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reacted to SeaWolf-AI's post with 🔥 about 11 hours ago
3,631 candidate molecules arrived in five days, from 83 accounts — roughly 700 a day. Far more than we expected. Thank you. Yesterday we opened the third season and 224 arrived within a day: Chagas disease. Why this disease Around 6 million people live with it, mostly in Latin America (WHO). Many carry it for decades without knowing, while the heart is slowly damaged. There are two drugs and both date from the 1960s, hard enough to tolerate that many patients cannot finish the two-month course. Sixty years without a new drug is not only a scientific problem. Most patients live where development costs cannot be recovered, which is why WHO calls this a neglected tropical disease. But the cost of proposing a candidate and filtering it has changed. So it seemed worth asking whether work nobody funds could be done by many people sharing it out. The problem this season The target is CYP51, the enzyme T. cruzi uses to build its membrane sterols. Block it and the parasite cannot survive. The difficulty is that we carry the same enzyme. Scoring: binding 30 · selectivity 30 · ADMET 15 · whole-cell 10 · novelty 10 · synthesis 5 Selectivity carries 30 points because nobody has solved it. Among the approved azoles on the board as reference compounds, some score 0 on selectivity — not a scorer fault, but the measurement. Taking part Design with any model, submit a SMILES, scored within minutes. Five ready-to-paste prompts per season, and the full rubric is published. Your molecule stays yours; private submission is the default. Prizes — 4,000 USD across three seasons Malaria 30 Sep · 1,000 | Tuberculosis 31 Oct · 2,000 | Chagas 30 Nov · 1,000 We know this does not cover the time you spend. It is a way of saying the work had worth. https://huggingface.co/spaces/FINAL-Bench/open-discovery-challenge
upvoted a collection 4 days ago
Armoring Models
reacted to SeaWolf-AI's post with ➕ 5 days ago
🧬 Your AI can design a malaria drug candidate. Can it tell you whether it's any good? Open Discovery Challenge #1 — Malaria is live. Design a molecule with any model — OpenAI, Claude, Gemini, Qwen, KIMI, DeepSeek, open weights, or by hand — submit it as SMILES, and it's scored in minutes on whole-cell activity, target binding, selectivity over the human enzyme, ADMET, novelty and synthesisability. You can check the scoring instead of trusting it. Approved drugs sit on the same leaderboard as the entries: DSM265, a clinical-stage antimalarial, scores 50.9. Teriflunomide — approved, but it hits the human enzyme — scores 2.8. Caffeine scores 1.8. If the clinical candidate lands on top and coffee lands at the bottom, the scorer discriminates. We caught 14 defects before opening — conventional toxicity cutoffs rejected all three approved antimalarials and coffee. All written up, along with the rule we now hold everything to: a gate that rejects an approved drug is a broken gate. Your molecule stays yours. No patent interest, nothing into our pipeline. You choose whether it's published — and publishing can cost you patentability, so we say so. USD 1,000 to the top entry when Season #1 closes 30 September 2026 — not payment for your tokens, but a way of saying the work had worth. Malaria killed ~597,000 people in 2023, three quarters of them children under five. Not for want of chemistry — for want of a market. No chemistry needed: the guide ships five prompts you can paste straight into your model, and the full rubric is published. 📖 https://huggingface.co/blog/FINAL-Bench/open-discovery-challenge 🚀 https://huggingface.co/spaces/FINAL-Bench/open-discovery-challenge Computational assessments of candidates — not measurements, not claims of efficacy.
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