A single drug that corrects a genetic splicing error has already become the first approved treatment for spinal muscular atrophy—and researchers now want to know whether that trick can work for many other diseases. The problem is that no one fully understands how cells decide which pieces of genetic code to keep or discard when building proteins. This process, called alternative splicing, lets one gene produce many different proteins, and when it goes wrong, it contributes to conditions from neurodegeneration to cancer. Decades of research have failed to explain the rules that govern splice site selection, leaving drug developers unable to design small molecules that reliably correct faulty splicing. This project combines chemistry, structural biology, machine learning, and cellular experiments to map the key sequences, proteins, and molecular interactions that control splicing decisions. The central question is whether small molecules can modulate splicing with high specificity at all. If the answer is yes, it would transform fundamental understanding of human gene expression and open a new route for pharmaceutical companies to develop therapies for diseases that currently have none. If the answer is no, that knowledge itself would redirect future efforts. This is fundamental science with no guaranteed application—but the precedent of spinal muscular atrophy shows how high the payoff can be.
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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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