The enigmatic in ovarian cancer is that in nearly 75% of patients, cancer do recurse during first two years and fail to respond to available therapeutic drugs due to acquired resistance62,63 in addition to late diagnosis in advanced clinical stages and metastasis within the peritoneal cavity63,64. Therefore, there is immediate need to design novel drugs to deal with the existing problem.Numerous studies since a decade has reported that Flavinoids as candidates are meant to block, retard, or reverse the progression of carcinogenesis80. Although various studies have been carried out using flavinoids but the anticancer mechanisms have not been defined clearly. However, it was found that the flavonoids such as quercetin and silymarin induce anti-cancer mechanisms in ovarian cancer cells65,66. Consequently, the effects of apigenin, luteolin and myricetin on ovarian cancer have to uncover the link between potential mechanisms underlying their anticancer effects. Quercetin inhibits cell proliferation of ovarian cancer cell line of SKOV-3 which correlated with findings of67 caused on concentration and time-dependent manner68 showed to inhibit UVB induced skin cancer cell proliferation and induce apoptosis in vivo models upon apigenin treatment. Taxifolin invitro studies have been efficient especially in anticancer, antimicrobial activities but leaves a strong gap in the invivo studies at root level.
The lead compound in the current study was recognised as taxifolin which has potent to exhibit anti-cancer effects on U2OS and Saos-2 in osteosarcoma cell lines by inhibiting the proliferation and disrupting colony formation. In vivo studies exhibit intraperitoneal administration in nude mice bearing U2OS xenograft that resists tumor growth. This potency is known to arrest the G1 phase of the cell cycle in U2OS and Saos-2 cell lines. Taxifolin has known to function by inhibiting colon carcinogenesis by NF-kB mediated Wnt/b catenin signalling through upregulation of Nrf2 pathway while downregulation in genes such as TNF-α, COX-2, β-catenin, and cyclin-D1 were inhibited by NF-kB and Wnt signalling pathway69. It is also reported that injection of taxifolin has reduced the proliferative activity on wistar rats with benign prostatic hyperplasia70. Taxifolin also has an excellent report on antiangiogenic effect by new blood vessels and its branches per area of chick chorioallantoic membrane assay which is inhibited by tube formation on matrigel matrix in human umbilical vein of endothelial cells which were evaluated against tachyzoites in vitro with IC50 of 1.39µg/mL(p ≤ 0.05) along with pyrimethamine. Taxifolin has known to express anti-proliferative effect on cancer cell types by inhibiting cell lipogenesis and inhibits the fatty acid synthesis in cancer cell lines which is able to prevent the growth of cancer cells79.
An extensive animal (rat) study of antioxidant activity on taxifolin acid has shown the decreased lipid peroxidation in the serum and liver levels. The presence of OH groups at position 5th and 7th together with 4-OXO function in the A and C rings were meant for scavenging effect while O-dihydroxy group in the B ring provided stability71. Consequently, In vivo studies on taxifolin induced in apoptosis of HCT116 and HT 29 cells revealed PARP1 over expression is responsible for ovarian cancer. AKT and catenin proved that down-regulated expression by taxifolin on HCT 116 and HT 29 cells demonstrates a decline in p-AKT and catenin in a dose of 40 µM against DMSO altering in G2 cell cycle and its regulators72. The expression levels of AKT, SKP-2, v-mc avian myelocytomatosis viral oncogene homolog(c-myc) and p-Ser473, have reduced activity on AKT gene by taxifolin73. Although the above mentioned experimental outcomes have contributed for diversified pharmacological activities with AKT1 protein, we still lack the detailed and molecular changes wrt to W80R mutant protein of AKT1 family. Consequently, the marginal overview of the molecular mechanism and atomic level with W80R mutation has aimed to identify hits for optimization from large data set of compounds from the PubChem database screening of flavonoids in parallel to W80R mutant protein of AKT1 targeting ovarian cancer. The Table 1 for the receptor molecule W80R of 480 amino acid sequence provides the detailed knowledge about the stability of protein using Protoparam tools of Expasy server. The extensive evaluation on W80R sequence at nucleotide level reveals its density, while other parameters such as A-T,C-G rich region, molecular weight, amino acid composition, theoretical pI, aliphatic index, instability index and GRAVY significantly stand up for stability factor. The most favoured region by RAMPAGE server was assessed to be 79.3% (Table 2) with active site binding. Furthermore, the reliability of the protein model has been assessed by 3D or homology modelling. Therefore, Generation of 3D protein structure from sequence information, in the absence of experimentally determined structures in protein data bank through computational approaches has become topmost priority in the scientific community based on structural biology research for several decades74,75,76. The protein was henceforth evaluated with SAVES server (structural analysis and verification) for quality check, structural refinement through energy minimization in lowest energy state in its stable conformation, followed by ProSA (Fig. 1) and superimposition analysis with experimentally determined template structure as well as atoms and RMSD assessment to obtained a high -quality structural model for virtual screening77. The predicted score for 3D homology model of RMSD for the W80R protein was 0.18, the model was considered as the best one for further validation purposes.3D QSAR studies have been performed with structural similarity to predict the unknown/untested ligands for better potency by correlating mathematical and statistical values. QSAR models can prioritize ideas in virtual screening as well in the optimization of lead compounds. Thus it has gained acceptance in in-silco drug discovery. The scatter plot QSAR tool (Fig. 2) assessed the molecular fields for the compounds which estimate the stability and establish statistical value to be 0.379 predicting the changes obtained in the training set composition with 92.7 measured higher F indicates more statistical significant regression. The dataset of 44 ligands was classified into test and training models randomly with combined mathematical and statistical approaches for the drug candidate represents phase activity of 358.477% extrapolated for 0.458 with the predicted activity of 333.692 and predicted error of -24.7856 which was a good combination as a lead compound (Table 6). As per Lipinski's rule of five, a drug is good molecule if it possesses ADME (absorption, distribution, metabolism, and excretion) properties43. All the physicochemical properties and drug-likeness were listed in Table 3, 4 and 5consequently; it becomes easy for the lead compound to enter the mammalian cell to interact with proteins and regulating gene expression in metabolic pathways. The top 10 hits obtained by molecular docking were further docked into the active binding sites of protein using a sitemap tool of above score 1 and grid generation followed by XP protocol (Table 7). However, a contour map is one such tool used in the present study to determine favourable regions based on field-based QSAR which depends on steric, electrostatic, hydrophobicity in solvent-accessible pockets based on least binding energy. This application plays a vital role in combination therapies of multi-drug-resistant conditions as well in drug discovery.
The evaluated hydrophobicity gives an accurate check for the drug-ability of a compound (Fig. 3). Sitemap tool treats entire protein to locate binding sites whose size, the extent of solvent exposure is assessed based on scoring function by ranks. Active sites are ranked based on ligand propensity of binding measured by their ability to bind tightly for passively absorbed small molecules. Among the predicted combinations, active site amino acid residues of site score 1.128, drug-ability score − 1.149, volume 384.486, and size 179 (Fig. 4) were taken for further analysis. Taxifolin holds good interactions with the binding domain of W80R, highest Glide score of -9.63kcal/mol with O-H of SER 208 and H bond GLU 198 and THR 211 amino acid residues and one pi-cation interaction and one hydrophobic bond with LYS 268 (Fig. 5). The lead molecule satisfied all the surface area calculations using QIKPROP tool of SASA, FISA,FOSA, PSA and partition coefficient of Qplogpoct, QPlogPw, QPlogPo, QPlogS, ClQPlog, QPlogHER, QPPCaco, QPPMDCK, QPlogKp, wherefore, this inhibitor of the PI3K/AKT pathway has shown diverse aptitudes for anticancer activity in both preclinical and clinical experimental values and also supported through in-silico analysis.
It has been reported by the administration of taxifolin in colorectal cancer cell lines and in HCT 116 xenograft mouse model had shown excellent antitumor activity. The studies proved that the administration of taxifolin hindered the mRNA expression of β-catenin thus compiling anti-proliferative activity which was arbitrated by PI3K/AKT signal by jamming Wnt/ β –catenin signaling transduction through hampering the β expression72. The elucidation of suppression by taxifolin on nuclear factor-kB, C-Fos, and mitogen-activated protein kinase also decreased osteoclast specific gene expression including Trap, Mmp-9, Cathepsin K, C-Fos, Nfatc1, and Rank; taxifolin osteoclastogenesis via regulation of many RANKL signaling pathways was also confirmed78,79. Taken together, these studies demonstrated that Wnt/catenin pathway plays a crucial role in ovarian cancer development and this idea also laid a strong platform for the development of targeted curatives.
CID- 44264122 with 2 hydrogen bonds of a hydroxyl group (-OH) interacting with LYS268, THR291, ILE290, and THR211 and ILE290 and –OH with THR 291 and oxy bond with residue LYS 268 (Fig. 6) with Glide XP score − 9.43Kcal/mol. The hydrogen bond interaction with residues of TYR474, SER215, THR211, with 1 pi-pi interaction at TRP80 residue, and 1 pi-cationic interaction bonding with LYS265 with G score − 9.36Kcal/mol showed good hydrophobic interactions (Fig. 7). The molecular dynamics simulation was performed to obtain lowest error and data loss. The fluctuations in relative positions of atoms in protein-ligand complex explains the structural stability (RMSD) at 0.45nm to 0.50nm between 600 to 800ps (Fig. 8a). The RMSF has shown a steep up graph at 5A with a slight medial deviation and not much structural change in protein cavity was observed80,81,82 (Fig. 8b). Residue interaction network (RINs) consider single amino acid as nodes and physio-chemical interactions as edges (Fig. 9) representing the protein structure as RINs have become common practice to explore the complexity inherent in macromolecular systems. Henceforth, the taxifolin has been suggested as a drug for human use in clinical trials.