アップデート
ライフサイエンスの発見のための AI を支えるモデルに関する視点と深掘り。
アップデート
This update enables researchers and computational biologists to generate high-fidelity, all-atom structural predictions for complex biomolecular assemblies through a guided, accessible workflow inside Vecura, removing the need to manage complex, resource-intensive technical infrastructure.
アップデート
This update enables structural biologists and therapeutic developers to design de novo protein binders through a guided workflow inside Vecura, without setting up complex technical infrastructure.
アップデート
This update enables researchers and scientists to predict energy, forces, and stress for atomic systems across a wide range of chemistries through a guided workflow inside Vecura, without setting up complex technical infrastructure.
アップデート
This update enables medicinal chemists and drug discovery researchers to automatically map out multi-step retrosynthetic routes and identify commercial precursors through a guided workflow inside Vecura, without setting up complex technical infrastructure.
アップデート
This update enables computational biologists and chemists to run high-performance molecular dynamics simulations through a guided, GPU-accelerated workflow on Vecura, eliminating the need to manage complex HPC infrastructure.
アップデート
This update enables computational chemists and drug discovery teams to predict protein-ligand binding affinity via a guided workflow inside Vecura, without setting up complex technical infrastructure.
アップデート
This update enables structural biologists and drug discovery researchers to predict high-resolution 3D co-crystal structures of Enterovirus A71 (EV-A71) 2A protease bound to small-molecule ligands through a guided workflow inside Vecura, without setting up complex technical infrastructure.
アップデート
Researchers and drug discovery scientists can now easily perform high-precision protein-ligand docking via SigmaDock on Vecura, eliminating the need for complex software installation and manual search-box configuration.
アップデート
This update enables structural biologists and protein engineers to model noncanonical amino acids and design customized peptide binders directly within Vecura, removing the burden of managing complex computational infrastructure.
アップデート
The integration of Genie 3 into Vecura allows researchers and protein engineers to perform high-speed de novo protein design—including unconditional generation, motif scaffolding, and binder design—through a streamlined, accessible interface.
アップデート
This update empowers protein engineers and computational biologists to design novel protein sequences and structures through a streamlined, guided workflow on Vecura, eliminating the need to manage complex GPU-heavy technical stacks.
アップデート
This update allows drug discovery researchers to perform state-of-the-art protein-ligand binding affinity scoring directly within the Vecura platform, eliminating the need to manage complex GPU-based inference pipelines.