Search space — eight-stage reduction strategy.
An eight-stage reduction strategy that takes the combinatorial sequence space down to ranked, testable neighborhoods.
How DiscoveryLab avoids exponential explosion and unverifiable mechanism claims.
Eight stages, each constraining, ranking, rejecting, or verifying candidates. The full peptide universe is never enumerated — only biologically plausible neighborhoods are searched, and candidate mechanisms must survive explicit graph and evidence checks.
Condition-first framing
Researchers begin with a biological condition or desired phenotype. The system maps it to pathways, receptor families, candidate mechanisms, contraindication concerns, relevant assays, and clinical/preclinical evidence.
Target and receptor narrowing
Instead of searching all possible peptides, DiscoveryLab selects a constrained biological target set — limited to evidence-supported receptors, pathways, and intervention hypotheses for the condition.
— Examples only. Coverage depends on available evidence per condition.
BioScout mimicry
Comparative BioScout identifies evolved source systems that already solve related biological problems and produces evidence-backed source-system search plans — not blind candidate generation.
Motif and scaffold constraints
The system extracts or applies pharmacophore hints, conserved motifs, receptor-binding residues, charge and hydrophobicity profiles, cyclization opportunities, secondary-structure propensity, protease resistance, and synthesis feasibility.
Family generation, not single sequences
Candidate families are generated around constrained scaffolds: parent sequence, conservative variants, non-natural amino-acid substitutions, cyclized versions, terminal modifications, stability-enhanced variants, and receptor-selectivity variants.
“The system searches local neighborhoods around biologically plausible scaffolds instead of sampling the full peptide universe.”
Genetic programming and cross-pollination
Successful families evolve under selection pressure from in-silico scores, with bounded mutation, crossover between motif families, scaffold recombination, and ncAA substitution strategies. Candidates failing safety, synthesis, or fit gates are rejected.
“Genetic programming is used as a constrained optimization layer, not as unconstrained random sequence generation.”
In-silico lab + mechanism verification
Candidates are scored before any wet-lab handoff: receptor fit, pathway relevance, predicted stability, solubility, aggregation risk, synthesis complexity, off-target concerns, novelty, manufacturability, assay suitability, graph-level mechanism verification, Lean audit artifact generation, and perturbation evidence support.
Human review and wet-lab handoff
Only candidates passing evidence, mechanism, quality, and safety gates move to LabSpace: batch creation, destination lab selection, capability matching, assay request, status tracking, returned wet-lab results, and feedback into candidate ranking and pathway assumptions.