Virtual Screening Against Carbohydrate-Binding Proteins: Evaluation and Application to Bacterial Burkholderia ambifaria Lectin

Tamir Dingjan, Émilie Gillon, Anne Imberty, Serge Pérez, Alexander Titz, Paul A. Ramsland, Elizabeth Yuriev

Research output: Contribution to journalArticleResearchpeer-review

8 Citations (Scopus)

Abstract

Bacterial adhesion to human epithelia via lectins constitutes a therapeutic opportunity to prevent infection. Specifically, BambL (the lectin from Burkholderia ambifaria) is implicated in cystic fibrosis, where lectin-mediated bacterial adhesion to fucosylated lung epithelia is suspected to play an important role. We employed structure-based virtual screening to identify inhibitors of BambL-saccharide interaction with potential therapeutic value. To enable such discovery, a virtual screening protocol was iteratively developed via 194 retrospective screening protocols against 4 bacterial lectins (BambL, BC2L-A, FimH, and LecA) with known ligands. Specific attention was given to the rigorous evaluation of retrospective screening, including calculation of analytical errors for enrichment metrics. The developed virtual screening workflow used crystallographic constraints, pharmacophore filters, and a final manual selection step. The protocol was applied to BambL, predicting 15 active compounds from virtual libraries of approximately 7 million compounds. Experimental validation using fluorescence polarization confirmed micromolar inhibitory activity for two compounds, which were further characterized by isothermal titration calorimetry and surface plasmon resonance. Subsequent testing against LecB from Pseudomonas aeruginosa demonstrated binding specificity of one of the hit compounds. This report demonstrates the utility of virtual screening protocols, integrating ligand-based pharmacophore filtering and structure-based constraints, in the search for bacterial lectin inhibitors.

Original languageEnglish
Pages (from-to)1976-1989
Number of pages14
JournalJournal of Chemical Information and Modeling
Volume58
Issue number9
DOIs
Publication statusPublished - 24 Sept 2018

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