole moment, and molecular weight are the key structural properties governing AChE inhibition activity. The MLR model was selected based on its statistical parameters: R2 = 0.701, R2test = 0.76, Q2CV = 0.638, and RMSE = 0.336, demonstrating its predictive reliability. Randomization tests, VIF tests, and applicability domain tests were adopted to verify the model's robustness. As a result, 11 new molecules were designed with higher anti-Alzheimer's activities than the model molecule. We demonstrated their improved pharmacokinetic properties through an in silico ADMET study. A molecular docking study was conducted to explore their AChE inhibition mechanisms and binding affinities in the active site. The binding scores of compounds M1, M2, and M6 were (-12.6 kcal/mol), (-13 kcal/mol), and (-12.4 kcal/mol), respectively, which are higher than the standard inhibitor Donepezil with a binding score of (-10.8 kcal/mol). Molecular dynamics simulations over 100 ns were used to validate the molecular docking results, indicating that compounds M1 and M2 remain stable in the active site, confirming their potential as promising anti-AChE inhibitors.

In Vitro Antibacterial, Antioxidant, Cytotoxicity Activity, and In Silico Molecular Modelling of Compounds Isolated from Roots of Hydnora johannis

The plant Hydnora johannis has been utilized in folk medicine. Analyzing phytochemical composition of dichloromethane/methanol (1 : 1) root part of Hydnora johannis gave oleic acid (1), caffeic acid-2-hydroxynonylester (2), catechin (3), and a pregnane derivative (4). NMR spectroscopy was used to characterize compounds 1-3, while compound 4 was identified through GC-MS analysis and literature comparison. The cytotoxicity of extracts from roots of H. johannis was conducted against MCF-7 cell lines (human breast cancer) by MTT assay. According to the cytotoxicity study, n-hexane extract exhibited a high level of toxicity with 28.9 ± 5.6% cell viability. Antibacterial activity was tested against Escherichia coli, Pseudomonas aeruginosa, Staphylococcus aureus, and Streptococcus pyogen. The highest bacterial growth mean inhibition zone was measured for catechin (3) (13.72 ± 0.05 mm)) against P. aeruginosa at 0.25 mg/mL and acceptable related to standard. Antioxidant activity was studied by the DPPH assay. Based on the data from the antioxidant study, DCM/MeOH extract (70.32%) and catechin (3) showed good antioxidant activity (65.61%) (IC50 0.25 μg/mL) relative to that of the positive control (78.21%, IC50 0.014 μg/mL) at 12.5 μg/mL. In each docking pose, catechin (3) scored higher binding affinity of -7.9, -7.2, and -6.4 kcal/mol towards PqsA, DNA gyraseB, and S. aureus PK, respectively, compared to amoxicillin (-8.1, -6.1, and -6.4 kcal/mol). All five Lipinski rules were obeyed by compounds 1-3, which showed an acceptable drug resemblance. The lipophilicity was computed as less than five (1.47-4.01) indicating a lipophilic property. Catechin (3) obeys Veber's rule implying its good oral bioavailability. Binding affinity scores of catechin (3)-protein interactions are in line with those from in vitro tests, indicating its potential antibacterial effect. The obtained cytotoxicity and antibacterial activity results support the utilization of H. johannis in folk medicine.

Fetus Exposure to Drugs and Chemicals: A Holistic Overview on the Assessment of Their Transport and Metabolism across the Human Placental Barrier

BACKGROUND

The placenta exerts a crucial role in fetus growth and development during gestation, protecting the fetus from maternal drugs and chemical exposure. However, diverse drugs and chemicals (xenobiotics) can penetrate the maternal placental barrier, leading to deleterious, adverse effects concerning fetus health. Moreover, placental enzymes can metabolize drugs and chemicals into more toxic compounds for the fetus. Thus, evaluating the molecular mechanisms through which drugs and chemicals transfer and undergo metabolism across the placental barrier is of vital importance. In this aspect, this comprehensive literature review aims to provide a holistic approach by critically summarizing and scrutinizing the potential molecular processes and mechanisms governing drugs and chemical transfer and metabolism across the placental barrier, which may lead to fetotoxicity effects, as well as analyzing the currently available experimental methodologies used to assess xenobiotics placental transfer and metabolism.

METHODS

A comprehensive and in-depth literature review was conducted in the most accurate scientific databases such as PubMed, Scopus, and Web of Science by using relevant and effective keywords related to xenobiotic placental transfer and metabolism, retrieving 8830 published articles until 5 February 2024. After applying several strict exclusion and inclusion criteria, a final number of 148 relevant published articles were included.

RESULTS

During pregnancy, several drugs and chemicals can be transferred from the mother to the fetus across the placental barrier by either passive diffusion or through placental transporters, resulting in fetus exposure and potential fetotoxicity effects. Some drugs and chemicals also appear to be metabolized across the placental barrier, leading to more toxic products for both the mother and the fetus. At present, there is increasing research development of diverse experimental methodologies to determine the potential molecular processes and mechanisms of drug and chemical placental transfer and metabolism. All the currently available methodologies have specific strengths and limitations, highlighting the strong demand to utilize an efficient combination of them to obtain reliable evidence concerning drug and chemical transfer and metabolism across the placental barrier. To derive the most consistent and safe evidence, in vitro studies, ex vivo perfusion methods, and in vivo animal and human studies can be applied together with the final aim to minimize potential fetotoxicity effects.

CONCLUSIONS

Research is being increasingly carried out to obtain an accurate and safe evaluation of drug and chemical transport and metabolism across the placental barrier, applying a combination of advanced techniques to avoid potential fetotoxic effects. The improvement of the currently available techniques and the development of novel experimental protocols and methodologies are of major importance to protect both the mother and the fetus from xenobiotic exposure, as well as to minimize potential fetotoxicity effects.

Copper-mediated cyclization of thiosemicarbazones leading to 1,3,4-thiadiazoles: Structural elucidation, DFT calculations, in vitro biological evaluation and in silico evaluation studies

Cancer's global impact necessitates innovative and less toxic treatments. Thiosemicarbazones (TSCs), adaptable metal chelators, offer such potential. In this study, we have synthesized N (4)-substituted heterocyclic TSCs from syringaldehyde (TSL1, TSL2), and also report the unexpected copper-mediated cyclization of the TSCs to form thiadiazoles (TSL3, TSL4), expanding research avenues. This work includes extensive characterization and studies such as DNA/protein binding, molecular docking, and theoretical analyses to demonstrate the potential of the as-prepared TSCs and thiadiazoles against different cancer cells. The DFT results depict that the thiadiazoles exhibit greater structural stability and reduced reactivity compared to the corresponding TSCs. The docking results suggest superior EGFR inhibition for TSL3 with a binding constant value of - 6.99 Kcal/mol. According to molecular dynamics studies, the TSL3-EGFR complex exhibits a lower average RMSD (1.39 nm) as compared to the TSL1-EGFR complex (3.29 nm) suggesting that both the thiadiazole and thiosemicarbazone examined here can be good inhibitors of EGFR protein, also that TSL3 can inhibit EGFR better than TSL1. ADME analysis indicates drug-likeness and oral availability of the thiadiazole-based drugs. The DNA binding experiment through absorption and emission spectroscopy discovered that TSL3 is more active towards DNA which is quantitatively calculated with a Kb value of 4.74 × 106 M-1, Kq value of 4.04 × 104 M-1and Kapp value of 5 × 106 M-1. Furthermore, the BSA binding studies carried out with fluorescence spectroscopy showed that TSL3 shows better binding capacity (1.64 × 105 M-1) with BSA protein. All the compounds show significant cytotoxicity against A459-lung, MCF-7-breast, and HepG2-liver cancer cell lines; TSL3 exhibits the best cytotoxicity, albeit less effective than cisplatin. Thiadiazoles demonstrate greater cytotoxicity than the TSCs. Overall, the promise of TSCs and thiadiazoles in cancer research is highlighted by this study. Furthermore, it unveils unexpected copper-mediated cyclization of the TSCs to thiadiazoles.

Network pharmacology prediction and molecular docking-based strategy to explore the potential mechanism of squalene against inflammation

Squalene (SQ) has been documented in the past for its ability to reduce inflammation, but its mechanism needs more information. In this study, we investigated squalene as an anti-inflammatory drug candidate and the framework involved in treating inflammation (INF) using the network pharmacology concept. The molecular targets of SQ and INF that are available in databases and the overlaps between these targets were demonstrated using InteractiVenn. The protein-protein networks were generated that in turn revealed several key targets and were further processed with Cytoscape. The gene ontology enrichment and Kyoto Encyclopedia of Genes and Genomes pathway (KEGG) studies were performed. We also performed molecular docking tests that validated the binding affinity of molecular targets and drugs. A total of 100 SQ targets and 11,417 INF-related targets yielded 93 overlapping targets. Seven core targets, CRHR1, EGFR, ERBB2, HIF1A, SLC6A3, MAP2K1, and F2R were found to be relevant with respective to SQ's anti-inflammatory activity. The underlying mechanism of SQ with regard to INF was interpreted by analyzing various enrichment analyses along with the KEGG pathway. In conclusion, SQ played a vital role in the management of INF by regulating CRHR1, EGFR, ERBB2, HIF1A, SLC6A3, MAP2K1, and F2R. The research outcomes are crucial as they offer significant insights into the use of SQ for combating inflammation.

Graphical Abstract

Supplementary Information

The online version contains supplementary material available at 10.1007/s40203-024-00217-0.

Quercetin increases the antidepressant-like effects of sclareol and antagonizes diazepam in thiopental sodium-induced sleeping mice: A possible GABAergic transmission intervention

Quercetin is the most common polyphenolic flavonoid present in fruits and vegetables demonstrating versatile health-promoting effects. This study aimed to examine the effects of quercetin (QR) and sclareol (SCL) on the thiopental sodium (TS)-induced sleeping and forced swimming test (FST) mouse models. SCL (1, 5, and 10 mg/kg, p.o.) or QR (50 mg/kg, p.o.) and/or diazepam (DZP) (3 mg/kg, i.p.) were employed. After 30 min of TS induction, individual or combined effects on the animals were checked. In the FST test, the animals were subjected to forced swimming after 30 min of administration of the test and/or controls for 5 min. In this case, immobility time was measured. In silico studies were conducted to evaluate the involvement of GABA receptors. SCL (5 and 10 mg/kg) significantly increased the latency and decreased sleeping time compared to the control in the TS-induced sleeping time study. DZP (3 mg/kg) showed a sedative-like effect in animals in both sleeping and FST studies. QR (50 mg/kg) exhibited a similar pattern of activity as SCL. However, its effects were more prominent than those of SCL groups. SCL (10 mg/kg) altered the DZP-3-mediated effects. SCL-10 co-treated with QR-50 significantly (p < 0.05) increased the latency and decreased sleep time and immobility time, suggesting possible synergistic antidepressant-like effects. In silico studies revealed that SCL and QR demonstrated better binding affinities with GABAA receptor, especially α2, α3, and α5 subunits. Both compounds also exhibited good ADMET and drug-like properties. In animal studies, the both compounds worked synergistically to provide antidepressant-like effects in a slightly different fashion. As a conclusion, the combined administration of SCL and QR may be used in upcoming neurological clinical trials, according to in vivo and in silico findings. However, additional investigation is necessary to verify this behavior and clarify the potential mechanism of action.

A novel mechanism for regulating lung immune homeostasis: Zukamu granules alleviated acute lung injury in mice by inhibiting NLRP3 inflammasome activation and regulating Th17/Treg cytokine balance

ETHNOPHARMACOLOGICAL RELEVANCE

Acute lung injury (ALI) is a severely acute lung inflammation with high morbidity and mortality. Zukamu granules (ZKMG) is one of the Uygur patent drugs commonly used in clinic, which is included in the National Essential Drugs List (2018 edition). Clinical studies have shown that ZKMG has a significant effect on acute upper respiratory tract infection, and has better anti-inflammatory and antipyretic effects. However, the immunomodulatory mechanism of ZKMG on ALI is still not clear.

AIM OF THE STUDY

The aim of this study is to investigate the lung protective effect and immunomodulatory mechanism of ZKMG on lipopolysaccharide (LPS) -induced ALI mice, and to provide an important basis for the treatment strategy and theoretical basis of ALI.

MATERIALS AND METHODS

First, network pharmacology was used to predict the potential signaling pathways and biological processes of ZKMG related to immunology. Molecular docking technique was used to predict the possibility between the core components of ZKMG acting on NLRP3 protein. In addition, protein levels of F4/80 in lung tissues were assessed by Immunohistochemistry (IHC). The contents of IL-1β, IL-18, IL-17A and IL-10 in the lung tissue and serum, MPO in the lung tissue were detected by enzyme-linked immunosorbent assay (ELISA). Real-time quantitative PCR analysis (RT-qPCR) was used to detect NLRP3 mRNA in lung tissue. Protein levels of NLRP3, Caspase-1, Cleaved caspase-1 p20, ASC, and GSDMD were detected by Western blot (WB).

RESULTS

The results of network pharmacology showed that the immune pathways of ZKMG were mainly Th17 signaling pathway, IL-17 signaling pathway, NOD-like receptor signaling pathway, etc. Molecular docking results showed that the core components of ZKMG had good binding ability to NLRP3 protein. The verification experiments showed that ZKMG can reduce the degree of lung injury, and reduce the level of inflammatory infiltration of neutrophils and macrophages by reducing the content of MPO and F4/80. In addition, ZKMG can reduce NLRP3 mRNA, inhibit the expression of NLRP3/Caspase-1/GSDMD and other related pathway proteins, and reduce inflammatory factors such as IL-1β and IL-18. It can also reduce the content of pro-inflammatory cytokine IL-17A, increase the content of anti-inflammatory cytokine IL-10 in lung tissue.

CONCLUSION

ZKMG can reduce the degree of lung tissue injury in ALI by inhibiting NLRP3/Caspase-1/GSDMD signaling pathway and restoring the IL-17A/IL-10 cytokine balance, and its protective mechanism may be related to the regulation of lung immune homeostasis. It will provide a new strategy for studying the regulation of lung immune homeostasis.

Exploring the Potential Mechanisms of Guanxinshutong Capsules in Treating Pathological Cardiac Hypertrophy based on Network Pharmacology, Computer-Aided Drug Design, and Animal Experiments

Cardiovascular diseases (CVDs) are significant causes of morbidity and mortality worldwide, and pathological cardiac hypertrophy (PCH) is an essential predictor of many heart diseases. Guanxinshutong capsule (GXST) is a Chinese patent medicine widely used in the clinical treatment of CVD, In our previous research, we identified 111 compounds of GXST. In order to reveal the potential molecular mechanisms by which GXST treats PCH, this study employed network pharmacology methods to screen for the active ingredients of GXST in treating PCH and predicted the potential targets. The results identified 26 active ingredients of GXST and 110 potential targets for PCH. Through a protein-protein interaction (PPI) network, gene ontology (GO), and Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis, we confirmed AKT1, MAPK1, and MAPK3 as the core proteins in GXST treatment of PCH, thus establishing the PI3K/AKT and MAPK signaling pathways as the significant mechanisms of GXST in treating PCH. The results of molecular docking (MD) demonstrate that flavonoid naringenin and diterpenoid tanshinone iia have the highest binding affinity with the core protein. Before performing molecular dynamics simulations (MDSs), the geometric structure of naringenin and tanshinone iia was optimized using density functional theory (DFT) at the B97-3c level, and RESP2 atomic charge calculations were carried out at the B3LYP-D3(BJ)/def2-TZVP level. Further MDS results demonstrated that in the human body environment, the complex of naringenin and tanshinone iii with core proteins exhibited high stability, flexibility, and low binding free energy. Additionally, naringenin and tanshinone iia showed favorable absorption, distribution, metabolism, excretion, and toxicity (ADMET) characteristics and passed the drug similarity (DS) assessment. Ultrasound cardiograms and cardiac morphometric measurements in animal experiments demonstrate that GXST can improve the PCH induced by isoproterenol (ISO). Protein immunoblotting results indicate that GXST increases the expression of P-eNOS and eNOS by activating the PI3K/AKT signaling pathway and the MAPK signaling pathway, further elucidating the mechanism of action of GXST in treating PCH. This study contributes to the elucidation of the key ingredients and molecular mechanisms of GXST in treating PCH.

Identification of novel potential cathepsin-B inhibitors through pharmacophore-based virtual screening, molecular docking, and dynamics simulation studies for the treatment of Alzheimer's disease

Cathepsin B is a cysteine protease lysosomal enzyme involved in several physiological functions. Overexpression of the enzyme enhances its proteolytic activity and causes the breakdown of amyloid precursor protein (APP) into neurotoxic amyloid β (Aβ), a characteristic hallmark of Alzheimer's disease (AD). Therefore, inhibition of the enzyme is a crucial therapeutic aspect for treating the disease. Combined structure and ligand-based drug design strategies were employed in the current study to identify the novel potential cathepsin B inhibitors. Five different pharmacophore models were developed and used for the screening of the ZINC-15 database. The obtained hits were analyzed for the presence of duplicates, interfering PAINS moieties, and structural similarities based on Tanimoto's coefficient. The molecular docking study was performed to screen hits with better target binding affinity. The top seven hits were selected and were further evaluated based on their predicted ADME properties. The resulting best hits, ZINC827855702, ZINC123282431, and ZINC95386847, were finally subjected to molecular dynamics simulation studies to determine the stability of the protein-ligand complex during the run. ZINC123282431 was obtained as the virtual lead compound for cathepsin B inhibition and may be a promising novel anti-Alzheimer agent.

Modification of ibuprofen to improve the medicinal effect; structural, biological, and toxicological study

Ibuprofen is classified as a non-steroidal anti-inflammatory drug (NSAID) that is employed as an initial treatment option for its non-steroidal anti-inflammatory, pain-relieving, and antipyretic properties. However, Ibuprofen is linked to specific well-known gastrointestinal adverse effects like ulceration and gastrointestinal bleeding. It has been linked to harmful effects on the liver, kidney, and heart. The purpose of the study is to create novel and potential IBU analogue with reduced side effects with the enhancement of their medicinal effects, so as to advance the overall safety profile of the drug. The addition of some novel functional groups including CH3, F, CF3, OCF3, Cl, and OH at various locations in its core structure suggestively boost the chemical as well as biological action. The properties of these newly designed structures were analyzed through chemical, physical, and spectral calculations using Density Functional Theory (DFT) and time-dependent DFT through B3LYP/6-31 g (d,p) basis set for geometry optimization. Molecular docking and non-bonding interaction studies were conducted by means of the human prostaglandin synthase protein (PDB ID: 5F19) to predict binding affinity, interaction patterns, and the stability of the protein-drug complex. Additionally, ADMET (Absorption, Distribution, Metabolism, Excretion, and Toxicity) and PASS (Prediction of Activity Spectra for Substances) predictions were employed to evaluate the pharmacokinetic and toxicological properties of these structures. Importantly, most of the analogues displayed reduced hepatotoxicity, nephrotoxicity, and carcinogenicity in comparison to the original drug. Moreover, molecular docking analyses indicated improved medicinal outcomes, which were further supported by pharmacokinetic calculations. Together, these findings suggest that the modified structures have reduced adverse effects along with improved therapeutic action compared to the parent drug.

In-silico identification and exploration of small molecule coumarin-1,2,3-triazole hybrids as potential EGFR inhibitors for targeting lung cancer

Globally, lung cancer is a significant public health concern due to its role as the leading cause of cancer-related mortalities. The promising target of EGFR for lung cancer treatment has been identified, providing a potential avenue for more effective therapies. The purpose of the study was to design a library of 1843 coumarin-1,2,3-triazole hybrids and screen them based on a designed pharmacophore to identify potential inhibitors targeting EGFR in lung cancer with minimum or no side effects. Pharmacophore-based screening was carried out and 60 hits were obtained. To gain a better understanding of the binding interactions between the compounds and the targeted receptor, molecular docking was conducted on the 60 screened compounds. In-silico ADME and toxicity studies were also conducted to assess the drug-likeness and safety of the identified compounds. The results indicated that coumarin-1,2,3-triazole hybrids COUM-0849, COUM-0935, COUM-0414, COUM-1335, COUM-0276, and COUM-0484 exhibit dock score of - 10.2, - 10.2, - 10.1, - 10.1, - 10, - 10 while reference molecule - 7.9 kcal/mol for EGFR (PDB ID: 4HJO) respectively. The molecular docking and molecular dynamics simulations revealed that the identified compounds formed stable interactions with the active site of EGFR, indicating their potential as inhibitors. The in-silico ADME and toxicity studies showed that the compounds had favorable drug-likeness properties and low toxicity, further supporting their potential as therapeutic agents. Finally, we performed DFT studies on the best-selected ligands to gain further insights into their electronic properties. The findings of this study provide important insights into the potential of coumarin-1,2,3-triazole hybrids as promising EGFR inhibitors for the management of lung cancer.

Targeting P2Y14R protects against necroptosis of intestinal epithelial cells through PKA/CREB/RIPK1 axis in ulcerative colitis

Purinergic signaling plays a causal role in the pathogenesis of inflammatory bowel disease. Among purinoceptors, only P2Y14R is positively correlated with inflammatory score in mucosal biopsies of ulcerative colitis patients, nevertheless, the role of P2Y14R in ulcerative colitis remains unclear. Here, based on the over-expressions of P2Y14R in the intestinal epithelium of mice with experimental colitis, we find that male mice lacking P2Y14R in intestinal epithelial cells exhibit less intestinal injury induced by dextran sulfate sodium. Mechanistically, P2Y14R deletion limits the transcriptional activity of cAMP-response element binding protein through cAMP/PKA axis, which binds to the promoter of Ripk1, inhibiting necroptosis of intestinal epithelial cells. Furthermore, we design a hierarchical strategy combining virtual screening and chemical optimization to develop a P2Y14R antagonist HDL-16, which exhibits remarkable anti-colitis effects. Summarily, our study elucidates a previously unknown mechanism whereby P2Y14R participates in ulcerative colitis, providing a promising therapeutic target for inflammatory bowel disease.

Exploring the potential mechanism of Heng-Gu-Gu-Shang-Yu-He-Ji therapy for osteoporosis based on network pharmacology and transcriptomics

ETHNOPHARMACOLOGICAL RELEVANCE

Heng-Gu-Gu-Shang-Yu-He-Ji (Osteoking, OK) is a well-known formula for fracture therapy. In clinic, OK is effective in treating fractures while alleviating osteoporosis (OP) symptoms. However, active components of OK and the associated molecular mechanisms remain not fully elucidated.

AIM OF THE STUDY

This study aims to systematically evaluate the anti-osteoporosis efficacy of OK and for the first time combine network pharmacology with high-throughput whole gene transcriptome sequencing to study its underlying mechanism.

MATERIALS AND METHODS

In this study, the osteoporosis model was established by the castration of both ovaries. The level of serum bone turnover factor was detected by enzyme-linked immunosorbent assay. Micro-CT and HE staining were used to observe the changes of bone histopathology, and nano-indentation technique was used to detect the biomechanical properties of rat bone. The main active Chemical components of OK were identified using UPLC-DAD. Efficacy verification and mechanism exploration were conducted by network pharmacology, molecular docking, whole gene transcriptomics and in vivo experiments.

RESULTS

In our study, OK significantly improved bone microarchitecture and bone biomechanical parameters in OVX rats, reduced osteoclast indexes such as C-telopeptide of type I collage (CTX-I) and increased Osteoprotegerin (OPG)/Receptor activator of NF-κB ligand (RANKL) levels. Mechanistically, PI3K/AKT pathway was a common pathway for genome enrichment analysis (KEGG) of both network pharmacology and RNA-seq studies. G protein-β-like protein (GβL), Ribosomal-protein S6 kinase homolog 2 (S6K2), and Phosphoinositide 3-kinase (PI3K) appeared differentially expression in the PI3K-AKT signaling pathway. These results were also confirmed by qRT-PCR and immunohistochemistry.

CONCLUSIONS

OK may be used to treat osteoporosis, at least partly by activating PI3K/AKT/mTORC1 signaling pathway.

Evaluating the Therapeutic Potential of Curcumin and Synthetic Derivatives: A Computational Approach to Anti-Obesity Treatments

Natural compounds such as curcumin, a polyphenolic compound derived from the rhizome of turmeric, have gathered remarkable scientific interest due to their diverse metabolic benefits including anti-obesity potential. However, curcumin faces challenges stemming from its unfavorable pharmacokinetic profile. To address this issue, synthetic curcumin derivatives aimed at enhancing the biological efficacy of curcumin have previously been developed. In silico modelling techniques have gained significant recognition in screening synthetic compounds as drug candidates. Therefore, the primary objective of this study was to assess the pharmacokinetic and pharmacodynamic characteristics of three synthetic derivatives of curcumin. This evaluation was conducted in comparison to curcumin, with a specific emphasis on examining their impact on adipogenesis, inflammation, and lipid metabolism as potential therapeutic targets of obesity mechanisms. In this study, predictive toxicity screening confirmed the safety of curcumin, with the curcumin derivatives demonstrating a safe profile based on their LD50 values. The synthetic curcumin derivative 1A8 exhibited inactivity across all selected toxicity endpoints. Furthermore, these compounds were deemed viable candidate drugs as they adhered to Lipinski's rules and exhibited favorable metabolic profiles. Molecular docking studies revealed that both curcumin and its synthetic derivatives exhibited favorable binding scores, whilst molecular dynamic simulations showed stable binding with peroxisome proliferator-activated receptor gamma (PPARγ), csyclooxygenase-2 (COX2), and fatty acid synthase (FAS) proteins. The binding free energy calculations indicated that curcumin displayed potential as a strong regulator of PPARγ (-60.2 ± 0.4 kcal/mol) and FAS (-37.9 ± 0.3 kcal/mol), whereas 1A8 demonstrated robust binding affinity with COX2 (-64.9 ± 0.2 kcal/mol). In conclusion, the results from this study suggest that the three synthetic curcumin derivatives have similar molecular interactions to curcumin with selected biological targets. However, in vitro and in vivo experimental studies are recommended to validate these findings.

Chemical profiling of volatile compounds of the essential oil of grey-leaved rockrose (Cistus albidus L.) and its antioxidant, anti-inflammatory, antibacterial, antifungal, and anticancer activity in vitro and in silico

Cistus albidus: L., also known as Grey-leaved rockrose and locally addressed as šṭab or tûzzâla lbîḍa, is a plant species with a well-established reputation for its health-promoting properties and traditional use for the treatment of various diseases. This research delves into exploring the essential oil extracted from the aerial components of Cistus albidus (referred to as CAEO), aiming to comprehend its properties concerning antioxidation, anti-inflammation, antimicrobial efficacy, and cytotoxicity. Firstly, a comprehensive analysis of CAEO's chemical composition was performed through Gas Chromatography-Mass Spectrometry (GC-MS). Subsequently, four complementary assays were conducted to assess its antioxidant potential, including DPPH scavenging, β-carotene bleaching, ABTS scavenging, and total antioxidant capacity assays. The investigation delved into the anti-inflammatory properties via the 5-lipoxygenase assay and the antimicrobial effects of CAEO against various bacterial and fungal strains. Additionally, the research investigated the cytotoxic effects of CAEO on two human breast cancer subtypes, namely, MCF-7 and MDA-MB-231. Chemical analysis revealed camphene as the major compound, comprising 39.21% of the composition, followed by α-pinene (19.01%), bornyl acetate (18.32%), tricyclene (6.86%), and melonal (5.44%). Notably, CAEO exhibited robust antioxidant activity, as demonstrated by the low IC50 values in DPPH (153.92 ± 4.30 μg/mL) and β-carotene (95.25 ± 3.75 μg/mL) assays, indicating its ability to counteract oxidative damage. The ABTS assay and the total antioxidant capacity assay also confirmed the potent antioxidant potential with IC50 values of 120.51 ± 3.33 TE μmol/mL and 458.25 ± 3.67 µg AAE/mg, respectively. In terms of anti-inflammatory activity, CAEO displayed a substantial lipoxygenase inhibition at 0.5 mg/mL. Its antimicrobial properties were broad-spectrum, although some resistance was observed in the case of Escherichia coli and Staphylococcus aureus. CAEO exhibited significant dose-dependent inhibitory effects on tumor cell lines in vitro. Additionally, computational analyses were carried out to appraise the physicochemical characteristics, drug-likeness, and pharmacokinetic properties of CAEO's constituent molecules, while the toxicity was assessed using the Protox II web server.

Network pharmacology study to explore the multiple molecular mechanism of SH003 in the treatment of non-small cell lung cancer

BACKGROUND

Non-small cell lung cancer (NSCLC) is one of the leading causes of human death worldwide. Herbal prescription SH003 has been developed to treat several cancers including NSCLC. Due to the multi-component nature of SH003 with multiple targets and pathways, a network pharmacology study was conducted to analyze its active compounds, potential targets, and pathways for the treatment of NSCLC.

METHODS

We systematically identified oral active compounds within SH003, employing ADME criteria-based screening from TM-MC, OASIS, and TCMSP databases. Concurrently, SH003-related and NSCLC-associated targets were amalgamated from various databases. Overlapping targets were deemed anti-NSCLC entities of SH003. Protein-protein interaction networks were constructed using the STRING database, allowing the identification of pivotal proteins through node centrality measures. Empirical validation was pursued through LC-MS analysis of active compounds. Additionally, in vitro experiments, such as MTT cell viability assays and western blot analyses, were conducted to corroborate network pharmacology findings.

RESULTS

We discerned 20 oral active compounds within SH003 and identified 239 core targets shared between SH003 and NSCLC-related genes. Network analyses spotlighted 79 hub genes, including TP53, JUN, AKT1, STAT3, and MAPK3, crucial in NSCLC treatment. GO and KEGG analyses underscored SH003's multifaceted anti-NSCLC effects from a genetic perspective. Experimental validations verified SH003's impact on NSCLC cell viability and the downregulation of hub genes. LC-MS analysis confirmed the presence of four active compounds, namely hispidulin, luteolin, baicalein, and chrysoeriol, among the eight compounds with a median of > 10 degrees in the herb-compounds-targets network in SH003. Previously unidentified targets like CASP9, MAPK9, and MCL1 were unveiled, supported by existing NSCLC literature, enhancing the pivotal role of empirical validation in network pharmacology.

CONCLUSION

Our study pioneers the harmonization of theoretical predictions with practical validations. Empirical validation illuminates specific SH003 compounds within NSCLC, simultaneously uncovering novel targets for NSCLC treatment. This integrated strategy, accentuating empirical validation, establishes a paradigm for in-depth herbal medicine exploration. Furthermore, our network pharmacology study unveils fresh insights into SH003's multifaceted molecular mechanisms combating NSCLC. Through this approach, we delineate active compounds of SH003 and target pathways, reshaping our understanding of its therapeutic mechanisms in NSCLC treatment.

Phytochemical profiling, in vitro biological activities, and in silico (molecular docking and absorption, distribution, metabolism, excretion, toxicity) studies of Polygonum cognatum Meissn

Polygonum cognatum Meissn, a perennial herbaceous belonging to the Polygonaceae family, is an aromatic plant. High-performance liquid chromatography/diode array detector method was developed and validated for the phytochemical analysis of the plant. Also, various methods were used to investigate the antioxidant, antimicrobial, and cytotoxic activities of the methanolic extracts. Antioxidant activities were researched by 2,2'-diphenyl-1-picrylhydrazyl and cupric reducing antioxidant capacity methods. Among the tested standard microbial strains, Candida albicans was found to be more sensitive with a 24.60 ± 0.55 mm inhibition zone according to the diffusion tests. In the microdilution tests, the minimum inhibitory concentration and minimum bactericidal/fungicidal concentration values were 4.75 and ≥ 4.75 mg/mL, respectively, for all tested pathogens. Human colon carcinoma cells were used to investigate cytotoxicity by using 3-[4,5-dimethylthiazol-2-yl]-2,5-diphenyl tetrazolium bromide analysis (IC50  = 2891 μg/mL for Plant A, IC50  = 3291 μg/mL for Plant B). Molecular docking and absorption, distribution, metabolism, excretion, and toxicity analysis were used to explain inhibition mechanisms of major phenolic compounds of plants against Tankyrase 1, Tankyrase 2 enzymes, and deoxyribonucleic acid gyrase subunit B and found compatible with experimental results.

Biochemical and molecular docking-based strategies of Acalypha indica and Boerhavia diffusa extract by targeting bacterial strains and cancer proteins

Antibiotic-resistant microbes have emerged around the world, presenting a risk to health. Plant-derived drugs have become a potential source for the production of antibiotic-resistant drugs and cancer therapies. In this study, we investigated the antibacterial, cytotoxic and antioxidant properties of Acalypha indica and Boerhavia diffusa, and conducted in silico molecular docking experiments against EGFR and VEGFR-2 proteins. The metabolic extract of A. indica inhibited Streptococcus iniae and Staphylococcus sciuri with inhibition zones of 21.66 ± 0.57 mm and 20.33 ± 0.57 mm, respectively. The B. diffusa leaf extract produced inhibition zones of 20.3333 ± 0.5773 mm and 20.33 ± 0.57 mm against Streptococcus iniae and Edwardsiella anguillarum, respectively. A. indica and B. diffusa extracts had toxicities of 162.01 μg/ml and 175.6 μg/ml, respectively. Moreover, B. diffusa (IC50 =154.42 µg/ml) leaf extract exhibited moderately higher antioxidant activity compared with the A. indica (IC50 = 218.97 µg/ml) leaf extract. Multiple interactions were observed at Leu694, Met769 and Leu820 sites for EGFR and at Asp1046 and Cys1045 sites for VEGFR during the molecular docking study. CID-235030, CID-70825 and CID-156619353 had binding energies of -7.6 kJ/mol, -7.5 kJ/mol and -7.6 kJ/mol, respectively, with EGFR protein. VEGFR-2 protein had docking energies of -7.5 kJ/mol, -7.6 kJ/mol and -7.3 kJ/mol, respectively, for CID-6420353, CID-156619353 and CID-70825 compounds. The MD simulation trajectories revealed the hit compound; CID-235030 and EGFR complex, CID-6420353 and VEGFR-2 exhibit stable profile in the root mean square deviation (RMSD), radius of gyration (Rg), solvent accessible surface area (SASA), hydrogen bond and root mean square fluctuation (RMSF) and the binding free energy by MM-PBSA method. This study indicates that methanol extracts of A. indica and B. diffusa may play a crucial role in developing antibiotic-resistant and cancer drugs.Communicated by Ramaswamy H. Sarma.

A computational investigation of potential plant-based bioactive compounds against drug-resistant Staphylococcus aureus of multiple target proteins

Drug-resistant Staphylococcus aureus (DRSA) poses a significant global health threat, like bacteremia, endocarditis, skin, soft tissue, bone, and joint infections. Nowadays, the resistance against conventional drugs has been a prompt and focused medical concern. The present study aimed to explore the inhibitory potential of plant-based bioactive compounds (PBBCs) against effective target proteins using a computational approach. We retrieved and verified 22 target proteins associated with DRSA and conducted a screening process that involved testing 87 PBBCs. Molecular docking was performed between screened PBBCs and reference drugs with selected target proteins via AutoDock. Subsequently, we filtered the target proteins and top PBBCs based on their binding affinity scores. Furthermore, molecular dynamic simulation was carried out through GROMACS for a duration of 100 ns, and the binding free energy was calculated using the gmx_MMPBSA. The result showed consistent hydrogen bonding interactions among the amino acid residues Ser 149, Arg 151, Thr 165, Thr 216, Glu 239, Ser 240, Ile 14, as well as Asn 18, Gln 19, Lys 45, Thr 46, Tyr 109, with their respective target proteins of the penicillin-binding protein and dihydrofolate reductase complex. Additionally, we assessed the pharmacokinetic properties of screened PBBCs via SwissADME and AdmetSAR. The findings suggest that β-amyrin, oleanolic acid, kaempferol, quercetin, and friedelin have the potential to inhibit the selected target proteins. In future research, both in vitro and in vivo, experiments will be needed to establish these PBBCs as potent antimicrobial drugs for DRSA.Communicated by Ramaswamy H. Sarma.

Tou Nong powder obstructs ulcerative colitis through the regulation of NF-κB/NLRP3/Caspase-1/GSDMD inflammasome pyroptotic pathway

ETHNOPHARMACOLOGICAL RELEVANCE

Tou Nong Powder (TNP), a classical Chinese medicinal formula originated from the Chinese Ming Dynasty, has been applied to treat skin ulcers in patients with deficient constitutions. According to theory of traditional Chinese medicine, colonic ulcers share similar pathological conditions with skin ulcers, and consequently, TNP has been applied to ulcerative colitis (UC) safely and effectively.

AIM OF STUDY

To investigate whether TNP obstructs 2,4,6-trinitrobenzene sulfonic acid (TNBS) induced enteric inflammation through regulation of NLRP3 inflammasome and attenuating enteric pyroptosis.

MATERIALS AND METHODS

Network pharmacology and UPLC-Q-TOF/MS were operated to identify compounds and pharmacological potential targets. The therapeutic effects of TNP were assessed on TNBS induced colitis via general symptoms (disease activity index, colonic weight and length) and histopathological observation. The NF-κB/NLRP3/Caspase-1/GSDMD signaling pathway regulation was investigated by Western blot and real time reverse transcription polymerase chain reaction (RT-qPCR).

RESULTS

TNP ameliorates the disease activity index, reverses the increase of colonic weight increase, alleviates colonic shortening and colonic histopathological injury. A decrease in tumor necrosis factor α (TNF-α), diamine oxidase (DAO), intercellular adhesion molecule-1 (ICAM-1), and endo-toxin (ET) were investigated in peripheral circulation. Moreover, TNP significantly obstructed the NF-κB/NLRP3/Caspase-1/GSDMD signaling pathway.

CONCLUSION

TNP displays a promising therapeutic effect on UC via suppressing NF-κB/NLRP3/Caspase-1/GSDMD signaling pathway and reducing the expression of IL-1β and IL-18.

Antioxidant activity, anti-tyrosinase activity, molecular docking studies, and molecular dynamic simulation of active compounds found in nipa palm vinegar

Tyrosinase is a key enzyme in melanogenesis and its inhibitors have become increasingly because of their potential activity as hypopigmenting agents which have less side effects. Nipa palm vinegar is an aqueous product that is normally used as a food supplement. The aim of this study was to study the determination of antioxidant activity and tyrosinase inhibitory activities of aqueous extract of original nipa palm vinegar (AE O-NPV), nipa palm vinegar powder (NPV-P) and aqueous extract of nipa palm vinegar powder (AE NPV-P) were examined. Nipa palm vinegars were evaluated the phenolic and flavonoid content, and the active compounds which were submitted to molecular docking and molecular dynamic simulation, chemoinformatics, rule of five, skin absorption and toxicity. The highest phenolic and flavonoid contents in the AE O-NPV were 2.36 ± 0.23 mg gallic acid equivalents/g extract and 5.11 ± 0.59 mg quercetin equivalents/g, and the highest ABTS radical cation scavenging activity was also found. The AE O-NPV, NPV-P and AE NPV-P showed anti-mushroom tyrosinase activity. The HPLC analysis showed that there were vanillic acid and three flavonoids (catechin, rutin and quercetin). The molecular docking study revealed that the binding of the vanillic acid and three flavonoids occurred in the active site residues (histidine and other amino acids). Moreover, the number of hydrogen bond acceptors/donors, solubility, polar surface area and bioavailability score of the vanillic acid and three flavonoids were acceptable compared to Lipinski's Rule of Five. The molecular dynamic simulation showed that vanillic acid interacts with HIS284 through π-π stacking hydrophobic interactions and forms a metal-acceptor interaction with the copper molecule at the tyrosinase active site. All compounds revealed good skin permeability and nontoxicity. Nipa palm vinegar could be a promising source of a new ingredient for tyrosinase inhibition for cosmetics or pharmaceutical products.

Current Trends and Challenges in Drug-Likeness Prediction: Are They Generalizable and Interpretable?

Importance: Drug-likeness of a compound is an overall assessment of its potential to succeed in clinical trials, and is essential for economizing research expenditures by filtering compounds with unfavorable properties and poor development potential. To this end, a robust drug-likeness prediction method is indispensable. Various approaches, including discriminative rules, statistical models, and machine learning models, have been developed to predict drug-likeness based on physiochemical properties and structural features. Notably, recent advancements in novel deep learning techniques have significantly advanced drug-likeness prediction, especially in classification performance. Highlights: In this review, we addressed the evolving landscape of drug-likeness prediction, with emphasis on methods employing novel deep learning techniques, and highlighted the current challenges in drug-likeness prediction, specifically regarding the aspects of generalization and interpretability. Moreover, we explored potential remedies and outlined promising avenues for future research. Conclusion: Despite the hurdles of generalization and interpretability, novel deep learning techniques have great potential in drug-likeness prediction and are worthy of further research efforts.

Therapeutic Potential of the Genus Zanthoxylum Phytochemicals: A Theoretical ADME/Tox Analysis

Natural products (NPs) are essential in the search for new drugs to treat a wide range of diseases, including infectious and malignant disorders. However, despite the discovery of many bioactive NPs, they often do not make it to market as drugs due to toxicity and other challenges. The development of NPs into drugs is a long and expensive process, and many promising compounds are abandoned along the way. These molecules require in silico ADMET profiling in order to speed up their development into drugs lower costs, and the high attrition rate. The objective of this work was to produce thorough ADMET profiles of secondary metabolites from several classes that were isolated from Zanthoxylum species. The genus has a long history of therapeutic use, including treating tumours, hypertension, gonorrhoea, coughs, bilharzia, chest pains, and toothaches. The study used a dataset of 406 compounds from the genus for theoretical ADMET analysis. The findings revealed that 81% of the compounds met Lipinski's rule of five, indicating good oral bioavailability. The drug-likeness criteria were taken into account, with percentages ranging from 66.2 to 88.1 percent. Additionally, 9.2% of the compounds were predicted to be lead-like, demonstrating their potential as promising drug development candidates. Interestingly, none of the compounds inhibited hERG I, while 33% inhibited hERG II, potentially having cardiac implications. Additionally, 30% of the compounds exhibited AMES toxicity inhibition, while 23.6% were identified as hepatotoxic and 22.2% would cause skin sensitivity. Moreover, 81.8% of the compounds demonstrated high intestinal absorption, making them desirable for oral drugs. In conclusion, these findings highlight the diverse properties of the investigated compounds and their potential for drug development.

Exploiting Pharma 4.0 Technologies in the Non-Biological Complex Drugs Manufacturing: Innovations and Implications

The pharmaceutical industry has entered an era of transformation with the emergence of Pharma 4.0, which leverages cutting-edge technologies in manufacturing processes. These hold tremendous potential for enhancing the overall efficiency, safety, and quality of non-biological complex drugs (NBCDs), a category of pharmaceutical products that pose unique challenges due to their intricate composition and complex manufacturing requirements. This review attempts to provide insight into the application of select Pharma 4.0 technologies, namely machine learning, in silico modeling, and 3D printing, in the manufacturing process of NBCDs. Specifically, it reviews the impact of these tools on NBCDs such as liposomes, polymeric micelles, glatiramer acetate, iron carbohydrate complexes, and nanocrystals. It also addresses regulatory challenges associated with the implementation of these technologies and presents potential future perspectives, highlighting the incorporation of digital twins in this field of research as it seems to be a very promising approach, namely for the optimization of NBCDs manufacturing processes.

Modelling enzyme inhibition toxicity of ionic liquid from molecular structure via convolutional neural network model

Deep learning (DL) methods further promote the development of quantitative structure-activity/property relationship (QSAR/QSPR) models by dealing with complex relationships between data. An acetylcholinesterase inhibitory toxicity model of ionic liquids (ILs) was established using a convolution neural network (CNN) combined with support vector machine (SVM), random forest (RF) and multilayer perceptron (MLP). A CNN model was proposed for feature self-learning and extraction of ILs. By comparing with the model results through feature engineering (FE), the model regression results based on the CNN model for feature extraction have been substantially improved. The results showed that all six models (FE-SVM, FE-RF, FE-MLP, CNN-SVM, CNN-RF, and CNN-MLP) had good prediction accuracy, but the results based on the CNN model were better. The hyperparameters of six models were optimized by grid search and the 10-fold cross validation. Compared with the existing models in the literature, the model performance has been further improved. The model could be used as an intelligent tool to guide the design or screening of low-toxicity ILs.

Mechanism of Simiao Decoction in the treatment of atherosclerosis based on network pharmacology prediction and molecular docking

To explore the molecular mechanism of Simiao Decoction (SMD) intervening atherosclerosis (AS). The main components and potential mechanisms of SMD remain unknown. This study aims to initially clarify the potential mechanism of SMD in the treatment of AS based on network pharmacology and molecular docking techniques. The principal components and corresponding protein targets of SMD were searched on Traditional Chinese Medicine Systems Pharmacology Database and Analysis Platform and the compound-target network was constructed by Cytoscape3.9.1. AS targets were searched on DrugBank, OMIM, and TTD databases. The intersection of compound target and disease target was obtained and the coincidence target was imported into STRING database to construct a protein-protein interaction network. We further performed Gene Ontology and Kyoto Encyclopedia of Genes and Genomes pathway enrichment analysis on the targets. The molecular docking method was used to verify the interaction between core components of SMD and targets. We created the active compounds-targets network and the active compounds-AS-targets network based on the network database containing Traditional Chinese Medicine Systems Pharmacology Database and Analysis Platform, DrugBank, OMIM, and TTD. We discovered that the therapy of AS with SMD involves 3 key substances-quercetin, kaempferol, and luteolin-as well as 5 crucial targets-ALB, AKT1, TNF, IL6, and TP53. The Gene Ontology and Kyoto Encyclopedia of Genes and Genomes enrichment analysis revealed that the shared targets involved a number of signaling pathways, including the advanced glycosylation end product-receptor of AGE signaling pathway in diabetic complications, Hepatitis B, Lipid and atherosclerosis, Chemical Carcinogenesis-Receptor Activation, and Pathways in Cancer. The molecular docking demonstrated that the binding energies of quercetin, kaempferol, and luteolin with 5 important targets were favorable. This study reveals the active ingredients and potential molecular mechanism of SMD in the treatment of AS, and provides a reference for subsequent basic research.

In-silico design, pharmacophore-based screening, and molecular docking studies reveal that benzimidazole-1,2,3-triazole hybrids as novel EGFR inhibitors targeting lung cancer

Lung cancer is a complex and heterogeneous disease, which has been associated with various molecular alterations, including the overexpression and mutations of the epidermal growth factor receptor (EGFR). In this study, designed a library of 1843 benzimidazole-1,2,3-triazole hybrids and carried out pharmacophore-based screening to identify potential EGFR inhibitors. The 164 compounds were further evaluated using molecular docking and molecular dynamics simulations to understand the binding interactions between the compounds and the receptor. In-si-lico ADME and toxicity studies were also conducted to assess the drug-likeness and safety of the identified compounds. The results of this study indicate that benzimidazole-1,2,3-triazole hybrids BENZI-0660, BENZI-0125, BENZI-0279, BENZI-0415, BENZI-0437, and BENZI-1110 exhibit dock scores of -9.7, -9.6, -9.6, -9.6, -9.6, -9.6 while referencing molecule -7.9 kcal/mol for EGFR (PDB ID: 4HJO), respectively. The molecular docking and molecular dynamics simulations revealed that the identified compounds formed stable interactions with the active site of EGFR, indicating their potential as inhibitors. The in-silico ADME and toxicity studies showed that the compounds had favorable drug-likeness properties and low toxicity, further supporting their potential as therapeutic agents. Finally, performed DFT studies on the best-selected ligands to gain further insights into their electronic properties. The findings of this study provide important insights into the potential of benzimidazole-1,2,3-triazole hybrids as promising EGFR inhibitors for the treatment of lung cancer. This research opens up a new avenue for the discovery and development of potent and selective EGFR inhibitors for the treatment of lung cancer.Communicated by Ramaswamy H. Sarma.

In vitro and in silico perspectives on the activation of antioxidant responsive element by citrus-derived flavonoids

Introduction

Oxidative stress plays an essential role in the pathogenesis of chronic diseases. Disrupting the Keap1-Nrf2 pathway by binding Keap1 is identified as a potential strategy to prevent oxidative stress-related chronic diseases. Therefore, of special interest is the utilization of dietary antioxidations from citrus, including narirutin, naringenin, hesperetin, hesperidin, naringin, neohesperidin dihydrochalcone, neohesperidin, and nobiletin, has been exploited as a prospective way to treat or prevent several human pathologies as Keap1-Nrf2 inhibitors for modulation of antioxidant properties.

Methods

To probe into the structural foundation of the molecular identification of citrus-derived antioxidations, we calculated the antioxidant responsive element activation ability of citrus-derived flavonoids after binding with Keap1. Also, the quantum chemistry properties and binding mode were performed theoretically with frontier molecular orbitals, molecular electrostatic potential analysis, molecular docking, and absorption, distribution, metabolism, excretion (ADME) calculation.

Results and discussion

Experimental findings combining computational assays revealed that the tested citrus-derived flavonoids can be grouped into strong agonists and weak agonists. The citrus-derived antioxidations were well housed in the bound zone of Keap1 via stable hydrogen bonding and hydrophobic interaction. Eventually, three of eight antioxidations were identified after ADME and physicochemical evaluations. The citrus-derived flavonoids were identified as potential dietary antioxidants of the Keap1-Nrf2 interaction, and can be used to improve oxidative stress-related chronic diseases.

Investigation of target genes and potential mechanisms related to compound Xiao-ai-fei honey ointment based on network pharmacology and bioinformatics analysis

BACKGROUND

Compound Xiao-ai-fei honey ointment (CXHO) is an anticancer preparation with a long history in Uyghur folk medicine in China and has been used for the treatment of gastric cancer (GC) in Xinjiang, China. Nevertheless, the mechanism of its anticancer effect remains to be investigated.

METHODS

Bioactive ingredients of CXHO were retrieved from the Traditional Chinese Medicine Systems Pharmacology Database and Analysis Platform database. Target genes of ingredients were acquired via the PubChem and Swiss target prediction database. Gene expression profiling of GC was obtained from GSE54129 in the GEO database and analyzed using the limma package in R. The hub genes associated with CXHO in GC were validated using the TIMER2.0 database, GEPIA2 database and Auto Dock tools. The effect of CXHO on migration of GC cells was detected by Transwell chamber assay and Wound healing assay. The effect of CXHO on expression levels of MMP2/MMP9 and NF-κb, PI3K/AKT signaling pathway was detected by Western blot assay.

RESULTS

Forty-five bioactive ingredients and their 819 related genes were found. A total of 462 differentially expressed genes were identified between GC patients and healthy controls. Seventeen common target genes were identified as hub genes CXHO against GC. Among them, MMP2 and MMP9 were significantly associated with tumor immune infiltrates and had good binding affinity with effective ingredients. Moreover, we validated the mRNA and protein expression levels and prognostic value of MMP2 and MMP9 by different databases. In addition, Kyoto encyclopedia of genes and genomes and gene ontology analyses showed that the 17 common target genes were mainly involved in steroid hormone biosynthesis and cancer-related pathways. Experimental results showed that CXHO inhibited migration of GC cells and down regulated the expression levels of MMP2/MMP9, NF-κb. In addition, CXHO can inhibited PI3K/AKT signaling pathway.

CONCLUSION

We identified and experimental validated 2 pivotal target genes of CXHO against GC and preliminarily analyzed the potential mechanisms by which CXHO inhibits the development of GC. All these findings support CXHO as a promising drug for the treatment of GC.

In-silico identification of small molecule benzofuran-1,2,3-triazole hybrids as potential inhibitors targeting EGFR in lung cancer via ligand-based pharmacophore modeling and molecular docking studies

Lung cancer is one of the most common and deadly types of cancer worldwide, and the epidermal growth factor receptor (EGFR) has emerged as a promising therapeutic target for the treatment of this disease. In this study, we designed a library of 1840 benzofuran-1,2,3-triazole hybrids and conducted pharmacophore-based screening to identify potential EGFR inhibitors. The 20 identified compounds were further evaluated using molecular docking and molecular dynamics simulations to understand their binding interactions with the EGFR receptor. In-silico ADME and toxicity studies were also performed to assess their drug-likeness and safety profiles. The results of this study showed the benzofuran-1,2,3-triazole hybrids BENZ-0454, BENZ-0143, BENZ-1292, BENZ-0335, BENZ-0332, and BENZ-1070 dock score of - 10.2, - 10, - 9.9, - 9.8, - 9.7, - 9.6, while reference molecule - 7.9 kcal/mol for EGFR (PDB ID: 4HJO) respectively. The molecular docking and molecular dynamics simulations revealed that the identified compounds formed stable interactions with the active site of the receptor, indicating their potential as inhibitors. The in-silico ADME and toxicity studies suggested that the compounds had good pharmacokinetic and safety profiles, further supporting their potential as therapeutic agents. Finally, performed DFT studies on the best-selected ligands to gain further insights into their electronic properties. The findings of this study provide important insights into the potential of benzofuran-1,2,3-triazole hybrids as promising EGFR inhibitors for the treatment of lung cancer. Overall, this study provides a valuable starting point for the development of novel EGFR inhibitors with improved efficacy and safety profiles.

Graphical Abstract

Supplementary Information

The online version contains supplementary material available at 10.1007/s40203-023-00157-1.

Network pharmacology prediction and molecular docking-based strategy to discover the potential pharmacological mechanism of Huang-Qi-Gui-Zhi-Wu-Wu decoction against deep vein thrombosis

BACKGROUND

Huangqi Guizhi Wuwu decoction (HQGZWWD) has been used to treat and prevent deep vein thrombosis (DVT) in China. However, its potential mechanisms of action remain unclear. This study aimed to utilize network pharmacology and molecular docking technology to elucidate the molecular mechanisms of action of HQGZWWD in DVT.

METHODS

We identified the main chemical components of HQGZWWD by reviewing the literature and using a Traditional Chinese Medicine Systems Pharmacology (TCMSP) database. We used GeneCards and Online Mendelian Inheritance in Man databases to identify the targets of DVT. Herb-disease-gene-target networks using Cytascape 3.8.2 software; a protein-protein interaction (PPI) network was constructed by combining drug and disease targets on the STRING platform. Additionally, we conducted Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses. Finally, molecular docking verification of active components and core protein targets was conducted.

RESULTS

A total of 64 potential targets related to DVT were identified in HQGZWWD, with 41 active components; quercetin, kaempferol, and beta-sitosterol were the most effective compounds. The PPI network analysis revealed that AKT1, IL1B, and IL6 were the most abundant proteins with the highest degree. GO analysis indicated that DVT treatment with HQGZWWD could involve the response to inorganic substances, positive regulation of phosphorylation, plasma membrane protein complexes, and signaling receptor regulator activity. KEGG analysis revealed that the signaling pathways included pathways in cancer, lipid and atherosclerosis, fluid shear stress and atherosclerosis, and the phosphatidylinositol 3-kinases/protein kinase B(PI3K-Akt) and mitogen-activated protein kinase (MAPK) signaling pathways. The molecular docking results indicated that quercetin, kaempferol, and beta-sitosterol exhibited strong binding affinities for AKT1, IL1B, and IL6.

CONCLUSION

Our study suggests that AKT1, IL1B, and IL6 are promising targets for treating DVT with HQGZWWD. The active components of HQGZWWD likely responsible for its effectiveness against DVT are quercetin, kaempferol, and beta-sitosterol, they may inhibit platelet activation and endothelial cell apoptosis by regulating the PI3K/Akt and MAPK signaling pathways, slowing the progression of DVT.

Towards artificial intelligence-enabled extracellular vesicle precision drug delivery

Extracellular Vesicles (EVs), particularly exosomes, recently exploded into nanomedicine as an emerging drug delivery approach due to their superior biocompatibility, circulating stability, and bioavailability in vivo. However, EV heterogeneity makes molecular targeting precision a critical challenge. Deciphering key molecular drivers for controlling EV tissue targeting specificity is in great need. Artificial intelligence (AI) brings powerful prediction ability for guiding the rational design of engineered EVs in precision control for drug delivery. This review focuses on cutting-edge nano-delivery via integrating large-scale EV data with AI to develop AI-directed EV therapies and illuminate the clinical translation potential. We briefly review the current status of EVs in drug delivery, including the current frontier, limitations, and considerations to advance the field. Subsequently, we detail the future of AI in drug delivery and its impact on precision EV delivery. Our review discusses the current universal challenge of standardization and critical considerations when using AI combined with EVs for precision drug delivery. Finally, we will conclude this review with a perspective on future clinical translation led by a combined effort of AI and EV research.

Design and synthesis of thiadiazole-oxadiazole-acetamide derivatives: Elastase inhibition, cytotoxicity, kinetic mechanism, and computational studies

Considering the biological significance of 1,3,4-thiadiazole/oxadiazole heterocyclic scaffolds, a novel series of 1,3,4-thiadiazole-1,3,4-oxadiazole-acetamide derivatives (7a-j) was designed and synthesized using molecular hybridization. The inhibitory effects of the target compounds on elastase were evaluated, and all of these molecules were found to be potent inhibitors compared to the standard reference oleanolic acid. Compound 7f exhibited the excellent inhibitory activity (IC₅₀ = 0.06 ± 0.02 μM), which is 214-fold more active than oleanolic acid (IC₅₀ = 12.84 ± 0.45 μM). Kinetic analysis was also performed on the most potent compound (7f) to determine the mode of binding with the target enzyme, and it was discovered that 7f inhibits the enzyme in a competitive manner. Furthermore, the MTT assay method was used to assess their toxicity on the viability of B16F10 melanoma cell lines, and all compounds did not display any toxic effect on the cells even at high concentrations. The molecular docking studies of all compounds also justified with their good docking score and among them, compound 7f had a good conformational state with hydrogen bond interactions within the receptor binding pocket, which is consistent with the experimental inhibition studies.