Updates
Perspectives and deep dives on the models powering AI for life science discovery.
Updates
This update empowers researchers to perform advanced antibody CDR co-design directly within Vecura, streamlining the generation of structurally optimized, antigen-specific antibody candidates without the need for complex local infrastructure.
Updates
This update enables therapeutic antibody and TCR developers to predict 3D structures of antibodies, nanobodies, and T-cell receptors through a guided workflow inside Vecura, without setting up complex technical infrastructure.
Updates
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.
Updates
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.
Updates
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.
Updates
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.
Updates
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.
Updates
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.
Updates
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.
Updates
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.
Updates
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.
Updates
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.