Optimization of small molecule ligands of p53-Y220C

Because genetic mutations destabilize the encoded proteins, their performance and function in the cells is hugely affected. In many cases, protein instability and its mutation can affect the progression and treatment of some diseases. In the last 10 years of research, it appears that such problems can be ameliorated by a method called pharmacological chaperones, which use small molecules to enter cells and act as a molecular scaffold to prevent proteins from mutating. The p53 tumour suppressor is a central to the natural physiological defence against cancer, inactivation of this suppressor causes lysosomal storage disease polysulfatase deficiency and mutations of the gene may allow cancer cells to grow and spread in the body. Among the large number of different mutations, p53-Y220C is a common cancer mutation which leads to the inactivation of the tumour suppressor protein. This paper reports a novel approach that uses small molecules to bind to the p53-Y220C protein to improve its stability and restore its native function. This paper describes the structural improvement of a small molecule inhibitor and the evaluation of its performance through medicinal chemistry optimization and in computer software simulation testing. Through design and molecular docking simulations and subsequent organic synthesis and performance testing, attempts were made to improve the stability of such small molecules and their ability to bind to the surface of p53-Y220C proteins while reducing their molecular weight. By optimizing the original binding house, it has better halogen bonds, hydrogen bonds and other weak interactions. Protein-stabilized drugs have high selectivity and broad applicability, but there are still many gaps to be filled in the field of their drug discovery. We optimized the structure of a previously existing small-molecule protein stabilizer and tried to improve the efficacy of this protein stabilizer by improving its stability and the binding force between molecules and proteins. We hope that through this type of optimization, we can contribute to the new field of medicinal chemistry and fill certain gaps, while providing basic data for the design of new drugs