
More than 95% of genes in the human genome are alternatively spliced to form multiple transcripts, often encoding proteins with differing or opposing function. The control of alternative splicing is now being elucidated, and with this comes the opportunity to develop modulators of alternative splicing that can control cellular function. A number of approaches have been taken to develop compounds that can experimentally, and sometimes clinically, affect splicing control, resulting in potential novel therapeutics. Here we develop the concepts that targeting alternative splicing can result in relatively specific pathway inhibitors/activators that result in dampening down of physiologic or pathologic processes, from changes in muscle physiology to altering angiogenesis or pain. The targets and pharmacology of some of the current inhibitors/activators of alternative splicing are demonstrated and future directions discussed.
570, Transcription, Genetic, 610, 32 Biomedical and Clinical Sciences, anzsrc-for: 3214 Pharmacology and Pharmaceutical Sciences, anzsrc-for: 32 Biomedical and Clinical Sciences, Genetic, anzsrc-for: 1115 Pharmacology and Pharmaceutical Sciences, Drug Discovery, Genetics, Animals, Humans, Molecular Targeted Therapy, Review Articles, Human Genome, 3214 Pharmacology and Pharmaceutical Sciences, Alternative Splicing, Gene Expression Regulation, 5.1 Pharmaceuticals, RNA, Transcription, Signal Transduction
570, Transcription, Genetic, 610, 32 Biomedical and Clinical Sciences, anzsrc-for: 3214 Pharmacology and Pharmaceutical Sciences, anzsrc-for: 32 Biomedical and Clinical Sciences, Genetic, anzsrc-for: 1115 Pharmacology and Pharmaceutical Sciences, Drug Discovery, Genetics, Animals, Humans, Molecular Targeted Therapy, Review Articles, Human Genome, 3214 Pharmacology and Pharmaceutical Sciences, Alternative Splicing, Gene Expression Regulation, 5.1 Pharmaceuticals, RNA, Transcription, Signal Transduction
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| influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | Top 10% | |
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