Structure Based Approaches to Probe Binding Hypothesis of Mutant p53 Modulators

Abstract

p53 is a tumor suppressor gene that is involved in normal cell growth and perform its normal physiological function by responding to DNA damage via activation of DNA repair genes thus, inducing apoptosis and in turns preventing the tumor progression. However, mutations within the core domain of the gene lose its ability to bind to damaged DNA which results in uncontrolled cell proliferation. Therefore, there is a need to modulate the mutant p53 gene by rescuing its function. Over the past few decades, scientists have been making efforts to cure lethal disease like cancer that is caused due to mutations in p53 gene via various experimental strategies such as mutagenesis and structural elucidation of oncogenes by X-ray crystallographic studies however, these represent very costly and time demanding endeavors. Consequently, in-silico models may considerably lessen the number of experimental studies required for hits selection and hence improving the success rate during early stages of drug development. Therefore, in the present project combined ligand and structure based computational studies were implemented to probe the 3D structural features of p53 modulators. Ligand-based pharmacophore model was generated for the virtual screening of new chemical entities against the R273H mutant p53 core domain. The model comprises of four different pharmacophoric features including two hydrophobic, one aromatic and one acceptor feature. The finally selected pharmacophore model showed 100% specificity, selectivity as well as MCC (Mathew’s Correlation Coefficient) values. Moreover, model was able to selectively screen three hits namely Etodolac, Naproxen and Prilocaine from Drug Bank database. Additionally, binding hypothesis of p53 modulators has been proposed by molecular docking studies of already known modulators of the R273H mutant p53 core domain and analyzing their interaction pattern with that of DNA. The results suggested that the docked modulators act as a bridge between the two complex biological entities. Briefly, the development of pharmacophore model and ligand-protein interaction profiling assisted in understanding of mutant p53 binding activity towards damaged DNA. The outcomes of present study can be further extended by experimental validation of screened hits obtained after virtual screening and exploring the stability of ligand-protein complexes by molecular dynamic simulations.