An E(3)-equivariant model transforms the output,y, according to the trans-rotation and parity operations applied to the inputxin 3D space52. Research has demonstrated that equivariant models can be trained with 1000 times less data while yielding superior results on the structures of bulk water53...
DynamicBind: predicting ligand-specific protein-ligand complex structure with a deep equivariant generative model Article Open access 05 February 2024 SurfDock is a surface-informed diffusion generative model for reliable and accurate protein–ligand complex prediction Article 27 November 2024 Augmented...
DynamicBind: predicting ligand-specific protein-ligand complex structure with a deep equivariant generative model. Nat. Commun. 15, 1071 (2024). Article Google Scholar Roche, R. et al. EquiPNAS: improved protein-nucleic acid binding site prediction using protein-language-model-informed equivariant ...
DynamicBind: predicting ligand-specific protein-ligand complex structure with a deep equivariant generative model Article Open access 05 February 2024 Explore related subjects Discover the latest articles, news and stories from top researchers in related subjects. Artificial Intelligence Data availability...
Source code for theNature CommunicationspaperDynamicBind: predicting ligand-specific protein-ligand complex structure with a deep equivariant generative model. DynamicBind recovers ligand-specific conformations from unbound protein structures (e.g. AF2-predicted structures), promoting efficient transitions betwee...
A Deep SE(3)-Equivariant Model for Learning Inverse Protein Folding Mmatthew McPartlon, Ben Lai, Jinbo Xu bioRxiv (2022) Learning inverse folding from millions of predicted structures Chloe Hsu, Robert Verkuil, Jason Liu, Zeming Lin, Brian Hie, Tom Sercu, Adam Lerer, Alexander Rives bioRxi...
不变函数是一种映射,使得输出空间不受输入空间中对称变换的影响,并且等变函数松弛不变函数。 它陈述了一个映射,使得输入空间中的对称性可以保留在输出空间中。数学上,假设存在一个对称变换 g 和从 X 到 Y 的映射函数 F,当满足式(10)的时候,F is then said to be equivariant to g 。
Generative Adversarial Networks (GANs). The GAN model is another type of generative models, especially popular in the computer vision domain [35 ]. It is an implicit generative model, whichlearns to sample real graphs. GAN consists of two main components, namely, a generator fG for generating ...
State-specific protein–ligand complex structure prediction with a multiscale deep generative model Article 12 February 2024 DynamicBind: predicting ligand-specific protein-ligand complex structure with a deep equivariant generative model Article Open access 05 February 2024 Language models can learn ...
DynamicBind: predicting ligand-specific protein-ligand complex structure with a deep equivariant generative model ArticleOpen access05 February 2024 Machine learning coarse-grained potentials of protein thermodynamics ArticleOpen access15 September 2023 ...