| AChE | Acetylcholinesterase |
| AD | Applicability domain |
| ADMET | Absorption, distribution, metabolism, excretion, and toxicity |
| AUC | Area under the curve |
| BEDROC | Boltzmann-enhanced discrimination of receiver operating characteristic |
| CADD | Computer-aided drug discovery |
| ChEMBL | Curated bioactivity database (EMBL-EBI) |
| CNN | Convolutional neural network |
| ECFP4 | Extended-connectivity fingerprint (radius 2, 2048 bits) |
| EF | Enrichment factor (EF1%, EF5%, EF10%) |
| EGFR | Epidermal growth factor receptor |
| hERG | Human ether-à-go-go-related gene (potassium channel) |
| HIV1-P | Human immunodeficiency virus type 1 protease |
| MCS | Maximum common substructure |
| ML | Machine learning |
| ML-QSAR | Machine-learning QSAR classifier |
| PAINS | Pan-assay interference compounds |
| PCA | Principal component analysis |
| PDB | Protein Data Bank |
| pp | Percentage points |
| PPARγ | Peroxisome proliferator-activated receptor gamma |
| PR-AUC | Area under the precision–recall curve |
| QSAR | Quantitative structure–activity relationship |
| RF | Random forest |
| RMSD | Root-mean-square deviation |
| ROC-AUC | Area under the receiver operating characteristic curve |
| SD | Standard deviation |
| SDF | Structure-data file |
| SMILES | Simplified molecular-input line-entry system |
| UniProt | Universal Protein Resource |
| VS | Virtual screening |