Structure-Based Drug Discovery

Structure-based drug discovery는 3D molecular structure를 사용해 target-ligand recognition, pose quality, binding affinity, candidate prioritization을 해석합니다.

이 wiki에서 SBDD concept는 Structure-based modeling을 받쳐주는 층입니다. 구체적인 project나 thesis direction이 생기면 Research page가 여기로 다시 연결됩니다.

SBDD Contract

SBDD note는 protein-ligand system을 아래 계약으로 고정한 뒤 method와 claim을 읽습니다.

PartMeaningTypical question
protein or receptorstructure source, chain, missing residues, cofactors, protonation?
binding site or pocketknown, predicted, ligand-defined, blind, template-derived?
ligand or candidate setstereo, tautomer, charge, conformer policy, library source?
pose or complex geometryreference, docked, generated, minimized, noisy, refined?
pose quality ruleRMSD, clash, strain, interaction, geometry validity?
score or predictorpose score, affinity, ranking score, filter, uncertainty?
metricpose success, enrichment, correlation, calibration, validity, utility?
split and leakage boundaryscaffold, protein family, complex pair, template, time, assay source?

The first reading question is not whether a method is AI-based. It is which part of the contract it changes.

Route Map

QuestionStartThen Check
how are receptor and ligand prepared?Receptor and ligand preparation, Docking workflowchemical state, missing atoms, receptor state
how is the pocket defined?Pocket definition contractknown, predicted, ligand-defined, blind, template-derived
how are poses generated?Pose generation, Pose RMSDatom mapping and symmetry
is a predicted pose plausible?Pose quality, Interaction fingerprintgeometry, contacts, denominator
what score is being optimized or ranked?Scoring function, Binding affinitylabel semantics and assay context
is this a screening claim?Virtual screening, Negative set, Ranking metricscandidate pool and early enrichment
is the benchmark clean?Protein-ligand split, Template leakageprotein family, scaffold, complex, assay/source

Core Concepts

Task Map

where is a protein or pocket and is a ligand.

Claim Separation

SBDD papers often use similar inputs but make different claims. Keep the claim narrow.

ClaimEvidence neededDo not confuse with
pose generationreference pose, symmetry-aware RMSD, pose plausibilityaffinity or enrichment
pose plausibilityclash, strain, interaction, chemical geometrycorrect binding free energy
scoringscore separates better/worse poses or ligandscalibrated affinity
affinity predictionassay-aware labels, split, uncertainty, baselinedocking score
virtual screeningcandidate pool, negative set, early enrichmentabsolute activity
structure-aware generationgenerated validity, novelty, conditioning, filterssynthesizability or selectivity

Denominators matter:

Filtering invalid poses or molecules before reporting ranking metrics changes the claim and must be stated.

Evaluation Denominators

EvaluationNumeratorDenominator
pose successposes within threshold and passing plausibility checksall generated or docked poses attempted
docking enrichmentactives recovered in early ranked setfull screened library or declared candidate pool
affinity correlationexamples with valid label and predictiondeclared benchmark after preprocessing
generation validitysamples passing chemistry and geometry rulesraw generated samples before repair/filtering
interaction recoverycontacts or fingerprints matching referenceevaluated complexes with defined pocket and pose

Public Note Template

FieldWrite
Systemprotein, pocket, ligand, complex, structure source
Preparationreceptor cleanup, ligand state, conformer policy, pocket rule
Methoddocking, scoring, diffusion, refinement, screening, generation
Outputpose, score, rank, affinity, candidate set, generated molecule
MetricRMSD, clash, strain, enrichment, correlation, calibration, validity
Splitscaffold, protein family, complex pair, template, assay/source, time
Leakage auditligand-defined pocket, template similarity, benchmark overlap
Public boundaryno private structures, internal target names, unpublished results, server paths

Checks

  • Is the task pose prediction, affinity prediction, enrichment, or molecule generation?
  • Is pose generation evaluated separately from scoring?
  • Are receptor and ligand inputs prepared consistently?
  • Are pose quality and binding affinity evaluated separately?
  • Is pose RMSD symmetry-corrected and separated from interaction or affinity claims?
  • Does the benchmark split test scaffold, protein-family, temporal, or structure-level generalization?
  • Is the protein-ligand split policy aligned with the claim?
  • Could training data or template databases leak a close protein, ligand, or bound complex into evaluation?
  • Are invalid generated structures filtered before ranking claims?