Chemical Fragments as Foundations for Understanding Target Space and Activity Prediction
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Abstract
The use of small inhibitors' fragment frequencies for understanding kinase potency and selectivity is described. By quantification of differences in the frequency of occurrence of fragments, similarities between small molecules and their targets can be determined. Naive Bayes models employing fragments provide highly interpretable and reliable means for predicting potency in individual kinases, as demonstrated in retrospective tests and prospective selections that were subsequently screened. Statistical corrections for prospective validation allowed us to accurately estimate success rates in the prospective experiment. Selectivity relationships between kinase targets are substantially explained by differences in the fragment composition of actives. By application of fragment similarities to the broader proteome, it is shown that targets related by sequence exhibit similar fragment preferences in small molecules. Of greater interest, certain targets unrelated by sequence are shown to have similar fragment preferences, even when the chemical similarity of ligands active at each target is low.
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