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Therapeutic perceptions in antisense RNA-mediated gene regulation for COVID-19.
de Jesus, Sabrina Ferreira; Santos, Laércio Ives; Rodrigues Neto, João Felício; Vieira, Thallyta Maria; Mendes, João Batista; D'angelo, Marcos Flavio Silveira Vasconcelos; Guimaraes, André Luiz Sena.
Afiliação
  • de Jesus SF; Department of Dentistry, State Universit of Montes Claros, Brazil.
  • Santos LI; Instituto Federal do Norte de Minas Gerais, Montes Claros Minas Gerais, Brazil; Department of Computer Science, Universidade Estadual de Montes Claros, Montes Claros Minas Gerais, Brazil.
  • Rodrigues Neto JF; Departament of Medicine, Universidade Estadual de Montes Claros, Montes Claros Minas Gerais, Brazil.
  • Vieira TM; Departament of Biology, Universidade Estadual de Montes Claros, Montes Claros Minas Gerais, Brazil.
  • Mendes JB; Department of Computer Science, Universidade Estadual de Montes Claros, Montes Claros Minas Gerais, Brazil.
  • D'angelo MFSV; Department of Computer Science, Universidade Estadual de Montes Claros, Montes Claros Minas Gerais, Brazil. Electronic address: marcos.dangelo@unimontes.br.
  • Guimaraes ALS; Departament of Medicine, Universidade Estadual de Montes Claros, Montes Claros Minas Gerais, Brazil. Electronic address: andreluizguimaraes@gmail.com.
Gene ; 800: 145839, 2021 Oct 20.
Article em En | MEDLINE | ID: mdl-34274470
COVID-19 was first reported in Wuhan, China, in December 2019. It is widely accepted that the world will not return to its prepandemic normality until safe and effective vaccines are available and a global vaccination program has been successfully implemented. Antisense RNAs are single-stranded RNAs that occur naturally or are synthetic and enable hybridizing and protein-blocking translation. Therefore, the main objective of this study was to identify target markers in the RNA of the severe acute respiratory syndrome coronavirus, or SARS-CoV-2, with a length between 21 and 28 bases that could enable the development of vaccines and therapies based on antisense RNA. We used a search algorithm in C language to compare 3159 complete nucleotide sequences from SARS-CoV-2 downloaded from the repository of the National Center for Biotechnology Information. The objective was to verify whether any common sequences were present in all 3159 strains of SARS-CoV-2. In the first of three datasets (SARS-CoV-2), the algorithm found two sequences each of 21 nucleotides (Sequence 1: CTACTGAAGCCTTTGAAAAAA; Sequence 2: TGTGGTTATACCTACTAAAAA). In the second dataset (SARS-CoV) and third dataset (MERS-CoV), no sequences of size N between 21 and 28 were found. Sequence 1 and Sequence 2 were input into BLAST® ≫ blastn and recognized by the platform. The gene identified by the sequences found by the algorithm was the ORF1ab region of SARS-CoV-2. Considerable progress in antisense RNA research has been made in recent years, and great achievements in the application of antisense RNA have been observed. However, many mechanisms of antisense RNA are not yet understood. Thus, more time and money must be invested into the development of therapies for gene regulation mediated by antisense RNA to treat COVID-19 as no effective therapy for this disease has yet been found.
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Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: RNA Antissenso / SARS-CoV-2 / COVID-19 Limite: Humans Idioma: En Revista: Gene Ano de publicação: 2021 Tipo de documento: Article

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: RNA Antissenso / SARS-CoV-2 / COVID-19 Limite: Humans Idioma: En Revista: Gene Ano de publicação: 2021 Tipo de documento: Article