Cell delivery peptides for small interfering RNAs targeting SARS-CoV-2 new variants through a bioinformatics and deep learning design
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Abstract
Nucleic acid technologies with designed delivery systems have surged as one the most promising therapies of the future, due to their contribution in combating SARS-CoV-2 severe disease. Nevertheless, the emergence of new variants of concern still represents a real threat in the years to come. It is here that the use of small interfering RNA sequences to inhibit gene expression and, thus, protein synthesis, may complement the already developed vaccines, with faster design and production. Here, we have designed new sequences targeting COVID-19 variants and other related viral diseases through bioinformatics, while also addressing the limited number of delivery peptides by a deep learning approach. Two sequences databases were produced, from which 62 were able to target the virus mRNA, and ten displayed properties present in delivery peptides, which we compared to the broad use TAT delivery peptide.
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SciScore for 10.1101/2022.02.09.479755: (What is this?)
Please note, not all rigor criteria are appropriate for all manuscripts.
Table 1: Rigor
NIH rigor criteria are not applicable to paper type.Table 2: Resources
Software and Algorithms Sentences Resources To do that, we retrieved the following genomes in FASTA format: 1) the human genome, coding and non-coding transcriptome (GRCh38, from NCBI and ENSEMBL, respectively); 2) the reference genomes of SARS-CoV-2 (NC_045512.2), SARS-CoV (NC_004718.3), MERS-CoV (NC_038294.1), and influenza (GCF_001343785.1); and 3) different SARS-CoV-2 variants (original 2019 variant and the currently dominant Delta and Omicron) from USA (Texas, California and New York), Brazil, Portugal, Spain, England, Germany, Russia, China (without Wuhan), and Wuhan strains, obtained from the Global Initiative on Sharing … SciScore for 10.1101/2022.02.09.479755: (What is this?)
Please note, not all rigor criteria are appropriate for all manuscripts.
Table 1: Rigor
NIH rigor criteria are not applicable to paper type.Table 2: Resources
Software and Algorithms Sentences Resources To do that, we retrieved the following genomes in FASTA format: 1) the human genome, coding and non-coding transcriptome (GRCh38, from NCBI and ENSEMBL, respectively); 2) the reference genomes of SARS-CoV-2 (NC_045512.2), SARS-CoV (NC_004718.3), MERS-CoV (NC_038294.1), and influenza (GCF_001343785.1); and 3) different SARS-CoV-2 variants (original 2019 variant and the currently dominant Delta and Omicron) from USA (Texas, California and New York), Brazil, Portugal, Spain, England, Germany, Russia, China (without Wuhan), and Wuhan strains, obtained from the Global Initiative on Sharing Avian Influenza Data (GISAID) [14]. NCBIsuggested: (NCBI, RRID:SCR_006472)ENSEMBLsuggested: (Ensembl, RRID:SCR_002344)Alignment to those genomes was performed using the short-reads aligner Bowtie v1.1.0 [15], reporting all valid alignments per read, with the following parameters: maximum number of attempts to match an alignment = 4, and maximum number of mismatches in the “seed” = 3, with “seed” length = 7. Bowtiesuggested: (Bowtie, RRID:SCR_005476)Results from OddPub: We did not detect open data. We also did not detect open code. Researchers are encouraged to share open data when possible (see Nature blog).
Results from LimitationRecognizer: An explicit section about the limitations of the techniques employed in this study was not found. We encourage authors to address study limitations.Results from TrialIdentifier: No clinical trial numbers were referenced.
Results from Barzooka: We did not find any issues relating to the usage of bar graphs.
Results from JetFighter: We did not find any issues relating to colormaps.
Results from rtransparent:- Thank you for including a conflict of interest statement. Authors are encouraged to include this statement when submitting to a journal.
- Thank you for including a funding statement. Authors are encouraged to include this statement when submitting to a journal.
- No protocol registration statement was detected.
Results from scite Reference Check: We found no unreliable references.
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