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The nucleocapsid protein of SARS-CoV-2 plays significant roles in viral assembly, immune evasion, and viral stability. Due to its immunogenicity, high expression levels during COVID-19, and conservation across viral strains, it represents an attractive target for antiviral treatment. In this study, we identified and characterized a single-stranded DNA aptamer, N-Apt17, which effectively disrupts the liquid-liquid phase separation (LLPS) mediated by the N protein. To enhance the aptamer's stability, a circular bivalent form, cb-N-Apt17, was designed and evaluated. Our findings demonstrated that cb-N-Apt17 exhibited improved stability, enhanced binding affinity, and superior inhibition of N protein LLPS; thus, it has the potential inhibition ability on viral replication. These results provide valuable evidence supporting the potential of cb-N-Apt17 as a promising candidate for the development of antiviral therapies against COVID-19.IMPORTANCEVariants of SARS-CoV-2 pose a significant challenge to currently available COVID-19 vaccines and therapies due to the rapid epitope changes observed in the viral spike protein. However, the nucleocapsid (N) protein of SARS-CoV-2, a highly conserved structural protein, offers promising potential as a target for inhibiting viral replication. The N protein forms complexes with genomic RNA, interacts with other viral structural proteins during virion assembly, and plays a critical role in evading host innate immunity by impairing interferon production during viral infection. In this investigation, we discovered a single-stranded DNA aptamer, designated as N-Apt17, exhibiting remarkable affinity and specificity for the N protein. Notably, N-Apt17 disrupts the liquid-liquid phase separation (LLPS) of the N protein. To enhance the stability and molecular recognition capabilities of N-Apt17, we designed a circular bivalent DNA aptamer termed cb-N-Apt17. In both in vivo and in vitro experiments, cb-N-Apt17 exhibited increased stability, enhanced binding affinity, and superior LLPS disrupting ability. Thus, our study provides essential proof-of-principle evidence supporting the further development of cb-N-Apt17 as a therapeutic candidate for COVID-19., Competing Interests: The authors declare no conflict of interest.

Background: Tumor Necrosis Factor-α (TNF-α) is a pro-inflammatory factor that plays a pivotal role in psoriasis. Due to limitations of monoclonal antibody-based therapies, it is needed to discover new anti-TNF-α factors instead of usual anti-TNF-α monoclonal antibodies. Compared to antibodies, single-stranded DNA or RNA molecules named aptamers, have advantages such as time-saving, less risk for immunogenicity and cost-effectiveness. Therefore, the aim of the present study was to assess the therapeutic effects of T1-T4 dimer anti-TNF-ɑ ssDNA aptamer topical treatment in the imiquimod (IMQ)-induced psoriasis animal model., Methods: 5% IMQ cream was prescribed on the right ear of BALB/c to induce psoriasis model. The hydrogel-containing anti-TNF-ɑ aptamer or treatment control aptamer (anti- Interleukin (IL)17A) was topically prescribed to the mice's ears 10 min before IMQ cream treatment. The psoriasis area severity index (PASI) score was used to evaluate psoriasis intensity. Histopathology analysis was done for mice ears sections. Mass, size, and cell number of mice spleens were measured. The IL-17 level was determined in culture supernatants of axillary lymph node cells using ELISA. The mRNA expression levels of IL-17A, IL-1β, STAT3, and S100a9, were evaluated in mice treated ear with quantitative Real Time-PCR., Results: The anti-TNF-ɑ ssDNA aptamer lower doses had significant decrease in IMQ-induced PASI score (p < 0.05). In addition, in these groups, the IL-17A, STAT3, and S100a9 mRNA levels were significantly lower than the IMQ group (p < 0.05)., Conclusion: According to our findings, this aptamer seems to be a prospective candidate for treating psoriatic inflammation especially in lower concentrations., Competing Interests: Declaration of Competing Interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2023 Elsevier Ltd. All rights reserved.)

This study was planned to in silico screening of ssDNA aptamer against Escherichia coli O157:H7 by combination of machine learning and the PseKNC approach. For this, firstly a total numbers of 47 validated ssDNA aptamers as well as 498 random DNA sequences were considered as positive and negative training data respectively. The sequences then converted to numerical vectors using PseKNC method through Pse-in-one 2.0 web server. After that, the numerical vectors were subjected to classification by the SVM, ANN and RF algorithms available in Orange 3.2.0 software. The performances of the tested models were evaluated using cross-validation, random sampling and ROC curve analyzes. The primary results demonstrated that the ANN and RF algorithms have appropriate performances for the data classification. To improve the performances of mentioned classifiers the positive training data was triplicated and re-training process was also performed. The results confirmed that data size improvement had significant effect on the accuracy of data classification especially about RF model. Subsequently, the RF algorithm with accuracy of 98% was selected for aptamer screening. The thermodynamics details of folding process as well as secondary structures of the screened aptamers were also considered as final evaluations. The results confirmed that the selected aptamers by the proposed method had appropriate structure properties and there is no thermodynamics limit for the aptamers folding., (Copyright © 2021. Published by Elsevier Ltd.)