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Date: 11-12-2020
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Rnai for Drug Discovery
RNA interference (RNAi) is a cellular mechanism to regulate the expression of genes and the replication of viruses. RNAi or gene silencing involves the use of a double-stranded RNA (dsRNA). Once in the cell, the dsRNAs are processed into short, 21–23 nucleotide dsRNAs termed small interfering RNAs (siRNAs) that are used in a sequencespecific manner to recognize and destroy complementary RNAs. There are several classes of naturally occurring small RNA species, including siRNAs, microRNAs (miRNAs) and repeat-associated siRNAs (rasiRNAs). The RNAi pathway has been exploited in simpler organisms to evaluate gene function by introducing dsRNAs that are specific to the targeted gene.
RNAi technology is being evaluated not only as an extremely powerful instrument for functional genomic analyses, but also as a potentially useful method to develop highly specific dsRNA-based genesilencing therapeutics. RNAi is an important method for analysing gene function and identifying new drug targets that uses double-stranded RNA to knock down or silence specific genes. The challenge has been to select reliably an siRNA segment that can efficiently silence the gene without triggering unwanted effects. One solution is to use algorithms to select highly functional siRNA sequences and then pool the best sequences for guaranteed gene knockdown. RNAi technology could considerably reduce the time needed for target validation and overall drug development, accelerating the drug discovery process. RNAi
screening can identify high-value drugs targets such as kinases involved in cell proliferation.
1. Use of siRNA Libraries to Identify Genes as Therapeutic Targets
The ability of RNAi to provide relatively easy ablation of gene expression has opened up the possibility of using collections of siRNAs to analyse the significance of hundreds or thousands of different genes whose expression is known to be upregulated in a disease, given an appropriate tissue culture model of that disease. Perhaps more important still is the possibility of using genome-wide collections of siRNAs, whether synthetic or in viral vectors, as screening tools. The libraries of RNAi reagents can be used in one of two ways.
One is in a high-throughput manner, in which each gene in the genome is knocked down one at a time and the cells or organism scored for a desired outcome, e.g. death of a cultured cancer cell but not a normal cell. Owing to the very large numbers of assays needed to look at the involvement of all genes in the human genome, this approach is very labour intensive.
The other approach is to use large pools of RNAi viral vectors and apply a selective pressure that only cells with the desired change in behaviour can survive. The genes knocked down in the surviving cells can then be identified by sequencing the RNAi vectors that they carry. This method is being used to investigate genes involved in neurodegenerative diseases, diabetes and cancer. Both approaches show considerable promise in identifying novel genes that may make important therapeutic targets for inhibition either by conventional drug discovery methods or, more controversially, by RNAi itself.
Sets of siRNAs focused on a specific gene class (siRNA libraries) have the capacity to increase greatly the pace of pathway analysis and functional genomics. RNAi-based functional chemogenomics has been integrated into drug discovery programs.
2. RNAi as a Tool for Assay Development
RNAi can be a useful tool for assay development, hit selection and specificity testing. RNAi can be used as a positive control to calibrate the assay readout based on the effects of known levels of mRNA or protein knockdown. Effects of compounds can then be tested against the known inhibitory effects of RNAi reagents. Selectivity of certain RNAi reagents can be used to advantage in assay development. By using RNAi reagents with known specificity for individual mRNA isoforms, it should be possible to predict the effects for compounds with similar specificity.
3. Challenges of Drug Discovery with RNAi
The advantages of cell-based RNAi screens over small-molecule screening for target identification include the fact that most cell types are amenable to RNAi and it is relatively easy to knock down any gene of interest. So far, every gene tested has been susceptible to RNAi. However, one of the big issues is how to make siRNAs ‘druggable’. Some of the challenges are:
- To ensure that the candidate siRNA is appropriately stabilised in a ‘druggable’ formulation or by chemical modifications. Stability of the RNA towards exo- and endonucleases can be resolved by appropriate chemical modifications.
- Safely and successfully delivering siRNA in an acceptable and effective manner.
- Scaling up siRNA synthesis in the near term and, ultimately, manufacturing reliably and effectively.
- Cell-based RNAi assays are particularly prone to edge effects because the cells in the outer wells of the plates grow at a different rate than the cells in the inner wells. One should ignore the outer wells.
- There are problems with the ‘penetrance’ of some RNAi screens, in which the level of GFP in the cells is heterogeneous, making it difficult to interpret. Actually, the expression levels of several proteins vary significantly within cells grown in culture. Therefore, the problem is not heterogeneity of the siRNA knockdown, but heterogeneity of protein expression, and is an artefact of the cell culture.
Analysis of the data can be improved by looking at single cells rather than entire wells. Once these issues have been resolved, there is potential for rapid earlystage drug development as RNAi-based therapy development relies predominantly on documented gene sequence data and leverages a natural process.
4. Role of MicroRNA in Drug Discovery
MicroRNAs (miRNAs), small and mostly non-coding RNA gene products, are molecules derived from larger segments of ‘precursor’ RNA that are found in all diverse multicellular organisms. miRNAs are 21–25 nucleotide transcripts that repress gene function through interactions with target mRNAs. miRNAs appear to regulate at least one-third of all gene expression and are also likely play significant roles in the manifestation of many disease states, including cancer and many metabolic and infectious diseases. Thus they represent a new class of drug targets for the pharmaceutical industry.
Investigators are seeking miRNA targets and functions with tools ranging from traditional genetics to computer-based genome scanning. Application to the Drosophila melanogaster and Anopheles gambiae genomes identifies several hundred target genes potentially regulated by one or more known miRNAs. These potential targets are rich in genes that are expressed at specific developmental stages and that are involved in cell fate specification, morphogenesis and the coordination of developmental processes, in addition to genes that are active in the mature nervous system. miRNAs can be used for rapid target gene identification and target validation. miRNAs and the genes they regulate are candidates for the development of new therapies. Several methods have been developed for computational prediction of miRNA targets. Online resources provide researchers with useful tools and data for assessing the impact of miRNAs on the gene or biological process of interest.
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