Integration of System Biology Tools to Investigate Huperzine A as an Anti-Alzheimer Agent

Khanal, Pukar; Zargari, Farshid; Far, Bahareh Farasati; Kumar, Dharmendra; Rajagopal, Mogana; Mahdi, Yasir K.; Jubair, Najwan; Saraf, Shailendra K.; Bansal, Parveen; Singh, Ranjit; Selvaraja, Malarvili; Dey, Yadu Nandan

doi:10.3389/fphar.2021.785964

Cited by 23 publications

(18 citation statements)

References 49 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…DCCM evaluates the magnitude of each pairwise cross-correlation coefficient to determine whether or not atomic pair motion is correlated i.e., positive or negative ( Khanal et al, 2021 ). We examined each DCCM component in this section, where C ij = 1 denotes the same period and phase (positive correlation), C ij = 0 indicates a lack of correlation, and C ij = −1 indicates a negative correlation between the fluctuations of i and j ( Khanal et al, 2021 ).…”

Section: Methodsmentioning

confidence: 99%

Systems and in vitro pharmacology profiling of diosgenin against breast cancer

Khanal

Patil²,

Bhandare

et al. 2023

Front. Pharmacol.

Self Cite

View full text Add to dashboard Cite

Aim: The purpose of this study was to establish a mode of action for diosgenin against breast cancer employing a range of system biology tools and to corroborate its results with experimental facts.Methodology: The diosgenin-regulated domains implicated in breast cancer were enriched in the Kyoto Encyclopedia of Genes and Genomes database to establish diosgenin-protein(s)-pathway(s) associations. Later, molecular docking and the lead complexes were considered for molecular dynamics simulations, MMPBSA, principal component, and dynamics cross-correlation matrix analysis using GROMACS v2021. Furthermore, survival analysis was carried out for the diosgenin-regulated proteins that were anticipated to be involved in breast cancer. For gene expression analyses, the top three targets with the highest binding affinity for diosgenin and tumor expression were examined. Furthermore, the effect of diosgenin on cell proliferation, cytotoxicity, and the partial Warburg effect was tested to validate the computational findings using functional outputs of the lead targets.Results: The protein-protein interaction had 57 edges, an average node degree of 5.43, and a p-value of 3.83e-14. Furthermore, enrichment analysis showed 36 KEGG pathways, 12 cellular components, 27 molecular functions, and 307 biological processes. In network analysis, three hub proteins were notably modulated: IGF1R, MDM2, and SRC, diosgenin with the highest binding affinity with IGF1R (binding energy −8.6 kcal/mol). Furthermore, during the 150 ns molecular dynamics (MD) projection run, diosgenin exhibited robust intermolecular interactions and had the least free binding energy with IGF1R (−35.143 kcal/mol) compared to MDM2 (−34.619 kcal/mol), and SRC (-17.944 kcal/mol). Diosgenin exhibited the highest cytotoxicity against MCF7 cell lines (IC50 12.05 ± 1.33) µg/ml. Furthermore, in H2O2-induced oxidative stress, the inhibitory constant (IC50 7.68 ± 0.51) µg/ml of diosgenin was lowest in MCF7 cell lines. However, the reversal of the Warburg effect by diosgenin seemed to be maximum in non-cancer Vero cell lines (EC50 15.27 ± 0.95) µg/ml compared to the rest. Furthermore, diosgenin inhibited cell proliferation in SKBR3 cell lines more though.Conclusion: The current study demonstrated that diosgenin impacts a series of signaling pathways, involved in the advancement of breast cancer, including FoxO, PI3K-Akt, p53, Ras, and MAPK signaling. Additionally, diosgenin established a persistent diosgenin-protein complex and had a significant binding affinity towards IGF1R, MDM2, and SRC. It is possible that this slowed down cell growth, countered the Warburg phenomenon, and showed the cytotoxicity towards breast cancer cells.

show abstract

Section: Methodsmentioning

confidence: 99%

Systems and in vitro pharmacology profiling of diosgenin against breast cancer

Khanal

Patil²,

Bhandare

et al. 2023

Front. Pharmacol.

Self Cite

View full text Add to dashboard Cite

show abstract

“…The dynamic cross-correlation matrix (DCCM) evaluates the magnitude of all pairwise cross-correlation coefficients to identify correlated (positive or negative) motion among pairs of atoms [ 33 ]. In this section, we studied each element of DCCM, where C ij = 1 indicates that have the same period and phase (positively correlated), C ij = 0 indicates no correlation and C ij = − 1 indicates that the fluctuations of i and j are negatively correlated [ 33 ].…”

Section: Methodsmentioning

confidence: 99%

Computational investigation of benzalacetophenone derivatives against SARS-CoV-2 as potential multi-target bioactive compounds

Khanal

Patil²,

Bhandare³

et al. 2022

Computers in Biology and Medicine

Self Cite

View full text Add to dashboard Cite

“…Drug delivery is a major topic of research in biomedicine that controls drug delivery and therapeutic drugs to target cells [ 9 , 10 , 11 ]. However, nanotechnology creates products that exhibit novel properties at nanoscale levels, which offer new tools for biologists [ 12 , 13 , 14 ]. Recently, the use of various organic–inorganic hybrid NPs because of advances in nanotechnology has drawn significant attention [ 15 ].…”

Section: Introductionmentioning

confidence: 99%

Formulation and Characterization of Poly (Ethylene Glycol)-Coated Core-Shell Methionine Magnetic Nanoparticles as a Carrier for Naproxen Delivery: Growth Inhibition of Cancer Cells

Yeganeh

Yousefi

et al. 2022

Cancers

View full text Add to dashboard Cite

An efficient and selective drug delivery vehicle for cancer cells can remarkably improve therapeutic approaches. In this study, we focused on the synthesis and characterization of magnetic Ni1−xCoxFe2O4 nanoparticles (NPs) coated with two layers of methionine and polyethylene glycol to increase the loading capacity and lower toxicity to serve as an efficient drug carrier. Ni1−xCoxFe2O4@Methionine@PEG NPs were synthesized by a reflux method then characterized by FTIR, XRD, FESEM, TEM, and VSM. Naproxen was used as a model drug and its loading and release in the vehicles were evaluated. The results for loading efficiency showed 1 mg of Ni1−xCoxFe2O4@Methionine@PEG NPs could load 0.51 mg of the naproxen. Interestingly, Ni1−xCoxFe2O4@Methionine@PEG showed a gradual release of the drug, achieving a time-release up to 5 days, and demonstrated that a pH 5 release of the drug was about 20% higher than Ni1−xCoxFe2O4@Methionine NPs, which could enhance the intracellular drug release following endocytosis. At pH 7.4, the release of the drug was slower than Ni1−xCoxFe2O4@Methionine NPs; demonstrating the potential to minimize the adverse effects of anticancer drugs on normal tissues. Moreover, naproxen loaded onto the Ni1−xCoxFe2O4@Methionine@PEG NPs for breast cancer cell lines MDA-MB-231 and MCF-7 showed more significant cell death than the free drug, which was measured by an MTT assay. When comparing both cancer cells, we demonstrated that naproxen loaded onto the Ni1−xCoxFe2O4@Methionine@PEG NPs exhibited greater cell death effects on the MCF-7 cells compared with the MDA-MB-231 cells. The results of the hemolysis test also showed good hemocompatibility. The results indicated that the prepared magnetic nanocarrier could be suitable for controlled anticancer drug delivery.

show abstract

Integration of System Biology Tools to Investigate Huperzine A as an Anti-Alzheimer Agent

Cited by 23 publications

References 49 publications

Systems and in vitro pharmacology profiling of diosgenin against breast cancer

Systems and in vitro pharmacology profiling of diosgenin against breast cancer

Computational investigation of benzalacetophenone derivatives against SARS-CoV-2 as potential multi-target bioactive compounds

Formulation and Characterization of Poly (Ethylene Glycol)-Coated Core-Shell Methionine Magnetic Nanoparticles as a Carrier for Naproxen Delivery: Growth Inhibition of Cancer Cells

Contact Info

Product

Resources

About