The Potential of Molecular Docking for Predictive Toxicology.

Molecular modeling techniques are widely used in medicinal chemistry for the study of biological targets, the rational design of new drugs, or the investigation of their mechanism of action.They are also applied in toxicology to identify chemical potential harmful effects.Molecular docking is a computational technique to predict the ligand binding mode and evaluate the interaction energy with a biological target.This chapter describes a computational workflow to predict possible endocrine disruptors on peroxisome proliferator-activated receptor alpha (PPARα), a nuclear receptor involved in glucose and lipid metabolism. The analyzed compounds are food contact chemicals, natural or synthetic substances intentionally added to food or released from the package or during production or technological processes.

Approaching Pharmacological Space: Events and Components.

The pharmacological space comprises all the dynamic events that determine the bioactivity (and/or the metabolism and toxicity) of a given ligand. The pharmacological space accounts for the structural flexibility and property variability of the two interacting molecules as well as for the mutual adaptability characterizing their molecular recognition process. The dynamic behavior of all these events can be described by a set of possible states (e.g., conformations, binding modes, isomeric forms) that the simulated systems can assume. For each monitored state, a set of state-dependent ligand- and structure-based descriptors can be calculated. Instead of considering only the most probable state (as routinely done), the pharmacological space proposes to consider all the monitored states. For each state-dependent descriptor, the corresponding space can be evaluated by calculating various dynamic parameters such as mean and range values.The reviewed examples emphasize that the pharmacological space can find fruitful applications in structure-based virtual screening as well as in toxicity prediction. In detail, in all reported examples, the inclusion of the pharmacological space parameters enhances the resulting performances. Beneficial effects are obtained by combining both different binding modes to account for ligand mobility and different target structures to account for protein flexibility/adaptability.The proposed computational workflow that combines docking simulations and rescoring analyses to enrich the arsenal of docking-based descriptors revealed a general applicability regardless of the considered target and utilized docking engine. Finally, the EFO approach that generates consensus models by linearly combining various descriptors yielded highly performing models in all discussed virtual screening campaigns.

Exploring antithrombotic mechanisms and effective constituents of Lagopsis supina using an integrated strategy based on network pharmacology, molecular docking, metabolomics, and experimental verification in rats.

ETHNOPHARMACOLOGICAL RELEVANCE: Thrombosis is a common cause of morbidity and mortality worldwide. Lagopsis supina (Stephan ex Willd.) Ikonn.-Gal. ex Knorring is an ancient Chinese herbal medicine used for treating thrombotic diseases. Nevertheless, the antithrombotic mechanisms and effective constituents of this plant have not been clarified. AIM OF THE STUDY: This work aimed to elucidate the pharmacodynamics and mechanism of L. supina against thrombosis. MATERIALS AND METHODS: Systematic network pharmacology was used to explore candidate effective constituents and hub targets of L. supina against thrombosis. Subsequently, the binding affinities of major constituents with core targets were verified by molecular docking analysis. Afterward, the therapeutic effect and mechanism were evaluated in an arteriovenous bypass thrombosis rat model. In addition, the serum metabolomics analysis was conducted using ultra-high performance liquid chromatography coupled with Q-Exactive mass spectrometry. RESULTS: A total of 124 intersected targets of L. supina against thrombosis were predicted. Among them, 24 hub targets were obtained and their mainly associated with inflammation, angiogenesis, and thrombosis approaches. Furthermore, 9 candidate effective constituents, including (22E,24R)-5α,8α-epidioxyergosta-6,22-dien-3ß-ol, aurantiamide, (22E,24R)-5α,8α-epidioxyergosta-6,9 (11),22-trien-3ß-ol, lagopsinA, lagopsin C, 15-epi-lagopsin C, lagopsin D, 15-epi-lagopsin D, and lagopsin G in L. supina and 6 potential core targets (TLR-4, TNF-α, HIF-1α, VEGF-A, VEGFR-2, and CLEC1B) were acquired. Then, these 9 constituents demonstrated strong binding affinities with the 6 targets, with their lowest binding energies were all less than -5.0 kcal/mol. The antithrombotic effect and potential mechanisms of L. supina were verified, showing a positively associated with the inhibition of inflammation (TNF-α, IL-1ß, IL-6, IL-8, and IL-10) and coagulation cascade (TT, APTT, PT, FIB, AT-III), promotion of angiogenesis (VEGF), suppression of platelet activation (TXB2, 6-keto-PGF1α, and TXB2/6-keto-PGF1α), and prevention of fibrinolysis (t-PA, u-PA, PAI-1, PAI-1/t-PA, PAI-1/u-PA, and PLG). Finally, 14 endogenous differential metabolites from serum samples of rats were intervened by L. supina based on untargeted metabolomics analysis, which were closely related to amino acid metabolism, inflammatory and angiogenic pathways. CONCLUSION: Our integrated strategy based on network pharmacology, molecular docking, metabolomics, and in vivo experiments revealed for the first time that L. supina exerts a significant antithrombotic effect through the inhibition of inflammation and coagulation cascade, promotion of angiogenesis, and suppression of platelet activation. This paper provides novel insight into the potential of L. supina as a candidate agent to treat thrombosis.

Uncovering the pharmacological mechanisms of Patchouli essential oil for treating ulcerative colitis.

ETHNOPHARMACOLOGICAL RELEVANCE: Pogostemonis Herba has long been used in traditional Chinese medicine to treat inflammatory disorders. Patchouli essential oil (PEO) is the primary component of Pogostemonis Herba, and it has been suggested to offer curative potential when applied to treat ulcerative colitis (UC). However, the pharmacological mechanisms of PEO for treating UC remain to be clarified. AIM OF THE STUDY: To elucidate the pharmacological mechanisms of PEO for treating UC. METHODS AND RESULTS: In the present study, transcriptomic and network pharmacology approaches were combined to clarify the mechanisms of PEO for treating UC. Our results reveal that rectal PEO administration in UC model mice significantly alleviated symptoms of UC. In addition, PEO effectively suppressed colonic inflammation and oxidative stress. Mechanistically, PEO can ameliorate UC mice by modulating gut microbiota, inhibiting inflammatory targets (OPTC, PTN, IFIT3, EGFR, and TLR4), and inhibiting the PI3K-AKT pathway. Next, the 11 potential bioactive components that play a role in PEO's anti-UC mechanism were identified, and the therapeutic efficacy of the pogostone (a bioactive component) in UC mice was partially validated. CONCLUSION: This study highlights the mechanisms through which PEO can treat UC, providing a rigorous scientific foundation for future efforts to develop and apply PEO for treating UC.

PFAS-Biomolecule Interactions: Case Study Using Asclepios Nodes and Automated Workflows in KNIME for Drug Discovery and Toxicology.

The Asclepios suite of KNIME nodes represents an innovative solution for conducting cheminformatics and computational chemistry tasks, specifically tailored for applications in drug discovery and computational toxicology. This suite has been developed using open-source and publicly accessible software. In this chapter, we introduce and explore the Asclepios suite through the lens of a case study. This case study revolves around investigating the interactions between per- and polyfluorinated alkyl substances (PFAS) and biomolecules, such as nuclear receptors. The objective is to characterize the potential toxicity of PFAS and gain insights into their chemical mode of action at the molecular level. The Asclepios KNIME nodes have been designed as versatile tools capable of addressing a wide range of computational toxicology challenges. Furthermore, they can be adapted and customized to accomodate the specific needs of individual users, spanning various domains such as nanoinformatics, biomedical research, and other related applications. This chapter provides an in-depth examination of the technical underpinnings and foundations of these tools. It is accompanied by a practical case study that demonstrates the utilization of Asclepios nodes in a computational toxicology investigation. This showcases the extendable functionalities that can be applied in diverse computational chemistry contexts. By the end of this chapter, we aim for readers to have a comprehensive understanding of the effectiveness of the Asclepios node functions. These functions hold significant potential for enhancing a wide spectrum of cheminformatics applications.

Hypotensive effect of potent angiotensin-I-converting enzyme inhibitory peptides from corn gluten meal hydrolysate: Gastrointestinal digestion and transepithelial transportation modifications.

The study examined the antihypertensive effect of peptides derived from pepsin-hydrolyzed corn gluten meal, namely KQLLGY and PPYPW, and their in silico gastrointestinal tract digested fragments, KQL and PPY, respectively. KQLLGY and PPYPW showed higher angiotensin I-converting enzyme (ACE)-inhibitory activity and lower ACE inhibition constant (Ki) values when compared to KQL and PPY. Only KQL showed a mild antihypertensive effect in spontaneously hypertensive rats with -7.83 and - 5.71 mmHg systolic and diastolic blood pressure values, respectively, after 8 h oral administration. During passage through Caco-2 cells, KQL was further degraded to QL, which had reduced ACE inhibitory activity. In addition, molecular dynamics revealed that the QL-ACE complex was less stable compared to the KQL-ACE. This study reveals that structural transformation during peptide permeation plays a vital role in attenuating antihypertensive effect of the ACE inhibitor peptide.

Integrated Network Pharmacology and Molecular Docking to Explore the Mechanisms of Ningshen Wendan Decoction in the Treatment of Schizophrenia.

Objective: Schizophrenia (SCZ) is a prevalent chronic mental disorder characterized by a high recurrence rate and significant disability. Currently, no satisfactory pharmacological treatments have been identified. Although Ningshen Wendan decoction (NSWDD) has shown promising results in improving cognitive function in patients with schizophrenia, its underlying mechanism of action remains unclear. Methods: This study systematically investigated the mechanisms of NSWDD in SCZ treatment using network pharmacology and molecular docking approaches. Results: Analysis of the interaction genes revealed 307 common targets of NSWDD and SCZ. Gene Ontology and Kyoto Encyclopedia of Genes and Genomes enrichment analyses indicated the involvement of multiple signaling pathways including interleukin 17 signaling pathway, multiple virus infections, Advanced glycosylation end products (AGEs) - receptor of AGEs (AGEs-RAGE) signaling pathway, tumor necrosis factor signaling pathway, and Hypoxia-inducible factor-1 (HIF-1) signaling pathway as key pathways influenced by NSWDD in treating SCZ. These pathways are associated with various biological processes such as transcriptional regulation, apoptosis regulation, gene expression regulation, and external stimulus-response. Molecular docking simulations indicated favorable binding interactions between components of NSWDD and target proteins via intermolecular forces. Conclusion: The study provided initial insights into the internal molecular mechanisms underlying the beneficial effect of NSWDD on SCZ through multi-target modulation across multiple pathways.

DrugReAlign: a multisource prompt framework for drug repurposing based on large language models.

Drug repurposing is a promising approach in the field of drug discovery owing to its efficiency and cost-effectiveness. Most current drug repurposing models rely on specific datasets for training, which limits their predictive accuracy and scope. The number of both market-approved and experimental drugs is vast, forming an extensive molecular space. Due to limitations in parameter size and data volume, traditional drug-target interaction (DTI) prediction models struggle to generalize well within such a broad space. In contrast, large language models (LLMs), with their vast parameter sizes and extensive training data, demonstrate certain advantages in drug repurposing tasks. In our research, we introduce a novel drug repurposing framework, DrugReAlign, based on LLMs and multi-source prompt techniques, designed to fully exploit the potential of existing drugs efficiently. Leveraging LLMs, the DrugReAlign framework acquires general knowledge about targets and drugs from extensive human knowledge bases, overcoming the data availability limitations of traditional approaches. Furthermore, we collected target summaries and target-drug space interaction data from databases as multi-source prompts, substantially improving LLM performance in drug repurposing. We validated the efficiency and reliability of the proposed framework through molecular docking and DTI datasets. Significantly, our findings suggest a direct correlation between the accuracy of LLMs' target analysis and the quality of prediction outcomes. These findings signify that the proposed framework holds the promise of inaugurating a new paradigm in drug repurposing.

Fritillaria steroidal alkaloids and their multi-target therapeutic mechanisms: insights from network pharmacology.

Medicinal Fritillaria herbs, known for their rich content of steroidal alkaloids, have emerged as promising candidates in the treatment of chronic diseases due to their diverse pharmacological properties. Leveraging advancements in network pharmacology and molecular docking, this study explores the multi-target mechanisms through which these alkaloids exert therapeutic effects. The integration of bioinformatics, systems biology, and pharmacology in drug discovery has provided insights into the molecular interactions and pathways influenced by Fritillaria steroidal alkaloids. This review synthesizes comprehensive literature from 1985 to 2024, revealing the potential of these compounds in addressing respiratory diseases, inflammation, and cancer. The integration of traditional Chinese medicine (TCM) with modern pharmacological techniques underscores the relevance of these compounds in next-generation drug discovery. While initial findings are promising, further empirical validation is necessary to fully harness the therapeutic potential of Fritillaria steroidal alkaloids.

In silico DFT and molecular modeling of novel pyrazine-bearing thiazolidinone hybrids derivatives: elucidating in vitro anti-cancer and urease inhibitors.

In the present work, one of the leading health issues i.e. cancer was targeted by synthesizing and biologically investigating the potential of pyrazine-based thiazolidinone derivatives (1-13). The basic structure of the synthesized compounds was determined using a variety of spectroscopic techniques, including 1H NMR, 13C NMR, and HREI-MS. These scaffolds were studied for their biological profiles as anti-cancer as well as anti-urease agents. The biological effectiveness of these compounds was compared using the reference tetrandrine (IC50 = 4.50 ± 0.20 µM) and thiourea (IC50 = 5.10 ± 0.10 µM), respectively. Among novel compounds, scaffold 3, 6, 7 and 10 demonstrated an excellent potency with highest inhibitory potential (IC50 = 1.70 ± 0.10 and 1.30 ± 0.20 µM), (IC50 = 4.20 ± 0.10 and 5.10 ± 0.30 µM), (IC50 = 2.10 ± 0.10 and 3.20 ± 0.20 µM) and (IC50 = 2.70 ± 0.20 and 4.20 ± 0.20 µM), respectively, out of which scaffold 3 emerged as the leading compound due to the presence of highly reactive -CF3 moiety which interacts via hydrogen bonding. Molecular docking investigations of the potent compounds was also carried out which revealed the binding interactions of ligands with the active sites of enzyme. Moreover, the electronic properties, nucleophilic and electrophilic sited of the lead compounds were also studied under density functional theory (DFT).

Bioassay Guided Isolation and α-Glucosidase Inhibition Studies of a New Sesquiterpene from Ochradenus aucheri.

AIMS: The aim of the current study was to explore the anti-diabetic potential of Ochradenus aucheri Boiss (O. aucheri). METHOD: All the fractions of O. aucheri were evaluated for α-glucosidase inhibition, followed by bioassay-guided isolation which resulted in a new sesquiterpenoid, as a potential α-glucosidase inhibitor. RESULTS: The preliminary screening showed that all the fractions including n-hexane (38.0 ± 1.38 µg/mL), dichloromethane (92.6 ± 6.18 µg/mL), ethyl acetate (29.2 ± 0.51 µg/mL) and n-butanol (361.8 ± 5.80 µg/mL) displayed significant α-glucosidase inhibitory activity. The activity-directed fractionation and purification of ethyl acetate fraction led to the isolation of one new sesquiterpenoid, Jardenol (1), and two known metabolites: ß-stitosterol-3-O-ß-D-glucopyranoside (2) and ß-Sitosterol (3). To the best of our knowledge, these metabolites have not been isolated from this plant previously. The structure of the new metabolite 1 was confirmed through 1D and 2D NMR spectroscopy, and MS analysis. Compound 1 showed significant α-glucosidase inhibition with an IC50 value of 138.2 ± 2.43 µg/mL as compared to positive control acarbose (IC50 = 942.0 ± 0.60 µg/mL). Additionally, in-silico docking was employed to predict the binding mechanism of compound 1 in the active site of the target enzyme, α-glucosidase. The docking results suggested that the compound forms strong interactions at the catalytic site of α-glucosidase. CONCLUSION: The results of the present study indicated that the newly purified secondary metabolite, Jardenol, can be a promising anti-diabetic compound.

In silico Profiling and Pharmacokinetic Modelling of Olivetol: Evaluating its Potential as a Therapeutic Agent for Diabetic Wound Healing.

BACKGROUND: Diabetic wound healing poses a significant challenge due to the intricate disruptions in cellular and molecular processes induced by hyperglycaemia, leading to delayed or impaired tissue repair. Computational techniques offer a promising avenue for unravelling the complexities of diabetic wound healing by elucidating the molecular mechanisms involved. METHODOLOGY: This study utilized in silico molecular docking and dynamics simulations to explore the potential therapeutic effectiveness of olivetol, a phenolic compound, in the context of diabetic wound healing. Furthermore, computational methodologies, encompassing pkCSM, Swiss ADME, OSIRIS® property explorer, PASS online web resource, and MOLINSPIRATION® software, were employed to forecast the pharmacokinetic properties, biological actions, and in vitro analyses, such as MTT and scratch assays, to evaluate the therapeutic effectiveness of olivetol in wound healing. RESULTS AND DISCUSSION: Our findings have revealed olivetol to be a promising candidate for targeting multiple pathways implicated in diabetic wound healing. Its ability to modulate inflammation, oxidative stress, extracellular matrix remodeling, angiogenesis, and cell signaling suggests a multifaceted approach to promoting effective wound repair. Moreover, olivetol has been found to demonstrate strong binding affinity with key MRSA target proteins, indicating its potential as an antimicrobial agent against MRSA infections in diabetic wounds. The in vitro MTT assay demonstrated cell viability with an IC50 value of 40.80 µM, highlighting its cytotoxicity potential. Additionally, the scratch assay confirmed promising wound healing activity, showcasing its effectiveness in promoting cell migration and closure. CONCLUSION: Olivetol emerges as a promising candidate for targeted interventions in non-healing diabetic wounds, particularly due to its ability to address prolonged inflammation, a common obstacle in diabetic wound healing.

Novel Quinoline Nitrate Derivatives: Synthesis, Characterization, and Evaluation of their Anticancer Activity with a Focus on Molecular Docking and NO Release.

BACKGROUND: Nitric Oxide (NO) has recently gained recognition as a promising approach in the field of cancer therapy. The quinoline scaffold is pivotal in cancer drug research and is known for its versatility and diverse mechanisms of action. OBJECTIVE: This study presents the synthesis, characterization, and evaluation of novel quinoline nitrate derivatives as potential anticancer agents. METHODS: The compounds were synthesized through a multi-step process involving the preparation of substituted 1-(2-aminophenyl) ethan-1-one, followed by the synthesis of substituted 2- (chloromethyl)-3,4-dimethylquinolines, and finally, the formation of substituted (3,4- dimethylquinolin-2-yl) methyl nitrate derivatives. The synthesized compounds were characterized using various spectroscopic techniques. Molecular docking studies were conducted to assess the binding affinity of the compounds to the EGFR tyrosine kinase domain. RESULTS: The docking scores revealed varying degrees of binding affinity, with compound 6k exhibiting the highest score. The results suggested a correlation between molecular docking scores and anticancer activity. Further evaluations included MTT assays to determine the cytotoxicity of the compounds against Non-Small Cell Lung Cancer (A-549) and pancreatic cancer (PANC-1) cell lines. Compounds with electron-donating groups displayed notable anticancer potential, and there was a correlation between NO release and anticancer activity. The study also investigated nitric oxide release from the compounds, revealing compound 6g as the highest NO releaser. CONCLUSION: The synthesized quinoline nitrate derivatives showed promising anticancer activity, with compound 6g standing out as a potential lead compound. The correlation between molecular docking, NO release, and anticancer activity suggests the importance of specific structural features in the design of effective anticancer agents.

Design of Novel Imidazole Derivatives as Potential Non-nucleoside Reverse Transcriptase Inhibitors Using Molecular Docking and Dynamics Strategies.

Human Immunodeficiency Virus (HIV) has become an epidemic causing Acquired Immunodeficiency Syndrome (AIDS). Highly active antiretroviral therapy (HAART) consists of Nucleoside Reverse Transcriptase Inhibitors (NRTIS), Nucleotide Reverse Transcriptase Inhibitors (NtRTIS), and Non- Nucleoside Reverse Transcriptase Inhibitors (NNRTIS) with HIV Protease Inhibitors (HIV PIs). However, the emergence of resistant strains of NNRTIS necessitates the search for better HIV-1-RT inhibitors. METHODS: In this study, a series of novel imidazoles (SP01-SP30) was designed using molecular docking inside the non-nucleoside inhibitory binding pocket (NNIBP) of the HIV-1-RT (PDB ID-1RT2) using Glide v13.0.137, Autodock Vina, and FlexX v2.1.3. Prime MMGBSA was used to study the free energy of binding of the inhibitors with the target enzyme. Molecular dynamics simulation studies were carried out to discover the dynamic behavior of the protein as well as to unveil the role of the essential amino acids required for the better binding affinity of the inhibitor within the NNIBP of the enzyme. The QikProp software module of Schrodinger and online SwissADME were also used to evaluate the drug-likeliness of these compounds. RESULTS: The imidazole derivative SP08 is predicted to be the most promising design compound that can be considered for further synthetic exploitations to obtain a molecule with the highest therapeutic index against HIV-1-RT. CONCLUSION: The results of the current study demonstrate the robustness of our in-silico drug design strategy that can be used for the discovery of novel HIV-1-RT inhibitors.

Mechanism of Polygala-Acorus in Treating Autism Spectrum Disorder Based on Network Pharmacology and Molecular Docking.

BACKGROUND: Recent epidemic survey data have revealed a globally increasing prevalence of autism spectrum disorders (ASDs). Currently, while Western medicine mostly uses a combination of comprehensive intervention and rehabilitative treatment, patient outcomes remain unsatisfactory. Polygala-Acorus, used as a pair drug, positively affects the brain and kidneys, and can improve intelligence, wisdom, and awareness; however, the underlying mechanism of action is unclear. OBJECTIVES: We performed network pharmacology analysis of the mechanism of Polygala-Acorus in treating ASD and its potential therapeutic effects to provide a scientific basis for the pharmaceutical's clinical application. METHODS: The chemical compositions and targets corresponding to Polygala-Acorus were obtained using the Traditional Chinese Medicine Systematic Pharmacology Database and Analysis Platform, Chemical Source Website, and PharmMapper database. Disease targets in ASD were screened using the DisGeNET, DrugBank, and GeneCards databases. Gene Ontology functional analysis and metabolic pathway analysis (Kyoto Encyclopedia of Genes and Genomes) were performed using the Metascape database and validated via molecular docking using AutoDock Vina and PyMOL software. RESULTS: Molecular docking analysis showed that the key active components of Polygala- Acorus interacted with the following key targets: EGFR, SRC, MAPK1, and ALB. Thus, the key active components of Polygala-Acorus (sibiricaxanthone A, sibiricaxanthone B tenuifolin, polygalic acid, cycloartenol, and 8-isopentenyl-kaempferol) have been found to bind to EGFR, SRC, MAPK1, and ALB. CONCLUSION: This study has preliminarily revealed the active ingredients and underlying mechanism of Polygala-Acorus in the treatment of ASD, and our predictions need to be proven by further experimentation.

Design, In silico Screening, Synthesis, Characterisation and DFT-based Electronic Properties of Dihydropyridine-based Molecule as L-type Calcium Channel Blocker.

BACKGROUND: People of all nationalities and social classes are now affected by the growing issue of hypertension. Over time, there has been a consistent rise in the fatality rate. A range of therapeutic compounds, on the other hand, are often used to handle hypertension. OBJECTIVES: The objectives of this study are first to design potential antihypertensive drugs based on the DHP scaffold, secondly, to analyse drug-likeness properties of the ligands and investigate their molecular mechanisms of binding to the model protein Cav1.2 and finally to synthesise the best ligand. MATERIALS AND METHODS: Due to the lack of 3D structures for human Cav1.2, the protein structure was modelled using a homology modelling approach. A protein-ligand complex's strength and binding interaction were investigated using molecular docking and molecular dynamics techniques. DFT-based electronic properties of the ligand were calculated using the M06-2X/ def2- TZVP level of theory. The SwissADME website was used to study the ADMET properties. RESULTS: In this study, a series of DHP compounds (19 compounds) were properly designed to act as calcium channel blockers. Among these compounds, compound 16 showed excellent binding scores (-11.6 kcal/mol). This compound was synthesised with good yield and characterised. To assess the structural features of the synthesised molecule quantum chemical calculations were performed. CONCLUSION: Based on molecular docking, molecular dynamics simulations, and drug-likeness properties of compound 16 can be used as a potential calcium channel blocker.

Exploring the bioactive ingredients of three traditional Chinese medicine formulas against age-related hearing loss through network pharmacology and experimental validation.

Traditional Chinese medicine (TCM) formulas, including the Er-Long-Zuo-Ci pill, Tong-Qiao-Er-Long pill, and Er-Long pill, have long been utilized in China for managing age-related hearing loss (ARHL). However, the specific bioactive compounds, pharmacological targets, and underlying mechanisms remain elusive. This study aims to find the shared bioactive ingredients among these three formulas, uncover the molecular pathways they regulate, and identify potential therapeutic targets for ARHL. Furthermore, it seeks to validate the efficacy of these major components through both in vivo and in vitro experiments. Common bioactive ingredients were extracted from the TCMSP database, and their putative target proteins were predicted using the Swiss Target Prediction database. ARHL-related target proteins were collected from GeneCards and OMIM databases. Our approach involved constructing drug-target networks and drug-disease-specific protein-protein interaction networks and conducting clustering, topological property analyses, and functional annotation through GO and KEGG enrichment analysis. Molecular docking analysis was utilized to delineate interaction mechanisms between major bioactive ingredients and key target proteins. Finally, in vivo and in vitro experiments involving ABR recording, immunofluorescent staining, HE staining, and quantitative PCR were conducted to validate the treatment effects of flavonoids on the declining auditory function in DBA/2 J mice. We identified 11 common chemical compounds across the three formulas and their associated 276 putative targets. Additionally, 3350 ARHL-related targets were compiled. As an intersection of the putative targets of the common compounds and ARHL-related proteins, 145 shared targets were determined. Functional enrichment analysis indicated that these compounds may modulate various biological processes, including cell proliferation, apoptosis, inflammatory response, and synaptic connections. Notably, potential targets such as TNFα, MAPK1, SRC, AKT, EGFR, ESR1, and AR were implicated. Flavonoids emerged as major bioactive components against ARHL based on target numbers, with molecular docking demonstrating diverse interaction models between these flavonoids and protein targets. Furthermore, baicalin could mitigate the age-related cochlear damage and hearing loss of DBA/2 J mice through its multi-target and multi-pathway mechanism, involving anti-inflammation, modulation of sex hormone-related pathways, and activation of potassium channels. This study offers an integrated network pharmacology approach, validated by in vivo and in vitro experiments, shedding light on the potential mechanisms, major active components, and therapeutic targets of TCM formulas for treating ARHL.

Design, synthesis, and computational analysis (molecular docking, DFT, MEP, RDG, ELF) of diazepine and oxazepine sulfonamides: biological evaluation for in vitro and in vivo anti-inflammatory, antimicrobial, and cytotoxicity predictions.

We report the synthesis and extensive characterization of Diazepane and Oxazepane derivatives, followed by their biological evaluation. These compounds were assessed for in vitro and in vivo antimicrobial, anti-inflammatory, and anticancer activities. Among the synthesized molecules, compound 5b demonstrated remarkable antibacterial activity against Staphylococcus aureus and Staphylococcus epidermidis with MIC values of 20 and 40 µg/mL, respectively. Additionally, 5b exhibited potent anti-inflammatory effects both in vitro and in vivo. Advanced computational studies, including DFT, MEP, RDG, and ELF analyses, were performed to understand the electronic distribution and molecular interactions. The bioactivity and physicochemical properties of these derivatives were further predicted using PASS and pkCSM platforms, emphasizing their potential as promising lead molecules in drug development.

Identification of senescence-related genes for potential therapeutic biomarkers of atrial fibrillation by bioinformatics, human histological validation, and molecular docking.

Background: Cellular senescence is pivotal in the occurrence and progression of atrial fibrillation (AF). This study aimed to identify senescence-related genes that could be potential therapeutic biomarkers for AF. Methods: AF-related differentially expressed genes (DEGs) were identified using the Gene Expression Omnibus dataset. Weighted gene co-expression network analysis (WGCNA) was used to analyze important modules and potential hub genes. Integrating senescence-related genes, potential biomarkers were identified. Their differential expression levels were then validated in human atrial tissue, HL-1 cells, and Angiotensin II-infused mice. Finally, molecular docking analysis was conducted to predict potential interactions between potential biomarkers and the senolytic drug Navitoclax. Results: We identified seven genes common to AF-related DEGs and senescence-related genes. Three significant modules were selected from WGCNA analysis. Taken together, three senescence-related genes (ETS1, SP1, and WT1) were found to be significantly associated with AF. Protein-protein interaction network analysis revealed biological connections among the predicted target genes of ETS1, SP1, and WT1. Notably, ETS1, SP1, and WT1 exhibited significant differential expression in clinical samples as well as in vitro and in vivo models. Molecular docking revealed favorable binding affinity between senolytic Navitoclax and these potential biomarkers. Conclusions: This study highlights ETS1, SP1, and WT1 as crucial senescence-related genes associated with AF, offering potential therapeutic targets, with supportive evidence of binding affinity with senolytic Navitoclax. These findings provide novel insights into AF pathogenesis from a senescence perspective.