Updates
Perspectives and deep dives on the models powering AI for life science discovery.
Updates
This update enables antibody engineers and protein scientists to accurately identify antigen-binding sites from 3D structures through a guided, high-throughput workflow inside Vecura, eliminating the need for complex local infrastructure setup.
Updates
This update enables medicinal chemists and computational biologists to accelerate lead optimization and de novo design through a guided, accessible workflow inside Vecura, eliminating the need to manage complex, containerized generative AI infrastructure.
Updates
This integration allows researchers and bioengineers to generate novel protein binders against specific therapeutic targets directly within the Vecura platform, bypassing the need for complex local infrastructure and specialized computational setups.
Updates
This update empowers medicinal chemists and structural biologists to rapidly identify and rank druggable protein binding sites via a streamlined, guided workflow on Vecura, eliminating the need to manage complex local installation or technical infrastructure.
Updates
This update enables structural biologists and drug discovery researchers to predict complex 3D biomolecular structures through a guided workflow inside Vecura, eliminating the need to manage complex GPU infrastructure and environment setups.
Updates
This update integrates the deep-learning-augmented docking tool gnina into Vecura, enabling researchers to perform advanced, CNN-powered molecular docking without the need to manage complex infrastructure or GPU acceleration.
Updates
This update enables computational biologists, medicinal chemists, and drug discovery researchers to predict small molecule binding poses and affinities through a guided workflow inside Vecura, without setting up complex technical infrastructure.
Updates
This update enables researchers and drug discovery teams to streamline antibody and nanobody design through a guided, high-performance workflow inside Vecura, eliminating the need to manage complex underlying technical infrastructure.
Updates
This update enables computational scientists and medicinal chemists to streamline fragment-based lead optimization through a guided, accessible workflow inside Vecura, eliminating the need to manage complex underlying technical infrastructure.
Updates
This update empowers drug discovery researchers to generate and optimize novel molecular analogs directly within the Vecura platform, streamlining lead optimization workflows without the need for complex infrastructure setup.
Updates
This update enables structural biologists and protein engineers to explore protein flexibility and capture metastable conformational states directly within Vecura, removing the burden of managing complex computational pipelines.
Updates
This update enables structural biologists, drug discovery researchers, and computational biochemists to predict the all-atom 3D structure of biomolecular complexes — proteins, DNA, RNA, ligands, and ions — through a guided workflow inside Vecura, without setting up complex GPU infrastructure or managing alignment pipelines.