AlphaFold - GapFiller

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  Validation of tool's process

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  AI prediction

The $2.6 Billion Problem We Are Solving Drug development costs an average of $2.6 billion and takes 12 years. The single biggest bottleneck is at the very beginning: we do not know what most proteins do. AlphaFold predicted the structure of 200 million proteins and won the 2024 Nobel Prize. But structure is not function. Over 100 million proteins remain completely uncharacterized — including 30–40% of the human proteome, a region scientists call the "dark proteome." This region is disproportionately implicated in Alzheimer's, Parkinson's, ALS, and cancer. A researcher manually characterizing one unknown protein spends 6–18 months reading literature and designing experiments. Most give up. The protein stays dark. The drug stays undiscovered. What We Built AlphaFold Gap-Filler is the missing piece. It takes an uncharacterized protein and produces a complete, specific, actionable drug development hypothesis in under 30 minutes — automatically, from scratch, with no prior knowledge of the protein. This is not a search engine. It is not a database lookup. It is a genuine multi-evidence reasoning system powered by Gemma 4 that synthesizes biology the way a world-class scientist would — except it does it for every protein simultaneously, at scale, without sleeping. Why Gemma 4 Made This Possible Every previous attempt at automated protein function prediction failed for the same reason: no model could hold enough context to reason like a biologist. A biologist characterizing an unknown protein does not look at one thing. They look at five things simultaneously: what do its evolutionary relatives do, what genes surround it in the genome, what other proteins does it interact with, what does its structure suggest, and what does the literature say. The synthesis of all five streams is where the insight comes from. Gemma 4's long-context window makes this possible for the first time. We assemble all five evidence streams — evolutionary homologs from BLAST, genomic neighborhood from Ensembl, interaction network from STRING DB, structural confidence from AlphaFold, and 50+ paper abstracts from PubMed — into a single inference call. Gemma 4 holds all of this simultaneously and reasons across it. No previous model could do this. No existing tool does this. This is the contribution.

Built With

• data
• gemma
• process
• research
• set