Druggability of a protein is its potential to be modulated by drug-like molecules. It is important in the target selection phase. We hypothesize: (1) Known drug-binding sites contain advantageous physicochemical properties for drug binding, or “druggable-microenvironments”; (2) 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 datasets. One dataset measures druggability using NMR-based screening. DrugFEATURE correlates well with this metric. The second dataset 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.