Mokhtar, Fatma ASelim, Nabil MElhawary, Seham SAbd El Hadi, Soha RHetta, Mona HAlbalawi, Marzough AShati, Ali AAlfaifi, Mohammad YElbehairi, Serag Eldin IFahmy, Lamiaa IIbrahim, Rana M2022-11-302022-11-302022-11https://doi.org/10.3390/ ph15111354http://repository.msa.edu.eg/xmlui/handle/123456789/5264Annona glabra L. (AngTE) and Annona squamosa L. (AnsTE) fruits have been widely used in cancer treatment. Accordingly, their extracts were used to synthesize silver nanoparticles via a biogenic route (Ang-AgNPs) and (Ans-AgNPs), respectively. Chemical profiling was established using UPLC-QTOF-MS/MS. All species were tested for anticancer activity against human cervical cancer cells (HeLa), prostate adenocarcinoma metastatic (PC3), and ovary adenocarcinoma (SKOV3) using sulphorhodamine B assay. Apoptosis was determined using Annexin flow cytometry along with cell cycle analysis and supported by a molecular docking. The antibacterial and synergistic effect when combined with gentamicin were evaluated. A total of 114 compounds were tentatively identified, mainly acetogenins and ent-kaurane diterpenes. AnsTE and Ans-AgNPs had the most potent cytotoxicity on HeLa and SKOV3 cells, inducing a significant apoptotic effect against all tumor cells. The AnsTE and Ans-AgNPs significantly arrested PC3, SKOV3, and HeLa cells in the S phase. The nanoparticles demonstrated greater antibacterial and antifungal activities, as well as a synergistic effect with gentamicin against P. aeruginosa and E. coli. Finally, a molecular docking was attempted to investigate the binding mode of the identified compounds in Bcl-2 proteins’ receptor, implying that the fruits and their nanoparticles are excellent candidates for treating skin infections in patients with ovarian or prostatic cancer.en-USAnnona; UPLC-QTOF-MS/MSsilver nanoparticlesanticancerapoptosisantibacterialantifungaldockingGreen Biosynthesis of Silver Nanoparticles Using Annona glabra and Annona squamosa Extracts with Antimicrobial, Anticancer, Apoptosis Potentials, Assisted by In Silico Modeling, and Metabolic ProfilingArticlehttps://doi.org/10.3390/ ph1511135