A Therapeutic Approach Against Leishmania donovani by Predicting RNAi Molecules Against the Surface Protein, gp63

Chemically Cross-Linked Hammerhead Ribozyme as an Efficient RNA Interference Tool

RNA-cleaving ribozymes are promising candidates as general tools of RNA interference (RNAi) in gene manipulation. However, compared with other RNA systems, such as siRNA and CRISPR technologies, the ribozyme tools are still far from broad applications on RNAi due to their poor performance in the cellular context. In this work, we report an efficient RNAi tool based on chemically modified hammerhead ribozyme (HHR). By the introduction of an intramolecular linkage into the minimal HHR to reconstruct the distal interaction within the tertiary ribozyme structure, this cross-linked HHR exhibits efficient RNA substrate cleavage activities with almost no sequence constraint. Cellular experiments suggest that both exogenous and endogenous RNA expression can be dramatically knocked down by this HHR tool with levels comparable to those of siRNA. Unlike the widely applied protein-recruiting RNA systems (siRNA and CRISPR), this ribozyme tool functions solely on RNA itself with great simplicity, which may provide a new approach for gene manipulation in both fundamental and translational studies.

The glycoprotein gp63- a potential pan drug target for developing new antileishmanial agents

Leishmaniasis is a tropical parasitic disease caused by Leishmania spp. They cause several presentations of illness ranging from cutaneous leishmaniasis to visceral leishmaniasis. The current arsenal of drugs to treat leishmaniasis is limited, and drug resistance further impedes the problem. Therefore, it is necessary to revisit the available information to identify an alternative or new target for treatment. The glycoprotein 63 (gp63), is a potential anti-leishmanial target that plays a significant role in host-pathogen interaction and virulence. Many studies are ongoing to develop gp63 inhibitors or use it as a vaccine target. In this review, we will discuss the potential of gp63 as a drug target. This review summarises the studies focusing on gp63 as a drug target and its inhibitors identified using in silico approaches.

A Comprehensive Computational Investigation into the Conserved Virulent Proteins of Shigella species Unveils Potential Small-Interfering RNA Candidates as a New Therapeutic Strategy against Shigellosis

Shigella species account for the second-leading cause of deaths due to diarrheal diseases among children of less than 5 years of age. The emergence of multi-drug-resistant Shigella isolates and the lack of availability of Shigella vaccines have led to the pertinence in the efforts made for the development of new therapeutic strategies against shigellosis. Consequently, designing small-interfering RNA (siRNA) candidates against such infectious agents represents a novel approach to propose new therapeutic candidates to curb the rampant rise of anti-microbial resistance in such pathogens. In this study, we analyzed 264 conserved sequences from 15 different conserved virulence genes of Shigella sp., through extensive rational validation using a plethora of first-generation and second-generation computational algorithms for siRNA designing. Fifty-eight siRNA candidates were obtained by using the first-generation algorithms, out of which only 38 siRNA candidates complied with the second-generation rules of siRNA designing. Further computational validation showed that 16 siRNA candidates were found to have a substantial functional efficiency, out of which 11 siRNA candidates were found to be non-immunogenic. Finally, three siRNA candidates exhibited a sterically feasible three-dimensional structure as exhibited by parameters of nucleic acid geometry such as: the probability of wrong sugar puckers, bad backbone confirmations, bad bonds, and bad angles being within the accepted threshold for stable tertiary structure. Although the findings of our study require further wet-lab validation and optimization for therapeutic use in the treatment of shigellosis, the computationally validated siRNA candidates are expected to suppress the expression of the virulence genes, namely: IpgD (siRNA 9) and OspB (siRNA 15 and siRNA 17) and thus act as a prospective tool in the RNA interference (RNAi) pathway. However, the findings of our study require further wet-lab validation and optimization for regular therapeutic use for treatment of shigellosis.

TP-MV: Therapeutic protein prediction by multi-view learning

Background:

Therapeutic peptide prediction is critical for drug development and therapy. Researchers have been studying this essential task, developing several computational methods to identify different therapeutic peptide types.

Objective:

Most predictors are the specific methods for certain peptides. Currently, developing methods to predict the presence of multiple peptides remains a challenging problem. Moreover, it is still challenging to combine different features to make the therapeutic prediction.

Method:

In this paper, we proposed a new ensemble method TP-MV for general therapeutic peptide recognition. TP-MV is developed using the stacking framework in conjunction with the KNN, SVM, ET, RF, and XGB. Then TP-MV constructs a multi-view learning model as meta-classifiers to extract the discriminative feature for different peptides.

Results:

In the experiment, the proposed method outperforms the other existing methods on the benchmark datasets, indicating that the proposed method has the ability to predict multiple therapeutic peptides simultaneously.

Conclusion:

The TP-MV is a useful tool for predicting therapeutic peptides.

Influence of virus-host interactions on plant response to abiotic stress

Environmental factors play a significant role in controlling growth, development and defense responses of plants. Changes in the abiotic environment not only significantly alter the physiological and molecular pathways in plants, but also result in attracting the insect pests that carry a payload of viruses. Invasion of plants by viruses triggers the RNA silencing based defense mechanism in plants. In counter defense the viruses have gained the ability to suppress the host RNA silencing activities. A new paradigm has emerged, with the recognition that plant viruses also have the intrinsic capacity to modulate host plant response to environmental cues, in an attempt to favour their own survival. Thus, plant-virus interactions provide an excellent system to understand the signals in crosstalk between biotic (virus) and abiotic stresses. In this review, we have summarized the basal plant defense responses to pathogen invasion while emphasizing on the role of RNA silencing as a front line of defense response to virus infection. The emerging knowledge indicates overlap between RNA silencing with the innate immune responses during antiviral defense. The suppressors of RNA silencing serve as Avr proteins, which can be recognized by the host R proteins. The defense signals also function in concert with the phytohormones to influence plant responses to abiotic stresses. The current evidence on the role of virus induced host tolerance to abiotic stresses is also discussed.

Specific delivering of RNAi using Spike's aptamer-functionalized lipid nanoparticles for targeting SARS-CoV-2: A strong anti-Covid drug in a clinical case study

Coronavirus (SARS-CoV-2) as a global pandemic has attracted the attention of many scientific centers to find the right treatment. We expressed and purified the recombinant receptor-binding domain (RBD) of the SARS-CoV-2 spike (S) protein, and specific RBD aptamers were designed using SELEX method. RNAi targeting nucleocapsid phosphoprotein was synthesized and human lung cells were inoculated with aptamer-functionalized lipid nanoparticles (LNPs) containing RNAi. The results demonstrated that RBD aptamer having K_D values of 0.290 nm possessed good affinity. Based on molecular docking and efficacy prediction analysis, siRNA molecule was showed the best action. LNPs were appropriately functionalized by aptamer and contained RNAi molecules. Antiviral assay using q-PCR and ELISA demonstrated that LNP functionalized with 35 µm Apt and containing 30 nm RNAi/ml of cell culture had the best antiviral activity compared to other concentrations. Applied aptamer in the nanocarrier has two important functions. First, it can deliver the drug (RNAi) to the surface of epithelial cells. Second, by binding to the SARS-CoV-2 spike protein, it inhibits the virus entrance into cells. Our data reveal an interaction between the aptamer and the virus, and RNAi targeted the virus RNA. CT scan and the clinical laboratory tests in a clinical case study, a 36-year old man who presented with severe SARS-CoV-2, demonstrated that inhalation of 10 mg Apt-LNPs-RNAi nebulized/day for six days resulted in an improvement in consolidation and ground-glass opacity in lungs on the sixth day of treatment. Our findings suggest the treatment of SARS-CoV-2 infection through inhalation of Aptamer-LNPs-RNAi.

Non-coding RNAs as Novel Biomarkers in Cancer Drug Resistance

Chemotherapy is often the primary and most effective anticancer treatment; however, drug resistance remains a major obstacle to it being curative. Recent studies have demonstrated that non-coding RNAs (ncRNAs), especially microRNAs and long non-coding RNAs, are involved in drug resistance of tumor cells in many ways, such as modulation of apoptosis, drug efflux and metabolism, epithelial-to-mesenchymal transition, DNA repair, and cell cycle progression. Exploring the relationships between ncRNAs and drug resistance will not only contribute to our understanding of the mechanisms of drug resistance and provide ncRNA biomarkers of chemoresistance, but will also help realize personalized anticancer treatment regimens. Due to the high cost and low efficiency of biological experimentation, many researchers have opted to use computational methods to identify ncRNA biomarkers associated with drug resistance. In this review, we summarize recent discoveries related to ncRNA-mediated drug resistance and highlight the computational methods and resources available for ncRNA biomarkers involved in chemoresistance.

A computational approach to design potential siRNA molecules as a prospective tool for silencing nucleocapsid phosphoprotein and surface glycoprotein gene of SARS-CoV-2

An outbreak, caused by an RNA virus, SARS-CoV-2 named COVID-19 has become pandemic with a magnitude which is daunting to all public health institutions in the absence of specific antiviral treatment. Surface glycoprotein and nucleocapsid phosphoprotein are two important proteins of this virus facilitating its entry into host cell and genome replication. Small interfering RNA (siRNA) is a prospective tool of the RNA interference (RNAi) pathway for the control of human viral infections by suppressing viral gene expression through hybridization and neutralization of target complementary mRNA. So, in this study, the power of RNA interference technology was harnessed to develop siRNA molecules against specific target genes namely, nucleocapsid phosphoprotein gene and surface glycoprotein gene. Conserved sequence from 139 SARS-CoV-2 strains from around the globe was collected to construct 78 siRNA that can inactivate nucleocapsid phosphoprotein and surface glycoprotein genes. Finally, based on GC content, free energy of folding, free energy of binding, melting temperature, efficacy prediction and molecular docking analysis, 8 siRNA molecules were selected which are proposed to exert the best action. These predicted siRNAs should effectively silence the genes of SARS-CoV-2 during siRNA mediated treatment assisting in the response against SARS-CoV-2.