A single drug that alters how cells read genetic instructions has already become the first approved treatment for spinal muscular atrophy, and this project aims to understand that process well enough to repeat the trick for other diseases. The problem is that cells routinely mix and match pieces of genetic blueprints—a process called alternative splicing—to produce different proteins from the same gene. When this goes wrong, it contributes to conditions from neurodegeneration to cancer. Despite decades of work, researchers still do not understand the basic rules that govern which pieces get used and which get skipped. Without that fundamental knowledge, they cannot design small molecules to correct faulty splicing. This project combines chemistry, structural biology, cellular experiments, and machine learning to map the sequences, proteins, and molecular interactions that control splice site selection. The central question is whether it is generally possible to modulate splicing with high specificity using small molecules. If the answer is yes, the work would transform fundamental understanding of human gene expression and open a new route for pharmaceutical companies to develop treatments for diseases that currently have none. This is fundamental science—there is no immediate practical application—but the precedent of the spinal muscular atrophy drug shows how such knowledge can lead directly to therapies.
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Alternative splicing (AS) of mRNA precursors plays important roles in tissue-specific gene regulation and biological regulatory mechanisms, as it can radically alter protein expression, cell phenotypes and physiological responses. Altered splicing also contributes to disease mechanisms, ranging from neurodegeneration to cancer. Drugs modulating AS have recently provided the first therapy for Spinal Muscular Atrophy, a common genetic disorder, illustrating the huge potential for treating many other diseases of unmet need, if only we understood the mechanisms controlling splice site selection and how to regulate them with small molecules. Unfortunately, despite decades of research, a comprehensive understanding of the mechanisms that control specificity of AS is lacking. This gap in basic knowledge prevents opportunities to harness splicing modulators as tools to study gene function, novel therapeutics or other biotech applications. This Project addresses head-on the major technical challenges that have limited progress in the AS field. Building on extensive preliminary data, we will use a multidisciplinary approach that combines chemical, structural, cellular, systems biology and machine learning to characterize mechanisms of splice site selection and identify targets for modulating these mechanisms using tool compounds. The outcomes will define key regulatory sequences, splicing factors and molecular interactions involved, thereby illuminating how the splicing machinery efficiently accommodates, yet also discriminates between, a wide range of splice site sequences. This will enable future applications harnessing splice site selection. Our primary goal is to answer the central question, 'Is it generally possible to modulate splicing with high specificity using small molecules?' Success will transform our basic understanding of human gene expression and unleash major opportunities for Pharma to develop new therapeutics.
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