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apt-scout is built around a hand-curated, verbatim-verified catalogue of aptamer–target binding affinities (Kd) — not a re-hosted aggregation. Every Kd is read back from its primary publication, stored with the exact source sentence, and labelled by measurement type (intrinsic equilibrium vs apparent/avidity); a verbatim re-verification found that ~40–50% of reported Kd values in existing aggregated aptamer collections are in fact apparent/avidity, not comparable. This curated Kd layer is then linked to a target-context profile of ~7,177 human proteins (the layers below are harvested from public databases and labelled as such).

apt-scout is an automated catalogue of 7,177 human protein targets, each evaluated across a five-layer schema (structure / modification / interaction / expression / disease) to prioritise targets for affinity-reagent (aptamer, antibody, ASO, small-molecule) design — with explicit annotation of activation-state-selective surfaces.

How the data was built (provenance): values are mechanically harvested from public databases — PDB / AlphaFold / EMDB (structure), UniProt (modifications), Open Targets / ChEMBL / PubMed / Aptagen / HPA (interaction), Human Protein Atlas / Vesiclepedia / ExoCarta / EV-Map (expression), Open Targets (disease). The raw source response is stored per target in each layer's raw_json column, so every value is traceable to its origin. Activation-state PDB pairs are a human-curated list of real PDB structures. No free-text was generated by an LLM in these layers.

How to verify any value: open a target, then check its source — e.g. PDB IDs at rcsb.org, UniProt at uniprot.org, expression at proteinatlas.org, disease at platform.opentargets.org. The raw_json column shows the exact upstream record (including PubMed queries + PMIDs).

Tiers: Tier 1 = 3,300 PDB-anchored targets; Tier 1.5 = 3,874 AlphaFold-confident targets; plus 3 controls.

Completeness / known limitations (transparent): some fields are not yet fully populated — ppi_count is pending; OMIM / ClinVar counts are blank in this production snapshot (held in a separate reference cohort); AlphaFold pLDDT is missing for 653 targets. A data-quality audit (incl. inter-rater verification) is in progress.

JSON API: append .json to any table or query. License: CC BY 4.0.

Data license: CC BY 4.0 · Data source: apt-scout automated curation pipeline (E. Dohi, NCNP) — values harvested from public databases; raw source stored per target

Custom SQL query

Queries

  • Kd — intrinsic, tightest binders
  • Kd — all source-verified measurements
  • Activation-state-selective targets
  • EV-associated targets with known aptamers
  • Top-priority targets
  • Kd — ready-to-use subset (intrinsic, protein, 1 per aptamer×target)
  • EV-Map conserved EV-hallmark proteins in apt-scout (104 of 182)
  • EV-surface aptamer candidates (surface ecto × EV-Map hallmark), ranked
  • Surface vs cargo — class counts (why the split matters)

Tables

aptamer_costructures

pdb_id, title, keywords, resolution_A, pmid, doi, experimental_method

114 rows

db_meta

key, value

7 rows

db_stats

ord, metric, value, grade, definition, source

23 rows

ev_map_conserved

gene_name, feature, category, misev_marker, entrezgene_id, pevs_median, in_apt_scout, apt_scout_uniprot

224 rows

kd_measurements

id, source_pmid, aptamer_name, target_name_canonical, target_uniprot, kd_value, kd_unit, kd_log10_molar, binding_constant_type, aptamer_chemistry, aptamer_modifications, assay_method, assay_buffer, assay_ph, assay_temperature_k, assay_cations, verification_status, source_db, source_record_id, aptamer_seq, aptamer_seq_raw, measurement_class, verbatim_quote, seq_source, tier, sequence_status, pi_provenance_flag, include_in_gold, doi

743 rows

kd_structure_crossmatch

target, n_kd_records, n_structures, pdb_ids

33 rows

membrane_surface_class

target_id, surface_class, is_surface_accessible, surface_evidence

7,197 rows

sqlite_sequence

name, seq

1 row

target_aptamer_pmids

target_id, aptamer_pmids, aptamer_pubmed_query

7,197 rows

target_layer1_structure

target_id, pdb_count_total, pdb_count_detailed, pdb_best_resolution_A, alphafold_mean_pLDDT, alphafold_model_count, emdb_count, has_cryoEM, has_xray, has_NMR, raw_json, recorded_utc

7,197 rows

target_layer2_modification

target_id, ptm_count, ptm_phospho_count, ptm_glyco_count, ptm_ubiq_count, has_activation_state_pdb_pair, activation_state_pdb_active, activation_state_pdb_inactive, conformational_states_count, raw_json, recorded_utc

7,197 rows

target_layer3_interaction

target_id, ppi_count, drug_count_approved, drug_count_clinical, aptamer_count_pubmed, aptamer_count_aptagen, antibody_count_hpa, has_known_aptamer, raw_json, recorded_utc

7,197 rows

target_layer4_expression

target_id, hpa_tissue_count, hpa_tissue_jsons, gtex_protein_id, ev_proteome_pride_id, in_vesiclepedia, in_exocarta, in_cev_map, raw_json, recorded_utc, cev_map_in, cev_map_is_ev_hallmark, cev_map_is_nonev_hallmark, cev_map_conservation_pct, cev_map_isolation, cev_map_detection, cev_map_n_samples, cev_map_source_doi

7,198 rows

target_layer5_disease

target_id, opentargets_top_disease_name, opentargets_top_disease_score, opentargets_disease_count, omim_count, clinvar_pathogenic_count, ev_biomarker_disease, ev_biomarker_pubmed_count, raw_json, recorded_utc, clinvar_likely_pathogenic_count, clinvar_benign_count, clinvar_vus_count

7,197 rows

target_names

target_id, gene_symbol, protein_name

7,198 rows

targets

id, target_type, seed_source, status, priority_score, added_utc, started_utc, completed_utc, error, tier, worker_host

7,198 rows

verification_human

row_id, verdict, checker, checked_utc, note

0 rows

... and 4 hidden tables

Views

  • v_target_full
  • v_targets_by_tier
  • v_citations
  • v_kd
  • v_surface_targets
  • v_targets

Download SQLite DB: scout.db 110.8 MB

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