Start from atoms and finish with an AI-designed candidate you can defend. Explore real protein structures, generate molecules, weigh the tradeoffs a real medicinal chemist weighs, and learn where quantum computing may—and may not—help early drug discovery.
Start with the science — how atoms become AI-designed drug candidates — then watch the platform put it to work against disease bosses with live AI inference and 3D protein visualization.
The first-principles journey — atoms, proteins, targets, binding, and where AI and quantum computing actually help. The video companion to the Science Journey.
Generating real drug candidates against disease bosses — live AI inference, 3D protein visualization, and the full game loop end to end.
Deep2Lead is not an animation. It uses real protein structures, real SMILES validation, and a real LLM to generate candidates you then have to defend on the evidence.
A first-principles course from atoms to AI-designed drugs — proteins, disease targets, SMILES, binding, ADMET, toxicity, and multi-objective tradeoffs — with a 19-question FAQ answering what students actually ask.
Gemma generates candidate molecules as SMILES strings, validated in real time with RDKit. See QED, synthetic accessibility, LogP, and Lipinski's Rule of Five — the same metrics real medicinal chemists use.
Battle 7 disease bosses in a turn-based format. Each round you design a molecule to beat the known drug's score. Earn XP, unlock achievements, climb the leaderboard.
Free-form design mode. Pick any of 20 curated disease targets, load its structure, run the model repeatedly, and compare candidates side by side as a saved, reproducible experiment.
Every candidate gets a report card — validity, affinity, selectivity, drug-likeness, ADME, toxicity, synthesis, developability — with hard gates and Pareto tradeoffs, explained in plain English.
Explore active spaces, qubits, Hamiltonians, and VQE convergence — and learn the honest boundary between a teaching simulation and real quantum chemistry.
Nothing to install. Open the site and start learning.
Begin with the Science Journey — atoms, proteins, disease targets, SMILES, and binding. No chemistry background required, and no jargon left unexplained.
Pick a real disease target, inspect its 3D structure, and generate candidate molecules with a fine-tuned Gemma model. Every SMILES string is validated with RDKit before it scores.
Strong binding is not enough. Read the full report card — selectivity, ADME, toxicity, synthesis, developability — and learn why a beautiful binder still fails a hard gate.
Take on the Discovery Arena, beat the known drug's score, and save your work as a reproducible experiment in your learner log.
Every target is a real protein involved in human disease, sourced from peer-reviewed research and the RCSB Protein Data Bank.
| Textbooks | Web simulators | Deep2Lead | |
|---|---|---|---|
| Real protein structures | ❌ | ⚠️ Static images | ✅ Live RCSB + AlphaFold |
| AI molecule generation | ❌ | ❌ | ✅ Fine-tuned Gemma LLM |
| Drug-likeness validation | ❌ | ❌ | ✅ RDKit, QED, Lipinski |
| Multi-objective tradeoffs | ⚠️ Described | ❌ One score | ✅ Report card + hard gates |
| Gamified learning | ❌ | ⚠️ Limited | ✅ XP, battles, badges |
| Plain-English explanations | ⚠️ Dense | ⚠️ Minimal | ✅ Student-friendly |
| Honest about its limits | ✅ | ❌ Overclaims | ✅ Simulations labeled as such |
| Cost | 💰 Expensive | 💰 Subscription | ✅ Free core curriculum |
Deep2Lead builds on the original 2021 paper — an independent research project by Tarun Kumar Chawdhury (arXiv:2108.05183) — and expands its accessibility mission for the generative AI era.
The original paper introduced accessible drug discovery using a Variational Autoencoder for molecular generation and DeepPurpose DTI for binding affinity — the first tool of its kind requiring no programming.
Tanisha Chawdhury's gamification insight transformed the pipeline: replace VAEs with a fine-tuned Gemma 4 LLM, swap DeepPurpose for MAMMAL DTI, and wrap it all in a 3D game any student can play.
VAE → Gemma 4 LLM (3× validity, 5× QED). DeepPurpose → MAMMAL DTI (pKd scoring). Static tool → gamified platform with XP, badges, and 7 disease bosses. Expert-only → any student.
Deep2Lead is a hosted platform, so here is plainly what that means for your data.
Your account email, your saved experiments and molecule designs, your Arena sessions, and your learning progress — so your work is still there when you come back.
No advertising trackers and no third-party analytics profiling. We do not sell your data, and we do not share your designs with anyone.
Sign in with a magic link sent to your email — there is no password for us to store or for anyone to leak. Delete your account and your work goes with it.
Deep2Lead exists exclusively to teach. It is built to make drug discovery and the role of AI in medicine understandable and exciting for students — not to produce medicines.
Nothing here constitutes medical advice, diagnosis, or treatment. Never use any output from Deep2Lead to make health decisions. Always consult a qualified medical professional.
Molecules generated here are AI-assisted simulations for learning only. They have not been synthesised, tested, validated, or approved by any regulatory authority. Real drug discovery takes years of rigorous laboratory and clinical work.
The language model may produce inaccurate, incomplete, or nonsensical structures. Drug-likeness, ADME, toxicity, patient, and quantum values are computational estimates or labeled simulations — they do not predict real-world activity, safety, or efficacy.
Protein structures come from RCSB PDB and AlphaFold DB for educational purposes and are subject to their own terms of use. Deep2Lead claims no ownership of any biological data.
Deep2Lead is provided "as is" without warranty of any kind, express or implied, including warranties of merchantability, fitness for a particular purpose, or non-infringement. Use at your own risk.
Designed for students aged 13 and above with appropriate supervision. It is a tool for sparking interest in STEM — not a professional research platform.
Free core curriculum, nothing to install. Begin with the science and work your way to a candidate you can defend.
Whether you're a student, educator, or researcher — we'd love to hear from you. Report bugs, suggest new targets, or ask about using Deep2Lead in your classroom.