In Silico Screening, Molecular Dynamics Simulation and Binding Free Energy Identify Single-Point Mutations That Destabilize p53 and Reduce Binding to DNA.

ABSTRACT: Considering p53's pivotal role as a tumor suppressor protein, proactive identification and characterization of potentially harmful p53 mutations are crucial before they appear in the population. To address this, four computational prediction tools-SIFT, Polyphen-2, PhD-SNP, and MutPred2-utilizing sequence-based and machine-learning algorithms, were employed to identify potentially deleterious p53 nsSNPs (nonsynonymous single nucleotide polymorphisms) that may impact p53 structure, dynamics, and binding with DNA. These computational methods identified three variants, namely, C141Y, C238S, and L265P, as detrimental to p53 stability. Furthermore, molecular dynamics (MD) simulations revealed that all three variants exhibited heightened structural flexibility compared to the native protein, esp

SUBMITTER: Islam SM 

PROVIDER: S-EPMC11695177 | biostudies-literature | 2025 Feb

REPOSITORIES: biostudies-literature