Ligand efficiency based approach for efficient virtual screening of compound libraries

Yi Yu Ke, Mohane Selvaraj Coumar, Hui Yi Shiao, Wen Chieh Wang, Chieh Wen Chen, Jen Shin Song, Chun Hwa Chen, Wen Hsing Lin, Szu Huei Wu, John T.A. Hsu, Chung Ming Chang, Hsing Pang Hsieh

Research output: Contribution to journalArticlepeer-review

8 Citations (Scopus)

Abstract

Here we report for the first time the use of fit quality (FQ), a ligand efficiency (LE) based measure for virtual screening (VS) of compound libraries. The LE based VS protocol was used to screen an in-house database of 125,000 compounds to identify aurora kinase A inhibitors. First, 20 known aurora kinase inhibitors were docked to aurora kinase A crystal structure (PDB ID: 2W1C); and the conformations of docked ligand were used to create a pharmacophore (PH) model. The PH model was used to screen the database compounds, and rank (PH rank) them based on the predicted IC50 values. Next, LE-Scale, a weight-dependant LE function, was derived from 294 known aurora kinase inhibitors. Using the fit quality (FQ = LE/LE-Scale) score derived from the LE-Scale function, the database compounds were reranked (PH-FQ rank) and the top 151 (0.12% of database) compounds were assessed for aurora kinase A inhibition biochemically. This VS protocol led to the identification of 7 novel hits, with compound 5 showing aurora kinase A IC50 = 1.29 μM. Furthermore, testing of 5 against a panel of 31 kinase reveals that it is selective toward aurora kinase A & B, with <50% inhibition for other kinases at 10 μM concentrations and is a suitable candidate for further development. Incorporation of FQ score in the VS protocol not only helped identify a novel aurora kinase inhibitor, 5, but also increased the hit rate of the VS protocol by improving the enrichment factor (EF) for FQ based screening (EF = 828), compared to PH based screening (EF = 237) alone. The LE based VS protocol disclosed here could be applied to other targets for hit identification in an efficient manner.

Original languageEnglish
Pages (from-to)226-235
Number of pages10
JournalEuropean Journal of Medicinal Chemistry
Volume83
DOIs
Publication statusPublished - 2014 Aug 18

All Science Journal Classification (ASJC) codes

  • Pharmacology
  • Drug Discovery
  • Organic Chemistry

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