In silico pharmacology最新文献

Cutavirus (CuV) is a newly discovered human parvovirus, which gained tremendous interest due to its association with cutaneous lymphoma T cells. CuV transmission primarily occur via fecal-oral route and identified as a causal agent of diarrhea. The current study based on prediction of novel multi-epitopic potential vaccine models against CuV by predicted by selecting highly antigenic proteins using reverse vaccinology approaches. A top-ranked T and B cell epitopes from lead vaccine candidate proteins were selected and linked via immunogenic adjuvant peptides and linker sequences to design model vaccine. The models were assessed in terms of physicochemical properties including antigenicity, non-allergenicity, and their binding affinities to TLR4 immune receptors. The in-silico restriction and cloning analysis were pursued to check the expression capacity of model vaccine. Several vaccine models were designed from lead epitopes of CuV vaccine candidates' proteins along with combination of immune-enhancer adjuvants and linkers. Physicochemical and immunoinformatics analyses prioritized a V2 model construct as top-ranked. The molecular docking and molecular dynamic simulation analyses ensured the V2 construct molecular stability and strong interaction with TLR4 immune receptor with binding affinity of - 41.27 kcal/mol. The normal mode analysis (NMA) predicted improved flexibility, proper molecular mobility, and decreased protein deformability of immune complex for the generation of powerful immune response. Molecular dynamics simulation confirmed the structural stability of the V2-TLR4 complex with minimal RMSD fluctuations and sustained hydrogen bonding. Principal component analysis (PCA) revealed limited conformational shifts, indicating a stable dynamic behavior of the vaccine-receptor complex. These results support the robust interaction and stability of the designed vaccine, reinforcing its potential for effective immune activation. Immune simulation predicted a strong primary and memory immune response with elevated levels of IgG, IFN-γ, and T-cell activity. Codon optimization yielded a CAI score of 0.98 and GC content of 53.1%, indicating efficient expression in E. coli. The multi-epitope vaccine construct prioritized in the current study is effectively bind with immune receptors and elicit potent immune response against CuV.

Supplementary information: The online version contains supplementary material available at 10.1007/s40203-025-00467-6.

IFI16, a tumor suppressor gene, negatively regulates AIM2, a protein implicated in various cancers and kidney diseases. Disrupting the IFI16-AIM2 interaction could present a novel therapeutic strategy for enhancing immune responses. This study aims to identify terpenoids capable of disrupting the IFI16-AIM2 interaction, potentially activating AIM2 and boosting immune responses against cancers, particularly lung squamous cell carcinoma (LUSC), and other AIM2-dysregulated diseases. KEGG pathway analysis and protein-protein interaction (PPI) analysis with STRING were employed to understand the interaction network between IFI16 and AIM2. Transcription levels of the IFI16-AIM2 have been identified across various cancers. Furthermore, we evaluated the potential of terpenoids, known for their anti-inflammatory and anticancer properties, to modulate IFI16-AIM2 interaction using in silico docking computation. We performed docking studies of various terpenoids with the binding pocket of IFI16 to identify potential lead compounds with favorable binding affinities and postures. Subsequent analyses were conducted to evaluate the docked complexes' stability and intermolecular interactions. Molecular dynamics simulation was performed to evaluate the stability of the protein-ligand complex under physiological conditions. PPI analysis showed a strong co-expression score for IFI16 and AIM2 (0.929), highlighting a close functional link. Transcriptomic data revealed upregulation of both genes in bladder, renal, breast, testis, and lung cancers. Survival analysis indicated that high IFI16 expression was associated with significantly poorer overall survival (HR = 1.6, p < 0.001), while elevated AIM2 modestly increased mortality risk (HR = 1.1, p = 0.0034). Immune correlation analysis in LUSC showed IFI16 negatively associated with immune infiltration, whereas AIM2 positively correlated with CD8 + T cells, neutrophils, and dendritic cells. Docking identified terpenoid compound C10 as the top hit, with strong binding energies to IFI16 (- 9.2 kcal/mol) and AIM2 (- 9.5 kcal/mol), outperforming the standard drug (- 8.89 kcal/mol). Molecular dynamics simulations confirmed complex stability, with protein RMSD stabilizing within 1-2 Å, ligand RMSD remaining < 2 Å, and RMSF indicating limited flexibility outside terminal regions. Persistent hydrogen bonds with key residues (Arg-55, Arg-63 for C2_6MB2; Arg-55, Gln-60 for C3_6MB2) further supported stable binding. These findings provide a promising starting point for the development of terpenoids-based therapies targeting the IFI16-AIM2 interaction for the treatment of cancers and other AIM2-dysregulated diseases. Further in vitro and in vivo studies will be necessary to validate the identified terpenoids' effectiveness and safety for therapeutic applications.

Supplementary information: The online version contains supplementary material available at 10.1007/s40203-025-00453-y.

Paraquat (PQ) is a highly toxic herbicide that is lethal and causes fatal multi-organ toxicity in humans, as there are no effective treatments available. Despite extensive studies on new therapeutic targets and lead compounds, the existing approaches for treating PQ-induced toxicity remain inadequate and challenging, highlighting the urgent need for curative therapeutic approaches of great significance. This study uses the computational approach to identify the potential phytoconstituent-based antioxidant exhibiting the potential binding affinity with the Toll-interacting protein (TOLLIP). Initially, using molecular docking, mechanics-generalized born surface area (MM/GBSA) binding energy calculation, and ADME-Tox (Absorption, Distribution, Metabolism, Excretion, and Toxicity), a total of 89 phytoconstituents were evaluated for binding affinity to the TOLLIP. The five compounds Arbutin, Coumaric acid, Ethyl gallate, Ferulic acid, and Vanillic acid with significant binding affinity and pharmacokinetic properties, were further subjected to molecular dynamic simulation, trajectory analysis (RMSD, RMSF, Radius of gyration), binding free energy, PCA, DCCM. Our extensive computational analysis identified the Ethyl gallate-TOLLIP complex as a promising candidate, characterized by exceptional structural stability, minimal fluctuation, and the highest negative binding free energy. Therefore, Ethyl gallate may act as a potent therapeutic agent for mitigating paraquat-induced toxicity by targeting TOLLIP.

Supplementary information: The online version contains supplementary material available at 10.1007/s40203-025-00455-w.

Since the detection of the Shamonda virus (SHAV), it has posed a significant threat to the health of female ruminant animals due to its detrimental effects on these livestock, such as abortion, stillbirth, premature delivery, and congenital anomalies in the offspring. Hence, there is a need for the development of an effective vaccine to prevent future outbreaks of this virus. This study, using an in-silico approach, retrieved the available polyprotein sequences of SHAV from the NCBI database. Various bioinformatics tools were used to predict B-cell, CTL, and HTL epitopes, which were then subjected to antigenicity, allergenicity, toxicity, interleukin-4, interleukin-6, and interferon-gamma prediction. The final B-cell, CTL, and HTL epitopes with appropriate linkers were used to design six distinct primary subunit vaccine candidates, with different adjuvants including HMGB1, beta-defensin (Bos taurus), and beta-synuclein protein. The physicochemical properties were predicted using the ExPASyProtparam server. The molecular weight of the six constructs ranges from 31.19 kDa to 52.26 kDa, with lengths between 296 and 472 amino acids, and aliphatic index from 50.17 to 78.38. The instability index (25.47 to 37.83), GRAVY score (between - 1.088 and - 0.280), and solubility scores between 0.583 and 0.678 were also observed. The secondary construct, 3-D modelling, refinement, and validation of the six constructs, were analyzed. Based on their exceptional qualities, constructs 1, 3, and 5 were further docked with Toll-Like Receptor-3. The complex of construct 5 shows the highest binding affinity, with a docking score of -310.72. The molecular dynamic simulation was analysed, and the immune simulation highlights the vaccine construct's ability to elicit innate and adaptive immune responses, indicating an effective vaccine candidate in the fight against the potential zoonotic illness, providing immediate targeted protection for animals and hopefully humans.

Farnesoid X receptor (FXR) is a multifunctional nuclear receptor that plays an essential role in liver regeneration, maintaining liver homeostasis, counterregulation of hepatic inflammation, and regulation of immune response. As the expression of FXR is downregulated during the development of liver cancer, there may be a loss of function, and hence, designing a novel therapeutic can help overcome this issue. Curcumin, a polyphenol extracted from the rhizome of Curcuma longa L., has multiple, molecular targets which make it a suitable ligand molecule as it acts as an anti-cancer, anti-inflammatory, and antioxidant. Despite its efficacy, it hinders applicability due to its low bioavailability, short half-life, rapid metabolism, and elimination. Curcumin analogs can be designed by incorporating fluoro atoms containing groups as they can improve metabolic stability, better physicochemical properties, and increased binding affinity. The study includes molecular docking of designed curcumin analogs with the FXR receptor (6HL1) and understanding their docking energy, interactions, molecular dynamic simulations, and ADMET properties. From 18 designed analogs, the best docking score was found in the 13d analog, which is - 10.228 kcal/mol. Further molecular dynamic simulation of the 6HL1-13d complex was performed to check its structural stability, and interactions, identifying some common amino acids such as TYR361 and MET265, which are present during both molecular docking and simulations.

Supplementary information: The online version contains supplementary material available at 10.1007/s40203-025-00456-9.

Annually, Hepatocellular Carcinoma promotes 905,677 fresh occurrences and causes about 830,180 mortalities globally. The fatal predominant neoplasia is one of the most aggressive and multi-factorial form of primary liver cancer. The yearly escalated sum of occurrences and fatalities are reported due to poor diagnostic system leading to late-stage diagnosis of tumors and inept treatment consequences. Henceforth, the present analysis aims to identify nascent HCC-associated biomarkers and their respective plant-derived small molecule inhibitors. In this place, meta-analysis of seven (GSE101685, GSE112790, GSE84402, GSE62232, GSE45436, GSE33006 and GSE6222) micro-array profiles including an aggregate of 443 HCC-tumor and normal liver samples has been implemented through GeneSpring software. The resultant 433 DEGs including 117 up-regulated genes and 316 down-regulated genes were subjected to functional annotation, pathway enrichment and gene-disease association analysis through Enrichr webserver. Sequentially, the top 10 hub nodes were recognized by employing Cytoscape software and MELK being the most frequently interacting node was reflected as the anti-HCC target. Eventually, the Molecular docking, Molecular dynamic simulations and MMGBSA analysis were accomplished by Schrödinger software for the plausible anti-HCC MELK target against plant-derived small molecules retrieved from NPASS database. The outcomes indicated potential phytocompounds Malabaricone C and Quercetagetin with steady interactions and enhanced binding affinities for MELK target. Thus, the study conclusively postulates plant-derived small molecules Malabaricone C and Quercetagetin as promising MELK inhibitors for targeting HCC patients with elated MELK expression levels. Conversely, the study fabricates a computational groundwork for MELK-associated targeted HCC therapeutics and simultaneously also sustains the obligatory molecular validations of the phytochemicals for clinical drug-development applications.

Supplementary information: The online version contains supplementary material available at 10.1007/s40203-025-00463-w.

Alpha-synuclein (α-syn) is a 140 amino acid neuronal protein linked to different neurodegenerative disorders. A point mutation in its gene has been related to a rare family type of Parkinson's disease (PD), and more alterations have been discovered in familial PD cases. Abnormal processing of α-syn can cause pathological alterations, altering its binding characteristics and functionality. Clinical trials aimed at reducing α-syn aggregation have faced obstacles due to challenges in identifying effective drugs during preclinical studies. Method To address this issue, we present computational methods that combines pharmacophore modeling, molecular docking, molecular dynamics, free energy calculations, and similarity index investigations to find possible hit compounds for preventing α-syn aggregation. Results A validated pharmacophore model was used to screen the ZINC natural product library, followed by established computational pipeline, yielding four novel inhibitors (ZINC000150351590, ZINC000299817386, ZINC000085509805, ZINC000095911811) with strong binding affinities (- 9.43 to - 9.06 kcal/mol). Molecular dynamics simulations confirmed stable protein-ligand complexes (average RMSD < 2.5 Å), while MM/PBSA analysis showed favorable binding free energies (- 56.7 to - 49.2 kcal/mol). Conclusion Evaluation of docking performance, stability, and binding energetics using MM/PBSA enabled the identification of four natural inhibitors of α-syn aggregation. These compounds represent promising leads for further investigation in Parkinson's disease drug discovery.

This study investigates the therapeutic potential of bioactive compounds from Lepidium sativum in the treatment of prostate cancer. Through a series of in silico analyses, three key compounds were identified and evaluated for their drug-likeness, pharmacokinetic properties, and safety profiles. These compounds demonstrated favorable drug-likeness according to Lipinski's rule and other drug-likeness criteria, high gastrointestinal tract absorption, and non-inhibition of major cytochrome P450 enzymes. Protein-protein interaction network analysis identified ten hub genes, with AKT1 and PIK3CA emerging as prime targets for therapeutic intervention. Functional annotation and pathway analysis highlighted key biological processes and pathways associated with prostate cancer, emphasizing the significance of these targets. Molecular docking and dynamic simulation studies further confirmed the binding affinities and stability of the identified compounds with both mutated and non-mutated forms of the target genes. These findings suggest that compounds from Lepidium sativum hold promise as potential therapeutics for prostate cancer, warranting further investigation and development.

Supplementary information: The online version contains supplementary material available at 10.1007/s40203-025-00482-7.

Traditional Chinese Medicine (TCM) offers multi-component therapies that modulate diverse molecular pathways in Non-Insulin Dependent Diabetes Mellitus (NIDDM). In this study, network pharmacology was applied to five TCM formulations containing HuaJiao to elucidate compound-gene interactions relevant to non-insulin dependent diabetes. Bioactive compounds and their predicted targets were retrieved from ETCM 2.0 and TCMSP, then cross-referenced with NIDDM-associated genes from CTD, TTD, and ETCM. A total of 133 common gene targets were identified across formulations, and a compound-target network was constructed and visualized in Cytoscape v3.10.1. Hub genes implicated in insulin signaling, glucose homeostasis, and inflammation were highlighted. Additionally, two HuaJiao compounds, spathulenol and haplopine, demonstrated multi-target interactionsTo further validate therapeutic relevance, molecular docking and 200-ns molecular dynamics simulations confirmed stable binding of haplopine within the COX-2 active site, stabilized primarily by Ser516, Tyr371, Trp373, and Phe504 through persistent hydrogen bonding, π-π interactions, and van der Waals forces. A 200-ns molecular dynamics simulation of spathulenol with muscarinic receptors showed moderate binding. These results highlight the polypharmacological potential of HuaJiao, underscore the novelty of integrating network pharmacology with docking and dynamics, and provide mechanistic insights that may guide rational design of TCM-based interventions for NIDDM. Keywords.

Supplementary information: The online version contains supplementary material available at 10.1007/s40203-025-00451-0.

The gut-brain axis (GBA) plays a pivotal role in maintaining neuroimmune and gastrointestinal homeostasis. Disruption of this bidirectional communication is implicated in disorders such as inflammatory bowel disease (IBD), autism spectrum disorders, and neuroinflammation. This study explores the therapeutic potential of phytocompounds derived from the lignocellulose extracted from the pods of Prosopis juliflora for modulating the GBA through an integrated in-silico approach. Gas Chromatography-Mass Spectrometry (GC-MS) analysis was used to identify 22 bioactive compounds from nanocellulose extract. Network pharmacology and protein-protein interaction (PPI) analysis was employed to identify key targets, followed by pathway enrichment to evaluate biological relevance. Molecular docking studies were conducted against EGFR (PDB ID: 4WKQ), and ADMET profiling was performed using SwissADME to assess pharmacokinetic fitness. EGFR emerged as a central hub gene bridging neurotrophic signalling and gut epithelial repair. Among the screened compounds, C13 (2 H-Pyran-2-one, 5,6-dihydro-6-pentyl-) and C16 (2(3 H)-Furanone, dihydro-3-(phenylmethyl)-) demonstrated strong binding affinity with key EGFR residues (THR854 and ASP855), suggesting a modulatory role. ADMET analysis confirmed high gastrointestinal absorption, blood-brain barrier permeability, and favourable drug-likeness without cytochrome P450 inhibition. The findings suggest that P. juliflora-derived compounds, particularly C13 and C16, hold promise for dual-targeted GBA modulation. These results warrant further in vitro and in vivo validation and support the development of lignocellulose-based nanocarriers for targeted delivery in gut-neurotherapeutics.