Current Computer - Aided Drug Design - Online First

There has been increasing interest in neuroimaging studies in recent years, and computer-aided approaches have gained prominence in improving diagnostic accuracy. Attention Deficit Hyperactivity Disorder (ADHD) is a prevalent neurodevelopmental disorder characterized by inattention, impulsivity, and hyperactivity. Traditional diagnostic approaches often rely on subjective assessments, highlighting the need for more objective, data-driven methods. This study aims to classify ADHD subtypes and assess medication effects by converting resting-state fMRI images into one-dimensional (1D) signals and extracting statistical features using Variational Mode Decomposition (VMD).

Resting-state fMRI data from the ADHD-200 dataset, including 41 healthy controls (HC), 41 medicated ADHD-Combined (ADHD-C) individuals, and 41 non-medicated ADHD-C individuals, were analyzed. The 1D fMRI signals were decomposed into nine sub-bands using VMD. Statistical features were extracted from each sub-band and classified using Support Vector Machines (SVM), Linear Discriminant Analysis (LDA), and Artificial Neural Networks (ANN).

VMD-derived features substantially improved classification performance. The highest binary classification accuracy was achieved by LDA: 96.34% distinguishing non-medicated ADHD from controls and 88.41% for medicated ADHD versus controls. The classification between medicated and non-medicated ADHD yielded 79.63% accuracy. Ternary classification across all groups reached 69.51% accuracy.

These findings show that the VMD-based approach improves the classification of ADHD subtypes and helps evaluate medication effects. However, the lower performance in multi-class classification reflects the complexity of ADHD neuroimaging data.

The VMD-based approach improves classification accuracy, especially in distinguishing ADHD subtypes and medication effects, supporting its potential as an objective tool for diagnosis and treatment planning.

Hyperlipidemia is linked to multiple cardiovascular and cerebrovascular diseases. Traditional Chinese Medicine formulations show potential for managing this condition, but the underlying mechanisms remain unclear. This study investigates the therapeutic effects of the Fangji-Astragalus (FJ-HQ) on hyperlipidemia and explores its key components and molecular pathways.

Network pharmacology was applied to identify active ingredients in FJ-HQ and drug-disease co-targets. Transcriptomic analysis and HPLC-MS/MS were integrated to screen core components and associated targets. In vivo and in vitro experiments evaluated the effects of FJ-HQ in hyperlipidemic rat models and cell models.

A total of 23 active ingredients and 109 drug–disease co-targets were identified, with enrichment in inflammatory and signaling pathways, notably the PI3K/AKT/mTOR and p53 pathways. Transcriptomic profiling revealed seven differentially expressed targets. Integrated chemical and serum analysis identified calycosin as the core component and highlighted CAMTA2 and RXRA as downstream targets. In hyperlipidemic rats, FJ-HQ lowered total cholesterol, triglycerides, and low-density lipoprotein cholesterol, and increased high-density lipoprotein cholesterol and apolipoprotein A1. FJ-HQ also modulated the expression of P53, AKT1, and IL6, as well as mRNA levels within the PI3K/AKT/mTOR pathway. In cell models, serum containing FJ-HQ inhibited lipid droplet formation.

These findings demonstrate that FJ-HQ alleviates hyperlipidemia by modulating the PI3K/AKT/mTOR and p53 pathways, reducing lipid levels, and suppressing lipid droplet formation, with calycosin as a pivotal active component.

In summary, our study confirms the therapeutic effects of FJ-HQ on hyperlipidemia and identifies calycosin as a crucial component. Furthermore, we have experimentally validated the influence of FJ-HQ on the PI3K/AKT/mTOR signaling pathway. These findings highlight the potential of FJ-HQ as an effective lipid-lowering agent and provide preclinical evidence for future treatments of hyperlipidemia.

Inflammatory bowel disease (IBD) poses a major threat to human health. Current pharmacological therapies primarily manage symptoms and are often associated with adverse effects.

To develop targeted natural drugs with fewer side effects for IBD therapy by identifying potential agents from medicinal and edible Chinese herbs (MECHs) and clarifying their underlying molecular mechanisms.

An integrated approach was employed, combining single-cell analysis, transcriptomics, reverse network pharmacology, immunological infiltration assessment, molecular docking, ADMET evaluation, and molecular dynamics (MD) simulations.

Multi-omic integration identified nine differentially infiltrating immune cell types and a CXCL8-CXCR2-driven neutrophil communication axis. Frequent intercellular communication was observed among neutrophils, epithelial cells, monocytes, B cells, and T cells. Topological screening yielded 15 hub targets and identified MMP2 and PTGS2 as key targets. Molecular docking, ADMET analyses, and 100-ns MD simulations converged on the natural product (NP) MOL009551 (isoprincepin) as a high-affinity, stable MMP2 binder (ΔG = -11.0 kcal/mol), supporting MMP2-directed isoprincepin as a novel therapeutic candidate for IBD.

Bioinformatic analyses suggest that MMP2 may play an important role in IBD, and isoprincepin, identified from MECHs, may serve as a potential therapeutic agent by modulating MMP2 activity. However, experimental validation of their direct interaction and therapeutic efficacy remains necessary, along with further mechanistic and preclinical studies to clarify their potential for IBD treatment.

This study provides a comprehensive understanding of the molecular mechanisms underlying IBD, identifies MMP2 as a key target, and highlights isoprincepin as a promising natural product for IBD therapy.

This study aimed to investigate the therapeutic mechanism of coptisine in rotator cuff injury (RCI) through network pharmacology and experimental validation. This is the first study to examine the role of coptisine in rotator cuff injury (RCI), revealing a novel mechanism by which coptisine inhibits the PI3K/Akt/mTOR pathway, thereby coordinating inflammation resolution and tendon repair.

Network pharmacology was used to identify potential coptisine and RCI targets, which were then analyzed functionally to indicate critical pathways. A rat RCI model (right supraspinatus tendon transection) was used to validate the mechanism by detecting pathological changes, inflammatory factors, and mRNA expression related to the PI3K/Akt/mTOR pathway.

Network pharmacology identified 29 overlapping coptisine and RCI targets, with an emphasis on the PI3K/Akt/mTOR pathway. Coptisine reduced tendon atrophy and inflammation in RCI rats, lowered blood TNF-α and IL-6 levels, elevated IL-10, and decreased PI3K, Akt, and mTOR mRNA expression in tendon tissues. These findings align with the pathway-target connection predicted by network pharmacology-specifically, core targets like PIK3CA and PIK3CB (key components of the PI3K/Akt/mTOR pathway) were confirmed to be regulated by coptisine, suggesting the alkaloid exerts anti-inflammatory and tendon-protective effects by suppressing this pathway, which is known to mediate inflammation and protein metabolism in injured tendons.

Coptisine improved RCI in rats by decreasing inflammation and the PI3K/Akt/mTOR pathway, suggesting a possible therapeutic target for RCI.

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.

Radiation Dermatitis (RD) is a common complication of radiation therapy, with approximately 90% of patients experiencing moderate to severe radiation dermatitis injury after radiotherapy. Jiedu Shengji oil (JDSJY) is a commonly used herbal topical preparation in our hospital, with remarkable clinical efficacy in treating radiation dermatitis. However, the mechanism of JDSJY in treating RD is unclear.

The aim of the study is to explore JDSJY's mechanism of action in treating RD through methods, such as network pharmacology and in vivo experiments.

The active components and disease targets of JDSJY were screened and intersected via network pharmacology for Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis. The pharmacodynamics of JDSJY was evaluated by establishing a rat model of RD.

Network pharmacology showed that the pathway network of JDSJY action involved 64 targets and 6 pathways and might act by targeting key targets, such as C-reactive protein (CRP) and regulating the MAPK signalling pathway. In addition, in vivo experiments showed that JDSJY reduced skin inflammation and inhibited apoptosis, significantly ameliorated mitochondrial damage in keratinocytes, and reduced the levels of antioxidant-related indicators.

Comprehensive network pharmacology and in vivo experiments revealed that JDSJY's therapeutic efficacy in RD is mediated by ameliorating oxidative stress and maintaining mitochondrial homeostasis in keratinocytes.

Epidermal growth factor receptor tyrosine kinase (EGFR TK) is a primary target for inhibiting cellular signal transduction in several types of cancer. Numerous EGFR TK inhibitors have been developed and approved as standard therapy for cancer management. However, the development of drug resistance and significant adverse effects have encouraged the search for alternative EGFR TK inhibitors.

This study attempted to identify 2,4-diaryl-6-styrylpyridine derivatives as alternative orthosteric-allosteric EGFR TK inhibitors through molecular docking, molecular dynamic simulation, binding free energy calculation, and pharmacokinetic properties analysis.

Two series of 2,4-diaryl-6-styrylpyridine derivatives were docked in orthosteric and allosteric sites of EGFR TK. Docking results were validated through molecular dynamic simulation and binding free energy calculation using YASARA Structure. Pharmacokinetic properties were analyzed using web-based free servers SwissADME and ADMETLab 3.0.

The molecular docking studies revealed relatively strong affinity, with binding energy ranging from -10.2 to -12.2 kcal/mol in the orthosteric site and from -7.7 to -10.9 kcal/mol in the allosteric site of EGFR TK. The proposed ligand complexes with the highest binding energy and proper hydrogen bonds showed comparable stability and binding free energy than native ligand complexes. The pharmacokinetic properties of the proposed ligands indicated relatively poor characteristics due to relatively high lipophilicity and certain toxicophores.

This study identified NASP06 and NASP01 as the most stable orthosteric and allosteric inhibitors of EGFR TK, respectively. These findings revealed a novel class of EGFR TK inhibitors capable of interacting with both orthosteric and allosteric sites.

Oral Squamous Cell Carcinoma (OSCC) is a multiple-phase carcinogenic disease that concurrently involves malignant lesions, invasion, and metastasis. It has been reported that Ubiquitin-conjugating enzymes play a significant role in the progression of OSCC and other fatal cancers through the process of ubiquitination. Among them, UBE2D1 represents a promising target for therapeutic intervention. Strategies aimed at inhibiting UBE2D1 could restore the function of tumor suppressors, such as p53, and potentially enhance the effectiveness of existing cancer therapies.

This study aims to discover the potential natural inhibitors of UBE2D1 from an extensive chemical library through computational techniques.

This study utilized in silico methods, such as virtual screening, molecular docking, analysis of pharmacokinetic parameters, and molecular dynamics simulation, to discover the most effective inhibitors for the ubiquitin-conjugating enzyme.

Based on binding affinity, the top six compounds, ZINC15113777, ZINC225461658, ZINC107430641, ZINC259440, ZINC4025306, and ZINC107283931, were found to be the best for the selected target. Also, molecular dynamic simulation results showed that all these compounds form stable complexes with UBE2D1.

Based on our analysis of the results, we have determined that natural products, specifically ZINC15113777, ZINC4025306, and ZINC107283931, have the ability to inhibit UBE2D1 efficiently and could be utilized as potential drugs for the treatment of OSCC and other cancers. Such approaches may help to reinstate normal apoptotic pathways and improve overall treatment outcomes in patients with cancers characterized by UBE2D1 dysregulation. Additionally, conducting in-vitro/vivo studies on these molecules could be a prospective avenue in the realm of pharmaceutical research.

The global spread of Strongyloides stercoralis has escalated public health concerns, affecting over 600 million people worldwide. The rise in global migration has heightened the risk of transmission, underscoring the urgent need for effective treatment options.

This study aimed to investigate ten polyphenolic phytochemicals derived from Mangifera indica as potential alternatives to combat S. stercoralis.

The efficacy of these compounds was evaluated using computational techniques, including density functional theory (DFT) analysis, molecular docking, adsorption, distribution, metabolism, excretion, and toxicity (ADMET) assessment, and molecular dynamics (MD) simulations.

DFT calculations revealed significant chemical reactivity in compounds such as kaempferol, ellagic acid, quercetin, norathyriol, mangiferin, and ferulic acid. Molecular docking identified mangiferin, quercetin, kaempferol, and norathyriol as top candidates for targeting key proteins (DAF-12) linked to S. stercoralis infection. A 200-ns MD simulation of the protein-ligand complex demonstrated the stability and binding behavior of these compounds compared to the reference drug, thiabendazole. ADMET screening confirmed their drug-likeness. Notably, quercetin and mangiferin exhibited strong binding affinities (∆Gbind = -42.35 and -54.57 kcal/mol, respectively), outperforming thiabendazole (∆Gbind = -28.94 kcal/mol).

Quercetin and mangiferin emerge as promising alternatives to thiabendazole, offering favorable chemical reactivity, potent inhibition constants, and strong biological activity for the treatment of S. stercoralis.

The function of HOXC antisense RNA 1 (HOXC-AS1) in lung adenocarcinoma (LUAD) remains largely unexplored.

The objective of this research was to examine the relationship between HOXC-AS1 levels and LUAD through both bioinformatics analysis and experimental validation.

We employed statistical methods and bioinformatics to evaluate the correlation between HOXC-AS1 expression and various clinical features, survival predictors, regulatory mechanisms, and immune cell infiltration in LUAD. The levels of HOXC-AS1 in LUAD cell lines were ascertained through quantitative reverse transcription PCR.

HOXC-AS1 displayed significantly increased expression in individuals with LUAD. There was a significant correlation between high HOXC-AS1 levels and diminished overall survival in LUAD patients, characterized by a hazard ratio of 0.66, a 95% confidence interval of 0.49 to 0.88, and a statistically significant P-value (0.005). An elevated expression of HOXC-AS1 was found to be a standalone predictor of poor overall survival in LUAD patients, with a P-value of 0.002. HOXC-AS1 was found to be implicated in various pathways, such as neuroactive ligand-receptor interaction and asthma, among others. The study revealed a substantial link between high HOXC-AS1 expression and unfavorable outcomes in LUAD, including poor survival and altered immune cell infiltration. LUAD cell lines exhibited a marked increase in HOXC-AS1 expression compared to the Beas-2B normal lung cell line.

The research indicated a strong association between higher levels of HOXC-AS1 and negative outcomes in LUAD, such as reduced survival rates and the presence of immune cell infiltration. HOXC-AS1 could potentially be utilized as a biomarker to anticipate patient prognosis and their likelihood of responding to immunotherapies in LUAD.

The extended IL-1 activity is implicated in autoimmune disorders, such as rheumatoid arthritis, diabetes mellitus, and Parkinson's disease, as well as delayed wound healing. Additionally, it can result in cytokine storms during pathogenic infections.

The regulation was carried out by Interleukin-1 receptor antagonist (IL-1RA), a key anti-inflammatory molecule. IL-1RA serves as a decoy protein that competes with Interleukin-1 receptors (IL-1RI and IL-1RII) for binding, effectively counteracting the activity of Interleukin-1 (IL-1). The deficiency was substantiated by commercially available recombinant IL-1RA called Anakinra. The main problem with the existing drug is that it has less pharmacokinetics and reduced binding affinity to its receptor, which requires frequent administration of the drug. To overcome these drawbacks, we have designed a new fusion protein by adding an Fc fragment of Human IgGI fused with IL-1RA using a linker in between, and the design aimed to transport the protein into the N-glycosylation pathway. These characteristic features increase the pharmacokinetics, solubility, and binding efficiency of the protein. As the protein was designed to be expressed in a eukaryotic system, to understand the possibility of the proposed hypothesis, we used machine learning-based AlphaFold2 to model the protein structure and molecular simulation studies to understand the functional integrity of the designed protein.

The in silico results showed that the modeled fusion protein structure has very good binding to its receptor with the support of 21 H bonds and 7 salt bridges and maintained the binding stability over the MD simulations.

These findings support fusion protein’s potential as a promising and stable therapeutic candidate.

Qi-Gui-Jian-Gu decoction (QGJG), as a clinical empirical formula, has clinical benefits in promoting bone formation, but the underlying mechanism for its application in treating fractures has not been investigated.

The potential therapeutic target and signaling pathway of QGJG for treating fractures were analyzed by network pharmacology. In vitro, we used bone marrow mesenchymal stem cells (MSCs) to evaluate osteogenic differentiation and mineralization by alizarin red staining, quantitative real-time polymerase chain reaction (qRT-PCR), western blot (WB), and immunofluorescence staining. In vivo, the 8w male SPF C57BL/6J mouse femoral fracture model was constructed, and the therapeutic effects of QGJG were evaluated.

By network pharmacology analysis, we found that glycogen synthase kinase 3 beta (GSK3β) was a potential therapeutic target of QGJG for treating fractures. The canonical Wnt signaling pathway was selected as the potential molecular mechanism. QGJG was confirmed to upregulate the mRNA levels of alkaline phosphatase (ALP) and bone morphogenetic protein 2 (BMP2), thereby promoting osteogenic differentiation and mineralization. Mechanistically, QGJG inhibited GSK3β while increasing p-Ser9-GSK3β to increase β-catenin protein expression and its nuclear translocation, implying the activation of the canonical Wnt signaling pathway. In vivo, QGJG administration promoted fracture healing, as demonstrated by the up-regulation of OPN and Osx, and accelerated the progression of ossification at 2 and 3 weeks after surgery.

QGJG promotes osteogenic differentiation and fracture healing by activating the canonical Wnt pathway.

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.

To Discover novel PTP1B inhibitors by high-throughput virtual screening

Type 2 Diabetes is a significant global health concern. According to projections, the estimated number of individuals affected by the condition will reach 578 million by the year 2030 and is expected to further increase to 700 million deaths by 2045. Protein Tyrosine Phosphatase 1B is an enzymatic protein that has a negative regulatory effect on the pathways involved in insulin signaling. This regulatory action ultimately results in the development of insulin resistance and the subsequent elevation of glucose levels in the bloodstream. The proper functioning of insulin signaling is essential for maintaining glucose homeostasis, whereas the disruption of insulin signaling can result in the development of type 2 diabetes. Consequently, we sought to utilize PTP1B as a drug target in this investigation.

The purpose of our study was to identify novel PTP1B inhibitors as a potential treatment for managing type 2 diabetes.

To discover potent PTP1B inhibitors, we have screened the Maybridge HitDiscover database by SBVS. Top hits have been passed based on various drug-likeness rules, toxicity predictions, ADME assessment, Consensus Molecular docking, DFT, and 300 ns MD Simulations.

Two compounds have been identified with strong binding affinity at the active site of PTP1B along with drug-like properties, efficient ADME, low toxicity, and high stability.

The identified molecules could potentially manage T2DM effectively by inhibiting PTP1B, providing a promising avenue for therapeutic strategies.

As a traditional Chinese medicine, Danshen shows potential efficacy for treating ulcerative colitis (UC). However, the bioactive components and mode of action were unclear.

This paper uses a combination of network pharmacology, serum medicinal chemistry, and gene expression profiling to clarify its possible molecular mechanism of action and material basis.

Ultra-high performance liquid chromatography-mass spectrometry (UPLC-MS) was utilized to analyze the herbal components and metabolites from the serum of Danshen-treated mice. Gene expression profiles were applied to construct a database of Danshen action targets. Then, active ingredient-target-biological functional module networks were constructed to analyze the mechanism of action. Molecular docking has further confirmed the possibility of its components to the targets.

As a result, 193 common targets between 1684 Danshen-related DEGs and 1492 UC targets were determined as the potential targets for Danshen in treatment with UC. Serum pharmacochemistry and target prediction showed that 22 components in serum acted on 777 targets. Intersection with common targets yielded 46 core targets, and an active ingredient-target-biological functional module network was constructed for analysis. Network prediction and molecular docking results showed that the main action modules were inflammatory response and cell apoptosis, which mainly acted on targets SRC, RELA, HSP90AA1, CTNNB1, STAT3, and CASP3. The main components of Danshen intervention in UC were predicted to include Catechol, 3,9-Dimethoxypterocarpan, 8-Prenylnaringenin, Isoferulic acid, Salvianolic acid C, and Danshensu.

The present study provides a scientific foundation for further explicating the mechanisms of Danshen against UC.