Journal of Molecular Modeling

Phytochemicals from Ayurvedic plants as potential medicaments for ovarian cancer: an in silico analysis

Ovarian cancer is one of the highly prominent gynecological malignancies after breast cancer. Although myriad literature is available, there is no specific biomarker available for the personalized treatment strategy. The unavailability of effective drug therapy for ovarian cancer calls for an urgent push in its development from the multidisciplinary scientific community. Indian Ayurvedic medicine pharmacology is widely appreciated and accepted for its immense healthcare benefits. Bioinformatics and cheminformatics approaches can be effectively used to screen phytochemicals present in the Indian Ayurvedic plants against ovarian cancer target receptors. Recent studies discern that POTE, a cancer-testis antigen (CTA) family, plays a crucial role in the proliferation and progression of cancers including ovarian cancer. Specifically, POTEE paralog has been observed to be hypermethylated in ovarian cancer. This study undertakes an in silico analysis of Indian Ayurvedic plants for their anticancer efficacy against ovarian cancer proliferation target receptor POTEE. Structures of 100 phytochemicals from 11 Ayurvedic plants were screened with ADME criteria, and qualified phytochemicals were subjected to molecular docking and interaction analysis. Only 6 phytochemicals having a high affinity to the target receptor (POTEE) were then subjected to an all-atom replica exchange molecular dynamics simulation for 50 ns. Binding affinities of 6 phytochemicals cedeodarin, deodarin, hematoxylin, matairesinol, quercetin, and taxifolin with POTEE were -8.1, -7.7, -7.7, -7.9, -8.0, and - 7.7 kcal/mol, respectively, and their RMSD were recorded as zero. This study concludes that phytochemicals present in Indian Ayurvedic plants namely Cedrus deodara and Asparagus racemosus possess inhibitory effects against ovarian cancer proliferation receptor POTEE.

Structure-Based Virtual Screening, Molecular Docking, and Molecular Dynamics Simulation of VEGF inhibitors for the clinical treatment of Ovarian Cancer

Vascular endothelial growth factor (VEGF) and its receptor play an important role both in physiologic and pathologic angiogenesis, which is identified in ovarian cancer progression and metastasis development. The aim of the present investigation is to identify a potential vascular endothelial growth factor inhibitor which is playing a crucial role in stimulating the immunosuppressive microenvironment in tumor cells of the ovary and to examine the effectiveness of the identified inhibitor for the treatment of ovarian cancer using various in silico approaches. Twelve established VEGF inhibitors were collected from various literatures. The compound AEE788 displays great affinity towards the target protein as a result of docking study. AEE788 was further used for structure-based virtual screening in order to obtain a more structurally similar compound with high affinity. Among the 80 virtual screened compounds, CID 88265020 explicates much better affinity than the established compound AEE788. Based on molecular dynamics simulation, pharmacophore and comparative toxicity analysis of both the best established compound and the best virtual screened compound displayed a trivial variation in associated properties. The virtual screened compound CID 88265020 has a high affinity with the lowest re-rank score and holds a huge potential to inhibit the VGFR and can be implemented for prospective future investigations in ovarian cancer.