RESUMO
Gastric cancer (GC) is a highly heterogeneous, complex disease and the fifth most common cancer worldwide (about 1 million cases and 784,000 deaths worldwide in 2018). GC has a poor prognosis (the 5-year survival rate is less than 20%), but there is an effort to find genes highly expressed during tumor establishment and use the related proteins as targets to find new anticancer molecules. Data were collected from the Gene Expression Omnibus (GEO) bank to obtain three dataset matrices analyzing gastric tumor tissue versus normal gastric tissue and involving microarray analysis performed using the GPL570 platform and different sources. The data were analyzed using the GEPIA tool for differential expression and KMPlot for survival analysis. For more robustness, GC data from the TCGA database were used to corroborate the analysis of data from GEO. The genes found in in silico analysis in both GEO and TCGA were confirmed in several lines of GC cells by RT-qPCR. The AlphaFold Protein Structure Database was used to find the corresponding proteins. Then, a structure-based virtual screening was performed to find molecules, and docking analysis was performed using the DockThor server. Our in silico and RT-qPCR analysis results confirmed the high expression of the AJUBA, CD80 and NOLC1 genes in GC lines. Thus, the corresponding proteins were used in SBVS analysis. There were three molecules, one molecule for each target, MCULE-2386589557-0-6, MCULE-9178344200-0-1 and MCULE-5881513100-0-29. All molecules had 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 for finding genes involved in GC and working with the corresponding proteins to search for new molecules with anticancer properties.
RESUMO
Due to the excessive and inappropriate use of antibiotics in farming and clinic, pathogens developed resistance mechanisms to currently used drugs. Thus, because of this resistance, drugs become ineffective, leading to public health problems worldwide. According to the World Health Organization (WHO), microbial resistance to drugs is one of the most threats that humanity must face. Therefore, it is imperative to seek alternative methods to overcome microbial resistance. Here, the potential of natural or synthetic antimicrobial peptides to overcome microbial resistance will be discussed, and how peptides could be a source for new therapeutics molecules. In this context, antimicrobial peptides (natural or synthetic) are considered promising molecules based on their antifungal, antiviral, and antibacterial properties, making them eligible for developing new drugs. In addition, they can act synergistically with existing drugs on the market, revealing a broad spectrum of applications.