FlowDock: A unified flow-based framework for flexible protein-ligand docking and binding affinity prediction

Accurate prediction of protein–ligand complexes and binding affinity is critical for hit identification and optimization for structure-based drug design. Traditional docking simulates binding processes with searching algorithms guided by energy-scoring functions, which are quite computationally expe...

Täydet tiedot

Bibliografiset tiedot

Päätekijät:	Jing Li, Ruiqiang Lu, Yi Tan, Pengyu Liang, Bo Liu, Shukai Gu, Huanxiang Liu, Xiaojun Yao
Aineistotyyppi:	Artigo
Kieli:	Inglês
Julkaistu:	Elsevier 2026-07-01
Sarja:	Acta Pharmaceutica Sinica B
Aiheet:	Structure-based drug design Protein–ligand docking Binding affinity prediction Machine learning in drug discovery Bayesian flow networks Deep equivariant generative models
Linkit:	http://www.sciencedirect.com/science/article/pii/S2211383526002492
Tagit:	Lisää tagi Ei tageja, Lisää ensimmäinen tagi!