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• W2035175173 abstract "Druggability of a protein is its potential to be modulated by drug-like molecules. It is important in the target selection phase. We hypothesize that: (i) known drug-binding sites contain advantageous physicochemical properties for drug binding, or “druggable microenvironments” and (ii) given a target, the presence of multiple druggable microenvironments similar to those seen previously is associated with a high likelihood of druggability. We developed DrugFEATURE to quantify druggability by assessing the microenvironments in potential small-molecule binding sites. We benchmarked DrugFEATURE using two data sets. One data set measures druggability using NMR-based screening. DrugFEATURE correlates well with this metric. The second data set is based on historical drug discovery outcomes. Using the DrugFEATURE cutoffs derived from the first, we accurately discriminated druggable and difficult targets in the second. We further identified novel druggable transcription factors with implications for cancer therapy. DrugFEATURE provides useful insight for drug discovery, by evaluating druggability and suggesting specific regions for interacting with drug-like molecules. CPT Pharmacometrics Syst. Pharmacol. (2014) 3, e93; doi:10.1038/psp.2013.66; published online 22 January 2014" @default.
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• W2035175173 date "2014-01-01" @default.
• W2035175173 modified "2023-10-11" @default.
• W2035175173 title "Identifying Druggable Targets by Protein Microenvironments Matching: Application to Transcription Factors" @default.
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• W2035175173 doi "https://doi.org/10.1038/psp.2013.66" @default.
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