Molecular docking of compounds from Clinacanthus nutans extract detected by GC-MS analysis with the SARS-CoV-2 main protease and ACE2 protein

Investigating the potential of mono-chalcone compounds in targeting breast cancer receptors through network pharmacology, molecular docking, molecular dynamics simulation, antiproliferative effects, and gene expressions

The study aims to investigate various aspects of synthesized mono-chalcone compounds 5 and 8 concerning breast cancer, including network pharmacology, molecular docking, molecular dynamics (MD) simulations, antiproliferative effects, and gene expressions. Initially, the compounds underwent a network pharmacology analysis targeting breast cancer-related targets, with MalaCards, SwissTargetPrediction, and PharmMapper identifying 70 breast cancer target receptors. Subsequently, protein-protein interaction (PPI) network analysis revealed two distinct target gene clusters. Survival analysis identified seven significant target genes following Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment and Gene Ontology (GO) evaluation. Molecular docking and MD simulations were conducted on these seven target genes (AKT2, BRAF, ESR1, FGFR1, IGF1, IGF1R, and KIT), revealing that compound 8 exhibited the highest binding affinities, as well as better stability and compactness when interacting with the targeted proteins. Next, the compounds underwent cell viability assay and gene expression analysis to validate the in silico findings. Both compounds demonstrated the ability to suppress breast cancer proliferation, with compound 8 showing increased selectivity in targeting breast cancer cells while causing minimal harm to normal breast cells. The suppression of breast cancer cell proliferation was attributed to decreased expression levels of AKT2, BRAF, FGFR1, IGF1, IGF1R, KIT, and ESR1. Hence, the results provide insights into the molecular interaction responsible for the anti-breast cancer capabilities of mono-chalcone compounds.

Supplementary Information

The online version contains supplementary material available at 10.1007/s13205-024-03991-y.

Network pharmacology, molecular docking and molecular dynamics simulation of chalcone scaffold-based compounds targeting breast cancer receptors

Compounds with a chalcone scaffold-based structure have demonstrated promising anticancer biological activity. However, the molecular interactions between chalcone scaffold-based compounds and breast cancer-associated proteins remain unclear. Through network pharmacology, molecular docking, and molecular dynamics (MD) simulation analyses, compounds with a chalcone scaffold-based structure were evaluated for their interaction with potential breast cancer targets. The compounds were retrieved from the ASINEX database, resulting in 575,302 compounds. A total of 342 compounds with chalcone scaffold-based structures were discovered. From the 342 compounds that was analysed, ten were chosen due to their adherence to Lipinski's rule, having an appropriate range of lipophilicity (LOGP), and topological polar surface area (TPSA), and absence of any toxicity. Based on target intersection, 50 target genes were found and subjected to protein-protein interaction (PPI), gene ontology (GO), and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analyses. Four target genes were found to be involved in the breast cancer pathway. Consequently, molecular docking was utilised to analyse the molecular interactions between the compounds and four target protein receptors. Compound 211 exhibited the highest binding affinities for the epidermal growth factor receptor (EGFR), fibroblast growth factor receptor 1 (FGFR1), oestrogen receptor (ESR1), and cyclin dependent kinase 6 (CDK6) with values of -8.95 kcal/mol, -8.60 kcal/mol, -10.33 kcal/mol, and -9.90 kcal/mol, respectively. During MD simulation, compound 211 and its respective proteins were stable, compact, and had minimal flexibility. The findings provide foundations for future studies into the interaction underlying the anti-breast cancer potential of compounds with chalcone-based scaffold structures.Communicated by Ramaswamy H. Sarma.

Antiviral and Immunomodulatory Activities of Clinacanthus nutans (Burm. f.) Lindau

Clinacanthus nutans (Burm. f.) Lindau has been used as a traditional herbal medicine for treating snake bites, scalds, burns, and viral and bacterial infections. It has been attracting an increasing amount of attention because of its biological activities, including its antidiabetic, antioxidant, antibacterial, anticancer, anti-inflammatory, antiviral, and immunoregulatory activities. Here, we conducted a panoramic survey of the literature regarding the immunoregulatory, anti-inflammatory, and antiviral activities of C. nutans. We discovered that C. nutans extracts have virucidal activities against herpes simplex virus types 1 and 2, varicella-zoster virus, cyprinid herpesvirus 3, porcine reproductive and respiratory syndrome virus, mosquito-borne chikungunya virus, and potentially SARS-CoV-2; such activities likely result from C. nutans interfering with the entry, penetration, infection, and replication of viruses. We also reviewed the phytochemicals in C. nutans extracts that exhibit anti-inflammatory and immunoregulatory activities. This updated review of the antiviral, anti-inflammatory, and immunoregulatory activities of C. nutans may guide future agricultural practices and reveal clinical applications of C. nutans.

Methodology-Centered Review of Molecular Modeling, Simulation, and Prediction of SARS-CoV-2

Despite tremendous efforts in the past two years, our understanding of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), virus-host interactions, immune response, virulence, transmission, and evolution is still very limited. This limitation calls for further in-depth investigation. Computational studies have become an indispensable component in combating coronavirus disease 2019 (COVID-19) due to their low cost, their efficiency, and the fact that they are free from safety and ethical constraints. Additionally, the mechanism that governs the global evolution and transmission of SARS-CoV-2 cannot be revealed from individual experiments and was discovered by integrating genotyping of massive viral sequences, biophysical modeling of protein-protein interactions, deep mutational data, deep learning, and advanced mathematics. There exists a tsunami of literature on the molecular modeling, simulations, and predictions of SARS-CoV-2 and related developments of drugs, vaccines, antibodies, and diagnostics. To provide readers with a quick update about this literature, we present a comprehensive and systematic methodology-centered review. Aspects such as molecular biophysics, bioinformatics, cheminformatics, machine learning, and mathematics are discussed. This review will be beneficial to researchers who are looking for ways to contribute to SARS-CoV-2 studies and those who are interested in the status of the field.

Multiplex Technologies in COVID-19 Research, Diagnostics, and Prognostics: Battling the Pandemic

Due to continuous technical developments and new insights into the high complexity of infectious diseases such as COVID-19, there is an increasing need for multiplex biomarkers to aid clinical management and support the development of new drugs and vaccines. COVID-19 disease requires rapid diagnosis and stratification to enable the most appropriate treatment course for the best possible outcomes for patients. In addition, these tests should be rapid, specific, and sensitive. They should rule out other potential causes of illness with simultaneous testing for other diseases. Elevated levels of specific biomarkers can be used to establish severity risks of chronic diseases so that patients can be provided the proper medication at the right time. This review describes the state-of-the-art technologies in proteomics, transcriptomics, and metabolomics, for multiplex biomarker approaches in COVID-19 research.

Christia vespertilionis extract induced antiproliferation and apoptosis in breast cancer (MCF7) cells

BACKGROUND

C. vespertiliomis extracts were evaluated for antiproliferative and apoptosis effect on breast cancer (MCF7) cells.

METHODS AND RESULTS

The leaves extracts were analysed for its antiproliferative effect on breast cancer (MCF7) cells and normal epithelial breast (MCF 10A) cells using Sulforhodamine B (SRB) assay. The selective extract was evaluated for its ability to induce apoptosis using Annexin V-FITC apoptosis staining and the expression of molecular genes using qualitative reverse transcription-polymerase chain reaction (RT-PCR) against MCF7 cells. Gas chromatography-mass spectrometry (GC-MS) was used to identify the compounds from the selective extract. The findings showed that dichloromethane fraction (CV-Dcm) extract had high antiproliferative effect against MCF7 cells (IC₅₀ = 24 µg/mL, selective index (SI) = 8.17). The percentages of apoptosis cells in CV-Dcm-treated MCF7 cells was 58.8%. The CV-Dcm extract induced downregulation of PCNA level. The apoptotic genes were also triggered in both extrinsic and intrinsic signaling pathways, affecting a 1.5-fold increase in BAX, 1.4-fold increase in cytochrome c, 1.3-fold increase in caspase-8, 1.7-fold increase in caspase-3 and 0.5-fold-decrease in BCL-2. Treated MCF7 cells also activated P53-dependent apoptotic death pathway.

CONCLUSIONS

The present work strongly suggests that high efficacy of CV-Dcm extract was attributed to its antiproliferative and apoptosis-inducing activation in MCF7 cells, most likely due to its favourable compounds.