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Nova Blueprint evaluates a molecular-design program against changing protein targets and antitargets. Your submitted program receives the current problem at runtime, constructs exactly 100 molecules from the provided reaction database, and writes a checkpoint for evaluation. The same frozen program must generalize across future provider epochs. Treat current-epoch performance as diagnosis, not permission to hard-code a target, protein sequence, molecule list, or other epoch-specific answer.

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Start with a competition brief

Before editing an agent or paying for an evaluation, record:
  • the current epoch and its exact immutable dataset slug;
  • target and antitarget counts, the antitarget weight, and allowed reactions;
  • required molecule count and runtime limit;
  • the random-baseline mean and standard deviation;
  • current score leader, current champion, win streak, and promotion margin;
  • the practice datasets you will use for regression and generalization checks;
  • the exact advisory crown-backtest command, when published.
Fetch the source data for that brief with:
The competition detail is the source of truth for the current challenge. Use the exact dataset slug it publishes; do not invent a latest alias. Its current_challenge.configuration includes the target and antitarget accessions and sequence hashes, structural and diversity gates, allowed reaction, random baseline, and any materialized time-budget and crown-threshold values. Protein sequences themselves stay in the immutable problem input and are mounted for the miner at runtime. When autoresearch_backtest is non-null, it points to an immutable replay of the three most recent settled epochs against their historical crown lines. Running its exact command is strongly recommended, but it is not required by preflight or live submission.

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Understand the score

For each valid molecule, the evaluator measures predicted binding to the target proteins and penalizes predicted binding to the antitarget proteins:
Higher is better. A normalized practice score expresses the raw score relative to that problem’s random baseline:
Compare raw scores only within the same epoch. Use normalized scores for cross-epoch practice comparisons. Every molecule gate is all-or-nothing: an invalid set receives no meaningful binding score. The submitted checkpoint must contain exactly the required number of unique, valid reaction identifiers and unique product structures. Products must satisfy the published heavy-atom, rotatable-bond, diversity, and set-entropy thresholds. Allowed reaction families can change by epoch.

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Know what winning means

The score leader and champion are different concepts. The score leader has the best observed score for an epoch. A challenger advances toward becoming champion only by beating the champion line by the configured margin on consecutive provider epochs. The live provider promotion rule requires four qualifying wins; an isolated high score does not replace the champion. The competition detail also publishes the reward cadence and the provider’s emissions override. Those values explain the economic reward; they do not change the molecular score.

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Use each dataset for its intended job

Use the smoke dataset to catch packaging, checkpoint, and validity failures. Use the multi-epoch practice dataset to decide whether a search improvement generalizes. Use an immutable epoch dataset to understand the current challenge, but do not promote a strategy from that result alone. The shipped multi-epoch practice set is a useful regression set. The rolling crown backtest is the stronger relative-competition loop: inspect every epoch’s margin_to_crown, cleared_crown_line, and beat_top_score, plus the aggregate worst margin. Clearing all three is strong evidence, not proof of the four consecutive live wins needed for promotion. Keep a control result and preserve every material change and per-epoch diagnostic; early experiments may combine related changes when separate paid runs would be unnecessarily expensive.

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Research before optimizing

Study three different evidence sources:
  1. The installed Nova skill and its references explain the binding contract, validity rules, reaction space, runtime helpers, and submission lifecycle.
  2. MetaNova-released competitor snapshots show how previous entrants searched, filtered, checkpointed, and used the runtime.
  3. Immutable Droyd datasets provide the exact problem inputs for reproducible hosted evaluation.
See Released Nova source for the folder-download workflow.