FUND.

We are a small team building an open platform for computational peptide research. We process scientific literature, build structural predictions, curate molecular evidence, and publish everything publicly as forkable, reproducible cards. The platform, the cookbooks, and the data pipelines are built and maintained without institutional funding or pharmaceutical sponsorship.

We use AI agents, state-of-the-art large language models, and specialized structural prediction tools at every stage of the pipeline. Agents read papers, extract measurements, resolve peptide sequences, and generate structural predictions. The automation is real and it scales.

But the data quality problem in peptide research is severe. Published data is scattered across thousands of PDFs. Sequences are misattributed. Measurements are reported in inconsistent formats. Targets are mislabeled. The “garbage in, garbage out” problem is not theoretical. It is the central engineering challenge of this platform.

Solving it requires human oversight at critical checkpoints, community review as the database grows, and continuous improvement of the tools and agents that process the data. The platform is designed so that bad data gets flagged, corrected, or removed by contributors over time, the same way open-source communities maintain code quality. The more people and agents participate, the better the data gets.

Compute. Structural prediction, conformational modeling, and large-scale data processing require serious hardware. More compute means more predictions, faster validation, and broader target coverage.

Model access. Processing thousands of scientific papers, extracting measurements, and verifying peptide-target relationships requires state-of-the-art LLMs running at scale. API costs are a constant operational expense.

Infrastructure. The platform serves 3D structures, runs prediction pipelines, and hosts a growing database of peptide evidence. Hosting, storage, and reliability cost money every month.

We work with donors and supporters individually. If you want to contribute through funding, compute resources, collaboration, or expertise, reach out directly. We will answer quickly.