Computationally Driven Discovery of Novel p53 Y220C Stabilizers

Abstract

The p53 Y220C mutation is a critical cancer‑driving factor, making the development of small‑molecule stabilizers capable of restoring its function an urgent clinical need. To accelerate the discovery of novel p53 Y220C stabilizers, this study employed an innovative computer‑aided drug design strategy. Using the highly active molecule Activator 7 as a template, we performed a systematic virtual screening of the Freedom Space compound library by leveraging the Scaffold Hopper module of InfiniSee software in combination with its three‑dimensional pharmacophore and shape features. The workflow adopted a multi‑stage filtering strategy: an initial rapid screening based on 3D shape and pharmacophore matching was followed by high‑precision molecular docking and binding free‑energy prediction using the crystal structure of the p53 Y220C–KG13 covalent complex as the receptor model.Through this rational design pipeline, a series of structurally novel hit compounds with favorable predicted binding profiles were successfully identified. Among them, Candidate 2 not only retained the hydrogen‑bond interaction between the template and the key residue Thr150 but also formed an additional hydrogen‑bond network with the mutation‑core residues Cys220 and Gly154 through its unique architecture, exhibiting higher predicted binding affinity and specificity. This compound, based on a novel scaffold, lays a foundation for the development of a new generation of proprietary p53 Y220C stabilizers.In summary, this study established an efficient computational screening methodology and discovered structurally novel potential p53 Y220C stabilizers, providing a critical starting point for subsequent experimental validation and lead‑compound optimization.