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references/target_annotations.md

Target Annotations and Features

Overview

Open Targets defines a target as "any naturally-occurring molecule that can be targeted by a medicinal product." Targets are primarily protein-coding genes identified by Ensembl gene IDs, but also include RNAs and pseudogenes from canonical chromosomes.

Core Target Annotations

1. Tractability Assessment

Tractability evaluates the druggability potential of a target across different modalities.

Modalities Assessed:

Small Molecule - Prediction of small molecule druggability - Based on structural features, chemical precedence - Buckets: Clinical precedence, Discovery precedence, Predicted tractable

Antibody - Likelihood of antibody-based therapeutic success - Cell surface/secreted protein location - Precedence categories similar to small molecules

PROTAC (Protein Degradation) - Assessment for targeted protein degradation - E3 ligase compatibility - Emerging modality category

Other Modalities - Gene therapy, RNA-based therapeutics - Oligonucleotide approaches

Tractability Levels:

  1. Clinical Precedence - Target of approved/clinical drug with similar mechanism
  2. Discovery Precedence - Target of tool compounds or compounds in preclinical development
  3. Predicted Tractable - Computational predictions suggest druggability
  4. Unknown - Insufficient data to assess

2. Safety Liabilities

Safety information aggregated from multiple sources to identify potential toxicity concerns.

Data Sources:

ToxCast - High-throughput toxicology screening data - In vitro assay results - Toxicity pathway activation

AOPWiki (Adverse Outcome Pathways) - Mechanistic pathways from molecular initiating event to adverse outcome - Systems toxicology frameworks

PharmGKB - Pharmacogenomic relationships - Genetic variants affecting drug response and toxicity

Published Literature - Expert-curated safety concerns from publications - Clinical trial adverse events

Safety Flags:

  • Organ toxicity - Liver, kidney, cardiac effects
  • Target safety liability - Known on-target toxic effects
  • Off-target effects - Unintended activity concerns
  • Clinical observations - Adverse events from drugs targeting gene

3. Baseline Expression

Gene/protein expression across tissues and cell types from multiple sources.

Data Sources:

Expression Atlas - RNA-Seq expression across tissues/conditions - Normalized expression levels (TPM, FPKM) - Differential expression studies

GTEx (Genotype-Tissue Expression) - Comprehensive tissue expression from healthy donors - Median TPM across 53 tissues - Expression variation analysis

Human Protein Atlas - Protein expression via immunohistochemistry - Subcellular localization - Tissue specificity classifications

Expression Metrics:

  • TPM (Transcripts Per Million) - Normalized RNA abundance
  • Tissue specificity - Enrichment in specific tissues
  • Protein level - Correlation with RNA expression
  • Subcellular location - Where protein is found in cell

4. Molecular Interactions

Protein-protein interactions, complex memberships, and molecular partnerships.

Interaction Types:

Physical Interactions - Direct protein-protein binding - Complex components - Sources: IntAct, BioGRID, STRING

Pathway Membership - Biological pathways from Reactome - Functional relationships - Upstream/downstream regulators

Target Interactors - Direct interactors relevant to disease associations - Context-specific interactions

5. Gene Essentiality

Dependency data indicating if gene is essential for cell survival.

Data Sources:

Project Score - CRISPR-Cas9 fitness screens - 300+ cancer cell lines - Scaled essentiality scores (0-1)

DepMap Portal - Large-scale cancer dependency data - Genetic and pharmacological perturbations - Common essential genes identification

Essentiality Metrics:

  • Score range: 0 (non-essential) to 1 (essential)
  • Context: Cell line specific vs. pan-essential
  • Therapeutic window: Selectivity between disease and normal cells

6. Chemical Probes and Tool Compounds

High-quality small molecules for target validation.

Sources:

Probes & Drugs Portal - Chemical probes with characterized selectivity - Quality ratings and annotations - Target engagement data

Structural Genomics Consortium (SGC) - Target Enabling Packages (TEPs) - Comprehensive target reagents - Freely available to academia

Probe Criteria: - Potency (typically IC50 < 100 nM) - Selectivity (>30-fold vs. off-targets) - Cell activity demonstrated - Negative control available

7. Pharmacogenetics

Genetic variants affecting drug response for drugs targeting the gene.

Data Source: ClinPGx

Information Included: - Variant-drug pairs - Clinical annotations (dosing, efficacy, toxicity) - Evidence level and sources - PharmGKB cross-references

Clinical Utility: - Dosing adjustments based on genotype - Contraindications for specific variants - Efficacy predictors

8. Genetic Constraint

Measures of negative selection against variants in the gene.

Data Source: gnomAD

Metrics:

pLI (probability of Loss-of-function Intolerance) - Range: 0-1 - pLI > 0.9 indicates intolerant to LoF variants - High pLI suggests essentiality

LOEUF (Loss-of-function Observed/Expected Upper bound Fraction) - Lower values indicate greater constraint - More interpretable than pLI across range

Missense Constraint - Z-scores for missense depletion - O/E ratios for missense variants

Interpretation: - High constraint suggests important biological function - May indicate safety concerns if inhibited - Essential genes often show high constraint

9. Comparative Genomics

Cross-species gene conservation and ortholog information.

Data Source: Ensembl Compara

Ortholog Data: - Mouse, rat, zebrafish, other model organisms - Orthology confidence (1:1, 1:many, many:many) - Percent identity and similarity

Utility: - Model organism studies transferability - Functional conservation assessment - Evolution and selective pressure

10. Cancer Annotations

Cancer-specific target features for oncology indications.

Data Sources:

Cancer Gene Census - Role in cancer (oncogene, TSG, fusion) - Tier classification (1 = established, 2 = emerging) - Tumor types and mutation types

Cancer Hallmarks - Functional roles in cancer biology - Hallmarks: proliferation, apoptosis evasion, metastasis, etc. - Links to specific cancer processes

Oncology Clinical Trials - Drugs in development targeting gene for cancer - Trial phases and indications

11. Mouse Phenotypes

Phenotypes from mouse knockout/mutation studies.

Data Source: MGI (Mouse Genome Informatics)

Phenotype Data: - Knockout phenotypes - Disease model associations - Mammalian Phenotype Ontology (MP) terms

Utility: - Predict on-target effects - Safety liability identification - Mechanism of action insights

12. Pathways

Biological pathway annotations placing target in functional context.

Data Source: Reactome

Pathway Information: - Curated biological pathways - Hierarchical organization - Pathway diagrams with target position

Applications: - Mechanism hypothesis generation - Related target identification - Systems biology analysis

Using Target Annotations in Queries

Query Template: Comprehensive Target Profile

query = """
  query targetProfile($ensemblId: String!) {
    target(ensemblId: $ensemblId) {
      id
      approvedSymbol
      approvedName
      biotype

      # Tractability
      tractability {
        label
        modality
        value
      }

      # Safety
      safetyLiabilities {
        event
        effects {
          dosing
          organsAffected
        }
      }

      # Expression
      expressions {
        tissue {
          label
        }
        rna {
          value
          level
        }
        protein {
          level
        }
      }

      # Chemical probes
      chemicalProbes {
        id
        probeminer
        origin
      }

      # Known drugs
      knownDrugs {
        uniqueDrugs
        rows {
          drug {
            name
            maximumClinicalTrialPhase
          }
          phase
          status
        }
      }

      # Genetic constraint
      geneticConstraint {
        constraintType
        score
        exp
        obs
      }

      # Pathways
      pathways {
        pathway
        pathwayId
      }
    }
  }
"""

variables = {"ensemblId": "ENSG00000157764"}

Annotation Interpretation Guidelines

For Target Prioritization:

  1. Druggability (Tractability):
  2. Clinical precedence >> Discovery precedence > Predicted
  3. Consider modality relevant to therapeutic approach

  4. Check for existing tool compounds

  5. Safety Assessment:

  6. Review organ toxicity signals
  7. Check expression in critical tissues
  8. Assess genetic constraint (high = safety concern if inhibited)

  9. Evaluate clinical adverse events from drugs

  10. Disease Relevance:

  11. Combine with association scores
  12. Check expression in disease-relevant tissues

  13. Review pathway context

  14. Validation Readiness:

  15. Chemical probes available?
  16. Model organism data supportive?

  17. Known drugs provide mechanism insight?

  18. Clinical Path Considerations:

  19. Pharmacogenetic factors
  20. Expression pattern (tissue-specific is better for selectivity)
  21. Essentiality (non-essential better for safety)

Red Flags:

  • High essentiality + ubiquitous expression - Poor therapeutic window
  • Multiple safety liabilities - Toxicity concerns
  • High genetic constraint (pLI > 0.9) - Critical gene, inhibition may be harmful
  • No tractability precedence - Higher risk, longer development
  • Conflicting evidence - Requires deeper investigation

Green Flags:

  • Clinical precedence + related indication - De-risked mechanism
  • Tissue-specific expression - Better selectivity
  • Chemical probes available - Faster validation
  • Low essentiality + disease relevance - Good therapeutic window
  • Multiple evidence types converge - Higher confidence
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