父亲用 GPT-6 Astra 为罕见病女儿设计迷你基因

Derek Croote @DerekCroote原推发布于 2026.09.17

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My daughter has an ultra-rare, autosomal dominant, monogenic neurological disorder with fewer than 200 cases worldwide. It is characterized by haploinsufficiency; however, unlike some genes underlying other genetic diseases, the affected gene is too large to fit into a standard AAV vector for a gene therapy intended to deliver neurons a working copy. I am using GPT-6 Astra and the Rosalind Workbench to design candidate minigenes for my daughter (and others affected) that are sufficiently sized for viral delivery while retaining the most important functional domains of the protein. The idea of minigenes has precedent: Elevidys by Sarepta Therapeutics is FDA approved for Duchenne Muscular Dystrophy and consists of a “micro-dystrophin” transgene about a third of the size of the wild type dystrophin. Specifically within Rosalind I am using the Biological Sequence & Alignment Viewer, Biohub ESM plugin (for folding candidate minigene variants and domains), and the Molecular Structure Viewer (for alignment to the wild-type reference predicted structure). Furthermore, I am leveraging additional databases like ClinVar to cross-reference pathogenic missense variants that suggest regions critical to functional activity, since little is known about the disease in general. I would be exceptionally thankful for the additional credits of the Pro plan as I keep quickly running out of usage, and this is a use case where I most certainly want the best available model.