| ML | Machine Learning |
| RF | Random Forest |
| MD | Molecular Dynamics |
| SF | Scoring Function |
| FBDD | Fragment-Based Drug Design |
| VS | Virtual Screening |
| MW | Molecular Weight |
| SAR | Structure-Activity Relationship |
| QSAR | Quantitative Structure-Activity Relationship |
| EF | Enrichment Factor |
| ROC | Receiver Operating Characteristic |
| PDB | Protein Data Bank |
| RMSD | Root-Mean-Square Deviation |
| MUV | Maximum Unbiased Validation |
| DUD | Directory of Useful Decoys |
| GPCR | G-Protein-Coupled Receptor |
| LADS | Latent Actives in the Decoy Set |
| BEDROC | Boltzmann-Enhanced Discrimination of Receiver Operating Characteristic |
| AUC | Area Under the Curve |
| RIE | Robust Initial Enhancement |
| DUD-E | Directory of Useful Decoys, Enhanced |
| DEKOIS | Demanding Evaluation Kits for Objective in Silico Screening |
| HTX | High Throughput X-ray Crystallography |
| RO3 | Rule of Three |
| DSF | Differential Scanning Fluorimetry |
| Rp | Pearson correlation coefficient |
| Rs | Spearman rank-correlation |
| BFGS | Broyden–Fletcher–Goldfarb–Shanno |