更新
关于驱动生命科学探索 AI 的模型的观点与深度解析
产品更新
This integration enables structural biologists and drug discovery researchers to generate diverse conformational ensembles of biomolecular complexes through an intuitive workflow on Vecura, eliminating the need for complex computational infrastructure setup.
产品更新
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.
产品更新
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.
产品更新
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.
产品更新
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.
产品更新
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.
产品更新
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.
产品更新
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.
产品更新
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.
产品更新
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.
产品更新
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.
产品更新
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.