Work

Development of an Integrated Computational Pipeline for PARP‐1 Inhibitor Screening Using Hybrid Virtual Screening and Molecular Dynamics Simulations

Year: 2025

Type: article

Abstract: Despite the promising anticancer properties of PARP-1 inhibitors, their clinical use is hindered by side effects. It is crucial to explore new structural variants of these inhibitors to increase efficacy and minimize side effects, enhancing their clinical viability and therapeutic scope. In this study, we developed a virtual screening workflow that synergistically integrates the capabilities of TransFoxMol, KarmaDock, and AutoDock Vina. This workflow not only streamlines the identification of potential inhibitors but also ensures a systematic approach to prioritizing candidates. Through structural clustering, we identified ten promising PARP-1 inhibitors. Additionally, molecular dynamics simulations and MM/PBSA were employed to elucidate the binding modes of compounds 1, 3, 6, and 9 with PARP-1, providing valuable insights into their interaction mechanisms and supporting future drug development efforts. This workflow serves as a versatile tool for early-stage drug discovery, offering a strategic foundation for the rational design of new PARP-1 inhibitors.

Source: ChemistryOpen

DOI: 10.1002/open.202500021

Authors: Guan Wang, Jingjing Guo, Feng Xu, Mingjuan Ji

Institutions: Taizhou Vocational and Technical College, Zhejiang University of Technology

Language: English

Topic: Computational Drug Discovery Methods

Subfield: Computational Theory and Mathematics

Field: Computer Science

Domain: Physical Sciences

SDG: Good health and well-being

Open Access status: gold

Estimated APC paid: $2,790