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from Bio import Alphabet
"""
Reduced (redundant or simplified) alphabets are used to represent protein sequences using an
alternative alphabet which lumps together several amino-acids into one letter, based
on physico-chemical traits. For example, all the aliphatics (I,L,V) are usually
quite interchangeable, so many sequence studies group them into one letter
Examples of reduced alphabets are available in:
http://viscose.ifg.uni-muenster.de/html/alphabets.html
Bio.utils.reduce_sequence is used to take a Protein alphabet, and reduce it using one of
the tables here, or a user-defined table.
"""
# The Murphy tables are from here:
# Murphy L.R., Wallqvist A, Levy RM. (2000) Simplified amino acid alphabets for protein
# fold recognition and implications for folding. Protein Eng. 13(3):149-152
murphy_15_tab = {"L": "L",
"V": "L",
"I": "L",
"M": "L",
"C": "C",
"A": "A",
"G": "G",
"S": "S",
"T": "T",
"P": "P",
"F": "F",
"Y": "F",
"W": "W",
"E": "E",
"D": "D",
"N": "N",
"Q": "Q",
"K": "K",
"R": "K",
"H": "H"}
class Murphy15(Alphabet.ProteinAlphabet):
letters = "LCAGSTPFWEDNQKH"
size = 15
murphy_15 = Murphy15()
murphy_10_tab = {"L": "L",
"V": "L",
"I": "L",
"M": "L",
"C": "C",
"A": "A",
"G": "G",
"S": "S",
"T": "S",
"P": "P",
"F": "F",
"Y": "F",
"W": "F",
"E": "E",
"D": "E",
"N": "E",
"Q": "E",
"K": "K",
"R": "K",
"H": "H"}
class Murphy10(Alphabet.ProteinAlphabet):
letters = "LCAGSPFEKH"
size = 10
murphy_10 = Murphy10()
murphy_8_tab = {"L": "L",
"V": "L",
"I": "L",
"M": "L",
"C": "L",
"A": "A",
"G": "A",
"S": "S",
"T": "S",
"P": "P",
"F": "F",
"Y": "F",
"W": "F",
"E": "E",
"D": "E",
"N": "E",
"Q": "E",
"K": "K",
"R": "K",
"H": "H"}
class Murphy8(Alphabet.ProteinAlphabet):
letters = "LASPFEKH"
size = 8
murphy_8 = Murphy8()
murphy_4_tab = {"L": "L",
"V": "L",
"I": "L",
"M": "L",
"C": "L",
"A": "A",
"G": "A",
"S": "A",
"T": "A",
"P": "A",
"F": "F",
"Y": "F",
"W": "F",
"E": "E",
"D": "E",
"N": "E",
"Q": "E",
"K": "E",
"R": "E",
"H": "E"}
class Murphy4(Alphabet.ProteinAlphabet):
letters = "LAFE"
size = 4
murphy_4 = Murphy4()
hp_model_tab = {"A": "P", # Hydrophilic
"G": "P",
"T": "P",
"S": "P",
"N": "P",
"Q": "P",
"D": "P",
"E": "P",
"H": "P",
"R": "P",
"K": "P",
"P": "P",
"C": "H", # Hydrophobic
"M": "H",
"F": "H",
"I": "H",
"L": "H",
"V": "H",
"W": "H",
"Y": "H"}
class HPModel(Alphabet.ProteinAlphabet):
letters = "HP"
size = 2
hp_model = HPModel()
pc_5_table = {"I": "A", # Aliphatic
"V": "A",
"L": "A",
"F": "R", # Aromatic
"Y": "R",
"W": "R",
"H": "R",
"K": "C", # Charged
"R": "C",
"D": "C",
"E": "C",
"G": "T", # Tiny
"A": "T",
"C": "T",
"S": "T",
"T": "D", # Diverse
"M": "D",
"Q": "D",
"N": "D",
"P": "D"}
class PC5(Alphabet.ProteinAlphabet):
letters = "ARCTD"
size = 5
hp_model = HPModel()
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