"""Clinical bioinformatics workflow example."""
from biopython_mcp.alignment import pairwise_align
from biopython_mcp.database import search_pubmed
from biopython_mcp.sequence import calculate_gc_content, translate_sequence
def analyze_patient_mutation() -> None:
"""
Simulate analyzing a patient's genetic variant.
This example demonstrates a clinical workflow for analyzing
a potential pathogenic mutation in the TP53 gene.
"""
print("=== Clinical Mutation Analysis Workflow ===\n")
print("Step 1: Research Background")
print("-" * 50)
print("Searching PubMed for TP53 mutation information...\n")
search_result = search_pubmed(
query="TP53 mutation clinical significance",
max_results=3,
email="clinician@example.com",
)
if search_result["success"]:
print(f"Found {search_result['count']} relevant articles:\n")
for i, article in enumerate(search_result["results"], 1):
print(f"{i}. PMID: {article['pmid']}")
print(f" Title: {article['title']}")
print(f" Abstract: {article['abstract'][:150]}...\n")
print("\nStep 2: Fetch Reference Sequence")
print("-" * 50)
print("Fetching TP53 reference sequence from GenBank...\n")
reference_seq = "ATGGAGGAGCCGCAGTCAGATCCTAGCGTCGAGCCCCCTCTGAGTCAGGAAACATTTTCAGACCTATGGAAACTACTTCCTGAAAACAACGTTCTGTCCCCCTTGCCGTCCCAAGCAATGGATGATTTGATGCTGTCCCCGGACGATATTGAACAATGGTTCACTGAAGACCCAGGTCCAGATGAAGCTCCCAGAATGCCAGAGGCTGCTCCCCCCGTGGCCCCTGCACCAGCAGCTCCTACACCGGCGGCCCCTGCACCAGCCCCCTCCTGGCCCCTGTCATCTTCTGTCCCTTCCCAGAAAACCTACCAGGGCAGCTACGGTTTCCGTCTGGGCTTCTTGCATTCTGGGACAGCCAAGTCTGTGACTTGCACGTACTCCCCTGCCCTCAACAAGATGTTTTGCCAACTGGCCAAGACCTGCCCTGTGCAGCTGTGGGTTGATTCCACACCCCCGCCCGGCACCCGCGTCCGCGCCATGGCCATCTACAAGCAGTCACAGCACATGACGGAGGTTGTGAGGCGCTGCCCCCACCATGAGCGCTGCTCAGATAGCGATGGTCTGGCCCCTCCTCAGCATCTTATCCGAGTGGAAGGAAATTTGCGTGTGGAGTATTTGGATGACAGAAACACTTTTCGACATAGTGTGGTGGTGCCCTATGAGCCGCCTGAGGTTGGCTCTGACTGTACCACCATCCACTACAACTACATGTGTAACAGTTCCTGCATGGGCGGCATGAACCGGAGGCCCATCCTCACCATCATCACACTGGAAGACTCCAGTGGTAATCTACTGGGACGGAACAGCTTTGAGGTGCGTGTTTGTGCCTGTCCTGGGAGAGACCGGCGCACAGAGGAAGAGAATCTCCGCAAGAAAGGGGAGCCTCACCACGAGCTGCCCCCAGGGAGCACTAAGCGAGCACTGCCCAACAACACCAGCTCCTCTCCCCAGCCAAAGAAGAAACCACTGGATGGAGAATATTTCACCCTTCAGATCCGTGGGCGTGAGCGCTTCGAGATGTTCCGAGAGCTGAATGAGGCCTTGGAACTCAAGGATGCCCAGGCTGGGAAGGAGCCAGGGGGGAGCAGGGCTCACTCCAGCCACCTGAAGTCCAAAAAGGGTCAGTCTACCTCCCGCCATAAAAAACTCATGTTCAAGACAGAAGGGCCTGACTCAGACTGACATTCTCCACTTCTTGTTCCCCACTGACAGCCTCCCACCCCCATCTCTCCCTCCCCTGCCATTTTGGGTTTTGGGTCTTTGAACCCTTGCTTGCAATAGGTGTGCGTCAGAAGCACCCAGGACTTCCATTTGCTTTGTCCCGGGGCTCCACTGAACAAGTTGGCCTGCACTGGTGTTTTGTTGTGGGGAGGAGGATGGGGAGTAGGACATACCAGCTTAGATTTTAAGGTTTTTACTGTGAGGGATGTTTGGGAGATGTAAGAAATGTTCTTGCAGTTAAGGGTTAGTTTACAATCAGCCACATTCTAGGTAGGGGCCCACTTCACCGTACTAACCAGGGAAGCTGTCCCTCACTGTTGAATTTTCTCTAACTTCAAGGCCCATATCTGTGAAATGCTGGCATTTGCACCTACCTCACAGAGTGCATTGTGAGGGTTAATGAAATAATGTACATCTGGCCTTGAAACCACCTTTTATTACATGGGGTCTAGAACTTGACCCCCTTGAGGGTGCTTGTTCCCTCTCCCTGTTGGTCGGTGGGTTGGTAGTTTCTACAGTTGGGCAGCTGGTTAGGTAGAGGGAGTTGTCAAGTCTCTGCTGGCCCAGCCAAACCCTGTCTGACAACCTCTTGGTGAACCTTAGTACCTAAAAGGAAATCTCACCCCATCCCACACCCTGGAGGATTTCATCTCTTGTATATGATGATCTGGATCCACCAAGACTTGTTTTATGCTCAGGGTCAATTTCTTTTTTCTTTTTTTTTTTTTTTTTTCTTTTTCTTTGAGACTGGGTCTCGCTTTGTTGCCCAGGCTGGAGTGGAGTGGCGTGATCTTGGCTTACTGCAGCCTTTGCCTCCCCGGCTCGAGCAGTCCTGCCTCAGCCTCCGGAGTAGCTGGGACCACAGGTTCATGCCACCATGGCCAGCCAACTTTTGCATGTTTTGTAGAGATGGGGTCTCACAGTGTTGCCCAGGCTGGTCTCAAACTCCTGGGCTCAGGCGATCCACCTGTCTCAGCCTCCCAGAGTGCTGGGATTACAATTGTGAGCCACCACGTCCAGCTGGAAGGGTCAACATCTTTTACATTCTGCAAGCACATCTGCATTTTCACCCCACCCTTCCCCTCCTTCTCCCTTTTTATATCCCATTTTTATATCGATCTCTTATTTTACAATAAAACTTTGCTGCCA"
print(f"Reference sequence length: {len(reference_seq)} bp\n")
patient_seq = "ATGGAGGAGCCGCAGTCAGATCCTAGCGTCGAGCCCCCTCTGAGTCAGGAAACATTTTCAGACCTATGGAAACTACTTCCTGAAAACAACGTTCTGTCCCCCTTGCCGTCCCAAGCAATGGATGATTTGATGCTGTCCCCGGACGATATTGAACAATGGTTCACTGAAGACCCAGGTCCAGATGAAGCTCCCAGAATGCCAGAGGCTGCTCCCCCCGTGGCCCCTGCACCAGCAGCTCCTACACCGGCGGCCCCTGCACCAGCCCCCTCCTGGCCCCTGTCATCTTCTGTCCCTTCCCAGAAAACCTACCAGGGCAGCTACGGTTTCCGTCTGGGCTTCTTGCATTCTGGGACAGCCAAGTCTGTGACTTGCACGTACTCCCCTGCCCTCAACAAGATGTTTTGCCAACTGGCCAAGACCTGCCCTGTGCAGCTGTGGGTTGATTCCACACCCCCGCCCGGCACCCGCGTCCGCGCCATGGCCATCTACAAGCAGTCACAGCACATGACGGAGGTTGTGAGGCGCTGCCCCCACCATGAGCGCTGCTCAGATAGCGATGGTCTGGCCCCTCCTCAGCATCTTATCCGAGTGGAAGGAAATTTGCGTGTGGAGTATTTGGATGACAGAAACACTTTTCGACATAGTGTGGTGGTGCCCTATGAGCCGCCTGAGGTTGGCTCTGACTGTACCACCATCCACTACAACTACATGTGTAACAGTTCCTGCATGGGCGGCATGAACCGGAGGCCCATCCTCACCATCATCACACTGGAAGACTCCAGTGGTAATCTACTGGGACGGAACAGCTTTGAGGTGCGTGTTTGTGCCTGTCCTGGGAGAGACCGGCGCACAGAGGAAGAGAATCTCCGCAAGAAAGGGGAGCCTCACCACGAGCTGCCCCCAGGGAGCACTAAGCGAGCACTGCCCAACAACACCAGCTCCTCTCCCCAGCCAAAGAAGAAACCACTGGATGGAGAATATTTCACCCTTCAGATCCGTGGGCGTGAGCGCTTCGAGATGTTCCGAGAGCTGAATGAGGCCTTGGAACTCAAGGATGCCCAGGCTGGGAAGGAGCCAGGGGGGAGCAGGGCTCACTCCAGCCACCTGAAGTCCAAAAAGGGTCAGTCTACCTCCCGCCATAAAAAACTCATGTTCAAGACAGAAGGGCCTGACTCAGACTGA"
print(f"Patient sequence length: {len(patient_seq)} bp")
print("(Simulated patient sequence - truncated for example)\n")
print("\nStep 3: Compare Sequences")
print("-" * 50)
print("Performing global alignment...\n")
alignment_result = pairwise_align(reference_seq[:500], patient_seq[:500], mode="global")
if alignment_result["success"]:
print(f"Alignment Score: {alignment_result['score']}")
print("Note: High score indicates high similarity\n")
print("\nStep 4: Translate to Protein")
print("-" * 50)
print("Reference protein:")
ref_protein = translate_sequence(reference_seq[:600], to_stop=True)
if ref_protein["success"]:
print(f" {ref_protein['protein_sequence'][:50]}...")
print(f" Length: {ref_protein['protein_length']} amino acids\n")
print("Patient protein:")
pat_protein = translate_sequence(patient_seq[:600], to_stop=True)
if pat_protein["success"]:
print(f" {pat_protein['protein_sequence'][:50]}...")
print(f" Length: {pat_protein['protein_length']} amino acids\n")
print("\nStep 5: Analyze GC Content")
print("-" * 50)
ref_gc = calculate_gc_content(reference_seq[:600])
pat_gc = calculate_gc_content(patient_seq[:600])
if ref_gc["success"] and pat_gc["success"]:
print(f"Reference GC%: {ref_gc['gc_content_percent']}%")
print(f"Patient GC%: {pat_gc['gc_content_percent']}%")
print(
f"Difference: {abs(ref_gc['gc_content_percent'] - pat_gc['gc_content_percent']):.2f}%\n"
)
print("\nStep 6: Clinical Interpretation")
print("-" * 50)
print("Summary:")
print(" - Sequences aligned successfully")
print(" - Protein sequences compared")
print(" - Further analysis would include:")
print(" * Identifying specific mutations")
print(" * Checking variant databases (ClinVar, COSMIC)")
print(" * Assessing pathogenicity predictions")
print(" * Reviewing relevant literature")
print(" * Clinical correlation with patient phenotype\n")
def main() -> None:
"""Run the clinical workflow example."""
print("\n" + "=" * 60)
print("BioPython MCP - Clinical Workflow Example")
print("=" * 60 + "\n")
analyze_patient_mutation()
print("=" * 60)
print("Workflow completed!")
print("=" * 60 + "\n")
print("Note: This is a simplified example for demonstration.")
print("Real clinical analysis requires additional validation,")
print("expert interpretation, and adherence to clinical guidelines.\n")
if __name__ == "__main__":
main()
