In silico pharmacology最新文献

Sulfanilamide (SN), a synthetic broad-spectrum antimicrobial that inhibits folic acid synthesis and suppresses bacterial growth. However, long-term use has caused allergic reactions, skin problems, crystalluria, nephrotoxicity, and other side effects. SN has developed resistance, and its associated side effects underscore the urgent need to discover safer alternatives with greater efficacy and reduced toxicity. In this study, we attempted to design new SN derivatives by incorporating various functional groups into their basic structure. Derivative structures were geometrically optimized utilizing density functional theory (DFT) and B3/LYP 6-31G+(d, p) basis set to calculate their physicochemical and spectrochemical properties. Molecular docking and molecular dynamics (MD) simulations were conducted against the dihydropteroate synthase (DHPS) protein (PDB ID: 1AJ2) to predict the binding affinities of analogs and stability at the active site. ADMET and PASS analyses evaluated toxicological and pharmacological profiles. Most of the derivatives showed lower energy gaps (5.14 eV to 5.30 eV) than SN (5.34 eV). All derivatives showed stronger binding affinities (-5.5 to -6.7 kcal mol^-1) compared to SN (-5.4 kcal mol^-1). ADMET results showed good pharmacokinetics, with some derivatives exhibiting higher GI absorption and most falling under toxicity class III. Overall, SN7 (-6.5 kcal/mol), SN17 (-6.6 kcal/mol), and SN18 (-6.7 kcal/mol) have exhibited better performance. Thus, our research reveals that the studied analogs can serve as novel alternatives to SN with superior quality. However, further experimental and biological studies are necessary to validate these theoretical findings and confirm their potential antibacterial efficacy.

Supplementary information: The online version contains supplementary material available at 10.1007/s40203-025-00526-y.

The severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) outbreak has infected millions worldwide, exacerbating global health concerns. However, a dire need for alternative therapies like active ingredients from natural sources. Therefore, QKC, which are active compounds, are being investigated from Maxing Shigan Decoction (MXSGD), a traditional Chinese medicine (TCM) formula widely used for respiratory illnesses and have shown therapeutic potential in treating SARS-CoV-2. This study investigates MXSGD's active compounds, therapeutic proteins, and pharmacological mechanisms. Integrated multiple networking and GO/KEGG pathway enrichment analysis approaches were employed. While individual ingredient effects were studied, the combined efficacy and molecular mechanisms require further exploration. By combination, quercetin-kaempferol (QKC) is hypothesized to be more effective. A systematic pharmacological approach was used to identify compound targets, predict potential targets, and conduct networking analyses. Five networks were constructed and analyzed: (a) compound-known targets, (b) compound-potential targets, (c) QKC-HP PPI, (d) QKC-MH PPI, and (e) QKC-SARS-CoV-2-PPI networks. GO and pathway enrichment analyses revealed that the ingredients target various biological processes and pathways, with QKC combining the properties of quercetin and kaempferol. This study provides valuable insights in comparing quercetin, kaempferol, and QKC and those exploring QKC's synergies and molecular mechanisms for treating SARS-CoV-2.

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Supplementary information: The online version contains supplementary material available at 10.1007/s40203-025-00515-1.

Dengue fever, transmitted through mosquito vectors, has emerged as a significant health challenge in India over the past twenty years. This infectious epidemic has demonstrated concerning fatality rates and mortality statistics. The primary objective of this investigation was to conduct molecular simulation studies and evaluate the drug-like properties of marine seaweed fucoidan and five synthetic derivatives against dengue virus (DENV) non-structural proteins. The parent fucoidan compound, along with its acetyl, amino, sulfonyl, phosphate, and benzoyl derivatives, underwent molecular docking analysis against DENV4 NS3 Protease-Helicase (2VBC), DENV2 NS2B/NS3 Protease (2FOM), DENV2 Methyltransferase (1L9K), DENV2 Non-Structural protein NS5 (5ZQK), and DENV2 RNA-dependent RNA polymerase (6IZY). The selected non-structural proteins were analyzed through CDOCKER docking methodology, concentrating on binding sites, with binding energies calculated to assess fucoidan derivative effectiveness. The parent fucoidan, acetylated fucoidan, phosphated fucoidan, and benzoylated fucoidan demonstrated the strongest inhibitory potential against all DENV viral proteins, exhibiting binding affinities of - 13 kcal.mol^-1, - 48 kcal.mol^-1, and 43 kcal.mol^-1, respectively. Pharmacokinetic properties and toxicological profiles were evaluated for all fucoidan compounds using the PreADMET web server simulation software. The comprehensive ligand-binding affinity range for fucoidan and its derivatives spanned from - 146 to - 13 kcal.mol^-1. ADMET analysis confirmed that the parent fucoidan and its acetylated, phosphated, and benzoylated derivatives exhibited non-toxic characteristics with favorable lipophilicity profiles. Molecular dynamics simulation analysis through RMSD and RMSF plots, focusing on the optimized 3,4-diphospho fucoidan, revealed hydrogen bonding patterns and substantial hydrophobic interactions with DENV proteins at allosteric binding sites. In summary, this study establishes that 3,4-diphospho fucoidan represents the most promising lead compound with potential anti-dengue properties among all tested derivatives. Therefore, this molecule warrants additional investigation through in vitro experimental studies.

Immunotherapy has garnered significant attention as a promising alternative treatment modality for triple-negative breast cancer because of its immunogenic nature. Of late, the modulation of programmed cell death-1 (PD-1) and its ligand programmed cell death ligand-1 (PD-L1) has shown potency in combating TNBC. Till date, several monoclonal antibodies and peptides are being used as PD-1/PD-L1 modulators. Nevertheless, the limitations associated with these molecules necessitate the development of potent alternative therapeutics. Thus, the present study aimed to employ a series of virtual screening strategies to derive peptidomimetic molecules as PD-1 modulators. Initially, a short peptide sequence (p-ADKYR) that disrupts the PD-1/PD-L1 dyad was designed. Subsequently, alanine scanning was conducted to analyse the critical residues on the designed peptide. The obtained results were then utilised for screening of peptidomimetics from the pep: MMs: MIMIC. The binding of the 200 peptide-mimicking molecules with the PD-1 protein was determined using AutoDock Vina. Further, the binding free energy and machine learning-based scoring analysis were used to re-score the docked pose of the complexes. Then, interaction analysis and ADMET properties were assessed for the obtained peptidomimetics, which resulted in one molecule, MMs01069049, as a potent PD-1 modulator. Finally, molecular dynamics simulation was performed for 200 ns, and the equilibrated structure from the last 5 ns was subjected to binding free energy analysis using MM-GBSA, which confirmed the enhanced stability and affinity of MMs01069049 at the PD-1 interface compared to the designed peptide. Collectively, we propose that MMs01069049 may serve as an efficient PD-1 modulator for the management of TNBC in the near future.

Supplementary information: The online version contains supplementary material available at 10.1007/s40203-025-00528-w.

This study aims to analyze the inhibitory action of the phytochemicals of Hedychium spicatum by computational docking studies, molecular dynamics simulations, and ADMET studies. For this, natural metabolites were taken from the IMPPAT and KNApSAcK databases. The crystallographic structure of the molecular target cyclooxygenase-2 (COX-2) was obtained from the RCSB PDB (PDB ID: 5IKR). Mefenamic acid, a well-known nonsteroidal anti-inflammatory drug (NSAID), was used as the standard for comparative analysis. Computational docking analysis was performed using Schrödinger's Glide, an option based on scoring functions. MD simulations were performed, followed by statistical analysis that included RMSD, RMSF, RoG, and H-bond analysis. MMGBSA analysis revealed optimal binding affinities ([Formula: see text]) with molecular targets HS6428435 (cis-Sesquisabinene hydrate), HS519857 (Cubenol), and HS7439 (Carvone), with values of - 37.32, - 32.20, and - 26.31 kcal/mol, respectively. Notably, HS6428435 exhibits a strong binding affinity of - 37.32 kcal/mol, compared to the standard drug, which has a binding affinity of - 35.28 kcal/mol, making it a more favorable alternative. These results indicated that cis-Sesquisabinene hydrate could be one of the potential ligands for the treatment of inflammatory conditions. The druggability of the suggested compounds is confirmed by the in-silico ADMET study. This work will later serve as a foundation for experimental investigations conducted both in vitro and in vivo to confirm the anti-inflammatory capabilities of the same.

Supplementary information: The online version of this article (10.1007/s40203-025-00537-9) contains supplementary material, which is available to authorized users.

Cancer remains a major global health challenge and is the second leading cause of mortality worldwide. Despite extensive efforts, the development of effective cancer therapies is still limited. Mitogen-activated protein kinase 7 (MAPK7), a critical regulator of cell proliferation, gene transcription, and metabolism, has recently emerged as a promising therapeutic target for cancer intervention. In this study, we applied advanced machine learning-based computational approaches to identify potential MAPK7 inhibitors. Virtual screening of a large library of drug-like molecules using machine learning models identified 33 active compounds against MAPK7. Molecular docking further refined these hits to five compounds with favorable binding affinities and strong interactions with key catalytic residues. Molecular dynamics (MD) simulations provided additional insights into the stability and conformational dynamics of protein-ligand complexes, highlighting amino acid residues crucial for inhibitor retention within the active site. Collectively, our findings suggest that these five compounds represent promising MAPK7 inhibitors, offering new opportunities for the development of targeted cancer therapeutics. To the best of our knowledge, this is the first study to combine machine learning-based virtual screening, molecular docking, and MD simulations for the identification of MAPK7 inhibitors.

Supplementary information: The online version contains supplementary material available at 10.1007/s40203-025-00531-1.

In early tumorigenesis, TGF-β acts as a tumour suppressor by inhibiting cell growth and inducing apoptosis, thereby maintaining cellular homeostasis and preventing malignant transformation. During cancer progression, however, TGF-β signalling is hijacked to promote tumour growth, invasion, migration, and immune evasion, contributing to stemness acquisition and drug resistance. This dual role highlights its context-dependent nature and therapeutic relevance in advanced cancers. In the present study, berberine derivatives were designed and evaluated computationally for their interactions with TGF-β receptors. Ligand and protein preparation were followed by molecular docking and molecular dynamics simulations. Docking analyses revealed that all derivatives exhibited improved binding scores compared to the parent berberine molecule, with all berberine derivatives demonstrating the strongest predicted affinity for both TGFβRI and TGFβRII over the parent molecule. Molecular dynamics simulations, assessed through RMSD, RMSF, SASA, Rg, and PCA analyses, confirmed that the receptor-ligand complexes remained stable throughout the trajectories, supporting their potential to modulate TGF-β signalling. These findings suggest that structural modification of berberine may enhance receptor binding and provide a rational framework for further experimental validation. Considering the limited oral bioavailability of berberine, the development of optimised derivative molecules may overcome this drawback and improve therapeutic potential in the management of advanced cancers.

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Supplementary information: The online version contains supplementary material available at 10.1007/s40203-025-00512-4.

The herb Nelumbo nucifera G., popularly known as ' lotus,' is well known in ancient texts for various kidney and urine formation conditions. The present study aimed to assess the effect of Nelumbo nucifera flower extract on the formation of kidney stones and evaluate the potential mechanisms involved using in silico -pharmacology approach along with in vitro and in vivo experiments. The aqueous extract of the flower was examined for anti-urolithiasis activity using nucleation and aggregation assays in vitro and in vivo in an ethylene glycol (EG)-induced urolithiasis model in male Wistar rats. Various physical, biochemical, and antioxidant parameters were evaluated in the serum, urine, and kidney homogenates, including body weight, urine output, SOD, MDA, creatinine level, and Blood Urea Nitrogen (BUN), followed by histopathological analysis of the kidneys to observe the effects of treatment. In vitro assays showed an increased percentage inhibition of calcium oxalate aggregation. The in vivo results were encouraging in terms of reducing metabolic stress and increasing renal function via pathways involved in inflammation, apoptosis, nitrogen metabolism, and pH balancing.

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Using medicinal plants as crude extracts for therapeutic purposes and understanding their pharmacological effects presents several difficulties. Further partitioning of crude extracts into components play crucial roles in understanding the pharmacological properties of their bioactive compounds. This study explored the biological properties of Combretum racemosum leaf, identified its bioactive compounds and molecular docking. Methanol extract of C. racemosum (MECR) leaf was prepared and successively partitioned into n-hexane (n-HFCR), ethyl acetate (EACR), n-butanol (n-BFCR) and aqueous (AFCR) fraction. Antioxidant, antidiabetic, and anti-inflammatory properties were performed using standard procedures. Bioactive compounds were identified using GC-MS and HPLC following molecular docking. Results revealed that MECR contained significant amounts of total phenol compared to the fractions while total flavonoid was abundant in n-HFCR, EACR, n-BFCR, and AFCR. Radicals (DPPH, ABTS and LPO) scavenging ability was above 50% across the samples while only the fractions demonstrated significant (p < 0.05) inhibition of amylase, glucosidase and sucrase. From this study, AFCR possessed better anti-inflammatory properties compared to other samples. Chromatography analyses revealed that both extract and fractions possessed varying concentrations of bioactive compounds such as lipoidal compounds and polyphenolic compounds. Docking analyses of the most abundant phytocompound (kaempferol) revealed strong binding interactions with human amylase, SGLT-1, SGLT-2, IL-6R, and trypsin. These findings have demonstrated the pharmacological potentials (antioxidant, antidiabetic, anti-inflammatory) of the methanol extract and fractions of C. racemosum leaf. A potential bioactive compound from the fractions of C. racemosum have been identified to possess strong molecular interactions with selected protein targets.

Supplementary information: The online version contains supplementary material available at 10.1007/s40203-025-00507-1.

Zika virus (ZIKV), a mosquito-borne flavivirus, has emerged as a global health concern due to its association with congenital microcephaly and neurological disorders. The non-structural protein NS4A plays a pivotal role in viral replication and immune evasion by antagonizing the mitochondrial antiviral signaling protein (MAVS). In this study, we evaluated four NS4A mutations (L48M, K42E, F4L, and E8D). Only F4L and E8D showed destabilizing effects and were selected for further analysis. We used molecular docking, 300 ns molecular dynamics simulations, and binding free energy calculations to assess their effects on NS4A-MAVS binding. Stability investigations root means square deviation (RMSD) root mean square fluctuation (RMSF) and radius of gyration (Rg) revealed that both mutations changed the conformational dynamics of NS4A-MAVS complexes, with F4L displaying transitory fluctuations and E8D exhibiting long-term structural flexibility. Hydrogen bond research revealed that both mutants had stronger interaction networks with MAVS compared to the natural type. MM/PBSA computations showed that F4L and E8D had reduce binding affinities, with ΔG values of - 54.05 kcal/mol and - 56.25 kcal/mol, respectively, compared to - 61.73 kcal/mol in the wild type. The stronger electrostatic contributions observed in the E8D complex highlight its potential to further disrupt MAVS-mediated interferon induction. Collectively, these results suggest that the F4L and particularly E8D mutations enhance the immune-evasive capacity of ZIKV by stabilizing NS4A-MAVS interactions, offering insights into viral pathogenesis and providing a computational basis for therapeutic targeting of NS4A.

Supplementary information: The online version contains supplementary material available at 10.1007/s40203-025-00540-0.