The article introduces the Quantitative Estimate of Druglikeness (QED) as a new metric to assess the druglikeness of compounds. Druglikeness is a key factor in early drug discovery, but traditional rules like Lipinski's Rule of Five (Ro5) have limitations, such as promoting undesirable molecular property inflation. QED is based on the concept of desirability and provides a quantitative measure of druglikeness by combining multiple molecular properties. It allows compounds to be ranked by their relative merit and can capture the abstract notion of chemical aesthetics in medicinal chemistry. QED is derived from the distribution of molecular properties of approved drugs, including molecular weight, lipophilicity, hydrogen bond donors and acceptors, polar surface area, rotatable bonds, aromatic rings, and structural alerts. The desirability functions are fitted to these properties using asymmetric double sigmoidal (ADS) functions. The QED value ranges from 0 (all properties unfavorable) to 1 (all properties favorable). The method is flexible and can be weighted based on the importance of each property. The study compares QED with other druglikeness measures, including Ro5, Veber, Ghose, and Gleeson's quantitative score. QED outperforms these methods in distinguishing druglike compounds from non-druglike ones. It also provides a continuous scale for druglikeness, unlike the binary classification of Ro5. QED is shown to correlate with chemists' subjective assessments of druglikeness and chemical attractiveness. The article also extends QED to assess the druggability of protein targets by considering the chemical attractiveness of their associated ligands. QED is used to prioritize targets based on the druglikeness of their ligands, providing an efficient means to quantify and rank druggability. The study shows that QED can identify druglike compounds that fail Ro5 and highlights the importance of considering druglikeness in drug discovery. The results indicate that QED provides a more nuanced and accurate assessment of druglikeness compared to traditional rules. It allows for a more realistic and graduated description of compound quality, moving away from a binary 'black and white' assessment. QED is a valuable tool in drug discovery, offering a quantitative measure of druglikeness that can be used to prioritize compounds and targets.The article introduces the Quantitative Estimate of Druglikeness (QED) as a new metric to assess the druglikeness of compounds. Druglikeness is a key factor in early drug discovery, but traditional rules like Lipinski's Rule of Five (Ro5) have limitations, such as promoting undesirable molecular property inflation. QED is based on the concept of desirability and provides a quantitative measure of druglikeness by combining multiple molecular properties. It allows compounds to be ranked by their relative merit and can capture the abstract notion of chemical aesthetics in medicinal chemistry. QED is derived from the distribution of molecular properties of approved drugs, including molecular weight, lipophilicity, hydrogen bond donors and acceptors, polar surface area, rotatable bonds, aromatic rings, and structural alerts. The desirability functions are fitted to these properties using asymmetric double sigmoidal (ADS) functions. The QED value ranges from 0 (all properties unfavorable) to 1 (all properties favorable). The method is flexible and can be weighted based on the importance of each property. The study compares QED with other druglikeness measures, including Ro5, Veber, Ghose, and Gleeson's quantitative score. QED outperforms these methods in distinguishing druglike compounds from non-druglike ones. It also provides a continuous scale for druglikeness, unlike the binary classification of Ro5. QED is shown to correlate with chemists' subjective assessments of druglikeness and chemical attractiveness. The article also extends QED to assess the druggability of protein targets by considering the chemical attractiveness of their associated ligands. QED is used to prioritize targets based on the druglikeness of their ligands, providing an efficient means to quantify and rank druggability. The study shows that QED can identify druglike compounds that fail Ro5 and highlights the importance of considering druglikeness in drug discovery. The results indicate that QED provides a more nuanced and accurate assessment of druglikeness compared to traditional rules. It allows for a more realistic and graduated description of compound quality, moving away from a binary 'black and white' assessment. QED is a valuable tool in drug discovery, offering a quantitative measure of druglikeness that can be used to prioritize compounds and targets.