Reinventing PARP1 inhibition: harnessing virtual screening and molecular dynamics simulations to identify repurposed drugs for anticancer therapeutics.

Abstract

Poly (ADP-ribose) polymerase 1 (PARP1) is a nuclear protein that plays a pivotal role in DNA repair and has emerged as a promising target for cancer therapy. Repurposing existing FDA-approved drugs for PARP1 inhibition offers an accelerated route to drug discovery. Here, we present an integrated approach to drug repurposing for PARP1 inhibition while utilizing an integrated approach involving structure-based virtual screening and molecular dynamics (MD) simulations. First, a curated library of 3648 FDA-approved drugs from DrugBank was screened to identify potential candidates capable of binding to the PARP1. Our study reveals a subset of drug molecules with favorable binding profiles and stable interactions within the PARP1 active site. The standout candidate, Nilotinib, was selected based on its drug profile and subjected to a detailed analysis, including interaction studies and 500 ns all-atom MD simulations. By integrating multiple computational approaches, we provide a rational framework for the selection of Nilotinib, demonstrating its PARP1 binding features and potential for therapeutic development after further experimentation. This study highlights the power of computational methods in accelerating drug repurposing efforts, offering an efficient strategy for identifying novel therapeutic options for PARP1-associated diseases.