Systematic comparison of ligand-based and structure-based virtual screening methods on poly (ADP-ribose) polymerase-1 inhibitors

Yue Zhao, Xiang Gui Wang, Zhong Ye Ma, Guo Li Xiong, Zhi Jiang Yang, Yan Cheng, Ai Ping Lu, Zhi Jun Huang*, Dong Sheng Cao*

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

Abstract

The poly (ADP-ribose) polymerase-1 (PARP1) has been regarded as a vital target in recent years and PARP1 inhibitors can be used for ovarian and breast cancer therapies. However, it has been realized that most of PARP1 inhibitors have disadvantages of low solubility and permeability. Therefore, by discovering more molecules with novel frameworks, it would have greater opportunities to apply it into broader clinical fields and have a more profound significance. In the present study, multiple virtual screening (VS) methods had been employed to evaluate the screening efficiency of ligand-based, structure-based and data fusion methods on PARP1 target. The VS methods include 2D similarity screening, structure-activity relationship (SAR) models, docking and complex-based pharmacophore screening. Moreover, the sum rank, sum score and reciprocal rank were also adopted for data fusion methods. The evaluation results show that the similarity searching based on Torsion fingerprint, six SAR models, Glide docking and pharmacophore screening using Phase have excellent screening performance. The best data fusion method is the reciprocal rank, but the sum score also performs well in framework enrichment. In general, the ligand-based VS methods show better performance on PARP1 inhibitor screening. These findings confirmed that adding ligand-based methods to the early screening stage will greatly improve the screening efficiency, and be able to enrich more highly active PARP1 inhibitors with diverse structures.

Original languageEnglish
Article numberbbab135
Number of pages13
JournalBriefings in Bioinformatics
Volume22
Issue number6
Early online date3 May 2021
DOIs
Publication statusPublished - Nov 2021

Scopus Subject Areas

  • Information Systems
  • Molecular Biology

User-Defined Keywords

  • data fusion
  • PARP1 inhibitors
  • pharmacophore
  • similarity searching
  • virtual screening (VS)

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