""" Check for primer dimers and cross-dimers. This module analyzes primer-primer interactions to identify potential dimer formation that can reduce PCR efficiency. """ import primer3 from typing import List, Dict def analyze_dimers( primer_list: List[str], temperature: float = 60.0, dg_threshold: float = -5.0, mv_conc: float = 50.0, dv_conc: float = 0.0, dntp_conc: float = 0.8, dna_conc: float = 50.0 ) -> Dict: """ Analyze primer dimers and cross-dimers for a set of primers. Parameters ---------- primer_list : list of str List of primer sequences to analyze temperature : float PCR annealing temperature in °C. Default: 60.0 dg_threshold : float ΔG threshold in kcal/mol for flagging dimers. Default: -5.0 Dimers with ΔG < threshold are likely to form mv_conc : float Monovalent cation concentration in mM. Default: 50.0 dv_conc : float Divalent cation concentration in mM. Default: 0.0 dntp_conc : float dNTP concentration in mM. Default: 0.8 dna_conc : float DNA concentration in nM. Default: 50.0 Returns ------- dict Dictionary containing: - 'interactions': list of all primer-primer interactions - 'problematic_dimers': list of dimers below threshold - 'has_issues': bool indicating if any dimers exceed threshold Example ------- >>> primers = ["ATGCGTACGATCGATCG", "CGTAGCTAGCTAGCTAG"] >>> analysis = analyze_dimers(primers, temperature=60.0) >>> if analysis['has_issues']: ... print("⚠ Primer dimers detected!") """ # Validate inputs primer_list = [p.upper().strip() for p in primer_list] if len(primer_list) < 2: raise ValueError("Need at least 2 primers to check for dimers") for primer in primer_list: if not all(base in 'ATCGN' for base in primer): raise ValueError(f"Invalid primer sequence: {primer}") interactions = [] problematic_dimers = [] # Check all pairwise interactions for i, primer1 in enumerate(primer_list): for j, primer2 in enumerate(primer_list): if i <= j: # Check each pair once, including self-dimers # Determine interaction type if i == j: interaction_type = "self-dimer" primer1_name = f"Primer_{i+1}" primer2_name = f"Primer_{i+1}" else: interaction_type = "cross-dimer" primer1_name = f"Primer_{i+1}" primer2_name = f"Primer_{j+1}" # Calculate homodimer (self-dimer) or heterodimer (cross-dimer) if i == j: result = primer3.calcHomodimer( primer1, mv_conc=mv_conc, dv_conc=dv_conc, dntp_conc=dntp_conc, dna_conc=dna_conc, temp_c=temperature, output_structure=True ) else: result = primer3.calcHeterodimer( primer1, primer2, mv_conc=mv_conc, dv_conc=dv_conc, dntp_conc=dntp_conc, dna_conc=dna_conc, temp_c=temperature, output_structure=True ) # Extract results dg = result.dg / 1000.0 # Convert cal/mol to kcal/mol tm = result.tm structure = result.ascii_structure if hasattr(result, 'ascii_structure') else "N/A" interaction = { 'type': interaction_type, 'primer1': primer1_name, 'primer2': primer2_name, 'primer1_seq': primer1, 'primer2_seq': primer2, 'dg': round(dg, 2), 'tm': round(tm, 2) if tm is not None else None, 'structure': structure, 'problematic': dg < dg_threshold, } interactions.append(interaction) if dg < dg_threshold: problematic_dimers.append(interaction) # Compile results results = { 'interactions': interactions, 'problematic_dimers': problematic_dimers, 'has_issues': len(problematic_dimers) > 0, 'num_primers': len(primer_list), 'num_interactions': len(interactions), 'num_problematic': len(problematic_dimers), 'parameters': { 'temperature': temperature, 'dg_threshold': dg_threshold, 'mv_conc': mv_conc, 'dv_conc': dv_conc, 'dntp_conc': dntp_conc, 'dna_conc': dna_conc, } } return results def check_3prime_complementarity( primer1: str, primer2: str, window_size: int = 5 ) -> Dict: """ Check for 3' end complementarity between two primers. 3' complementarity is critical as it can lead to primer extension and dimer formation during PCR. Parameters ---------- primer1 : str First primer sequence primer2 : str Second primer sequence window_size : int Number of bases at 3' end to check. Default: 5 Returns ------- dict Dictionary with 3' complementarity analysis Example ------- >>> result = check_3prime_complementarity("ATGCGTACGATCG", "CGATCGTACGCAT") >>> print(f"3' complementarity: {result['complementary_bases']} bp") """ from Bio.Seq import Seq primer1 = primer1.upper() primer2 = primer2.upper() # Get 3' ends primer1_3prime = primer1[-window_size:] primer2_3prime = primer2[-window_size:] # Get reverse complement of primer2's 3' end primer2_3prime_rc = str(Seq(primer2_3prime).reverse_complement()) # Count complementary bases at 3' end complementary_bases = 0 for i in range(min(len(primer1_3prime), len(primer2_3prime_rc))): if primer1_3prime[-(i+1)] == primer2_3prime_rc[i]: complementary_bases += 1 else: break is_problematic = complementary_bases >= 3 return { 'primer1_3prime': primer1_3prime, 'primer2_3prime': primer2_3prime, 'complementary_bases': complementary_bases, 'is_problematic': is_problematic, 'warning': f"High 3' complementarity ({complementary_bases} bp)" if is_problematic else None, } def analyze_multiplex_compatibility( primer_pairs: List[Dict], temperature: float = 60.0, dg_threshold: float = -5.0 ) -> Dict: """ Analyze compatibility of multiple primer pairs for multiplex PCR. Parameters ---------- primer_pairs : list of dict List of primer pair dictionaries, each with 'forward_seq' and 'reverse_seq' temperature : float PCR annealing temperature dg_threshold : float ΔG threshold for dimer flagging Returns ------- dict Multiplex compatibility analysis Example ------- >>> pairs = [ ... {'forward_seq': 'ATGC...', 'reverse_seq': 'CGTA...'}, ... {'forward_seq': 'GCTA...', 'reverse_seq': 'TAGC...'} ... ] >>> compat = analyze_multiplex_compatibility(pairs) >>> print(f"Multiplex compatible: {compat['is_compatible']}") """ # Collect all primers all_primers = [] primer_labels = [] for i, pair in enumerate(primer_pairs): all_primers.append(pair['forward_seq']) all_primers.append(pair['reverse_seq']) primer_labels.append(f"Pair{i+1}_F") primer_labels.append(f"Pair{i+1}_R") # Analyze all interactions dimer_analysis = analyze_dimers( primer_list=all_primers, temperature=temperature, dg_threshold=dg_threshold ) # Check Tm compatibility tm_values = [] for pair in primer_pairs: if 'forward_tm' in pair and 'reverse_tm' in pair: tm_values.extend([pair['forward_tm'], pair['reverse_tm']]) tm_range = max(tm_values) - min(tm_values) if tm_values else 0 tm_compatible = tm_range <= 5.0 # All primers should have Tm within 5°C # Compile multiplex results is_compatible = not dimer_analysis['has_issues'] and tm_compatible results = { 'is_compatible': is_compatible, 'num_pairs': len(primer_pairs), 'total_primers': len(all_primers), 'dimer_analysis': dimer_analysis, 'tm_range': round(tm_range, 2) if tm_values else None, 'tm_compatible': tm_compatible, 'recommendations': [], } # Add recommendations if dimer_analysis['has_issues']: results['recommendations'].append( f"Remove or redesign primers with problematic dimers (ΔG < {dg_threshold} kcal/mol)" ) if not tm_compatible: results['recommendations'].append( f"Adjust primer Tm values to be within 5°C (current range: {tm_range:.1f}°C)" ) if is_compatible: results['recommendations'].append("Primer set is compatible for multiplex PCR") return results