In silico pharmacology最新文献

An in-silico approach was implemented to develop a multi-epitope subunit vaccine construct against the recent outbreak of the Monkeypox virus. The contribution of 10 different antigenic proteins based on their antigenicity led to the selection of 10 HTL, 9 CTL, and 6 BCL epitopes. The construct was further investigated for its allergenicity, antigenicity, and physio-chemical properties using servers such as AllerTOP and Allergen FP, VaxiJen and ANTIGENPro, and ProtParam respectively. The secondary structure of the vaccine was predicted using the SOPMA server followed by I-TASSER for the 3D structure. After refinement and validation of structural stability of the modelled vaccine, a molecular docking assay was implemented to study the interaction of the known TLR4 receptor with that of the constructed vaccine using the ClusPro server. The docked vaccine and TLR4 receptor were studied using the molecular dynamics (MD) simulation to validate the stability of the complex. After codon optimization the cDNA was constructed and in-silico cloning of the vaccine construct was carried out. The vaccine was also subjected to computational immune assay which predicted a powerful immune response against the Monkeypox virus validating that the developed multi-epitope vaccine construct can be a potent vaccine candidate.

Supplementary information: The online version contains supplementary material available at 10.1007/s40203-024-00220-5.

The drug target protein β-secretase 1 (BACE1) is one of the promising targets in the design of the drugs to control Alzheimer's disease (AD). Patients with neurodegenerative diseases are increasing in number globally due to the increase in the average lifetime. Neuro modulation is the only remedy for overcoming these age related diseases. In recent times, marine bioactive compounds are reported from Phaeophyceae (Brown Algae), Rhodophyta (Red Algae) and Chlorophyta (Green Algae) for neuro-modulation. Hence, an important attempt is made to understand the binding and stability of the identified bioactive compounds from the above marine algae using BACE1 as the molecular target. The docking study shows that the bioactive compound Fucotriphlorethol A ( - 17.27 kcal/mol) has good binding affinity and energy compared to other compounds such as Dieckol ( - 16.77 kcal/mol), Tetraphlorethol C ( - 15.12 kcal/mol), 2-phloroeckol ( - 14.98 kcal/mol), Phlorofucofuroeckol ( - 13.46 kcal/mol) and the co-crystal ( - 8.59 kcal/mol). Further, molecular dynamics simulations studies had been carried out for β-secretase 1 complex with Fucotriphlorethol A and Phlorofucofuroeckol for 100 ns each. Results are compared with that of the co-crystal inhibitor. Molecular dynamics simulations studies also support the stability and flexibility of the two bioactive compounds Fucotriphlorethol A and Phlorofucofuroeckol with BACE1.

Supplementary information: The online version contains supplementary material available at 10.1007/s40203-024-00210-7.

Genes related to MAPK-ERK signaling pathways, and epithelial-mesenchymal transition induction is evolutionarily conserved and has crucial roles in the regulation of important cellular processes, including cell proliferation. In this study, six cannabinoids from Cannabis sativa were docked with MAPK-ERK signaling pathways to identify their possible binding interactions. The results showed that all the cannabinoids have good binding affinities with the target proteins. The best binding affinities were MEK- tetrahydrocannabinol (- 8.8 kcal/mol) and P13k-cannabinol (- 8.5 kcal/mol). The root mean square deviation was calculated and used two alternative variants (rmsd/ub and rmsd/lb) and the values of rmsd/lb fluctuated 8.6-2.0 Å and for rmsd/ub from 1.0 to 2.0 Å that suggests the cannabinoids and protein complex are accurate and cannot destroy on binding. The study analyzed the pharmacokinetic and drug-likeness properties of six cannabinoids from C. sativa leaves using the SwissADME web tool. Lipinski's rule of five was used to predict drug-likeness and showed that all compounds have not violated it and the total polar surface area of cannabinoids was also according to Lipinski's rule that is benchmarked of anticancer drugs. Cannabinoids are meet the requirements of leadlikeness and synthetic accessibility values showed they can be synthesized. The molecular weight, XLOGP3, solubility (log S), and flexibility (FLEX) are according to the bioavailability radar. The bioavailability score and consensus Log Po/w fall within the acceptable range for the suitable drug. Pharmacokinetics parameters showed that cannabinoids cannot cross the blood-brain barrier, have high GI absorption as well as cannabinoids are substrates of (CYP1A2, CYP2C19, CYP2C9, CYP2D6, and CYP3A4) but no substrate of P-glycoprotein. Based on these findings, the study suggests that cannabinoids are suitable drugs that could be used as effective inhibitors for target proteins involved in cancer pathways. Among the six cannabinoids, cannabinol and tetrahydrocannabinol exerted maximum binding affinities with proteins of MAPK-ERK signaling pathways, and their pharmacokinetics and drug-likeness-related profiles suggest that these cannabinoids could be superlative inhibitors in cancer treatment. Further in vitro, in vivo, and clinical studies are needed to explore their potential in cancer treatment.

Supplementary information: The online version contains supplementary material available at 10.1007/s40203-024-00213-4.

In the case of hepatocellular carcinoma, there is a need to find novel immune biomarkers to predict cancer prognosis, which will help prolong patient survival. On the basis of these findings, we explored the role of the hub genes in hepatocellular carcinoma via computational analysis for future immunotherapy. To study this phenomenon, we selected three datasets downloaded from the GEO database (GSE25097, GSE76427 and GSE84402). The gene expression analysis platform (GEAP) online tool was used for the data analysis to identify the DEGs. Functional enrichment analysis was performed by GO and KEGG enrichment analysis. The genes associated with these genes were identified via Cytoscape software. Immune cell infiltration and correlation analysis were used to screen the hub genes. The results revealed that the PTTG1, NCAPG, RACGAP1, PBK, ASPM, AURKA, CDCA5, KIF20A, MELK and PRC1 genes were correlated with immune targets, and these hub gene biomarkers will aid in future cancer prognosis and immunotherapy targeting in hepatocellular carcinoma patients.

Supplementary information: The online version contains supplementary material available at 10.1007/s40203-024-00215-2.

Inflammation is an adaptive response that involves activation, and recruitment of cells of innate and adaptive immune cells for restoring homeostasis. To safeguard the host from the threat of inflammatory agents, microbial invasion, or damage, the immune system activates the transcription factor NF-κB and produces cytokines such as TNF-α, IL- 6, IL-1β, and α. Sirtuin 1 (SIRT1) controls the increased amounts of proinflammatory cytokines, which in turn controls inflammation. Three phytoconstituents resveratrol (RES), pterostilbene (PTE), and curcumin (CUR) which are SIRT1- activators and that have marked anti-inflammatory effects (in-vivo), were chosen for the current study. These compounds were compared for their anti-inflammatory potential by in-silico docking studies for IL-6, TNF-α, NF-κB, and SIRT1 and in-vitro THP-1 cell line studies for IL-6, TNF-α. PTE was found to be more effective than RES and CUR in lowering the concentrations of IL-6 and TNF-α in THP-1 cell line studies, and it also showed a favorable docking profile with cytokines and SIRT1. Thus, PTE appears to be a better choice for further research and development as a drug or functional food supplement with the ability to reduce inflammation in metabolic disorders.

Graphical abstract: Schematic representation of in-silico and in-vitro analysis of Resveratrol, Pterostilbene, and Curcumin.

The major challenge in the development of affordable medicines from natural sources is the unavailability of logical protocols to explain their mechanism of action in biological targets. FimH (Type 1 fimbrin with D-mannose specific adhesion property), a lectin on E. coli cell surface is a promising target to combat the urinary tract infection (UTI). The present study aimed at predicting the inhibitory capacity of saccharides on FimH. As mannosides are considered FimH inhibitors, the readily accessible saccharides from the PubChem collection were utilized. The artificial neural networks (ANN)-based machine learning algorithm Self-organizing map (SOM) has been successfully employed in predicting active molecules as they could discover relationships through self-organization for the ligand-based virtual screening. Docking was used for the structure-based virtual screening and molecular dynamic simulation for validation. The result revealed that the predicted molecules malonyl hexose and mannosyl glucosyl glycerate exhibit exactly similar binding interactions and better docking scores as that of the reference bioassay active, heptyl mannose. The pharmacokinetic profile matches that of the selected bioflavonoids (quercetin malonyl hexose, kaempferol malonyl hexose) and has better values than the control drug bioflavonoid, monoxerutin. Thus, these two molecules can effectively inhibit type 1 fimbrial adhesin, as antibiotics against E. coli and can be explored as a prophylactic against UTIs. Moreover, this investigation can pave the way to the exploration of the potential benefits of plant-based treatments.

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Supplementary information: The online version contains supplementary material available at 10.1007/s40203-024-00212-5.

Depression is a common psychiatric comorbidity among patients with epilepsy (PWE), affecting more than a third of PWE. Management of depression may improve quality of life of epileptic patients. Unfortunately, available antidepressants worsen epilepsy by reducing the seizure threshold. This situation demands search of new safer target for combined directorate of epilepsy and comorbid depression. A system biology approach may be useful to find novel pathways/markers for the cure of both epilepsy and associated depression via analyzing available genomic and proteomic information. Hence, the system biology approach using curated 64 seed genes involved in temporal lobe epilepsy and mental depression was applied. The interplay of 600 potential proteins was revealed by the Disease Module Detection (DIAMOnD) Algorithm for the treatment of both epilepsy and comorbid depression using these seed genes. The gene enrichment analysis of seed and diamond genes through DAVID suggested 95 pathways. Selected pathways were refined based on their syn or anti role in epilepsy and depression. In conclusion, total 8 pathways and 27 DIAMOnD genes/proteins were finally deduced as potential new targets for modulation of selected pathways to manage epilepsy and comorbid depression.

Supplementary information: The online version contains supplementary material available at 10.1007/s40203-024-00208-1.