Current Computer - Aided Drug Design - Volume 21, Issue 3, 2025

Histone deacetylase 9 (HDAC9) is an important member of the class IIa family of histone deacetylases. It is well established that over-expression of HDAC9 causes various types of cancers including gastric cancer, breast cancer, ovarian cancer, liver cancer, lung cancer, lymphoblastic leukaemia, etc. The important role of HDAC9 is also recognized in the development of bone, cardiac muscles, and innate immunity. Thus, it will be beneficial to find out the important structural attributes of HDAC9 inhibitors for developing selective HDAC9 inhibitors with higher potency.

The classification QSAR-based methods namely Bayesian classification and recursive partitioning method were applied to a dataset consisting of HADC9 inhibitors. The structural features strongly suggested that sulphur-containing compounds can be a good choice for HDAC9 inhibition. For this reason, these models were applied further to screen some natural compounds from Allium sativum. The screened compounds were further accessed for the ADME properties and docked in the homology-modelled structure of HDAC9 in order to find important amino acids for the interaction. The best-docked compound was considered for molecular dynamics (MD) simulation study.

The classification models have identified good and bad fingerprints for HDAC9 inhibition. The screened compounds like ajoene, 1,2 vinyl dithiine, diallyl disulphide and diallyl trisulphide had been identified as compounds having potent HDAC9 inhibitory activity. The results from ADME and molecular docking study of these compounds show the binding interaction inside the active site of the HDAC9. The best-docked compound ajoene shows satisfactory results in terms of different validation parameters of MD simulation study.

This in-silico modelling study has identified the natural potential lead (s) from Allium sativum. Specifically, the ajoene with the best in-silico features can be considered for further in-vitro and in-vivo investigation to establish as potential HDAC9 inhibitors.

Plants represent a rich reservoir of bioactive compounds with established therapeutic value in diverse diseases. Notably, the Toll-like receptor-4 (TLR-4) signaling pathway plays a pivotal role in inflammation. Upon engagement with pro-inflammatory ligands like lipopolysaccharide, TLR-4 triggers downstream cascades involving nuclear factor ĸappa B and mitogen-activated protein kinases. This signaling cascade ultimately dictates the onset and progression of inflammatory diseases. Therefore, targeting TLR-4 signaling offers a promising therapeutic approach for managing inflammatory disorders.

This study investigated the potential of Costus speciosus rhizome phytocompounds, a traditional medicinal plant, as novel as modulators of TLR-4 signaling, highlighting their mechanisms of action and potential clinical applications. In the present study, 18 phytocompounds isolated from the rhizome of Costus speciosus, were studied against TLR-4/AP-1 signaling, which is implicated in the inflammatory process using a computational approach.

The compounds exhibited binding affinities ranging from -4.087 to -8.93 kcal/mol with the TLR-4 protein due to the formation of multiple intermolecular interactions. Benzenepropanoic acid, 3,5-bis(1,1-dimethylethyl)-4-hydroxy-, methyl ester (compound 7) exhibited exceptional binding energy (-8.93 kcal/mol), indicating strong affinity for the TLR-4 protein. Additionally, compound 7 displayed favorable ADMET properties, suggesting promising drug development potential. Molecular dynamics simulations confirmed the stability of the compound 7-TLR4 complex, further supporting its ability to modulate TLR-4 signaling.

These findings highlight the therapeutic potential of Costus speciosus phytocompounds, particularly compound 7, as potent anti-inflammatory modulators. Further research is warranted to validate their anti-inflammatory and neuroprotective effects in pre-clinical models, paving the way for their development as novel therapeutic agents for inflammatory diseases.

The development of polymeric-based drug delivery has seen faster growth in the past two decades. In polymers, copolymers are utilized as drug carriers to decrease the side effects and dosage-related toxicity.

The primary objective of the study is to utilize computational resources to design drug molecules and perform in silico physicochemical property analysis. In our study, we designed new copolymers based on N-(2-Hydroxypropyl) methacrylamide as backbone along with polyethylene glycol and lauryl methacrylate.

Different functional groups were selected for attaching to the side chain of the copolymers through a random trial and error approach. In order to predict the pharmacokinetic properties (absorption, distribution, metabolism, excretion, and toxicity), the designed copolymer molecules were evaluated utilizing Swiss ADME and pkCSM pharmacokinetics servers. Molecular interaction between the designed copolymer molecules and human serum albumin was performed using AutoDock Vina and PatchDock server.

The designed molecules are shown to be soluble in water and have high gastrointestinal absorption. Only one molecule is predicted to pass through the blood-brain barrier. Two designed molecules have been shown to have carcinogenic properties. Lethal dose 50, cytochrome P450, and permeability glycoprotein substrate formation were also analyzed for toxicity and metabolism.

Our study will provide insight for designing new drug compounds or carriers

and analyzing their physicochemical properties to further optimize compounds for clinical studies.

The clinical use of doxorubicin (DOX), an anthracycline antibiotic with broad-spectrum applications against various malignant tumors, is limited by doxorubicin-induced cardiotoxicity (DIC). Eriodictyol (ERD) has shown cardioprotective effects, but the mechanism of its protective effect on DIC remains unknown.

This study aimed to explore the potential mechanisms by which ERD confers protection against DIC.

ERD and DIC targets were identified from the TCMSP, PharmMaper, SwissTargetPrediction, TargetNet, BATMAN, GeneCards, and PharmGKB databases. Differential gene expression data between DIC and normal tissues were extracted from the GEO database. A protein‒protein interaction (PPI) network of the intersecting ERD-DIC targets was constructed using the STRING platform and visualized with Cytoscape 3.10.0 software. Gene Ontology (GO) functional enrichment analysis and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis for ERD-DIC cross-targets were conducted. Validation included molecular docking with AutoDock Tools software and molecular dynamics simulations with Gromacs 2019.6 software.

Network pharmacology analysis revealed 43 intersecting ERD-DIC targets, including 6 key targets. GO functional enrichment analysis indicated that the intersecting targets were enriched in 550 biological processes, 45 cell components, and 41 molecular functions. KEGG pathway enrichment analysis identified 114 enriched signaling pathways. Molecular docking revealed a strong binding affinity between ERD and 6 key targets, as well as multiple targets within the ROS pathway. Molecular dynamics simulations indicated that ERD has favorable binding with 3 crucial targets.

The systematic network pharmacology analysis suggests that ERD may mitigate DIC through multiple targets and pathways, with the ROS pathway potentially playing a crucial role. These findings provide a reference for foundational research and clinical applications of ERD in treating DIC.

Diabetic Retinopathy (DR) is one of the common chronic complications of diabetes mellitus, which has developed into the leading cause of irreversible visual impairment in adults worldwide. The Compound Qilian Tablets (CQLT) were developed in China for the treatment and prevention of DR, but their mechanism of action still needs to be clarified.

In the present study, network pharmacology, molecular docking, and in vivo validation experiments were used to investigate the active components and molecular mechanisms of CQLT against DR.

The active components and targets of CQLT were collected through the TCSMP database, and the targets of DR were obtained from GeneCards, OMIM, and Drugbank databases. We established a protein-protein interaction network using the STRING database. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses were conducted using the Metascape database. Molecular docking using AutoDock Vina was performed to investigate the interactions between components of CQLT and core targets. Moreover, we selected ZDF rats to establish a DR model for the experimental studies.

39 active components and 448 targets in CQLT were screened, among which 90 targets were shared with DR. KEGG pathway enrichment analysis identified 181 pathways. The molecular docking results demonstrated that the main active components had strong binding ability to the core targets. The results from animal experiments indicate that the mechanism of CQLT against DR is associated with inhibiting the retinal mTOR/HIF-1α/VEGF signaling pathway, alleviating the inflammatory response, suppressing retinal neovascularization, and protecting the function and morphology of the retina.

The present study preliminarily explored the mechanism of CQLT in treating DR and demonstrated that CQLT exerts anti-DR effects through multiple components, multiple targets, and multiple pathways. These findings suggest that CQLT shows promise as a potential therapeutic agent for DR and could contribute to developing novel treatments.

One of the most important targets in cancer immunotherapy is programmed cell death ligand 1 (PD-L1). Monoclonal antibodies developed for this target have disadvantages due to their low bioavailability and some immune-related adverse effects. Additionally, small molecules targeting PD-L1 are still in the experimental stage. At this point, discovering non-toxic natural compounds that directly or indirectly target PD-L1 is essential. In this in silico study, a comprehensive literature search was conducted to identify publications reporting the master regulator of PD-L1, which was suggested as a Signal Transducer and Activator of Transcription 3 (STAT3). The relationship between STAT3 and PD-L1 was further investigated through bioinformatic analysis.

Subsequently, natural compounds targeting PD-L1 and STAT3 were screened, and compounds with suitable toxicity profiles were docked against both PD-L1 and STAT3. Following molecular docking, the selected molecules underwent DNA docking, ADMET profile analysis, and in silico assessment of biological activities. The relationship between PD-L1 and STAT3 was determined in 52 out of the 453 articles, and it was further demonstrated in gene-gene interactions. Following the virtual screening, 76 natural compounds were identified, and after pre-filtering based on physicochemical properties, drug-likeness, and ADMET profiles, 29 compounds remained.

Subsequent docking revealed that two compounds, 6-Prenylapigenin, and Gelomulide J, persisted. ADMET and biological activity prediction results suggested that 6-Prenylapigenin is non-toxic and has the potential to inhibit PD-L1 and STAT3 in silico. The present study highlights that STAT3 serves as the master regulator of PD-L1, and it further suggests that 6-Prenylapigenin exhibits the potential to modulate PD-L1 and/or STAT3.

This finding could pave the way for the development of small molecules designed to block the PD-1/PD-L1 interaction by silencing the PD-L1 and/or STAT3 genes or reducing protein levels.

Translationally controlled tumour protein (TCTP) is associated with tumor diseases, such as breast cancer, and its inhibitor can reduce the growth of tumor cells. Unfortunately, there is currently no effective medication available for treating TCTP-related breast cancer.

The objective of this study was to explore the inhibitor candidates among natural compounds for the treatment of breast cancer related to TCTP protein.

To explore the potential inhibitors of TCTP, we first screened out four potential inhibitors in the Traditional Chinese Medicine (TCM) for cancer based on AI virtual screening using the docking method, and then revealed the interaction mechanism of TCTP and four candidate inhibitors from TCM with molecular docking and molecular dynamics (MD) methods.

Based on the conformational characteristics and the MD properties of the four leading compounds, we designed the new skeleton molecules with the AI method using MolAICal software. Our MD simulations have revealed that different small molecules bind to different sites of TCTP, but the flexible regions and the signaling pathways are almost the same, and the VDW and hydrophobic interactions are crucial in the interactions between TCTP and ligands.

We have proposed the candidate inhibitor of TCTP. Our study has provided a potential new method for exploring inhibitors from Traditional Chinese Medicine (TCM).

Triple-negative breast cancer (TNBC) is a highly aggressive form of breast cancer lacking specific receptors, with dysregulated and overactivated Hedgehog (Hh) and mTOR/PI3K/AKT signaling pathways as potential therapeutic targets.

This study aimed to identify potential inhibitors among 53 alkaloids derived from 9 marine bryozoans using in silico approaches. It sought to analyze their impact on key signaling targets and their potential for future experimental validation.

In this research, selected targets were evaluated for protein-protein interactions, co-expression survival, and expression profiles. The protein expression was validated through the Human Protein Atlas (HPA) database and druggability through DGIdb. Online web servers were employed to assess drug-likeness, physiochemical properties, pharmacokinetics, and toxicological characteristics of the compounds. Molecular docking and dynamic simulations were carried out for ligand-protein interactions. Common Pharmacophore features, bioavailability, bioactivity, and biological activity spectrum (BAS) were also analyzed.

Out of the 13 compounds studied, 10 displayed strong binding affinity with binding energies ranging from >-6.5 to <-8 Kcal/mol across all targets. Molecular dynamics simulations provided insights into Amathamide E's stability and conformational changes. Pharmacophore modeling revealed common features in 14 compounds potentially responsible for their biological activity.

Our findings indicate the potential of marine-derived compounds as TNBC inhibitors. Further in vitro and in vivo validation is necessary to establish their effectiveness and explore their role as novel anti-TNBC agents.

Non-small cell lung cancer (NSCLC) is the most common type of lung cancer. Traditional Chinese medicine, known for its multi-target and multi-pathway characteristics, offers a potential treatment approach for NSCLC.

This study aimed to explore the mechanism of the competitive endogenous network of 'Scutellaria barbata D.Don-Houttuynia cordata-Radix Scutellariae' in treating NSCLC through bioinformatics analysis and in vitro experiments.

Various databases and ceRNA networks were utilized to collect and screen components and target genes, molecular docking and molecular dynamics simulations to determine the binding ability of ligand-receptor complexes. In vitro experiments were conducted to validate the effects of active ingredients of 'Scutellaria barbata D.Don-Houttuynia cordata-Radix Scutellariae' on non-small cell lung cancer cell line A549.

The key target proteins CCL2, EDN1, MMP9, PPARG, and SPP1 were docked well with their corresponding TCM ligands. Among the ligand-receptor complexes, MMP9-Luteolin and MMP9-Quercetin demonstrated the weaking binding force, while the SPP1-Quercetin complex, associated with NSCLC prognosis, exhibited stable structure formation through hydrogen bond interaction during MD simulation. In vitro experiments confirmed the inhibitory effect of Quercetin on SPP1 expression, as well as the proliferation and migration of A549 cells.

The findings suggest that 'Scutellaria barbata D.Don-Houttuynia cordata-Radix Scutellariae' may potentially treat lung cancer by suppressing the expression of SPP1. This study provides valuable insights and novel research directions for understanding the mechanism of traditional Chinese medicine in combating lung cancer.