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Keywords:

  • binding site prediction;
  • pharmacophore modeling;
  • protein function prediction;
  • Tanimoto coefficient;
  • virtual screening

A pharmacophore-based virtual screening method was developed and validated for use in predicting the function of a novel protein in terms of small metabolite binding. Five test cases were used for the validation study which spanned two different folds, four superfamilies, and three enzyme classes. Binding sites were predicted using a combination of two methods (CASTp and THEMATICS). The binding site was mapped with chemical probes representing hydrogen-bond donor, acceptor, negative ionizable, positive ionizable, and hydrophobe. The interaction maps were converted to three or four feature pharmacophore models and used to search a database containing 80 018 tautomers/protomers/conformers of 10 535 metabolites. The pharmacophore-based virtual screening eliminated >92% of the database as potential substrates and retrieved specific hits, which were ranked using a physics-based scoring function. The known substrate or product was ranked within the top 0.7% and substrate-like compounds within the top 1% of the metabolite database for all of the five test cases. The results suggest that using this pharmacophore-based virtual screening is a time-efficient strategy that can be applied to screen large databases to help predict the function of small metabolite binding proteins.