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关于驱动生命科学探索 AI 的模型的观点与深度解析
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This update enables medicinal chemists, formulation scientists, and drug discovery teams to predict solid solubility with ease through a guided, no-code workflow inside Vecura, removing the need for complex technical or environment setup.
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This update enables biologists and bioengineers to design VHH (nanobody) antibody sequences through a guided workflow inside Vecura, without setting up complex technical infrastructure.
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This update enables clinical researchers and drug discovery teams to predict complex polypharmacy side effects through a simplified, containerized workflow within Vecura, eliminating the need for complex local infrastructure setup.
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This integration empowers structural biologists and drug discovery researchers to automatically identify and rank druggable protein pockets directly within the Vecura platform, eliminating the need for complex, manual environment configuration.
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BioEmu is now available on Vecura, allowing structural biologists and researchers to generate and refine protein conformational ensembles through a streamlined workflow, eliminating the need for complex, resource-intensive infrastructure.
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This update enables researchers and drug discovery teams to predict 3D biomolecular structures and binding affinities through a guided workflow inside Vecura, without setting up complex GPU infrastructure or managing model weights.
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This update enables drug discovery researchers and computational biologists to generate novel small-molecule candidates and screen compound libraries against protein targets through a guided workflow inside Vecura, without setting up complex GPU infrastructure or managing API integrations.
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This update empowers structural biologists and drug discovery researchers to predict complex 3D atomic structures of proteins, DNA, RNA, and ligands directly within Vecura, eliminating the need for complex local infrastructure setup.
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This update enables drug discovery researchers and protein engineers to design high-affinity protein binding pockets through an optimized, guided workflow inside Vecura, eliminating the need for complex local infrastructure setup.
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Drug discovery researchers can now leverage PepMLM within Vecura to generate custom peptide binders from target sequences alone, accelerating hit discovery without the need for complex structural modeling infrastructure.
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This update enables computational chemists and drug discovery researchers to generate physically realistic 3D conformer ensembles for macrocyclic molecules and cyclic peptides through a guided workflow inside Vecura, without setting up complex technical infrastructure.
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This update enables researchers and biotech scientists to design novel protein binders, peptides, and therapeutic candidates through a guided workflow inside Vecura, without setting up complex GPU infrastructure or managing large model weights.