RESUMO
P2 receptors are a family of transmembrane receptors activated by nucleotides and nucleosides. Two classes have been described in mammals, P2X and P2Y, which are implicated in various diseases. Currently, only P2Y12 has medicines approved for clinical use as antiplatelet agents and natural products have emerged as a source of new drugs with action on P2 receptors due to the diversity of chemical structures. In drug discovery, in silico virtual screening (VS) techniques have become popular because they have numerous advantages, which include the evaluation of thousands of molecules against a target, usually proteins, faster and cheaper than classical high throughput screening (HTS). The number of studies using VS techniques has been growing in recent years and has led to the discovery of new molecules of natural origin with action on different P2X and P2Y receptors. Using different algorithms it is possible to obtain information on absorption, distribution, metabolism, toxicity, as well as predictions on biological activity and the lead-likeness of the selected hits. Selected biomolecules may then be tested by molecular dynamics and, if necessary, rationally designed or modified to improve their interaction for the target. The algorithms of these in silico tools are being improved to permit the precision development of new drugs and, in the future, this process will take the front of drug development against some central nervous system (CNS) disorders. Therefore, this review discusses the methodologies of in silico tools concerning P2 receptors, as well as future perspectives and discoveries, such as the employment of artificial intelligence in drug discovery.
RESUMO
The southern muriqui (Brachyteles arachnoides) is the largest neotropical primate. This species is endemic to Brazil and is currently critically endangered due to its habitat destruction. The genetic basis underlying adaptive traits of New World monkeys has been a subject of interest to several investigators, with significant concern about genes related to the immune system. In the absence of a reference genome, RNA-seq and de novo transcriptome assembly have proved to be valuable genetic procedures for accessing gene sequences and testing evolutionary hypotheses. We present here a first report on the sequencing, assembly, annotation and adaptive selection analysis for thousands of transcripts of B. arachnoides from two different samples, corresponding to 13 different blood cells and fibroblasts. We assembled 284,283 transcripts with N50 of 2,940 bp, with a high rate of complete transcripts, with a median high scoring pair coverage of 88.2%, including low expressed transcripts, accounting for 72.3% of complete BUSCOs. We could predict and extract 81,400 coding sequences with 79.8% of significant BLAST hit against the Euarchontoglires SwissProt dataset. Of these 64,929 sequences, 34,084 were considered homologous to Supraprimate proteins, and of the remaining sequences (30,845), 94% were associated with a protein domain or a KEGG Orthology group, indicating potentially novel or specific protein-coding genes of B. arachnoides. We use the predicted protein sequences to perform a comparative analysis with 10 other primates. This analysis revealed, for the first time in an Atelid species, an expansion of APOBEC3G, extending this knowledge to all NWM families. Using a branch-site model, we searched for evidence of positive selection in 4,533 orthologous sets. This evolutionary analysis revealed 132 amino acid sites in 30 genes potentially evolving under positive selection, shedding light on primate genome evolution. These genes belonged to a wide variety of categories, including those encoding the innate immune system proteins (APOBEC3G, OAS2, and CEACAM1) among others related to the immune response. This work generated a set of thousands of complete sequences that can be used in other studies on molecular evolution and may help to unveil the evolution of primate genes. Still, further functional studies are required to provide an understanding of the underlying evolutionary forces modeling the primate genome.
