Source Code for Module Bio.Alphabet.Reduced

  1  # Copyright 2004 by Iddo Friedberg. 
  2  # All rights reserved. 
  3  # This code is part of the Biopython distribution and governed by its 
  4  # license.  Please see the LICENSE file that should have been included 
  5  # as part of this package. 
  6   
  7  """Reduced alphabets which lump together several amino-acids into one letter. 
  8   
  9  Reduced (redundant or simplified) alphabets are used to represent protein sequences using an 
 10  alternative alphabet which lumps together several amino-acids into one letter, based 
 11  on physico-chemical traits. For example, all the aliphatics (I,L,V) are usually 
 12  quite interchangeable, so many sequence studies group them into one letter 
 13   
 14  Examples of reduced alphabets are available in: 
 15   
 16  http://viscose.ifg.uni-muenster.de/html/alphabets.html 
 17   
 18  The Murphy tables are from here: 
 19   
 20  Murphy L.R., Wallqvist A, Levy RM. (2000) Simplified amino acid 
 21  alphabets for protein fold recognition and implications for folding. 
 22  Protein Eng. 13(3):149-152 
 23   
 24  Bio.utils.reduce_sequence is used to take a Protein alphabet, and reduce it using one of 
 25  the tables here, or a user-defined table. 
 26  """ 
 27   
 28  from Bio import Alphabet 
 29   
 30   
 31  murphy_15_tab = {"L": "L", 
 32               "V": "L", 
 33               "I": "L", 
 34               "M": "L", 
 35               "C": "C", 
 36               "A": "A", 
 37               "G": "G", 
 38               "S": "S", 
 39               "T": "T", 
 40               "P": "P", 
 41               "F": "F", 
 42               "Y": "F", 
 43               "W": "W", 
 44               "E": "E", 
 45               "D": "D", 
 46               "N": "N", 
 47               "Q": "Q", 
 48               "K": "K", 
 49               "R": "K", 
 50               "H": "H"} 
 51   
 52   
 53 -class Murphy15(Alphabet.ProteinAlphabet): 
 54      letters = "LCAGSTPFWEDNQKH" 
 55      size = 15 
 56  murphy_15 = Murphy15() 
 57   
 58  murphy_10_tab = {"L": "L", 
 59               "V": "L", 
 60               "I": "L", 
 61               "M": "L", 
 62               "C": "C", 
 63               "A": "A", 
 64               "G": "G", 
 65               "S": "S", 
 66               "T": "S", 
 67               "P": "P", 
 68               "F": "F", 
 69               "Y": "F", 
 70               "W": "F", 
 71               "E": "E", 
 72               "D": "E", 
 73               "N": "E", 
 74               "Q": "E", 
 75               "K": "K", 
 76               "R": "K", 
 77               "H": "H"} 
 78   
 79   
 80 -class Murphy10(Alphabet.ProteinAlphabet): 
 81      letters = "LCAGSPFEKH" 
 82      size = 10 
 83  murphy_10 = Murphy10() 
 84   
 85  murphy_8_tab = {"L": "L", 
 86               "V": "L", 
 87               "I": "L", 
 88               "M": "L", 
 89               "C": "L", 
 90               "A": "A", 
 91               "G": "A", 
 92               "S": "S", 
 93               "T": "S", 
 94               "P": "P", 
 95               "F": "F", 
 96               "Y": "F", 
 97               "W": "F", 
 98               "E": "E", 
 99               "D": "E", 
100               "N": "E", 
101               "Q": "E", 
102               "K": "K", 
103               "R": "K", 
104               "H": "H"} 
105   
106   
107 -class Murphy8(Alphabet.ProteinAlphabet): 
108      letters = "LASPFEKH" 
109      size = 8 
110  murphy_8 = Murphy8() 
111   
112  murphy_4_tab = {"L": "L", 
113               "V": "L", 
114               "I": "L", 
115               "M": "L", 
116               "C": "L", 
117               "A": "A", 
118               "G": "A", 
119               "S": "A", 
120               "T": "A", 
121               "P": "A", 
122               "F": "F", 
123               "Y": "F", 
124               "W": "F", 
125               "E": "E", 
126               "D": "E", 
127               "N": "E", 
128               "Q": "E", 
129               "K": "E", 
130               "R": "E", 
131               "H": "E"} 
132   
133   
134 -class Murphy4(Alphabet.ProteinAlphabet): 
135      letters = "LAFE" 
136      size = 4 
137  murphy_4 = Murphy4() 
138   
139  hp_model_tab = {"A": "P",   # Hydrophilic 
140              "G": "P", 
141              "T": "P", 
142              "S": "P", 
143              "N": "P", 
144              "Q": "P", 
145              "D": "P", 
146              "E": "P", 
147              "H": "P", 
148              "R": "P", 
149              "K": "P", 
150              "P": "P", 
151              "C": "H",  # Hydrophobic 
152              "M": "H", 
153              "F": "H", 
154              "I": "H", 
155              "L": "H", 
156              "V": "H", 
157              "W": "H", 
158              "Y": "H"} 
159   
160   
161 -class HPModel(Alphabet.ProteinAlphabet): 
162      letters = "HP" 
163      size = 2 
164  hp_model = HPModel() 
165   
166  pc_5_table = {"I": "A", # Aliphatic 
167           "V": "A", 
168           "L": "A", 
169           "F": "R", # Aromatic 
170           "Y": "R", 
171           "W": "R", 
172           "H": "R", 
173           "K": "C", # Charged 
174           "R": "C", 
175           "D": "C", 
176           "E": "C", 
177           "G": "T", # Tiny 
178           "A": "T", 
179           "C": "T", 
180           "S": "T", 
181           "T": "D", # Diverse 
182           "M": "D", 
183           "Q": "D", 
184           "N": "D", 
185           "P": "D"} 
186   
187   
188 -class PC5(Alphabet.ProteinAlphabet): 
189      letters = "ARCTD" 
190      size = 5 
191  hp_model = HPModel() 
192