Excavating phytochemicals from plants possessing antiviral activities for identifying SARS-CoV hemagglutinin-esterase inhibitors by diligent computational workflow

Shatavari supplementation in postmenopausal women alters the skeletal muscle proteome and pathways involved in training adaptation

PURPOSE

Shatavari is an understudied, widely available herbal supplement. It contains steroidal saponins and phytoestrogens. We previously showed that six weeks of shatavari supplementation improved handgrip strength and increased markers of myosin contractile function. Mechanistic insights into shatavari's actions are limited. Therefore, we performed proteomics on vastus lateralis (VL) samples that remained from our original study.

METHODS

In a randomised double-blind trial, women (68.5 ± 6 years) ingested either placebo or shatavari (equivalent to 26,500 mg/d fresh weight) for six weeks. Tandem mass tag global proteomic analysis of VL samples was conducted (N = 7 shatavari, N = 5 placebo). Data were normalized to total peptides and scaled using a reference sample. Data were filtered using a 5% FDR. For each protein, the pre to post supplementation difference was expressed as log2 fold change. Welch's t tests with Benjamini-Hochberg corrections were performed for each protein. Pathway enrichment (PADOG, CAMERA) was interrogated in Reactome (v85).

RESULTS

No individual protein was significantly different between supplementation conditions. Both PADOG and CAMERA indicated that pathways related to (1) Integrin/MAPK signalling, (2) metabolism/insulin secretion; (3) cell proliferation/senescence/DNA repair/cell death; (4) haemostasis/platelets/fibrin; (5) signal transduction; (6) neutrophil degranulation and (7) chemical synapse function were significantly upregulated. CAMERA indicated pathways related to translation/amino acid metabolism, viral infection, and muscle contraction were downregulated.

CONCLUSION

Our analyses indicate that shatavari may support muscle adaptation responses to exercise. These data provide useful signposts for future investigation of shatavari's utility in conserving and enhancing musculoskeletal function in older age.

TRIAL REGISTRATION

NCT05025917 30/08/21, retrospectively registered.

Phyto-therapeutic potential of Withania somnifera: Molecular mechanism and health implications

Withania somnifera, the plant named Indian ginseng, Ashwagandha, or winter cherry, has been used since ancient times to cure various health ailments. Withania somnifera is rich in constituents belonging to chemical classes like alkaloids, saponins, flavonoids, phenolic acids, and withanolides. Several chemotypes were identified based on their phytochemical composition and credited for their multiple bioactivities. Besides, exhibiting neuroprotective, immunomodulatory, adaptogenic, anti-stress, bone health, plant has shown promising anti-cancer properties. Several withanolides have been reported to play a crucial role in cancer; they target cancer cells by different mechanisms such as modulating the expression of tumor suppressor genes, apoptosis, telomerase expression, and regulating cell signaling pathway. Though, many treatments are available for cancer; however, to date, no assured reliable cure for cancer is made available. Additionally, synthetic drugs may lead to development of resistance in time; therefore, focus on new and natural drugs for cancer therapeutics may prove a longtime effective alternative. This current report is a comprehensive combined analysis upto 2023 with articles focused on bio-activities of plant Withania somnifera from various sources, including national and international government sources. This review focuses on understanding of various mechanisms and pathways to inhibit uncontrolled cell growth by W. somnifera bioactives, as reported in literature. This review provides a recent updated status of the W. somnifera on pharmacological properties in general and anti-cancer in particular and may provide a guiding resource for researchers associated with natural product-based cancer research and healthcare management.

In Silico Identification of Anti-SARS-CoV-2 Medicinal Plants Using Cheminformatics and Machine Learning

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), the causative pathogen of COVID-19, is spreading rapidly and has caused hundreds of millions of infections and millions of deaths worldwide. Due to the lack of specific vaccines and effective treatments for COVID-19, there is an urgent need to identify effective drugs. Traditional Chinese medicine (TCM) is a valuable resource for identifying novel anti-SARS-CoV-2 drugs based on the important contribution of TCM and its potential benefits in COVID-19 treatment. Herein, we aimed to discover novel anti-SARS-CoV-2 compounds and medicinal plants from TCM by establishing a prediction method of anti-SARS-CoV-2 activity using machine learning methods. We first constructed a benchmark dataset from anti-SARS-CoV-2 bioactivity data collected from the ChEMBL database. Then, we established random forest (RF) and support vector machine (SVM) models that both achieved satisfactory predictive performance with AUC values of 0.90. By using this method, a total of 1011 active anti-SARS-CoV-2 compounds were predicted from the TCMSP database. Among these compounds, six compounds with highly potent activity were confirmed in the anti-SARS-CoV-2 experiments. The molecular fingerprint similarity analysis revealed that only 24 of the 1011 compounds have high similarity to the FDA-approved antiviral drugs, indicating that most of the compounds were structurally novel. Based on the predicted anti-SARS-CoV-2 compounds, we identified 74 anti-SARS-CoV-2 medicinal plants through enrichment analysis. The 74 plants are widely distributed in 68 genera and 43 families, 14 of which belong to antipyretic detoxicate plants. In summary, this study provided several medicinal plants with potential anti-SARS-CoV-2 activity, which offer an attractive starting point and a broader scope to mine for potentially novel anti-SARS-CoV-2 drugs.

Identification of potential inhibitors of omicron variant of SARS-Cov-2 RBD based virtual screening, MD simulation, and DFT

Emergence of the SARS-CoV-2 Omicron variant of concern (VOC; B.1.1.529) resulted in a new peak of the COVID-19 pandemic, which called for development of effective therapeutics against the Omicron VOC. The receptor binding domain (RBD) of the spike protein, which is responsible for recognition and binding of the human ACE2 receptor protein, is a potential drug target. Mutations in receptor binding domain of the S-protein have been postulated to enhance the binding strength of the Omicron VOC to host proteins. In this study, bioinformatic analyses were performed to screen for potential therapeutic compounds targeting the omicron VOC. A total of 92,699 compounds were screened from different libraries based on receptor binding domain of the S-protein via docking and binding free energy analysis, yielding the top 5 best hits. Dynamic simulation trajectory analysis and binding free energy decomposition were used to determine the inhibitory mechanism of candidate molecules by focusing on their interactions with recognized residues on receptor binding domain. The ADMET prediction and DFT calculations were conducted to determine the pharmacokinetic parameters and precise chemical properties of the identified molecules. The molecular properties of the identified molecules and their ability to interfere with recognition of the human ACE2 receptors by receptor binding domain suggest that they are potential therapeutic agents for SARS-CoV-2 Omicron VOC.