Brito, D.M.S.; Lima, O.G.; Mesquita, F.P.; da Silva, E.L.; de Moraes, M.E.A.; Burbano, R.M.R.; Montenegro, R.C.; Souza, P.F.N. A Shortcut from Genome to Drug: The Employment of Bioinformatic Tools to Find New Targets for Gastric Cancer Treatment. Pharmaceutics2023, 15, 2303.
Brito, D.M.S.; Lima, O.G.; Mesquita, F.P.; da Silva, E.L.; de Moraes, M.E.A.; Burbano, R.M.R.; Montenegro, R.C.; Souza, P.F.N. A Shortcut from Genome to Drug: The Employment of Bioinformatic Tools to Find New Targets for Gastric Cancer Treatment. Pharmaceutics 2023, 15, 2303.
Brito, D.M.S.; Lima, O.G.; Mesquita, F.P.; da Silva, E.L.; de Moraes, M.E.A.; Burbano, R.M.R.; Montenegro, R.C.; Souza, P.F.N. A Shortcut from Genome to Drug: The Employment of Bioinformatic Tools to Find New Targets for Gastric Cancer Treatment. Pharmaceutics2023, 15, 2303.
Brito, D.M.S.; Lima, O.G.; Mesquita, F.P.; da Silva, E.L.; de Moraes, M.E.A.; Burbano, R.M.R.; Montenegro, R.C.; Souza, P.F.N. A Shortcut from Genome to Drug: The Employment of Bioinformatic Tools to Find New Targets for Gastric Cancer Treatment. Pharmaceutics 2023, 15, 2303.
Abstract
Gastric cancer (GC) is a highly heterogeneous, complex disease and the fifth most common cancer worldwide (about one million cases and 784 000 deaths worldwide in 2018). CG is lately diagnosed and guarantees a poor prognosis for GC (the 5-year survival rate is less than 20%, but in early detection can reach 90%). This study evaluated the transcriptional profile in tumor gastric samples to find genes highly expressed during tumor establishment and use the related proteins as targets to find new anticancer molecules. Data was collected at Gene Expression Omnibus (GEO) bank to obtain 3 dataset matrices that analyze gastric tumor tissue versus normal gastric tissue, performed microarray using GPL570 platform, and from different sources. The genes found in silico analysis were confirmed in several lines of GC cells by RT-qPCR. The protein data bank was used to find the correspondent proteins. Then a structural-based virtual screening was done to find molecules, and docking analysis was done using the DockThor server. Our results of transcriptomic analysis, together with RT-qPCR, confirm the high expression of the genes AJUBA, FBXL13, CCDC69, CD80 and NOLC1 in GC lines. Based on that, the correspondent proteins were used in SBVS analysis. Five molecules, one each target, MCULE-2386589557-0-6, MCULE-7343047040-0-1, MCULE-5230409338-0-3, MCULE-9178344200-0-1 and MCULE -5881513100-0-29. All molecules have favorable pharmacokinetic, pharmacodynamic and toxicological properties. Molecular docking analysis revealed that the molecules interact with proteins in critical sites for their activity. Using a virtual screening approach, a molecular docking study was performed for proteins encoded by genes that play important roles in cellular functions for carcinogenesis. Combining a systematic collection of public microarray data with a comparative meta-profiling, RT-qPCR, SBVS, and molecular docking analysis provided a suitable approach to find genes involved in GC and work the correspondent protein to strive for new molecules with anticancer properties.
Biology and Life Sciences, Biochemistry and Molecular Biology
Copyright:
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
,
,
*
