Development and application of ribonucleic acid therapy strategies against COVID-19

Lin, Ning; Liu, Mujiexin; Gou, Yushu; Yang, Yue; He, Bifang; Huang, Jian

doi:10.7150/ijbs.72706

Cited by 20 publications

(13 citation statements)

References 189 publications

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“…Selecting the feature encodings that are useful and autonomous is a key stage in establishing machine learning-based models (Lv et al, 2021 ; Zhang D. et al, 2021 ; Ao et al, 2022a ; Li et al, 2022a ; Ning et al, 2022 ; Teng et al, 2022 ; Wei et al, 2022 ). Representing the DNA sequences with a mathematical manifestation is very important in functional element identification.…”

Section: Methodsmentioning

confidence: 99%

Computational prediction of promotors in Agrobacterium tumefaciens strain C58 by using the machine learning technique

et al. 2023

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Promotors are those genomic regions on the upstream of genes, which are bound by RNA polymerase for starting gene transcription. Because it is the most critical element of gene expression, the recognition of promoters is crucial to understand the regulation of gene expression. This study aimed to develop a machine learning-based model to predict promotors in Agrobacterium tumefaciens (A. tumefaciens) strain C58. In the model, promotor sequences were encoded by three different kinds of feature descriptors, namely, accumulated nucleotide frequency, k-mer nucleotide composition, and binary encodings. The obtained features were optimized by using correlation and the mRMR-based algorithm. These optimized features were inputted into a random forest (RF) classifier to discriminate promotor sequences from non-promotor sequences in A. tumefaciens strain C58. The examination of 10-fold cross-validation showed that the proposed model could yield an overall accuracy of 0.837. This model will provide help for the study of promoters in A. tumefaciens C58 strain.

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Section: Methodsmentioning

confidence: 99%

Computational prediction of promotors in Agrobacterium tumefaciens strain C58 by using the machine learning technique

et al. 2023

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“…There are several aptamer drugs in clinical trial towards different types of tumors and other diseases. Aptamers have also been applied to inhibit SARS virus and the diagnosis of COVID-19 by targeting antigenic viral proteins [ 45 ].…”

Section: Noncoding Rnas In Approved and Emerging Nucleic Acid Drugsmentioning

confidence: 99%

“…The simple structure, negligible toxicity, site-specific cleavage activity and recyclable catalytic potential of ribozymes benefit their effective modulation of gene expression. Several ribozymes have already been tested in clinical trials for solid tumors, HIV, SARS and other disease [ 45 , 47 ]. However, it is challenging due to the new mutations in the conserved target region and RNase degradation.…”

Section: Noncoding Rnas In Approved and Emerging Nucleic Acid Drugsmentioning

confidence: 99%

“…In addition, a RNA editing CRISPR-Cas system, CRISPR-Cas13, has also been developed, which has a higher safety profile than CRISPR-Cas9 [ 47 ]. Recently, the CRISPR-Cas13-based system named PAC-MAN (prophylactic antiviral CRISPR in human cells) has been used in the treatment of SARS-CoV-2 [ 45 ]. More advanced RNA editing platforms that can elicit ADAR-mediated RNA editing, have been engineered in humans, namely CIRTS, RESCUE, RESTORE and LEAPER [ 49 ].…”

Section: Noncoding Rnas In Approved and Emerging Nucleic Acid Drugsmentioning

confidence: 99%

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Noncoding RNAs Emerging as Drugs or Drug Targets: Their Chemical Modification, Bio-Conjugation and Intracellular Regulation

Wang

Tian

et al. 2022

Molecules

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With the increasing understanding of various disease-related noncoding RNAs, ncRNAs are emerging as novel drugs and drug targets. Nucleic acid drugs based on different types of noncoding RNAs have been designed and tested. Chemical modification has been applied to noncoding RNAs such as siRNA or miRNA to increase the resistance to degradation with minimum influence on their biological function. Chemical biological methods have also been developed to regulate relevant noncoding RNAs in the occurrence of various diseases. New strategies such as designing ribonuclease targeting chimeras to degrade endogenous noncoding RNAs are emerging as promising approaches to regulate gene expressions, serving as next-generation drugs. This review summarized the current state of noncoding RNA-based theranostics, major chemical modifications of noncoding RNAs to develop nucleic acid drugs, conjugation of RNA with different functional biomolecules as well as design and screening of potential molecules to regulate the expression or activity of endogenous noncoding RNAs for drug development. Finally, strategies of improving the delivery of noncoding RNAs are discussed.

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“…Peptide nucleic acids (PNAs) were introduced in 1991 as nucleic acid analogues composed of a 2-aminoethylglycine backbone that replaces the sugar phosphate backbone and a base covalently bonded through a carboxymethyl linker (Figure ). − …”

Section: Introductionmentioning

confidence: 99%

Parameterization of the miniPEG-Modified γPNA Backbone: Toward Induced γPNA Duplex Dissociation

Tamez

Nilsson

Mihailescu

et al. 2023

J. Chem. Theory Comput.

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γ-Modified peptide nucleic acids (γPNAs) serve as potential therapeutic agents against genetic diseases. Miniature poly(ethylene glycol) (miniPEG) has been reported to increase solubility and binding affinity toward genetic targets, yet details of γPNA structure and dynamics are not understood. Within our work, we parameterized missing torsional and electrostatic terms for the miniPEG substituent on the γ-carbon atom of the γPNA backbone in the CHARMM force field. Microsecond timescale molecular dynamics simulations were carried out on six miniPEG-modified γPNA duplexes from NMR structures (PDB ID: 2KVJ). Three NMR models for the γPNA duplex (PDB ID: 2KVJ) were simulated as a reference for structural and dynamic changes captured for the miniPEG-modified γPNA duplex. Principal component analysis performed on the γPNA backbone atoms identified a single isotropic conformational substate (CS) for the NMR simulations, whereas four anisotropic CSs were identified for the ensemble of miniPEG-modified γPNA simulations. The NMR structures were found to have a 23°helical bend toward the major groove, consistent with our simulated CS structure of 19.0°. However, a significant difference between simulated methyl-and miniPEG-modified γPNAs involved the opportunistic invasion of miniPEG through the minor and major groves. Specifically, hydrogen bond fractional analysis showed that the invasion was particularly prone to affect the second G−C base pair, reducing the Watson−Crick base pair hydrogen bond by 60% over the six simulations, whereas the A−T base pairs decreased by only 20%. Ultimately, the invasion led to base stack reshuffling, where the well-ordered base stacking was reduced to segmented nucleobase stacking interactions. Our 6 μs timescale simulations indicate that duplex dissociation suggests the onset toward γPNA single strands, consistent with the experimental observation of decreased aggregation. To complement the insight of miniPEG-modified γPNA structure and dynamics, the new miniPEG force field parameters allow for further exploration of such modified γPNA single strands as potential therapeutic agents against genetic diseases.

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Development and application of ribonucleic acid therapy strategies against COVID-19

Cited by 20 publications

References 189 publications

Computational prediction of promotors in Agrobacterium tumefaciens strain C58 by using the machine learning technique

Computational prediction of promotors in Agrobacterium tumefaciens strain C58 by using the machine learning technique

Noncoding RNAs Emerging as Drugs or Drug Targets: Their Chemical Modification, Bio-Conjugation and Intracellular Regulation

Parameterization of the miniPEG-Modified γPNA Backbone: Toward Induced γPNA Duplex Dissociation

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