Current Computer - Aided Drug Design - Online First

Penicillin G Acylase (PGA) plays a central role in the synthesis of β- lactam antibiotics. While certain variants have been extensively studied, their catalytic efficiency remains suboptimal for industrial application, necessitating further enzyme engineering to enhance substrate binding and reaction kinetics. This study aims to rationally design and engineer PGA variants with improved catalytic efficiency and stability toward β-lactam antibiotics, using an integrated approach of 4D QSAR modeling and neural network-guided mutation prediction.

A dataset of 30 enzyme-substrate complexes involving three PGA variants and diverse β-lactam substrates was compiled. Ten complexes were randomly selected for external validation. The binding conformation of Cefotaxime to a Bacillus thermotolerans PGA variant was used as a reference for molecular docking and structural alignment. Binding site analyses identified optimal substrate orientations, followed by 4D grid-based energy profiling, which revealed 15 high-energy hotspot residues per variant. These positions were systematically mutated in silico, generating 1130 variants through a neural network-based residue substitution algorithm.

Subsequent docking studies with Cefotaxime showed a strong positive correlation between predicted docking energies and Ki values derived from the 4D QSAR model, validating the model's predictive capability. Molecular dynamics simulations (2 × 100 ns) for selected variants, particularly Sequence Id_0, Id_2, Id_5, and Id_7, demonstrated stable binding interactions and favourable atomic distances, indicative of improved substrate affinity.

In Sequence Id_11, the hotspot is Phe148. Chain A showed the best results with Val and Leu as single mutants, followed by Met56 in Chain B with Leu, and Ser144 in Chain A with Glu, Ala, Ile, and Arg. In the case of Sequence Id_03, the hotspot is Phe147. Chain A showed good results with Ala, Lys, Thr, and Ser, whereas Tyr71 in Chain B showed good results with Glu, Lys, and Thr, and Arg266 in Chain B showed good results with Ala, Thr, and Val. Those that showed the highest sum of docking scores and Ki were chosen for further studies.

The study highlights the critical role of residue Phe148 in mediating stable interactions with Cefotaxime and other β-lactam substrates. The integrated computational strategy establishes a robust framework for engineering catalytically superior PGA variants, offering a valuable basis for further experimental validation and application in antibiotic biosynthesis.

DNA methyltransferase 1 (DNMT1) has recently emerged as a potential therapeutic target for diabetic wound healing (DWH) Studies have shown that inhibition of DNMT1 may be valuable in accelerating DWH

Virtual screening of 3,646 phytochemicals derived from the IMPPAT database was performed against DNMT1. This was followed by exhaustive docking ADMET analysis and molecular dynamics simulation to identify potential phytochemical inhibitors of DNMT1

Out of the 17967 phytochemicals present in the database 3646 of them were chosen for fast screening based on their drug-likeness properties. When compared with the reference compound over 2500 compounds exhibited lower binding energies. The top 972 compounds having binding energies ≤ 8.7 kcal/mol were chosen and 40 out of 972 compounds passed through the ADMET filters. These were then subjected to molecular docking and the compound with the least binding energy and favourable hydrogen bonding was then selected for molecular dynamics simulation. The stability of the Oroxindin-DNMT1 complex was further validated by molecular dynamics simulation studies

Derived from the traditional Chinese remedy Huang-Qin Oroxindin has been shown to possess a range of pharmacological effects including anti-inflammatory antitumor and antioxidant properties. The wound-healing potential of Oroxindin has to be evaluated in vitro and in vivo for further validation

Oroxindin emerged as the ideal phytochemical among the 3,646 screened The ability of Oroxindin to accelerate DWH still needs to be evaluated in vitro and in vivo for further validation

The white water lily (Nymphaea alba) is a traditional medicinal plant recognized for its diverse array of bioactive properties. However, its potential in wound healing remains largely unexplored. This study aimed to evaluate the phytochemical profile, cytotoxicity, and wound healing efficacy of Nymphaea alba flower extract (NAFE) using both in vitro and in vivo models, as well as computational network analysis.

Qualitative phytochemical screening of NAFE was conducted using standard techniques. Cytotoxicity was assessed on HaCaT keratinocyte cells at concentrations ranging from 0 to 1000 µg/ml. In vivo wound healing was evaluated using excision wound models in Wistar albino rats treated with 2.5% and 5% NAFE ointments, measuring wound contraction, epithelialization time, and breaking strength. In vitro scratch assays were used to assess cell migration at selected concentrations of NAFE. A wound-healing-associated network analysis was performed using IMPPAT, STRING, GeneCards, and OMIM databases to explore the molecular targets and interactions of bioactive compounds.

Phytochemical analysis confirmed the presence of alkaloids, flavonoids, phenolics, tannins, and glycosides. NAFE was found to be non-cytotoxic with an IC50 of 245 µg/ml. In vivo, 5% NAFE ointment showed 98.92% wound closure by day 14 and complete closure by day 21, comparable to betadine. Epithelialization time (15.83±0.16 days) was nearly equivalent to the standard drug. In vitro assays demonstrated enhanced HaCaT cell migration at concentrations of 122.5 and 245 µg/ml. Network analysis identified kaempferol and quercetin as key compounds interacting with wound-healing proteins, notably AKT1, ESR1, and EGFR.

The findings suggest that NAFE promotes wound healing by enhancing wound contraction, epithelialization, and cell migration, likely through the modulation of molecular pathways involved in tissue repair. The presence of bioactive compounds such as kaempferol and quercetin underpins the extract's pharmacological potential.

Nymphaea alba flower extract exhibits promising wound-healing activity through multiple mechanisms, including enhancement of cell migration and regulation of key proteins involved in tissue regeneration. These results support its potential as a natural therapeutic agent in wound management.

Ovarian cystadenoma (OC) is a common benign tumor in women. Wang’s formula for gynecological masses (WGM), a patented traditional Chinese medicine, was reported to have therapeutic potential for OC.

Here, we explored the pharmacological effects of WGM on treating OC via network pharmacology, molecular docking, and molecular dynamics simulations. The active ingredients in WGM and their putative targets were acquired from the TCMSP and BATMAN-TCM platforms. The known therapeutic targets of OC were obtained from the DrugBank, OMIM, and GeneCards databases. GO and KEGG analyses of the overlapping targets were performed via the DAVID database. Molecular docking and molecular dynamics (MD) simulations were conducted to evaluate the binding efficacy of the chemical ingredients to the core targets.

In total, 287 chemicals in WGM may relieve OC by targeting 134 genes involved in malignant tumors, endocrine resistance, and oxidative stress, of which ERBB2, ESR1, and AKT1 play vital roles. Molecular docking revealed stable binding energies of the receptors to the ligands, which bond via electrostatic interactions and van der Waals interactions in MD simulations.

The in silico bioinformatics analysis revealed the mechanisms of WGM treatment for OC. More pharmacological evidence of WGM treatment for OC, such as in vivo and clinical studies, is needed before WGM can benefit more patients.

Xiaoqinglong Decoction (XQLD) is a traditional Chinese medicinal formula commonly used to treat chronic urticaria (CU). However, its underlying therapeutic mechanisms remain incompletely characterized. This study employed an integrated approach combining network pharmacology, bioinformatics, molecular docking, and molecular dynamics simulations to identify the active components, potential targets, and related signaling pathways involved in XQLD's therapeutic action against CU, thereby providing a mechanistic foundation for its clinical application.

The active components of XQLD and their corresponding targets were identified using the Traditional Chinese Medicine Systems Pharmacology (TCMSP) database. CU-related targets were retrieved from the OMIM and GeneCards databases. Subsequently, core components and targets were determined via protein-protein interaction (PPI) network analysis and component-target-pathway network construction. Topological analyses were performed using Cytoscape software to prioritize core nodes within these networks. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses were conducted via the DAVID database to identify enriched biological processes and signaling pathways. Molecular docking was performed to evaluate binding interactions between key components and core targets, while molecular dynamics (MD) simulations were employed to assess the stability of the component-target complexes with the lowest binding energy. Finally, CU-related targets of XQLD were validated using datasets from the Gene Expression Omnibus (GEO) database.

A total of 135 active components and 249 potential targets of XQLD were identified, alongside 1,711 CU-related targets. Core components, such as quercetin, kaempferol, beta-sitosterol, naringenin, stigmasterol, and luteolin, exhibited high degree values in the constructed networks. The core targets identified included AKT1, TNF, IL6, TP53, PTGS2, CASP3, BCL2, ESR1, PPARG, and MAPK3. GO and KEGG pathway enrichment analyses revealed the PI3K-Akt signaling pathway as a central regulatory mechanism. Molecular docking studies demonstrated strong binding affinities between active components and core targets, with the stigmasterol-AKT1 complex exhibiting the lowest binding energy (-11.4 kcal/mol) and high stability in MD simulations. Validation using GEO datasets identified 12 core genes shared between CU-related targets and XQLD-associated targets, including PTGS2 and IL6, which were also prioritized as core targets in the network pharmacology analyses.

This study comprehensively integrates multidisciplinary approaches to clarify the potential molecular mechanisms of XQLD in treating CU, highlighting its multitarget and multipathway synergistic effects. Molecular docking and dynamics simulations confirm the stable interaction between stigmasterol and the core target AKT1. Additionally, GEO dataset analysis verifies the pathogenic relevance of targets such as PTGS2 and IL6, significantly enhancing the credibility of our findings. These results provide a modern scientific basis for the traditional therapeutic effects of XQLD on CU and have important implications for developing multitarget treatments for this condition. However, this study mainly relies on database mining and computational simulations. Further in vitro and in vivo experimental validations are needed to confirm the predicted component-target-pathway interactions.

This study identifies the active components, potential targets, and pathways through which XQLD exerts therapeutic effects on CU. These findings provide a theoretical foundation for further mechanistic studies and support their clinical application in the treatment of CU.

Inflammation is a natural process; however, chronic inflammation may result in numerous health issues. Etoricoxib (ETX), a selective cyclooxygenase-2 (COX-2) inhibitor, serves as an anti-inflammatory agent for various types of arthritis. However, prolonged use of ETX is associated with several adverse effects, including cardiovascular toxicity.

The current research aims to design analogues of ETX having superior pharmacokinetic properties and safer toxicological profiles employing the bioisosteric approach.

The bioisosteres of various groups in ETX were produced utilizing the MolOpt online tool, resulting in the generation of novel ETX analogues. The pharmacokinetics (ADME) and toxicological profiles of the generated analogues were calculated by ADMETLab 3.0 server. The druglikeness (DL) and drugscore (DS) were calculated using OSIRIS property explorer (PEO). The molecular docking analysis of the ETX analogues against the target protein (PDB ID: 5KIR) was carried out using AutoDock Vina, and their results were visualized by Discovery Studio 2021. Molecular dynamics (MD) simulation of the top three complexes was conducted using the Schrödinger suite. Binding free energy for the A098-5KIR, A188-5KIR, and D121-5KIR complexes was conducted using MM-GBSA/PBSA method.

A total of 1200 ETX bioisosteres were produced; among them, 51 were screened on the basis of ADMET profile, DL, and DS scores and selected for the docking study. A docking study revealed that 12 analogues show good interactions and docking scores. Furthermore, the MD simulation of ligands A098, A188, and D121 demonstrated stability throughout the 100 ns simulation period.

The findings of the ADMET study, DL, DS, docking study, MD simulation, and binding free energy calculation indicate that the analogues A098, A188, and D121, which are bioisosteres of ETX, may serve as potential anti-inflammatory agents for inflammation-related disorders.

Chemotherapy remains a primary treatment for stopping cancer cell growth. Unfortunately, resistance to chemotherapy is a challenge that leads to cancer relapse. Overexpression of the antiapoptotic proteins is a major cause of this resistance. BH3 mimetic compounds were developed in this work to deal with this issue by blocking the Bcl-2 anti-apoptotic proteins. Currently, only a few BH3 mimetics are approved drugs, and even fewer can effectively target all antiapoptotic Bcl-2 proteins.

The present study aimed to explore and screen the prodiginine family of molecules for new potential and effective BH-3 mimetics.

Molecular docking and molecular dynamics (MD) simulations were used to assess the potential of 30 prodiginine analogs as BH3 mimetics, including the obatoclax molecule, a prodiginine member used in clinical trials as a BH3 mimetic.

Molecular docking results showed four prodiginines to have lower free binding energy values for five Bcl-2 proteins (Bcl-2, Mcl-1, Bcl-w, Bcl-xl, and Bfl1) compared to the reference drug, obatoclax. The five analogs presented safe pharmacological profiles according to Lipinski’s rule of five. Furthermore, MD simulations demonstrated butylcycloheptyl prodiginine-Bcl-2 and prodigiosin-R2-Bcl-xl complexes to be more stable than the reference complexes obatoclax-Bcl-2 and obatoclax-Bcl-xl.

Based on these results, butylcycloheptyl prodigiosin and prodigiosin-R2 could be more effective BH3 mimetics and should be further studied.

XueFuZhuYu pills (XFZY), a traditional Chinese herbal formula originated from the xuefuzhuyu decoction in Correction on Errors in Medical Classics, has a certain clinical effect on the treatment of hyperprolactinemia (HPRL) caused by antipsychotics. However, the active ingredients and mechanism by which XFZY contributes to the hyperprolactinemia caused by antipsychotics remain unclear.

The aim of the study was to investigate the molecular basis of XFZY in the therapy of antipsychotic-induced HPRL and to establish a scientific foundation for its application.

First, the UHPLC-Q-TOF-MS/MS methodology was employed to perform chromatographic separation and gather mass spectrometry data. Subsequently, the preprocessed mass spectrometry data were uploaded to the Global Natural Products Social Molecular Networking (GNPS) platform for spectral library interrogation and molecular network analysis. Next, based on the detected chemical constituents and the Traditional Chinese Medicine Systems Pharmacology (TCMSP) database, the effective chemical components within XFZY were chosen. Swiss Target Prediction was employed to determine probable targets of components, and we used Cytoscape to create a network of components and their associated targets. After that, HPRL-related targets were found and filtered using four disease databases, and then a protein-protein interaction (PPI) network was built using the STRING database. Cytoscape was utilized to conduct visualization and cluster analysis. Meanwhile, the Metascape database was adopted for the enrichment analysis of GO and KEGG. At last, Autodock Vina was applied to perform molecular docking between the principal components and target proteins.

In total, 213 compounds were discovered in XFZY. Two hundred eight active chemical components, 622 probable targets, and 242 HPRL-related target genes were identified. There were 76 common targets between the XFZY and HPRL. Following analysis, 1371 GO biological process items and 162 KEGG signal pathways were identified. The primary chemicals and target proteins exhibited great affinity in molecular docking.

This research manifests that XFZY, as a traditional Chinese medicine formula, proffers a novel pathway for the treatment of antipsychotic-induced HPRL. We elucidated the specific molecular mechanisms underlying the anti-HPRL effects of XFZY and its active ingredients, laying a foundation for the subsequent clinical applications of this formula.

Our group previously reported isatin-based hydrazones (ISB1-ISB6) were further evaluated for their in vitro acetylcholine esterase, butylcholinestrase and cytotoxic effects on cancer cell lines. The compounds successfully suppressed AChE and BChE, with Ki values ranging from 1.06±0.07 to 23.57±1.64 nM for AChE and 15.31±1.28 to 84.41±8.04 nM for BChE. However, the IC50 values of these compounds for AChE and BChE were found to be in the ranges of 1.45-25.51 nM and 16.38-92.90 nM, respectively.

Furthermore, to explore the anti-tumor potential of our newly synthesized compounds, we conducted a cytotoxic MTT assay to assess their impact on two different cancer cell lines: MCF7 and A2780.

Our findings highlight diverse cytotoxic profiles among the compounds. Specifically, ISB2, ISB3, and ISB4 demonstrated potential cytotoxicity in the A2780 cell line, while ISB6 exhibited significant cytotoxicity in the MCF7 cell line. This suggests that these compounds have different effects on cancer cell types, indicating the need for further investigation into their potential applications in cancer therapy.

Finally, molecular docking and dynamic study revealed that lead molecule ISB3 provides stability in the AChE and BChE protein-ligand complex.

An important characteristic of the quality-by-design approach is defining risk, which is a combination of the probability of harm and its severity. During risk assessment, it is essential to determine how the formulation, properties of active ingredients and excipients, and process parameters can potentially affect critical quality attributes or critical process parameters.

to develop an algorithm and a mathematical model for predicting quality risks in the pharmaceutical development of bisoprolol fumarate tablets with indapamide.

The software programs “Microsoft Excel 2016” and “Statistica 10.0” (StatSoft, Inc.) were used to predict potential risks and to build a regression model of quality-related risks for bisoprolol fumarate tablets with indapamide.

A mathematical model for predicting the tablet quality risk has been developed, incorporating significant predictors: Carr's index for powder mixtures (Х1), evaluation of the pressing process (Х2), uniformity of tablet weight (Х3), tablets hardness testing (Х4), disintegration time (Х6). Four levels of quality risk are defined: low risk [0.8-1.0], moderate risk [0.6-0.8], high risk [0.4-0.6], and critical risk [0-0.4]. The calculated coefficient of determination of the forecasting model (R²=0.8168) testifies to its high quality.

The developed algorithm and mathematical model for predicting tablet quality risks are highly informative and qualitative. The proposed approach represents an innovative and promising tool for assessing and predicting risks associated with the quality of medicinal products, particularly during the early stages of pharmaceutical development.

The potency content of penicillin serves as a crucial indicator for measuring its pharmacological effects, playing a vital role in quality control and clinical applications. In recent years, with the continuous improvement of production efficiency and quality requirements in the pharmaceutical industry, the need for high-frequency monitoring of drug potency has become increasingly urgent. Infrared spectroscopy, as an emerging research tool, has demonstrated immense potential in the field of drug potency testing.

The objective of this study is to develop a real-time monitoring model for penicillin potency content utilizing near-infrared (NIR) spectroscopy data. This model aims to enable rapid and accurate detection of potency content during the penicillin production process, ultimately enhancing production efficiency and reducing costs.

During the penicillin production process, NIR spectroscopy data from penicillin samples were scanned and collected to form a comprehensive dataset. Five distinct spectral preprocessing methods were combined with three regression models to construct detection models. By comparing the performance of different combinations, the optimal model configuration was identified.

The optimal model configuration identified in this study integrates the Savitzky-Golay filtering method with ridge regression. Under this optimal model, the coefficient of determination for the test set reached 0.990669, indicating an extremely high degree of agreement between the model's predicted values and the actual measured values. This real-time monitoring model for penicillin potency content can be applied as a rapid and non-destructive monitoring method in factory settings.

This study successfully developed a real-time monitoring model for penicillin potency based on NIR spectroscopy technology. The research findings not only provide strong support for potency monitoring during the penicillin production process but also offer new insights and methodologies for non-destructive testing of other pharmaceuticals and chemicals.

Acute pharyngitis (AP) is a prevalent ailment. Gynostemma pentaphylla (GP), a traditional Chinese medicine (TCM), may treat AP due to its anti-tumor and anti-inflammatory properties, but this remains unexplored.

This study utilized the TCMSP and Swiss Target Prediction databases to analyze GP's chemical composition and target proteins. The Genecards database was used to identify targets relevant to AP. A PPI network diagram of drug-disease intersection targets was created using the STRING database, and Cytoscape was utilized to create a network visualization diagram of “GP active components-targets-AP” in order to determine key active components of GP in treating AP. Gene ontology (GO) and biological pathway (KEGG) enrichment analyses were conducted on targets in the David database. Molecular docking verification of key targets and components was performed using AutoDock Vina software. In animal experiments, a rat model of AP was induced by a 15% concentrated ammonia solution, and HE staining was conducted to observe histopathological changes in the rat pharynx after intragastric administration of Houyanqing. ELISA was used to detect expression levels of serum interleukin-1-beta (IL-1β), interleukin-6 (IL-6), and tumor necrosis factor (TNF-α).

A total of 18 active ingredients were screened from GP, among which Ruvoside _ qt, Rhamnazin, 3 ' -methyleriodictyol, and sitosterol were five key active ingredients. The key targets involved EGFR, STAT3, MAPK3, SRC, AKT1, etc. KEGG enrichment analysis showed that GP mainly acted on Pathways in cancer, P13K-AKT signaling Pathways, JAK-STAT signaling pathways, and other signaling pathways. Molecular docking results showed that four core compounds and five key targets met the energy matching. Animal experiments showed that compared with the normal group, the expression levels of IL-1β, IL-6, and TNF-α in the AP model group were significantly up-regulated (P < 0.05). In addition, compared with the model group, intragastric administration of the dexamethasone group and gypenosides group could alleviate the up-regulation of inflammatory factors in model rats, and the levels of IL-1β, IL-6, and TNF-α were decreased (P < 0.05).

This study predicted the possible targets of GP in the treatment of AP through network pharmacology. The results suggest that gypenosides may inhibit the expression of inflammatory factors by regulating Pathways in cancer, P13K-AKT, and JAK-STAT signaling pathways to treat AP.

Multidrug-resistant (MDR) E. coli presents a significant challenge in clinical settings, necessitating the exploration of novel therapeutic agents. Phytochemicals from Punica granatum (pomegranate) leaves have shown potential antibacterial properties. This study aims to identify and evaluate the efficacy of these phytochemicals against MDR E. coli

This study aims to identify and evaluate the efficacy of most potential phytochemical of Punica granatum leaf against MDR E. coli. through molecular docking, adme, toxicity, molecular dynamic simulation, MMPBSA and DFT approaches

We performed molecular docking of 11 phytochemicals from the IMPPAT database with four MDR E. coli targets: 1AJ6, 1FJ8, 4BJP, and 6BU3. Granatin B demonstrated the best binding affinity and was further analyzed. ADME (Absorption, Distribution, Metabolism, and Excretion) and toxicity analyses were conducted to assess its pharmacokinetic properties and safety profile. Molecular Dynamics (MD) simulations were performed to evaluate the stability of Granatin B with the targets. Finally, density functional theory (DFT) analysis was carried out to understand the electronic properties and reactivity of Granatin B

Granatin B exhibited the highest binding affinity among the 11 phytochemicals, indicating strong potential as an inhibitor of MDR E. coli. ADME analysis revealed favorable pharmacokinetic properties and toxicity analysis confirmed that Granatin B is non-toxic. MD simulations showed stable interactions between Granatin B and all four targets. DFT analysis provided insights into the electronic properties and reactive sites of Granatin B, supporting its potential mechanism of action

Granatin B from Punica granatum leaves is a promising candidate for treating MDR E. coli infections. The integration of molecular docking, ADME, toxicity, MD simulations, and DFT analysis underscores its therapeutic potential and paves the way for further experimental validation and development as a novel antibacterial agent

Liver fibrosis, a chronic liver disease, threatens people's health, increases the burden of healthcare, and currently lacks effective treatment measures. Bugantang (BGT) is a traditional Chinese herbal prescription from Jin Kui Yi with promising potential for treating liver fibrosis. Despite this potential, the efficacy and mechanism for treating liver fibrosis remain unclear.

To primarily prove the efficacy, predict the active components of BGT, and explore the mechanism of BGT on liver fibrosis.

The liver condition of CCL4-induced mice was examined using hematoxylin and eosin staining. The targets and active compounds of BGT were sourced from HERB and TCMSP databases, while the targets related to liver fibrosis were acquired from DisGeNET, Gene Expression Omnibus, and GeneCards databases. The core targets were identified, and the network of protein-protein interactions was established. KEGG and GO analyses were performed on DAVID. Molecular docking and molecular dynamics simulations assessed the active components’ interactions with potential targets.

A total of 215 targets and 152 active compounds were identified for BGT. The network analysis identified kaempferol, quercetin, 2-(2,4-dihydroxyphenyl)-7-hydroxy-4H-chromen-4-one, sitosterol, naringenin, adenosine, plo, and beta-sitosterol as potential key compounds, and AKT1, MMP9, SRC, TNF, ESR1, NF-κB, and PPARG as potential key targets. KEGG and GO analyses revealed that the therapeutic effect of BGT on liver fibrosis may be associated with the PI3K-AKT and MAPK signaling pathways, as well as cell apoptosis, protein phosphorylation, and inflammation. Molecular docking demonstrated high-affinity binding of the identified targets to the active compounds. Additionally, molecular dynamics simulation further confirmed that the bindings of AKT1-beta-sitosterol and MMP9-quercetin exhibited good stability.

The potential of BGT in alleviating liver fibrosis may be attributed to a combination of various active compounds, targets, and pathways. These results could support the use of BGT in treating liver fibrosis and facilitate the development of new drug candidates for this condition.

DENV NS2B-NS3 protease inhibitors were designed based upon the reference molecule, 4-(1,3-dioxoisoindolin-2-yl)-N-(4-ethylphenyl) benzenesulfonamide, reported by our team with the aim to optimize lead compound via rational approach. Top five best scoring molecules with zinc ids ZINC23504872, ZINC48412318, ZINC00413269, ZINC13998032 and ZINC75249613 bearing ‘pyrimidin-4(3H)-one’ basic scaffold have been identified as a promising candidate against DENV protease enzyme.

The shape and electrostatic complementary between identified HITs and reference molecules were found to be Tanimotoshape 0.453, 0.690, 0.680, 0.685 & 0.672 respectively and Tanimotoelectrostatic 0.211, 0.211, 0.441, 0.442, 0.442 and 0.442 respectively. The molecular docking studies suggested that the identified HITs displayed the good interactions with active site residues and lower binding energies. The stability of docked complexes was assessed by MD simulations studies. The RMSD values of protein backbone (1.6779, 3.1563, 3.3634, 3.3893 & 3.0960 Å) and protein backbone RMSF values (1.0126, 1.0834, 1.0890, 0.9974 & 1.0080 Å respectively) for all top five HITs were stable and molecules did not fluctuate from the active pocket during entire 100ns MD run.

The druggability Dscore below 1 indicate the tightly binding of ligand at the active site. Dscore for ZINC23504872 was found to be 1.084 while for the second class of compounds ZINC48412318, ZINC00413269, ZINC13998032 and ZINC75249613, 0.503, 0.484, 0.487 and 0.501 Dscores were observed. In-silico ADMET calculations suggested that all five HITs were possessed the drug likeliness properties and did not violate the Lipinski’s rule of five.

Summing up, these in-silico generated data suggested that the identified molecules bearing pyrimidin-4(3H)-one would be promising scaffold for DENV protease inhibitors. However, experimental results are needed to prove the obtained results.

NSCLC is the predominant form of lung cancer, often exhibiting resistance to chemotherapy. Thymol and citral have shown promise as anticancer agents in different cancer cell lines but have not been evaluated in combination against NSCLC. Hence, we planned to investigate the anticancer effect of thymol-citral combination and explore its mechanisms of action against A549 cells.

A549 cells were exposed to varying concentrations of thymol and citral, alone and in combination. Cell proliferation, plasma membrane integrity, apoptotic markers, reactive oxygen species (ROS) levels, cell cycle distribution, senescence induction, and migration potential were assessed. Additionally, in vitro safety was evaluated in human bronchial epithelial cells (HBECs) and human red blood cells (RBCs).

Thymol and citral showed synergistic action against A549 cells, with a CI value of 0.75. After 24 h, they induced apoptosis, caused G0/G1 phase arrest, and increased ROS levels, suggesting oxidative stress as the mechanism. This combination also induced cell senescence, significantly inhibited A549 cell migration, and was non-toxic to human RBCs and HBECs.

Overall, the thymol-citral synergistic combination was found to be a safe and effective therapy option for non-small cell lung cancer.

Centipeda minima (CM) is a traditional Chinese herbal medicine used for the treatment of sinusitis and rhinitis, and it possesses anti-cancer properties. However, the mechanism of CM in the treatment of nasopharyngeal carcinoma (NPC) remains unclear.

This study aimed to explore the mechanism of CM in the treatment of NPC using a network pharmacology approach.

The active components and targets of CM and NPC were screened using TCMSP, SwissTarget, and GeneCards database. The association between CM components and NPC targets or pathways was analyzed using String, Cytoscape 3.9.1, David 6.7, and AutoDock Vina. The Sangerbox platform was used to conduct differential expression and Kaplan-Meier survival analysis of core genes.

We identified 17 active compounds of CM and 146 corresponding targeted proteins in NPC. These targets may modulate pathways in cancer, PI3K-Akt, apoptosis, prolactin, relaxin, and TNF signaling. The top 5 core genes of the PPI network were found to be AKT1, STAT3, CASP3, EGFR, and SRC, which may be the main targets of CM in treating NPC. Molecular docking confirmed the binding energies of quercetin with CASP3, 8-Hydroxy-9,10-diisobutyryloxythymol with AKT1, and plenolin with AKT1, which were particularly low, suggesting robust and stable interactions. The expression levels of AKT1, CASP3, EGFR, SRC, MMP9, CCND1, and PTGS2 were significantly higher in head and neck squamous cell carcinoma (HNSC) samples compared to normal samples. In addition, the hub genes could predict the prognosis of HNSC as the Kaplan-Meier survival curve showed that patients with lower expressions of AKT1, STAT3, CASP3, EGFR, MMP9, ESR1, PTGS2, and PPARG had better overall survival.

By conducting a network pharmacology approach, we revealed the main ingredients, key targets, and regulatory pathways of Centipeda minima in the treatment of NPC.