资源

探索 AI 驱动的生命科学发现资源

来自 Vecura 的研究洞察、产品更新、实用案例、网络研讨会与公司新闻。

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应用案例

Molecular Dynamics, Trajectory and Ensemble Analysis on Vecura

Proteins move, and a single structure does not capture that. Vecura provides five related operations for working with protein dynamics: running physics-based simulations, analysing existing trajectories, generating trajectories with learned models, analysing conformational ensembles, and generating ensembles from sequence. Together they support biophysical characterisation, ensemble-based docking, binding kinetics and conformational landscape exploration. The five operations differ mainly in what you start from and how much physical accuracy you need. The selection table below is the fastest route to the right one.

洞察

Making Water Visible: How Generative AI Can Support Protein Structure Research

Water is fundamental to biological systems, yet the individual water molecules surrounding proteins are often difficult and expensive to model. SuperWater, a generative AI framework developed to predict water molecule positions around biomolecular complexes, offers a new approach to this longstanding computational challenge.

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