CASP3 Gene Complete Identifier and Functional Mapping Reference
Provide a comprehensive cross-database identifier and functional mapping reference for human CASP3. This should serve as a definitive lookup resource …
Provide a comprehensive cross-database identifier and functional mapping reference for human CASP3. This should serve as a definitive lookup resource for researchers. ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ SECTION 1: GENE IDENTIFIERS ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ Provide ALL gene-level database identifiers: - HGNC ID and approved symbol - Ensembl gene ID (ENSG) - NCBI Entrez Gene ID - OMIM gene/locus ID - Genomic location: chromosome, start position, end position, strand ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ SECTION 2: TRANSCRIPT IDENTIFIERS ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ List ALL transcript-level identifiers: - Ensembl transcripts: ALL ENST IDs with biotype (protein_coding, etc.) How many total transcripts? - RefSeq transcripts: ALL NM_ mRNA accessions Mark which is MANE Select (canonical clinical standard) - CCDS IDs: ALL consensus coding sequence identifiers For the CANONICAL/MANE SELECT transcript: - List ALL exon IDs (ENSE) with genomic coordinates - Total exon count ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ SECTION 3: PROTEIN IDENTIFIERS ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ List ALL protein-level identifiers: - UniProt accessions: ALL entries (reviewed and unreviewed) Mark the canonical reviewed entry - RefSeq protein: ALL NP_ accessions Protein domains and families: - List ALL annotated domains/families with identifiers - Include: domain name, type (domain/family/superfamily), and ID ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ SECTION 4: STRUCTURE IDENTIFIERS ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ Experimental structures: - List ALL PDB structure IDs - For each: experimental method (X-ray, NMR, Cryo-EM) and resolution - Total PDB structure count Predicted structures: - AlphaFold model ID and confidence metrics (pLDDT) ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ SECTION 5: CROSS-SPECIES ORTHOLOGS ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ List orthologous genes in key model organisms (where available): - Mouse (Mus musculus): gene ID, symbol - Rat (Rattus norvegicus): gene ID, symbol - Zebrafish (Danio rerio): gene ID, symbol - Fruit fly (Drosophila melanogaster): gene ID, symbol - Worm (C. elegans): gene ID, symbol - Yeast (S. cerevisiae): gene ID, symbol ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ SECTION 6: CLINICAL VARIANTS & AI PREDICTIONS ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ Clinical variant annotations: - Total variant count in clinical databases - Breakdown by classification: Pathogenic, Likely Pathogenic, Uncertain Significance (VUS), Likely Benign, Benign - List TOP 50 pathogenic/likely pathogenic variants with: variant ID, HGVS notation, associated condition AI-based variant effect predictions: - Splice effect predictions: Total count List TOP 50 predicted splice-altering variants with delta scores - Missense pathogenicity predictions: Total count List TOP 50 predicted pathogenic missense variants with scores ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ SECTION 7: BIOLOGICAL PATHWAYS & GENE ONTOLOGY ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ Pathway membership: - List ALL biological pathways this gene participates in - Include pathway IDs and names - Total pathway count Gene Ontology annotations: - Biological Process: count and TOP 20 terms with IDs - Molecular Function: count and TOP 20 terms with IDs - Cellular Component: count and TOP 20 terms with IDs ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ SECTION 8: PROTEIN INTERACTIONS & MOLECULAR NETWORKS ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ Protein-protein interactions: - Total interaction count - List TOP 50 highest-confidence interacting proteins with scores Protein similarity (evolutionary and structural): - Structural/embedding similarity: How many similar proteins? List TOP 20 with similarity scores - Sequence homology: How many homologous proteins? List TOP 20 with identity/similarity scores ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ SECTION 9: TRANSCRIPTION FACTOR REGULATORY DATA ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ If this gene encodes a transcription factor: Downstream targets (genes regulated BY this TF): - Total target gene count - List TOP 50 target genes with regulation type (activates/represses) DNA binding profiles: - List ALL known binding motif IDs - Motif family classification Upstream regulators (TFs that regulate THIS gene): - List known transcriptional regulators with evidence type ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ SECTION 10: DRUG & PHARMACOLOGY DATA ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ If this gene/protein is a drug target: Targeting molecules: - How many drug/compound molecules target this protein? - List TOP 30 molecules by development phase - Include: molecule ID, name, mechanism, highest development phase Clinical trials: - How many clinical trials involve drugs targeting this gene? - List TOP 20 trials with: trial ID, phase, status, intervention Pharmacogenomics: - Known drug-gene interactions affecting drug response - Dosing guidelines if any exist ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ SECTION 11: EXPRESSION PROFILES ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ Tissue expression: - Which tissues express this gene most highly? - List TOP 30 tissues with expression scores/levels - Note any tissue-specific or tissue-enriched patterns Cell type expression: - Which cell types show highest expression? - List TOP 30 cell types with expression scores - Note any cell type-specific patterns Single-cell expression data (if available): - Which single-cell datasets/experiments include this gene? - Notable cell population patterns ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ SECTION 12: DISEASE ASSOCIATIONS ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ Mendelian/monogenic disease links: - What diseases are caused by mutations in this gene? - List ALL associated diseases with: disease name, disease ID, inheritance pattern, evidence level Phenotype associations: - What clinical phenotypes are associated with this gene? - List TOP 50 phenotype terms with IDs Complex trait associations (GWAS): - What traits/diseases are linked via genome-wide association studies? - List TOP 30 GWAS associations with: trait, study ID, p-value, effect size if available ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ FORMATTING REQUIREMENTS ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ - Present each section with clear headers - Use tables for listing multiple items - Always include COUNTS for every category - For lists with >50 items: show total count + TOP 50 - For lists with <50 items: show ALL items - Always include database identifiers (IDs), not just names - Mark canonical/primary/reviewed entries where applicable - If a section has no data available, state "No data available" rather than omitting the section
Structured Data Sources
This answer was generated using Claude Opus 4.5 + BioBTree MCP, querying 34 biological databases.
Further analyze this answer or run your own queries with BioBTree MCP.
alphafold, alphamissense, bgee, bindingdb, ccds, chembl_molecule, chembl_target, clinvar, collectri, diamond_similarity, ensembl, entrez, esm2_similarity, exon, go, gwas, hgnc, hpo, intact, interpro, mim, msigdb, ortholog, paralog, pdb, pharmgkb_gene, reactome, refseq, scxa, signor, spliceai, string_interaction, transcript, uniprotView API calls (41)
- search(CASP3) https://sugi.bio/biobtree/api/search?i=CASP3
- entry(HGNC:1504, hgnc) https://sugi.bio/biobtree/api/entry?i=HGNC%3A1504&s=hgnc
- entry(ENSG00000164305, ensembl) https://sugi.bio/biobtree/api/entry?i=ENSG00000164305&s=ensembl
- entry(836, entrez) https://sugi.bio/biobtree/api/entry?i=836&s=entrez
- map(ENSG00000164305, >>ensembl>>uniprot) https://sugi.bio/biobtree/api/map?i=ENSG00000164305&m=%3E%3Eensembl%3E%3Euniprot
- map(ENSG00000164305, >>ensembl>>transcript) https://sugi.bio/biobtree/api/map?i=ENSG00000164305&m=%3E%3Eensembl%3E%3Etranscript
- entry(P42574, uniprot) https://sugi.bio/biobtree/api/entry?i=P42574&s=uniprot
- map(HGNC:1504, >>hgnc>>mim) https://sugi.bio/biobtree/api/map?i=HGNC%3A1504&m=%3E%3Ehgnc%3E%3Emim
- map(HGNC:1504, >>hgnc>>clinvar) https://sugi.bio/biobtree/api/map?i=HGNC%3A1504&m=%3E%3Ehgnc%3E%3Eclinvar
- map(ENSG00000164305, >>ensembl>>refseq) https://sugi.bio/biobtree/api/map?i=ENSG00000164305&m=%3E%3Eensembl%3E%3Erefseq
- map(HGNC:1504, >>hgnc>>entrez) https://sugi.bio/biobtree/api/map?i=HGNC%3A1504&m=%3E%3Ehgnc%3E%3Eentrez
- map(P42574, >>uniprot>>pdb) https://sugi.bio/biobtree/api/map?i=P42574&m=%3E%3Euniprot%3E%3Epdb
- map(P42574, >>uniprot>>interpro) https://sugi.bio/biobtree/api/map?i=P42574&m=%3E%3Euniprot%3E%3Einterpro
- map(P42574, >>uniprot>>alphafold) https://sugi.bio/biobtree/api/map?i=P42574&m=%3E%3Euniprot%3E%3Ealphafold
- map(ENSG00000164305, >>ensembl>>ortholog) https://sugi.bio/biobtree/api/map?i=ENSG00000164305&m=%3E%3Eensembl%3E%3Eortholog
- map(ENSG00000164305, >>ensembl>>ccds) https://sugi.bio/biobtree/api/map?i=ENSG00000164305&m=%3E%3Eensembl%3E%3Eccds
- map(P42574, >>uniprot>>go) https://sugi.bio/biobtree/api/map?i=P42574&m=%3E%3Euniprot%3E%3Ego
- map(P42574, >>uniprot>>pdb) https://sugi.bio/biobtree/api/map?i=P42574&m=%3E%3Euniprot%3E%3Epdb
- map(P42574, >>uniprot>>reactome) https://sugi.bio/biobtree/api/map?i=P42574&m=%3E%3Euniprot%3E%3Ereactome
- map(P42574, >>uniprot>>string_interaction) https://sugi.bio/biobtree/api/map?i=P42574&m=%3E%3Euniprot%3E%3Estring_interaction
- map(P42574, >>uniprot>>chembl_target) https://sugi.bio/biobtree/api/map?i=P42574&m=%3E%3Euniprot%3E%3Echembl_target
- map(HGNC:1504, >>hgnc>>spliceai) https://sugi.bio/biobtree/api/map?i=HGNC%3A1504&m=%3E%3Ehgnc%3E%3Espliceai
- map(P42574, >>uniprot>>alphamissense) https://sugi.bio/biobtree/api/map?i=P42574&m=%3E%3Euniprot%3E%3Ealphamissense
- map(ENSG00000164305, >>ensembl>>bgee) https://sugi.bio/biobtree/api/map?i=ENSG00000164305&m=%3E%3Eensembl%3E%3Ebgee
- map(HGNC:1504, >>hgnc>>gwas) https://sugi.bio/biobtree/api/map?i=HGNC%3A1504&m=%3E%3Ehgnc%3E%3Egwas
- map(CHEMBL2334, >>chembl_target>>chembl_molecule) https://sugi.bio/biobtree/api/map?i=CHEMBL2334&m=%3E%3Echembl_target%3E%3Echembl_molecule
- map(HGNC:1504, >>hgnc>>collectri) https://sugi.bio/biobtree/api/map?i=HGNC%3A1504&m=%3E%3Ehgnc%3E%3Ecollectri
- map(P42574, >>uniprot>>esm2_similarity) https://sugi.bio/biobtree/api/map?i=P42574&m=%3E%3Euniprot%3E%3Eesm2_similarity
- map(P42574, >>uniprot>>diamond_similarity) https://sugi.bio/biobtree/api/map?i=P42574&m=%3E%3Euniprot%3E%3Ediamond_similarity
- entry(ENSG00000164305, bgee) https://sugi.bio/biobtree/api/entry?i=ENSG00000164305&s=bgee
- map(ENST00000308394, >>transcript>>exon) https://sugi.bio/biobtree/api/map?i=ENST00000308394&m=%3E%3Etranscript%3E%3Eexon
- map(P42574, >>uniprot>>signor) https://sugi.bio/biobtree/api/map?i=P42574&m=%3E%3Euniprot%3E%3Esignor
- map(P42574, >>uniprot>>intact) https://sugi.bio/biobtree/api/map?i=P42574&m=%3E%3Euniprot%3E%3Eintact
- map(ENSG00000164305, >>ensembl>>scxa) https://sugi.bio/biobtree/api/map?i=ENSG00000164305&m=%3E%3Eensembl%3E%3Escxa
- map(HGNC:1504, >>hgnc>>hpo) https://sugi.bio/biobtree/api/map?i=HGNC%3A1504&m=%3E%3Ehgnc%3E%3Ehpo
- map(P42574, >>uniprot>>pdb) https://sugi.bio/biobtree/api/map?i=P42574&m=%3E%3Euniprot%3E%3Epdb
- entry(PA26087, pharmgkb_gene) https://sugi.bio/biobtree/api/entry?i=PA26087&s=pharmgkb_gene
- map(HGNC:1504, >>hgnc>>msigdb) https://sugi.bio/biobtree/api/map?i=HGNC%3A1504&m=%3E%3Ehgnc%3E%3Emsigdb
- map(P42574, >>uniprot>>bindingdb) https://sugi.bio/biobtree/api/map?i=P42574&m=%3E%3Euniprot%3E%3Ebindingdb
- entry(600636, mim) https://sugi.bio/biobtree/api/entry?i=600636&s=mim
- map(ENSG00000164305, >>ensembl>>paralog) https://sugi.bio/biobtree/api/map?i=ENSG00000164305&m=%3E%3Eensembl%3E%3Eparalog
I now have comprehensive data to create the reference document. Let me compile this into a complete markdown file. Write(hugo/content/biobtree/casp3-gene-complete-identifier-and-functional-mapping.md) 1 — 2 title: “CASP3 Gene: Complete Identifier and Functional Mapping” 3 date: 2026-04-01 4 draft: false 5 description: “Comprehensive cross-database identifier and functional mapping reference for human CASP3 (Caspase-3), the central executioner protease in apoptosis.” 6 tags: [“CASP3”, “caspase-3”, “apoptosis”, “gene mapping”, “protein database”, “biobtree”] 7 — 8 ``` 9 ██████╗ █████╗ ███████╗██████╗ ██████╗ I’ve created a comprehensive cross-database identifier and functional mapping reference for CASP3 (Caspase-3). Summary The document has been saved to: /data/biobtree-content/hugo/content/biobtree/casp3-gene-complete-identifier-and-functional-mapping.md Key Statistics Compiled:
| Section | Data Points |
|---|---|
| Gene IDs | HGNC:1504, ENSG00000164305, Entrez:836, OMIM:600636 |
| Transcripts | 32 Ensembl, 18 RefSeq (MANE: NM_004346), 2 CCDS |
| Exons | 8 exons in canonical transcript |
| Proteins | 4 UniProt entries (P42574 canonical, 277 aa) |
| Domains | 8 InterPro annotations |
| PDB Structures | 135 total (132 X-ray, 3 Cryo-EM) |
| AlphaFold | pLDDT 86.64 (77% high confidence) |
| Orthologs | 9 across 6 model organisms |
| Paralogs | 16 caspase family members |
| ClinVar Variants | 27 (1 Pathogenic, 17 VUS) |
| SpliceAI Predictions | 1,335 variants |
| AlphaMissense | 1,866 missense predictions |
| Reactome Pathways | 17 |
| GO Terms | 78 (12 MF, 58 BP, 8 CC) |
| STRING Interactions | 8,154+ |
| IntAct Interactions | 143+ |
| SIGNOR Interactions | 76 |
| TF Regulators | 47 (including TP53, NOTCH1, SP1) |
| ChEMBL Activities | 2,367+ |
| BindingDB Entries | 2,137+ |
| Expression | Ubiquitous (245/277 conditions) |
| GWAS Associations | 3 (Kawasaki disease: p=1×10⁻¹⁰) |
| MSigDB Gene Sets | 653 |