Leash Bio 谈 DEL 数据、Hermes 模型与 Minos 科学智能体沙盒
原标题：Lab-in-the-Loop at Compute Speed — Ian Quigley, Leash Bio
AI 摘要
Leash Bio 的 Ian Quigley 在 Latent Space 播客中介绍了该公司利用 DNA 编码文库（DEL）收集蛋白质与小分子相互作用数据的工作，通过表观严谨性获得干净可复现的数据用于大规模建模。其团队还开发了仅用自有数据训练的模型 Hermes，在公开基准上可与 Boltz 匹敌，并发现模型会记忆蛋白质的“昵称”而非结合位点。播客结尾透露，他们基于多年数据构建了面向智能体的科学推理沙盒，可提供数万条“lab-in-the-loop”模拟用于科学强化学习，该工作已发展为 Minos，并发布预印本、博客和开放数据集。
正文节选
A few years ago I stumbled upon Leash Bio’s Substack, and was hooked. Be it their Kaggle competition that showed that no, we really haven’t solved protein-ligand binding, or their crazy discovery that knowing a molecule’s author is perhaps all you need to know to predict how good it is. Their substack — or at least Owl Posting’s1 deep dive on them — should be required reading for any scientist trying to do chemistry with AI. So I was super excited to finally be able to sit down with Ian Quigley