Figure 2.

Workflow of QSKR model construction and lead compound screening. (1) Feature extraction methods: features are extracted from molecular SMILES,⁶⁷ 3D structures and complex structures. (2) Different machine learning methods are employed to evaluate and construct regression models for k_off. (The AutoQSAR model’s performance is illustrated in the figure, with R² = 0.90 on the training set and R² = 0.80 on the test set.) (3) After docking with different N-HSP90α conformations, further screening is conducted using the QSKR model for predictive selection. The selected compounds are then subjected to surface plasmon resonance (SPR) experiments to determine the dissociation rate constant (k_off).