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 protein designers and structural biologists to generate de novo protein backbones with co-designed sequences conditioned on user-defined 3D ellipsoidal layouts through 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 RNA 3D structures from sequence data through a guided workflow inside Vecura, without setting up complex GPU infrastructure or managing multiple dependencies.
アップデート
This update enables researchers, bioinformaticians, and drug discovery scientists to analyze genetic variants, optimize codon sequences, and assess coding sequence fitness through a guided workflow inside Vecura, without setting up complex technical infrastructure.
アップデート
This update enables medicinal chemists, drug-discovery researchers, and computational scientists to generate novel, chemically valid 3D small molecules from scratch through a guided workflow inside Vecura, without setting up complex GPU infrastructure or managing pretrained model weights.
アップデート
This update enables synthetic biologists and drug discovery researchers to generate high-affinity de novo protein binders through a streamlined workflow inside Vecura, eliminating the need for managing complex GPU-intensive infrastructure.
アップデート
This update enables structural biologists and researchers to generate diverse 3D protein conformational ensembles directly within Vecura, simplifying the study of protein dynamics without requiring complex local infrastructure or high-performance computing setups.
アップデート
This update enables drug discovery researchers and structural biologists to predict and visualize complex protein-ligand binding poses through a streamlined, high-performance workflow inside Vecura, removing the need for complex infrastructure setup.
アップデート
This update allows researchers and immunologists to predict complex TCR-pMHC structural interactions and isolate unbound molecule conformations directly within the Vecura platform, eliminating the need for complex, resource-heavy local infrastructure.
アップデート
This update enables researchers and computational biologists to design custom protein backbones through a guided workflow inside Vecura, removing the need for complex local infrastructure or manual environment configuration.
アップデート
This update enables structural biologists and researchers to perform high-accuracy, restraint-guided protein-protein docking directly within the Vecura platform, eliminating the need for complex, manual computational environment setups.
アップデート
This update enables computational biologists, peptide engineers, and drug discovery researchers to design macrocyclic peptide backbones — either as free-standing monomers or as binders targeting specific proteins — through a guided workflow inside Vecura, without setting up complex GPU infrastructure or managing RFdiffusion dependencies.
アップデート
This update enables computational biologists and drug discovery researchers to predict protein-ligand binding structures through a guided workflow inside Vecura, without setting up complex technical infrastructure.