Tree-based machine learning (ML) algorithms, such as Extra Trees (ET), Random Forest (RF), Gradient Boosting Machine (GBM), and XGBoost (XGB) are among the most widely used in early drug discovery, gi

Figshare2025-10-20 更新30

Distribution of Bound Conformations in Conformational Ensembles for X‑ray Ligands Predicted by the ANI-2X Machine Learning Potential

生物分子构象预测

虚拟筛选优化

In this study, we systematically studied the energy distribution of bioactive conformations of small molecular ligands in their conformational ensembles using ANI-2X, a machine learning potential, in

NIAID Data Ecosystem20

EnOpt-ing for Accuracy: Refining the Art of Ensemble Docking (dataset)

分子对接

虚拟筛选优化

This dataset contains files related to the manuscript "EnOpt-ing for Accuracy: Refining the Art of Ensemble Docking" by Bhatt, Wang, and Durrant. The compound_libraries_smiles.zip file includes SMILE

NIAID Data Ecosystem40

Flowr.root: A flow matching based foundation model for joint multi-purpose structure-aware 3D ligand generation and affinity prediction

基于结构的药物设计

分子亲和力预测

Curated data and checkpoints

Zenodo2026-05-07 更新20