From target to lead, without the guesswork.

Generate hypotheses, design and rank candidates, and run docking and dynamics campaigns with an AI co-scientist that reasons over structure, literature, and your own assay data.

Built for: Computational chemists, Structural biologists, Discovery leads

Challenges

• Evidence is scattered: Target rationale lives across papers, patents, and internal decks. Pulling it into one defensible story takes weeks.
• Candidate triage is slow: Docking, ADMET, and resistance coverage are run in separate tools and stitched together by hand before every design cycle.
• Simulation is a bottleneck: Setting up and interpreting MD runs requires specialist time your discovery team rarely has to spare.

What LiteFold does

• Evidence-grounded hypothesis generation: Rosalind reads the literature, variant databases, and structural data to propose and rank testable hypotheses with citations attached.
• Structure-based design and ranking: Design, dock, and score candidates against binding quality, selectivity, and ADMET liabilities before anything is synthesized.
• Docking and MD campaign orchestration: Plan docking campaigns and molecular dynamics runs from a single prompt, then get the results interpreted in plain scientific language.
• Antibody and protein engineering: Model antibody–receptor interfaces, score binding precision, and propose mutations that improve affinity and developability.