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.

We report a simple model that predicts the maximum recommended therapeutic dose (MRTD) of small molecule drugs based on an assessment of likely protein–drug interactions. Previously, we reported methods for computational estimation of drug promiscuity and potency. We used these concepts to build a linear model derived from 238 small molecular drugs to predict MRTD. We applied this model successfully to predict MRTDs for 16 nonsteroidal antiinflammatory drugs (NSAIDs) and 14 antiretroviral drugs. Of note, based on the estimated promiscuity of low‐dose drugs (and active chemicals), we identified 83 proteins as “high‐risk off‐targets” (HROTs) that are often associated with low doses; the evaluation of interactions with HROTs may be useful during early phases of drug discovery. Our model helps explain the MRTD for drugs with severe adverse reactions caused by interactions with HROTs.