B bX@sdZddlZddlZddlmZmZddlmZddlmZddddddd d d d d dddddddZddddddddddddddddd dZ dd!d"ddddd#d$d%d&d'd(d)d*d+d,dZ d-d.dddddd/d$d$d&d'd(d)d*d+d0dZ d1dddddddd2d3d4d5d6d7d8d9d:dZ d;dd?d@dAdBdCdDdEdFdZ dGdHddddddIdJdKdLdMdNdOdPdQdRdSdTdUdVdWdXdYdZd[d\d]d^Zd_ddddddd`dadbdcdddedfdgdhdidjdkdldmdndodpZdqdrdsdtdudvdwdxdydzd{d|d}d}d~dddddddddddddddddddddddddddddddddddddddddddddddddddddddddddddddddddddddddǜWZddddddddddddddddddddddddddddddddddddddddddddddddd0Zddddddddddddddddddd d d d d dddddddddd Zddddddddd d!d"d#ddddd$d%d&d'd$d%d&d'd(d)d*d*d+d,d-d.d/d0d1d2d(d)d*d*d3d4d5d6d3d4d5d6d70ZdUd8d9Zd:d;ZdVd=d>ZdWdAdBZdXdDdEZdYdHdIZdJdKZdZdOdPZd[dQdRZedSkrddTlmZedS(\aCalculate the melting temperature of nucleotide sequences. This module contains three different methods to calculate the melting temperature of oligonucleotides: 1. Tm_Wallace: 'Rule of thumb' 2. Tm_GC: Empirical formulas based on GC content. Salt and mismatch corrections can be included. 3. Tm_NN: Calculation based on nearest neighbor thermodynamics. Several tables for DNA/DNA, DNA/RNA and RNA/RNA hybridizations are included. Correction for mismatches, dangling ends, salt concentration and other additives are available. Tm_staluc is the 'old' NN calculation and is kept for compatibility. It is, however, recommended to use Tm_NN instead, since Tm_staluc may be depreceated in the future. Also, Tm_NN has much more options. Using Tm_staluc and Tm_NN with default parameters gives (essentially) the same results. General parameters for most Tm methods: - seq -- A Biopython sequence object or a string. - check -- Checks if the sequence is valid for the given method (default= True). In general, whitespaces and non-base characters are removed and characters are converted to uppercase. RNA will be backtranscribed. - strict -- Do not allow base characters or neighbor duplex keys (e.g. 'AT/NA') that could not or not unambigiously be evaluated for the respective method (default=True). Note that W (= A or T) and S (= C or G) are not ambiguous for Tm_Wallace and Tm_GC. If 'False', average values (if applicable) will be used. This module is not able to detect self-complementary and it will not use alignment tools to align an oligonucleotide sequence to its target sequence. Thus it can not detect dangling-ends and mismatches by itself (don't even think about bulbs and loops). These parameters have to be handed over to the respective method. Other public methods of this module: - make_table : To create a table with thermodynamic data. - salt_correction: To adjust Tm to a given salt concentration by different formulas. This method is called from Tm_GC and Tm_NN but may also be accessed 'manually'. It returns a correction term, not a corrected Tm! - chem_correction: To adjust Tm regarding the chemical additives DMSO and formaldehyde. The method returns a corrected Tm. Chemical correction is not an integral part of the Tm methods and must be called additionally. For example: >>> from Bio.SeqUtils import MeltingTemp as mt >>> from Bio.Seq import Seq >>> mystring = 'CGTTCCAAAGATGTGGGCATGAGCTTAC' >>> myseq = Seq(mystring) >>> print('%0.2f' % mt.Tm_Wallace(mystring)) 84.00 >>> print('%0.2f' % mt.Tm_Wallace(myseq)) 84.00 >>> print('%0.2f' % mt.Tm_GC(myseq)) 58.73 >>> print('%0.2f' % mt.Tm_NN(myseq)) 60.32 Tm_NN with default values gives same result as 'old' Tm_staluc. However, values differ for RNA, since Tm_staluc had some errors for RNA calculation. These errors have been fixed in this version. New Tm_NN can do slightly more: Using different thermodynamic tables, e.g. from Breslauer '86 or Sugimoto '96: >>> print('%0.2f' % mt.Tm_NN(myseq, nn_table=mt.DNA_NN1)) # Breslauer '86 72.19 >>> print('%0.2f' % mt.Tm_NN(myseq, nn_table=mt.DNA_NN2)) # Sugimoto '96 65.47 Tables for RNA and RNA/DNA hybrids are included: >>> print('%0.2f' % mt.Tm_NN(myseq, nn_table=mt.RNA_NN1)) # Freier '86 73.35 >>> print('%0.2f' % mt.Tm_NN(myseq, nn_table=mt.R_DNA_NN1)) # Sugimoto '95 58.45 Several types of salc correction (for Tm_NN and Tm_GC): >>> for i in range(1, 8): ... print("Type: %d, Tm: %0.2f" % (i, Tm_NN(myseq, saltcorr=i))) ... Type: 1, Tm: 54.27 Type: 2, Tm: 54.02 Type: 3, Tm: 59.60 Type: 4, Tm: 60.64 Type: 5, Tm: 60.32 Type: 6, Tm: 59.78 Type: 7, Tm: 59.78 Correction for other monovalent cations (K+, Tris), Mg2+ and dNTPs according to von Ahsen et al. (2001) or Owczarzy et al. (2008) (for Tm_NN and Tm_GC): >>> print('%0.2f' % mt.Tm_NN(myseq, Na=50, Tris=10)) 60.79 >>> print('%0.2f' % mt.Tm_NN(myseq, Na=50, Tris=10, Mg=1.5)) 67.39 >>> print('%0.2f' % mt.Tm_NN(myseq, Na=50, Tris=10, Mg=1.5, saltcorr=7)) 66.81 >>> print('%0.2f' % mt.Tm_NN(myseq, Na=50, Tris=10, Mg=1.5, dNTPs=0.6, ... saltcorr=7)) 66.04 Dangling ends and mismatches, e.g.:: Oligo: CGTTCCaAAGATGTGGGCATGAGCTTAC CGTTCCaAAGATGTGGGCATGAGCTTAC ::::::X::::::::::::::::::::: or ::::::X::::::::::::::::::::: Template: GCAAGGcTTCTACACCCGTACTCGAATG TGCAAGGcTTCTACACCCGTACTCGAATGC Here: >>> print('%0.2f' % mt.Tm_NN('CGTTCCAAAGATGTGGGCATGAGCTTAC')) 60.32 >>> print('%0.2f' % mt.Tm_NN('CGTTCCAAAGATGTGGGCATGAGCTTAC', ... c_seq='GCAAGGcTTCTACACCCGTACTCGAATG')) 55.39 >>> print('%0.2f' % mt.Tm_NN('CGTTCCAAAGATGTGGGCATGAGCTTAC', shift=1, ... c_seq='TGCAAGGcTTCTACACCCGTACTCGAATGC')) 55.69 The same for RNA: >>> print('%0.2f' % mt.Tm_NN('CGUUCCAAAGAUGUGGGCAUGAGCUUAC', ... c_seq='UGCAAGGcUUCUACACCCGUACUCGAAUGC', ... shift=1, nn_table=mt.RNA_NN3, ... de_table=mt.RNA_DE1)) 73.00 Note, that thermodynamic data are not available for all kind of mismatches, e.g. most double mismatches or terminal mismatches combined with dangling ends: >>> print('%0.2f' % mt.Tm_NN('CGTTCCAAAGATGTGGGCATGAGCTTAC', ... c_seq='TtCAAGGcTTCTACACCCGTACTCGAATGC', ... shift=1)) Traceback (most recent call last): ValueError: no thermodynamic data for neighbors '.C/TT' available Make your own tables, or update/extend existing tables. E.g., add values for locked nucleotides. Here, 'locked A' (and its complement) should be represented by '1': >>> mytable = mt.make_table(oldtable=mt.DNA_NN3, ... values={'A1/T1':(-6.608, -17.235), ... '1A/1T':(-6.893, -15.923)}) >>> print('%0.2f' % mt.Tm_NN('CGTTCCAAAGATGTGGGCATGAGCTTAC')) 60.32 >>> print('%0.2f' % mt.Tm_NN('CGTTCCA1AGATGTGGGCATGAGCTTAC', ... nn_table=mytable, check=False)) ... # 'check' must be False, otherwise '1' would be discarded 62.53 N)SeqUtilsSeq)BiopythonWarning)BiopythonDeprecationWarning)rr)rg0)rg4)rg)g333333"g8)g333333!gfffff7)ggfffff0)g333333g))ggL1)g333333g4)gffffffg+)g'g;)g333333&g33333:)g&g:)initzinit_A/Tzinit_G/Cz init_oneG/Cz init_allA/Tz init_5T/AsymzAA/TTzAT/TAzTA/ATzCA/GTzGT/CAzCT/GAzGA/CTzCG/GCzGC/CGzGG/CC)g333333?g")rgffffff)g gfffff5)gffffffgffffff.)gffffffgffffff2)gffffff g5)g"g9)gffffffgffffff0)g!g7)g'g=)g%gffffff:)g%gffffff<)gffffff@gffffff@)g?gffffff)gg3333336)ggffffff4)ggL5)g!g333336)g gffffff6)g333333g5)gffffff g3333336)g333333%g333333;)g#gffffff8)g gfffff3)g?g)g@g@)gffffffgL5)g g3)rg%)gg/)g333333 g6)g%g;)gffffff$g333333:)gffffffg3333333)g*gA)g gffffff3)gffffff,g33333sA)gffffff(g33333=)gzG @g)g(\ @g%@)gHzGg3)g(\"g33333:)g(\g4)gzG$gfffff:)g&g=)g(\$g;)gzG(g@@)gHzG%g33333:)g(\-g33333sB)gHz*gY@)g@g(\@)g@gGz&@)g\(\g3)gQ8"g9)g!gfffff6)g(\&g<)g(\'gL?)g%g<)gQk*g33333sA)g(\%gffffff;)g ףp= 0gLD)g\(\,gA)g)\+g33333sG)gR1gYL)gGzg333333')gQg)g(\$g?)gHzG)g33333sC)g(\g5)g= ףp=g+)gzG"g333338)gQg0)gGz.&g<)rzinit_A/Tzinit_G/Cz init_oneG/Cz init_allA/Tz init_5T/ArzAA/TTzAT/TAzTA/ATzCA/GTzGT/CAzCT/GAzGA/CTzCG/GCzGC/CGzGG/CCzGT/TGzGG/TTzAG/TTzTG/ATzTT/AGzTG/GTzAT/TGzCG/GTzCT/GGzGG/CTzGT/CG)gffffff?g333333)g'g333333B)g333333g5)gg333333)g gfffff7)g$gffffff<)g)gfffff?)gL0ǧG)g333333"g7)g333333!gfffff6)g g1)g"g3333337)gg()g333333g3333337)gg+)g"g:)g333333gfffff5)rzinit_A/Tzinit_G/Cz init_oneG/Cz init_allA/Tz init_5T/ArzTT/AAzGT/CAzCT/GAzAT/TAzTG/ACzGG/CCzCG/GCzAG/TCzTC/AGzGC/CGzCC/GGzAC/TGzTA/ATzGA/CTzCA/GTzAA/TT)g?g?)gg )gffffffgffffff')gffffffg )gffffff @g$@)g333333@gL0@)gg()gffffff@g#@)gg333333)gffffffg)gg333333)g333333gffffff)gffffffgffffff)ggffffff*)g333333g)g?g @)gffffff?gffffff?)g@g@)gffffff?g?)g333333g)gg)ggffffff)gffffff@g@)g@g+@)g333333?gffffff?)g?gffffff?)gffffff@gffffff@)g333333@g333333-@)gffffff?g @)g333333?g333333)g@gffffff,@)gffffffgffffff)g333333 @g @)gffffff@g3333334@)g333333?g333333?)gg)g333333g#)g@g)@)gg)gg)g @g!@)gffffff@gffffff0@)gg#)gg.)gg/)g?g @)gg%)gg/)gg )g?g)g!g9)ggffffff1)g!gffffff9)gg+)ggffffff+)g333333g3)g g7)gg333333))g g9)g333333 gffffff&)gffffffg)ggffffff)g@g!@)g333333g5)gg4)gffffffg3333334)g\(\?gffffff)gg6)gffffffg333332)gg333333)gg333333)g g333333%)g?g)g333333g333333()gg/)gffffffg!)g?g)g?g?)gffffff@gL5@)gg )g333333@gfffff0@)gffffffg6)gffffff g')g?gffffff)g?g@)gg)WzAG/TTzAT/TGzCG/GTzCT/GGzGG/CTzGG/TTzGT/CGzGT/TGzTG/ATzTG/GTzTT/AGzAA/TGzAG/TAzCA/GGzCG/GAzGA/CGzGG/CAzTA/AGzTG/AAzAC/TTzAT/TCzCC/GTzCT/GCzGC/CTzGT/CCzTC/ATzTT/ACzAA/TCzAC/TAzCA/GCzCC/GAzGA/CCzGC/CAzTA/ACzTC/AAzAA/TAzCA/GAzGA/CAzTA/AAzAC/TCzCC/GCzGC/CCzTC/ACzAG/TGzCG/GGzGG/CGzTG/AGzAT/TTzCT/GTzGT/CTzTT/ATzAI/TCzTI/ACzAC/TIzTC/AIzCI/GCzGI/CCzCC/GIzGC/CIzAI/TAzTI/AAzAA/TIzTA/AIzCI/GAzGI/CAzCA/GIzGA/CIzAI/TTzTI/ATzAT/TIzTT/AIzCI/GTzGI/CTzCT/GIzGT/CIzAI/TGzTI/AGzAG/TIzTG/AIzCI/GGzGI/CGzCG/GIzGG/CIzAI/TIzTI/AIzCI/GIzGI/CI)gg333333)gg333333)g333333gffffff%)g g6)gg?)gffffffg)ggffffff)g333333g333333%)gg)gg)gffffffg#)gffffffg3333333)g333333g)g g!)gffffffgfffff0)gg3333335)gg)ggffffff)gg)gg)gg+)g gffffff)gffffffg)gg)gg333333)gffffffg333333)g g )gg+)gg333333)gffffffg333333)gffffffg)gg)g333333g333333#)gg/)g333333g333333&)gffffffg&)gg)g333333g333333)g gffffff!)g g")gffffffg")gffffffg333332)gg/)gg0)g333333g%)g g#)0zAA/TAzTA/AAzCA/GAzGA/CAzAC/TCzTC/ACzCC/GCzGC/CCzAG/TGzTG/AGzCG/GGzGG/CGzAT/TTzTT/ATzCT/GTzGT/CTzAA/TCzAC/TAzCA/GCzCC/GAzGA/CCzGC/CAzTA/ACzTC/AAzAC/TTzAT/TCzCC/GTzCT/GCzGC/CTzGT/CCzTC/ATzTT/ACzAA/TGzAG/TAzCA/GGzCG/GAzGA/CGzGG/CAzTA/AGzTG/AAzAG/TTzAT/TGzCG/GTzCT/GGzGG/CTzGT/CGzTG/ATzTT/AG)g?gffffff@)g333333g1)g g$)g333333gffffff)g333333?gffffff @)gg333333))gg')gffffffg*)gg)gffffffg,)g333333g%)gg.)gg4)gg%)gg+)gɿg)gffffffg)gg333333)gg0)gg)g@g-@)gɿg)gg)g@gffffff,@)gg )g333333gffffff&)g g$)gffffffg333333*)g333333@g$@)gg333333*)gg.)gffffffg333333)) zAA/.TzAC/.GzAG/.CzAT/.AzCA/.TzCC/.GzCG/.CzCT/.AzGA/.TzGC/.GzGG/.CzGT/.AzTA/.TzTC/.GzTG/.CzTT/.Az.A/ATz.C/AGz.G/ACz.T/AAz.A/CTz.C/CGz.G/CCz.T/CAz.A/GTz.C/GGz.G/GCz.T/GAz.A/TTz.C/TGz.G/TCz.T/TA)ggffffff*)gg)gg333333.)gffffffg)g"g7)gffffffg333333%)g333333!g3333336)gg(\O4)ggL4)gffffffg)ggffffff0)g gffffff#)gg0)gffffffgffffff)g333333gffffff0)gg333333)gg333333)g@g6@)g333333?g@)gg)gffffff?g @)gffffffg-)gٿg)g333333gffffff)gffffff @g333333'@)g?g @)gffffffg)g?gffffff@)g@g333333 @)gffffff?g @)g@g333333%@)0z.T/AAz.T/CAz.T/GAz.T/TAz.G/ACz.G/CCz.G/GCz.G/TCz.C/AGz.C/CGz.C/GGz.C/TGz.T/AGz.T/CGz.T/GGz.T/TGz.A/ATz.A/CTz.A/GTz.A/TTz.G/ATz.G/CTz.G/GTz.G/TTzAT/.AzCT/.AzGT/.AzTT/.AzAG/.CzCG/.CzGG/.CzTG/.CzAC/.GzCC/.GzGC/.GzTC/.GzAT/.GzCT/.GzGT/.GzTT/.GzAA/.TzCA/.TzGA/.TzTA/.TzAG/.TzCG/.TzGG/.TzTG/.TcCsL|dkr2dddddddddddddddddd}n|}|rH|||S)aReturn a table with thermodynamic parameters (as dictionary). Arguments: - oldtable: An existing dictionary with thermodynamic parameters. - values: A dictionary with new or updated values. E.g., to replace the initiation parameters in the Sugimoto '96 dataset with the initiation parameters from Allawi & SantaLucia '97: >>> from Bio.SeqUtils.MeltingTemp import make_table, DNA_NN2 >>> table = DNA_NN2 # Sugimoto '96 >>> table['init_A/T'] (0, 0) >>> newtable = make_table(oldtable=DNA_NN2, values={'init': (0, 0), ... 'init_A/T': (2.3, 4.1), ... 'init_G/C': (0.1, -2.8)}) >>> print("%0.1f, %0.1f" % newtable['init_A/T']) 2.3, 4.1 N)rr)rzinit_A/Tzinit_G/Cz init_oneG/Cz init_allA/Tz init_5T/ArzAA/TTzAT/TAzTA/ATzCA/GTzGT/CAzCT/GAzGA/CTzCG/GCzGC/CGzGG/CC)copyupdate)Zoldtablevaluestabler 7lib/python3.7/site-packages/Bio/SeqUtils/MeltingTemp.py make_tables,  rcsdd|}tt|}|dkr0|S|dkr>> from Bio.SeqUtils import MeltingTemp as mt >>> mt._check('10 ACGTTGCAAG tccatggtac', 'Tm_NN') 'ACGTTGCAAGTCCATGGTAC' Tm_WallaceTm_GC)ABCDGHIKMNRSTVWXYTm_NN)rrrrrcsg|]}|kr|qSr r ).0base)basesetr r sz_check..)joinsplitupperstrrZback_transcribe)seqmethodr )r&r _checksr.cCsB|dkr|std|r t|}d}|s,|S|||d}|d} t||||fdkr~|dks~||kr~|dt||7}|d} |tddkr| std |dkrd t| }|d krd t| d d | }|dkrdt| }|dkrdt| }|dkr*dt|dt| }|dkrjdt |dddt| dt| d }|dkr,d\} } } }d\}}}|dkr|d}d}|||| d  t|||| d d d|| d|} |dkrt| | }|dkrDdt |dddt| dt| d }|S|dkrd d!d"t| t| } d#d$d%t| d&t| d }d'd(d)t| d*t| d}| | t| t |d| |t| ddt|d||t| |t| d d}|dkr>td+|S),aCalculate a term to correct Tm for salt ions. Depending on the Tm calculation, the term will correct Tm or entropy. To calculate corrected Tm values, different operations need to be applied: - methods 1-4: Tm(new) = Tm(old) + corr - method 5: deltaS(new) = deltaS(old) + corr - methods 6+7: Tm(new) = 1/(1/Tm(old) + corr) Arguments: - Na, K, Tris, Mg, dNTPS: Millimolar concentration of respective ion. To have a simple 'salt correction', just pass Na. If any of K, Tris, Mg and dNTPS is non-zero, a 'sodium-equivalent' concentration is calculated according to von Ahsen et al. (2001, Clin Chem 47: 1956-1961): [Na_eq] = [Na+] + [K+] + [Tris]/2 + 120*([Mg2+] - [dNTPs])^0.5 If [dNTPs] >= [Mg2+]: [Na_eq] = [Na+] + [K+] + [Tris]/2 - method: Which method to be applied. Methods 1-4 correct Tm, method 5 corrects deltaS, methods 6 and 7 correct 1/Tm. The methods are: 1. 16.6 x log[Na+] (Schildkraut & Lifson (1965), Biopolymers 3: 195-208) 2. 16.6 x log([Na+]/(1.0 + 0.7*[Na+])) (Wetmur (1991), Crit Rev Biochem Mol Biol 126: 227-259) 3. 12.5 x log(Na+] (SantaLucia et al. (1996), Biochemistry 35: 3555-3562 4. 11.7 x log[Na+] (SantaLucia (1998), Proc Natl Acad Sci USA 95: 1460-1465 5. Correction for deltaS: 0.368 x (N-1) x ln[Na+] (SantaLucia (1998), Proc Natl Acad Sci USA 95: 1460-1465) 6. (4.29(%GC)-3.95)x1e-5 x ln[Na+] + 9.40e-6 x ln[Na+]^2 (Owczarzy et al. (2004), Biochemistry 43: 3537-3554) 7. Complex formula with decision tree and 7 empirical constants. Mg2+ is corrected for dNTPs binding (if present) (Owczarzy et al. (2008), Biochemistry 47: 5336-5353) Examples -------- >>> from Bio.SeqUtils import MeltingTemp as mt >>> print('%0.2f' % mt.salt_correction(Na=50, method=1)) -21.60 >>> print('%0.2f' % mt.salt_correction(Na=50, method=2)) -21.85 >>> print('%0.2f' % mt.salt_correction(Na=100, Tris=20, method=2)) -16.45 >>> print('%0.2f' % mt.salt_correction(Na=100, Tris=20, Mg=1.5, method=2)) -10.99 )zKsequence is missing (is needed to calculate GC content or sequence length).rg@gMbP?r2xr/z>Total ion concentration of zero is not allowed in this method.g0@g?gffffff?g)@gffffff'@r0gZd;O?r1g)\(@dg@gh㈵>g)>)g\(\@gx&g ףp= @gQ?)gHg@J@gQ @gL@g@g)\(?g@g\(\@g`"?gI +?gQ?gX9v?g>p?gT[r?gQ @gv?gPn?g/$u?z.Allowed values for parameter 'method' are 1-7.) ValueErrorr+summathZsqrtrangeZlog10lenlogrGC)NarTrisMgdNTPsr-r,corrZMonZmgZmonabcdefgZdntpsZkarr r r salt_correctionsl1 $   "      6  &&B, rK??cCst|r|||8}|rp|dkr(|||8}|dkr`|dks@|dkrHtd|d|dd|7}|d krptd |S) a$Correct a given Tm for DMSO and formamide. Please note that these corrections are +/- rough approximations. Arguments: - melting_temp: Melting temperature. - DMSO: Percent DMSO. - fmd: Formamide concentration in %(fmdmethod=1) or molar (fmdmethod=2). - DMSOfactor: How much should Tm decreases per percent DMSO. Default=0.65 (von Ahsen et al. 2001). Other published values are 0.5, 0.6 and 0.675. - fmdfactor: How much should Tm decrease per percent formamide. Default=0.65. Several papers report factors between 0.6 and 0.72. - fmdmethod: 1. Tm = Tm - factor(%formamide) (Default) 2. Tm = Tm + (0.453(f(GC)) - 2.88) x [formamide] Here f(GC) is fraction of GC. Note (again) that in fmdmethod=1 formamide concentration is given in %, while in fmdmethod=2 it is given in molar. - GC: GC content in percent. Examples: >>> from Bio.SeqUtils import MeltingTemp as mt >>> mt.chem_correction(70) 70 >>> print('%0.2f' % mt.chem_correction(70, DMSO=3)) 67.75 >>> print('%0.2f' % mt.chem_correction(70, fmd=5)) 66.75 >>> print('%0.2f' % mt.chem_correction(70, fmdmethod=2, fmd=1.25, ... GC=50)) 66.68 r/r4Nrz'GC' is missing or negativegˡE?gY@g ףp= @)r/r4z'fmdmethod' must be 1 or 2)r8) melting_tempZDMSOZfmdZ DMSOfactorZ fmdfactorZ fmdmethodr>r r r chem_correction^s&  rOTcCst|}|rt|d}dtt|jddtt|jd}dtt|jddtt|jd d tt|jd }|r|rtd n||7}|S) aCalculate and return the Tm using the 'Wallace rule'. Tm = 4 degC * (G + C) + 2 degC * (A+T) The Wallace rule (Thein & Wallace 1986, in Human genetic diseases: a practical approach, 33-50) is often used as rule of thumb for approximate Tm calculations for primers of 14 to 20 nt length. Non-DNA characters (e.g., E, F, J, !, 1, etc) are ignored by this method. Examples: >>> from Bio.SeqUtils import MeltingTemp as mt >>> mt.Tm_Wallace('ACGTTGCAATGCCGTA') 48.0 >>> mt.Tm_Wallace('ACGT TGCA ATGC CGTA') 48.0 >>> mt.Tm_Wallace('1ACGT2TGCA3ATGC4CGTA') 48.0 rr4)rrr r6)rrrr5)rrrrr"g @)rrgUUUUUU@)rrzFambiguous bases B, D, H, K, M, N, R, V, Y not allowed when strict=True)r+r.r9mapcountr8)r,checkstrictrNtmpr r r rs <rr22c  Cs| dkrtdt|}|r&t|d}t|} tt|jddt|tt|jddt|tt|jdd t|} |r| rtd n| | 7} |r|\}}}}n|d krd \}}}}d } |dkrd\}}}}d } |dkrd\}}}}d} |dkrd\}}}}d} |dkr,d\}}}}d} |dkrFd\}}}}d} |dkr`d\}}}}d} |dkrzd\}}}}d} |dkrtd||| |t|d}| r|t ||||| || d7}| r|||ddt|8}|S)al Return the Tm using empirical formulas based on GC content. General format: Tm = A + B(%GC) - C/N + salt correction - D(%mismatch) A, B, C, D: empirical constants, N: primer length D (amount of decrease in Tm per % mismatch) is often 1, but sometimes other values have been used (0.6-1.5). Use 'X' to indicate the mismatch position in the sequence. Note that this mismatch correction is a rough estimate. >>> from Bio.SeqUtils import MeltingTemp as mt >>> print("%0.2f" % mt.Tm_GC('CTGCTGATXGCACGAGGTTATGG', valueset=2)) 69.20 Arguments: - valueset: A few often cited variants are included: 1. Tm = 69.3 + 0.41(%GC) - 650/N (Marmur & Doty 1962, J Mol Biol 5: 109-118; Chester & Marshak 1993), Anal Biochem 209: 284-290) 2. Tm = 81.5 + 0.41(%GC) - 675/N - %mismatch 'QuikChange' formula. Recommended (by the manufacturer) for the design of primers for QuikChange mutagenesis. 3. Tm = 81.5 + 0.41(%GC) - 675/N + 16.6 x log[Na+] (Marmur & Doty 1962, J Mol Biol 5: 109-118; Schildkraut & Lifson 1965, Biopolymers 3: 195-208) 4. Tm = 81.5 + 0.41(%GC) - 500/N + 16.6 x log([Na+]/(1.0 + 0.7 x [Na+])) - %mismatch (Wetmur 1991, Crit Rev Biochem Mol Biol 126: 227-259). This is the standard formula in approximative mode of MELTING 4.3. 5. Tm = 78 + 0.7(%GC) - 500/N + 16.6 x log([Na+]/(1.0 + 0.7 x [Na+])) - %mismatch (Wetmur 1991, Crit Rev Biochem Mol Biol 126: 227-259). For RNA. 6. Tm = 67 + 0.8(%GC) - 500/N + 16.6 x log([Na+]/(1.0 + 0.7 x [Na+])) - %mismatch (Wetmur 1991, Crit Rev Biochem Mol Biol 126: 227-259). For RNA/DNA hybrids. 7. Tm = 81.5 + 0.41(%GC) - 600/N + 16.6 x log[Na+] Used by Primer3Plus to calculate the product Tm. Default set. 8. Tm = 77.1 + 0.41(%GC) - 528/N + 11.7 x log[Na+] (von Ahsen et al. 2001, Clin Chem 47: 1956-1961). Recommended 'as a tradeoff between accuracy and ease of use'. - userset: Tuple of four values for A, B, C, and D. Usersets override valuesets. - Na, K, Tris, Mg, dNTPs: Concentration of the respective ions [mM]. If any of K, Tris, Mg and dNTPS is non-zero, a 'sodium-equivalent' concentration is calculated and used for salt correction (von Ahsen et al., 2001). - saltcorr: Type of salt correction (see method salt_correction). Default=5. 0 or None means no salt correction. - mismatch: If 'True' (default) every 'X' in the sequence is counted as mismatch. r0z0salt-correction method 5 not applicable to Tm_GCr)rrrrr"gI@)rrg{GP@)rrg ףp=@@zHambiguous bases B, D, H, K, M, N, R, V, Y not allowed when 'strict=True'r/)g33333SQ@g= ףp=?ir/rr4)g`T@g= ףp=?ir/r5r6)g`T@g= ףp=?ir/)gS@gffffff?ir/r1)gP@g?ir/r2)g`T@g= ףp=?iXr/)gfffffFS@g= ףp=?ir/z0allowed values for parameter 'valueset' are 0-8.g?)r?rr@rArBr,r-r!gY@) r8r+r.rr>r9rPrQr<rK)r,rRrSZvaluesetZusersetr?rr@rArBsaltcorrZmismatchZ percent_gcrTrrrrrNr r r rs\D  T              rcCs&|rtd|ntd|tdS)zLThrow an error or a warning if there is no data for the neighbors (PRIVATE).z0no thermodynamic data for neighbors %r availablezJno themodynamic data for neighbors %r available. Calculation will be wrongN)r8warningswarnr) neighborsrSr r r _key_error@s r[Fr0c% Cs|st}|st}|st}|s t}t|}|s:t|}t|}|rZt|d}t|d}|}|}d}d}d}d}|st|t|kr|dkrd||}|dkrdt ||}t|t|kr|t|t|d7}t|t|kr|t|t|d7}x6| ds | dr<|dd}|dd}qWx6| dsX| drt|dd}|dd}q@W| ds| dr|ddd |dd}y$||||7}||||7}Wn t k rt ||YnX|dd}|dd}| ds | dr|d ddddd |d dddd}y$||||7}||||7}Wn t k rt ||YnX|dd}|dd}|dddddd |ddddd}||kr ||||7}||||7}|dd}|dd}|d dd |d d}||kr~||||7}||||7}|dd}|dd}||d |7}||d |7}t|dkr||d |7}||d |7}n ||d |7}||d |7}| dr||d|7}||d|7}| drH||d|7}||d|7}|d|d}|d|d}|d|d}||d||7}||d||7}||d||7}||d||7}x6tt|dD] }|||dd |||d} | |kr:||| |7}||| |7}n| ddd|kr||| ddd|7}||| ddd|7}n| |kr||| |7}||| |7}nT| ddd|kr||| ddd|7}||| ddd|7}n t | |qW| | dd}!| rH| d}!||d|7}||d|7}d}"|rht| | |||||d}#|dkrz||#7}d|||"t|!d}$|dkr|$|#7}$|dkrdd|$d|#d}$|$S)a Return the Tm using nearest neighbor thermodynamics. Arguments: - seq: The primer/probe sequence as string or Biopython sequence object. For RNA/DNA hybridizations seq must be the RNA sequence. - c_seq: Complementary sequence. The sequence of the template/target in 3'->5' direction. c_seq is necessary for mismatch correction and dangling-ends correction. Both corrections will automatically be applied if mismatches or dangling ends are present. Default=None. - shift: Shift of the primer/probe sequence on the template/target sequence, e.g.:: shift=0 shift=1 shift= -1 Primer (seq): 5' ATGC... 5' ATGC... 5' ATGC... Template (c_seq): 3' TACG... 3' CTACG... 3' ACG... The shift parameter is necessary to align seq and c_seq if they have different lengths or if they should have dangling ends. Default=0 - table: Thermodynamic NN values, eight tables are implemented: For DNA/DNA hybridizations: - DNA_NN1: values from Breslauer et al. (1986) - DNA_NN2: values from Sugimoto et al. (1996) - DNA_NN3: values from Allawi & SantaLucia (1997) (default) - DNA_NN4: values from SantaLucia & Hicks (2004) For RNA/RNA hybridizations: - RNA_NN1: values from Freier et al. (1986) - RNA_NN2: values from Xia et al. (1998) - RNA_NN3: valuse from Chen et al. (2012) For RNA/DNA hybridizations: - R_DNA_NN1: values from Sugimoto et al. (1995) Note that ``seq`` must be the RNA sequence. Use the module's maketable method to make a new table or to update one one of the implemented tables. - tmm_table: Thermodynamic values for terminal mismatches. Default: DNA_TMM1 (SantaLucia & Peyret, 2001) - imm_table: Thermodynamic values for internal mismatches, may include insosine mismatches. Default: DNA_IMM1 (Allawi & SantaLucia, 1997-1998; Peyret et al., 1999; Watkins & SantaLucia, 2005) - de_table: Thermodynamic values for dangling ends: - DNA_DE1: for DNA. Values from Bommarito et al. (2000) (default) - RNA_DE1: for RNA. Values from Turner & Mathews (2010) - dnac1: Concentration of the higher concentrated strand [nM]. Typically this will be the primer (for PCR) or the probe. Default=25. - dnac2: Concentration of the lower concentrated strand [nM]. In PCR this is the template strand which concentration is typically very low and may be ignored (dnac2=0). In oligo/oligo hybridization experiments, dnac1 equals dnac1. Default=25. MELTING and Primer3Plus use k = [Oligo(Total)]/4 by default. To mimic this behaviour, you have to divide [Oligo(Total)] by 2 and assign this concentration to dnac1 and dnac2. E.g., Total oligo concentration of 50 nM in Primer3Plus means dnac1=25, dnac2=25. - selfcomp: Is the sequence self-complementary? Default=False. If 'True' the primer is thought binding to itself, thus dnac2 is not considered. - Na, K, Tris, Mg, dNTPs: See method 'Tm_GC' for details. Defaults: Na=50, K=0, Tris=0, Mg=0, dNTPs=0. - saltcorr: See method 'Tm_GC'. Default=5. 0 means no salt correction. r#rr/.z..Nr4/rz init_allA/Tz init_oneG/Crz init_5T/Arrrzinit_A/Tzinit_G/Cg@g& .>rgn?)r?rr@rArBr-r,r0igfffffq@)r/r4r5r6)r1r2)DNA_NN3DNA_TMM1DNA_IMM1DNA_DE1r+rZ complementr.r<abs startswithendswithKeyErrorr[rr>rQr;rKr:r=)%r,rRrSZc_seqshiftnn_tableZ tmm_tableZ imm_tableZde_tablednac1dnac2Zselfcompr?rr@rArBrWZtmp_seqZtmp_cseqZdelta_hZdelta_sZd_hZd_sZleft_deZright_deZleft_tmmZ right_tmmZendsATr>Z basenumberrZkrrCrNr r r r#MsW       0  0        $     r#cCs^tdt|s(t||d|d|dS|dkrJt||d|d|tdStd|ddS) aReturn DNA/DNA Tm using nearest neighbor thermodynamics (OBSOLETE). This method may be depreceated in the future. Use Tm_NN instead. Tm_NN with default values gives the same result as Tm_staluc. s is the sequence as string or Seq object dnac is DNA concentration [nM] saltc is salt concentration [mM]. rna=0 is for DNA/DNA (default), use 1 for RNA/RNA hybridisation. For DNA/DNA, see Allawi & SantaLucia (1997), Biochemistry 36: 10581-10594 For RNA/RNA, see Xia et al (1998), Biochemistry 37: 14719-14735 Examples -------- >>> print("%0.2f" % Tm_staluc('CAGTCAGTACGTACGTGTACTGCCGTA')) 59.87 >>> print("%0.2f" % Tm_staluc('CAGTCAGTACGTACGTGTACTGCCGTA', rna=True)) 77.90 You can also use a Seq object instead of a string, >>> from Bio.Seq import Seq >>> s = Seq('CAGTCAGTACGTACGTGTACTGCCGTA') >>> print("%0.2f" % Tm_staluc(s)) 59.87 >>> print("%0.2f" % Tm_staluc(s, rna=True)) 77.90 z2Tm_staluc is deprecated; please use Tm_NN instead.g@)rkrlr?r/)rkrlr?rjzrna=z not supportedN)rXrYrr#RNA_NN2r8)sZdnacZsaltcZrnar r r Tm_staluc?s"rq__main__) run_doctest)NN)rrrrrr/N)rrrLrMr/N)TT) TTr2NrUrrrrrT)TTNrNNNNr\r\FrUrrrrr0)rUrUr) __doc__r:rXZBiorrrrZDNA_NN1ZDNA_NN2raZDNA_NN4ZRNA_NN1roZRNA_NN3Z R_DNA_NN1rcrbrdZRNA_DE1rr.rKrOrrr[r#rq__name__Z Bio._utilsrsr r r r s                          0 0x7.r a.