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Commit c3ce0b79 authored by Studer Gabriel's avatar Studer Gabriel
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add support for AAindex database (Kawashima et al., 2000)

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modules/seq/alg/doc/seqalg.rst
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......@@ -945,3 +945,24 @@ etc.) to be set, which is the case if you load a file in hhm format.
:type db: :class:`ContextProfileDB`
:raises: Exception if profile doesn't have HMM information assigned
AAIndex annotations
-------------------
.. autoclass:: ost.seq.alg.aaindex.AAIndex
:members:
:special-members: __getitem__
The annotations/scores can either refer to single amino acids or represent
pairwise values. The two types are:
.. autoclass:: ost.seq.alg.aaindex.AnnoType
:members:
:undoc-members:
The actual data of an entry in the aaindex database is stored in a
:class:`aaindex.AAIndexData` object:
.. autoclass:: ost.seq.alg.aaindex.AAIndexData
:members:
modules/seq/alg/pymod/CMakeLists.txt
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......@@ -4,5 +4,17 @@ set(OST_SEQ_ALG_PYMOD_SOURCES
if (NOT ENABLE_STATIC)
pymod(NAME seq_alg OUTPUT_DIR ost/seq/alg
CPP ${OST_SEQ_ALG_PYMOD_SOURCES}
PY __init__.py mat.py renumber.py)
PY __init__.py mat.py renumber.py aaindex.py)
endif()
copy_if_different("${CMAKE_CURRENT_SOURCE_DIR}" "${STAGE_DIR}/share/openstructure/aaindex"
"aaindex1" "AAINDEX1" "ost_seq_alg_pymod")
install(FILES "aaindex1" DESTINATION "share/openstructure/aaindex/")
copy_if_different("${CMAKE_CURRENT_SOURCE_DIR}" "${STAGE_DIR}/share/openstructure/aaindex"
"aaindex2" "AAINDEX2" "ost_seq_alg_pymod")
install(FILES "aaindex2" DESTINATION "share/openstructure/aaindex/")
copy_if_different("${CMAKE_CURRENT_SOURCE_DIR}" "${STAGE_DIR}/share/openstructure/aaindex"
"aaindex3" "AAINDEX3" "ost_seq_alg_pymod")
install(FILES "aaindex3" DESTINATION "share/openstructure/aaindex/")
modules/seq/alg/pymod/aaindex.py 0 → 100644
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import os
from enum import Enum
from ost import GetSharedDataPath
def _StrToFloat(str_item):
"""Returns None if *str_item* looks like invalid number, casts to
float otherwise"""
x = str_item.strip()
if x.lower() in ["na", "-", "none"]:
return None
return float(x)
class AnnoType(str, Enum):
"""Possible types of aaindex entries"""
SINGLE = 'SINGLE' #: Single amino acid annotation
PAIR = 'PAIR' #: Pairwise amino acid annotation, substitution/pairwise scores
class AAIndexData:
"""Data object representing an annotation in aaindex, preferably
constructed from it's static :func:`Parse` method. The following
attributes are available:
* key: aaindex accession number (e.g. ANDN920101)
* desc: descriptive title
* ref: Reference to article if available
* authors: Authors of article if available
* title: Title of article if available
* journal: Journal of article if available
* anno_type: Enum (:class:`AnnoType`) specifying whether we're dealing
with a single or pairwise amino acid annotation/score.
* anno: :class:`dict` with annotation. If *anno_type* is SINGLE,
keys are amino acid one letter codes (single character strings).
If *anno_type* is PAIR, keys are two one letter codes added
together (two character strings). Even when the thing is
symmetric, both keys exist. I.e. 'AB' AND 'BA'.
Values are of type :class:`float` (None if not available).
"""
def __init__(self):
self.key = None
self.desc = None
self.ref = None
self.authors = None
self.title = None
self.journal = None
self.anno_type = AnnoType.SINGLE
self.anno = dict()
@staticmethod
def Parse(data):
"""Creates :class:`AAIndexData` from data.
:param data: Iterable with strings in data format described for aaindex.
:returns: :class:`AAIndexData`, if iterable contains several entries,
parsing stops at separation sequence ('//'). None is returned
if nothing could be parsed.
:raises: descriptive error in case of corrupt data
"""
key = ""
desc = ""
ref = ""
authors = ""
title = ""
journal = ""
anno = dict()
anno_type = None
# temp variables, used for parsing
values = list()
pair_rows = None
pair_cols = None
current_data_type = None
stuff_read = False
for line in data:
if line.startswith("//"):
break # we're done
elif line.strip() == "":
continue # nothing to read
elif line[0] in ["H", "D", "R", "A", "T", "J", "I", "M"]:
stuff_read = True
current_data_type = line[0] # something we're interested in
elif line.startswith(" "):
pass # continuation of previous stuff
else:
current_data_type = None # unkown data, skip...
if current_data_type == "H":
key = line[2:].strip()
elif current_data_type == "D":
desc += line[2:]
elif current_data_type == "R":
ref += line[2:]
elif current_data_type == "A":
authors += line[2:]
elif current_data_type == "T":
title += line[2:]
elif current_data_type == "J":
journal += line[2:]
elif current_data_type == "I":
if anno_type == AnnoType.PAIR:
raise RuntimeError("Observed single AA and pairwise "
"features in the same aaindex entry")
anno_type = AnnoType.SINGLE
if line.startswith("I"):
# header, must match expected aa ordering
aakeys = [item.strip() for item in line[1:].split()]
exp_aa_keys = ["A/L", "R/K", "N/M", "D/F", "C/P", "Q/S",
"E/T", "G/W", "H/Y", "I/V"]
if aakeys != exp_aa_keys:
raise RuntimeError(f"Keys in single AA AAIndex entry "
"are expected to be "
"I A/L R/K N/M D/F C/P Q/S E/T G/W H/Y I/V "
"got {line}")
else:
# its numbers... will be added to anno dict below
values += [_StrToFloat(x) for x in line.split()]
elif current_data_type == "M":
if anno_type == AnnoType.SINGLE:
raise RuntimeError("Observed single AA and pairwise "
"features in the same aaindex entry")
anno_type = AnnoType.PAIR
if line.startswith("M"):
# header, don't expect strict one letter code ordering here
# also because some pair entries include gaps ('-').
# expect something like: "M rows = <x>, cols = <x>"
split_line = line[1:].split(',')
split_line = sorted([item.strip() for item in split_line])
# after sorting we should have exactly two elements, the
# first starting with cols and the second with rows
if len(split_line) != 2 or \
not split_line[0].startswith("cols") or \
not split_line[1].startswith("rows"):
raise RuntimeError(f"Expect value header in pair "
"AAIndex entry to be of form: "
"\"M rows = <x>, cols = <x>\" got: "
"{line}")
pair_cols = split_line[0].split("=")[1].strip()
pair_rows = split_line[1].split("=")[1].strip()
if len(pair_cols) != len(pair_cols):
raise RuntimeError(f"Expect rows and cols to have same "
"number of elements when parsing "
"pair AAIndex entry got {line}")
else:
# its numbers... will be added to anno dict below
values += [_StrToFloat(x) for x in line.split()]
if not stuff_read:
return None
if key == "":
raise RuntimeError("Cannot parse AAIndex entry without key...")
if anno_type == AnnoType.SINGLE:
olcs = "ARNDCQEGHILKMFPSTWYV"
if len(olcs) != len(values):
raise RuntimeError(f"Expected {len(olcs)} values in single AA "
"AAIndex entry, got {len(values)}")
for olc, value in zip(olcs, values):
anno[olc] = value
elif anno_type == AnnoType.PAIR:
# number of values can differ as the provided matrix can either be
# diagonal (symmetric A -> B == B -> A) or rectangular (non-symmetric
# A -> B != B -> A)
# For the former, number of columns and rows must be equal, no such
# requirement for non-symmetric case
n_values_match = False
n_cols = len(pair_cols)
n_rows = len(pair_rows)
n_nonsym = n_cols * n_rows
if len(values) == n_nonsym:
n_values_match = True
value_idx = 0
for a in pair_rows:
for b in pair_cols:
anno[a+b] = values[value_idx]
value_idx += 1
if n_cols == n_rows:
n_values_match = True
N = n_cols
n_sym = (N*N - N) / 2 # number of elements below diagonal
n_sym += N # add diagonal elements again
if len(values) == n_sym:
value_idx = 0
for row_idx, row in enumerate(pair_rows):
for col in pair_cols[: row_idx+1]:
anno[row+col] = values[value_idx]
anno[col+row] = values[value_idx]
value_idx += 1
if not n_values_match:
raise RuntimeError(f"Number of parsed values doesn't match "
"parsed rows and cols descriptors")
else:
raise RuntimeError("Cannot parse AAIndex entry without values...")
data = AAIndexData()
data.key = key
data.title = title
data.ref = ref
data.authors = authors
data.title = title
data.journal = journal
data.anno_type = anno_type
data.anno = anno
return data
def GetScore(self, olc):
"""Score/Annotation getter
:param olc: One letter code of amino acid
:type olc: :class:`string`
:returns: Annotation/score for *olc*
:raises: :class:`ValueError` if *olc* is not known or
:class:`RuntimeError` if anno_type of this
:class:`AAIndexData` object is not AnnoType.SINGLE.
"""
if self.anno_type == AnnoType.SINGLE:
if olc in self.anno:
return self.anno[olc]
else:
raise ValueError(f"OLC not in AAIndex: {olc}")
raise RuntimeError("Cannot return score for single amino acid with "
"AAIndex of type PAIR")
def GetPairScore(self, olc_one, olc_two):
"""Score/Annotation getter
:param olc_one: One letter code of first amino acid
:type olc_one: :class:`string`
:param olc_two: One letter code of second amino acid
:type olc_two: :class:`string`
:returns: Pairwise annotation/score for *olc_one*/*olc_two*
:raises: :class:`ValueError` if key constructed from *olc_one* and
*olc_two* is not known or
:class:`RuntimeError` if anno_type of this
:class:`AAIndexData` object is not AnnoType.PAIR.
"""
if self.anno_type == AnnoType.PAIR:
anno_key = olc_one + olc_two
if anno_key in self.anno:
return self.anno[anno_key]
else:
raise ValueError(f"Cannot find annotation for following pairs "
"of olcs: {olc_one}, {olc_two}")
raise RuntimeError("Cannot return score for pair of amino acid "
"with AAIndex of type SINGLE")
class AAIndex:
"""Provides access to data from the amino acid index database (aaindex):
Kawashima, S. and Kanehisa, M.; AAindex: amino acid index database.
Nucleic Acids Res. 28, 374 (2000).
Files are available `here <https://www.genome.jp/aaindex/>`_
:param aaindex_files: Paths to aaindex files. If not given, the files
aaindex1, aaindex2 and aaindex3 from the specified
source are used (Release 9.2, Feb 2017).
:type aaindex_files: :class:`list` of :class:`str`
"""
def __init__(self, aaindex_files = None):
if aaindex_files is None:
aaindex_dir = os.path.join(GetSharedDataPath(), 'aaindex')
self.files_to_load = [os.path.join(aaindex_dir, "aaindex1"),
os.path.join(aaindex_dir, "aaindex2"),
os.path.join(aaindex_dir, "aaindex3")]
else:
self.files_to_load = list(aaindex_files)
self.aaindex_entries = dict()
def keys(self):
"""Emulate dict like behvaiour and returns all available keys, accession
numbers respectively.
:returns: keys (or accession numbers) of all available aaindex entries
"""
self._LoadAll()
return self.aaindex_entries.keys()
def values(self):
"""Emulate dict like behvaiour and returns all available entries.
:returns: iterable of entries (type :class:`AAIndexData`)
"""
self._LoadAll()
return self.aaindex_entries.values()
def __getitem__(self, key):
"""Getter by aaindex accession number (e.g. ANDN920101)
:param key: aaindex accession number
:type key: :class:`str`
:returns: :class:`AAIndexData` object
"""
while True:
if key in self.aaindex_entries:
return self.aaindex_entries[key]
# key is not available let's load the next aaindex file
if not self._Load():
# all files loaded, there is entry with *key* in any of them
break
raise KeyError(f"{key} does not exist in provided aa_index files")
def _LoadAll(self):
"""Loads all remaining files specified in self.files_to_load
"""
while self._Load():
pass
def _Load(self):
"""Loads and removes first element in self.files_to_load. Returns False
if there is no file to load anymore, True if one is successfully loaded.
"""
if len(self.files_to_load) == 0:
return False
path = self.files_to_load.pop(0)
if not os.path.exists(path):
raise RuntimeError(f"Tried to load {path} but file doesnt exist.")
with open(path, 'r') as fh:
data = fh.readlines()
data_it = iter(data)
while True: # read as long as it spits out AAIndexData entries
entry = AAIndexData.Parse(data_it)
if entry is None:
break # nothing to read anymore...
else:
self.aaindex_entries[entry.key] = entry
return True
modules/seq/alg/pymod/aaindex1 0 → 100644
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modules/seq/alg/pymod/aaindex2 0 → 100644
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H TANS760101
D Statistical contact potential derived from 25 x-ray protein structures
R PMID:1004017
A Tanaka, S. and Scheraga, H.A.
T Medium- and long-range interaction parameters between amino acids
for predicting three-dimensional structures of proteins
J Macromolecules 9, 945-950 (1976)
M rows = ARNDCQEGHILKMFPSTWYV, cols = ARNDCQEGHILKMFPSTWYV
-2.6
-3.4 -4.3
-3.1 -4.1 -3.2
-2.8 -3.9 -3.1 -2.7
-4.2 -5.3 -4.9 -4.2 -7.1
-3.5 -4.5 -3.8 -3.2 -5.0 -3.4
-3.0 -4.2 -3.4 -3.3 -4.4 -3.6 -2.8
-3.8 -4.5 -4.0 -3.7 -5.4 -4.4 -3.8 -3.9
-4.0 -4.9 -4.4 -4.3 -5.6 -4.7 -4.5 -4.7 -4.9
-5.9 -6.2 -5.8 -5.4 -7.3 -5.9 -5.7 -6.3 -6.6 -8.2
-4.8 -5.1 -4.6 -4.3 -6.2 -5.0 -4.6 -5.2 -5.6 -7.5 -6.0
-3.1 -3.6 -3.3 -3.2 -4.4 -3.7 -3.8 -3.8 -4.1 -5.6 -4.6 -2.7
-4.6 -5.0 -4.2 -4.3 -6.2 -3.5 -4.6 -5.1 -5.4 -7.4 -6.3 -4.7 -5.8
-5.1 -5.8 -5.0 -4.9 -6.8 -5.3 -5.0 -5.6 -6.4 -8.0 -7.0 -4.9 -6.6 -7.1
-3.4 -4.2 -3.6 -3.3 -5.3 -4.0 -3.5 -4.2 -4.5 -6.0 -4.8 -3.6 -5.1 -5.2 -3.5
-2.9 -3.8 -3.1 -2.7 -4.6 -3.6 -3.2 -3.8 -4.3 -5.5 -4.4 -3.0 -4.1 -4.7 -3.4 -2.5
-3.3 -4.0 -3.5 -3.1 -4.8 -3.7 -3.3 -4.1 -4.5 -5.9 -4.8 -3.3 -4.6 -5.1 -3.6 -3.3 -3.1
-5.2 -5.8 -5.3 -5.1 -6.9 -5.8 -5.2 -5.8 -6.5 -7.8 -6.8 -5.0 -6.9 -7.4 -5.6 -5.0 -5.1 -6.8
-4.7 -5.6 -5.0 -4.7 -6.6 -5.2 -4.9 -5.4 -6.1 -7.4 -6.2 -4.9 -6.1 -6.6 -5.2 -4.7 -4.9 -6.8 -6.0
-4.3 -4.9 -4.3 -4.0 -6.0 -4.7 -4.2 -5.1 -5.3 -7.3 -6.2 -4.2 -6.0 -6.5 -4.7 -4.2 -4.4 -6.5 -5.9 -5.5
//
H TANS760102
D Number of contacts between side chains derived from 25 x-ray protein structures
R PMID:1004017
A Tanaka, S. and Scheraga, H.A.
T Medium- and long-range interaction parameters between amino acids
for predicting three-dimensional structures of proteins
J Macromolecules 9, 945-950 (1976)
M rows = ARNDCQEGHILKMFPSTWYV, cols = ARNDCQEGHILKMFPSTWYV
36
20 14
39 34 22
36 35 31 24
15 13 21 10 48
34 29 30 17 13 7
27 34 27 38 9 19 9
115 58 80 83 53 75 54 75
25 17 25 32 11 17 24 40 8
119 33 51 43 33 29 35 109 27 81
174 47 63 60 49 53 53 155 49 230 167
55 20 39 54 14 32 70 92 21 53 86 20
26 9 7 13 11 1 12 32 7 44 58 21 6
62 32 27 32 32 21 22 67 38 103 175 32 20 53
33 20 22 23 24 23 17 62 15 41 46 34 16 19 11
64 44 42 37 28 44 41 145 43 65 93 51 14 36 38 34
70 36 46 38 22 28 28 116 36 67 110 50 16 39 32 69 29
38 15 21 24 17 22 15 52 23 40 68 20 17 41 19 31 20 7
65 45 50 52 43 32 40 103 44 81 105 64 19 45 42 71 53 32 33
101 44 50 53 53 46 39 183 42 216 306 67 52 114 58 106 79 62 85 152
//
H ROBB790102
D Interaction energies derived from side chain contacts in the interiors of
known protein structures
R PMID:513136
A Robson, B. and Osguthorpe, D.J.
T Refined Models for Computer-Simulation of Protein Folding - Applications
to the Study of Conserved Secondary Structure and Flexible Hinge Points
During the Folding of Pancreatic Trypsin-Inhibitor
J J. Mol. Biol. 132, 19-51 (1979)
* (Glu is not available)
M rows = ARNDCQEGHILKMFPSTWYV, cols = ARNDCQEGHILKMFPSTWYV
-0.268
0.529 3.717
0.010 1.153 0.130
0.926 5.172 1.921 6.271
-0.180 5.014 0.245 10.310 -20.000
0.017 1.212 0.149 2.021 0.296 0.169
0.902 4.911 1.835 6.052 9.050 1.926 5.832
NA NA NA NA NA NA NA NA
-0.187 1.759 0.088 3.336 -0.099 0.112 3.090 NA -0.106
-0.899 1.278 -0.577 3.643 -0.811 -0.547 3.248 NA -0.818 -1.530
-0.865 2.952 -0.542 8.760 -0.777 -0.513 7.540 NA -0.784 -1.496 -1.461
0.920 4.514 1.808 5.256 8.223 1.910 5.139 NA 3.084 3.368 7.538 4.533
-0.525 6.049 -0.202 14.958 -0.437 -0.173 12.775 NA -0.443 -1.156 -1.121 11.998 -0.781
-0.961 0.394 -0.638 1.098 -0.873 -0.609 1.021 NA -0.879 -1.592 -1.557 1.135 -1.217 -1.653
-1.470 0.099 -1.148 0.322 -1.382 -1.118 0.449 NA -1.389 -2.101 -2.066 0.817 -1.726 -2.162 -2.672
0.022 1.048 0.134 1.660 0.376 0.153 1.603 NA 0.133 -0.476 -0.441 1.554 -0.101 -0.537 -1.047 0.128
-0.177 1.054 0.053 1.890 -0.089 0.067 1.792 NA -0.096 -0.808 -0.773 1.786 -0.433 -0.869 -1.379 0.072 -0.085
-1.052 2.069 -0.730 7.299 -0.964 -0.700 6.288 NA -0.971 -1.683 -1.649 6.663 -1.308 -1.744 -2.254 -0.629 -0.961 -1.836
-0.899 2.657 -0.577 8.069 -0.811 -0.547 6.961 NA -0.818 -1.530 -1.495 7.042 -1.155 -1.591 -2.101 -0.476 -0.807 -1.683 -1.530
-0.617 0.944 -0.295 2.100 -0.529 -0.265 1.944 NA -0.536 -1.248 -1.214 2.000 -0.874 -1.310 -1.819 -0.194 -0.526 -1.401 -1.248 -0.966
//
H BRYS930101
D Distance-dependent statistical potential (only energies of contacts within
0-5 Angstrooms are included)
R PMID:8497488
A Bryant, S.H. and Lawrence, C.E.
T An Empirical Energy Function for Threading Protein-Sequence Through the
Folding Motif
J Proteins 16, 92-112 (1993)
M rows = ARNDCQEGHILKMFPSTWYV, cols = ARNDCQEGHILKMFPSTWYV
0.230
0.237 -0.145
0.159 -0.303 -0.206
0.140 -0.527 -0.534 0.539
0.159 0.174 0.105 -0.137 -0.524
-0.008 0.222 -0.187 -0.128 0.487 -0.430
0.182 -0.717 -0.262 -0.178 0.121 -0.728 1.060
0.282 -0.037 -0.097 -0.336 -0.187 -0.072 -0.041 -0.068
-0.079 0.111 -0.141 -0.270 -0.187 0.247 0.072 0.127 0.392
-0.535 -0.014 0.456 0.229 -0.415 0.020 0.385 0.127 -0.062 -0.051
-0.245 0.374 0.430 0.316 -0.061 0.391 0.480 -0.004 0.029 -0.223 -0.070
0.063 0.734 0.222 -0.759 1.115 -0.181 -0.782 0.065 -0.235 -0.058 -0.015 0.567
-0.364 0.509 0.405 0.097 -0.032 0.013 0.188 0.084 0.293 -0.103 -0.253 0.347 -0.006
0.132 -0.018 0.336 0.118 -0.095 0.283 0.270 0.457 -0.141 -0.348 -0.460 0.259 -0.501 -0.163
0.022 -0.176 0.109 0.175 -0.199 -0.545 -0.064 0.127 0.037 0.382 -0.170 0.068 -0.104 -0.083 0.033
0.115 -0.263 -0.334 -0.565 -0.164 0.298 -0.207 -0.100 0.080 0.254 0.390 -0.246 0.259 0.357 0.057 -0.150
0.002 0.250 -0.018 -0.433 0.021 0.060 -0.006 -0.106 0.061 0.167 0.075 -0.170 0.087 0.058 0.108 -0.430 -0.315
0.117 -0.244 0.538 1.287 0.080 0.459 -0.089 0.036 -0.098 -0.505 -0.635 -0.822 -0.783 -0.185 -0.312 0.298 0.040 0.707
-0.030 0.044 -0.491 0.694 0.069 -0.036 -0.004 0.121 -0.305 -0.100 -0.289 -0.294 -0.218 -0.335 0.071 0.442 0.492 -0.105 0.211
-0.359 -0.011 0.158 0.442 -0.026 -0.191 0.255 0.141 0.006 -0.253 -0.454 0.253 -0.265 -0.288 0.358 0.316 0.251 -0.034 0.075 -0.641
//
H THOP960101
D Mixed quasichemical and optimization-based protein contact potential
R PMID:8876187
A Thomas, P.D. and Dill, K.A.
T An iterative method for extracting energy-like quantities
from protein structures
J Proc. Natl. Acad. Sci. USA 93, 11628-11633 (1996)
M rows = ARNDCQEGHILKMFPSTWYV, cols = ARNDCQEGHILKMFPSTWYV
-0.08
0.07 0.23
-0.14 0.04 -0.86
0.10 -0.15 -0.12 0.60
-0.30 -0.40 -0.32 0.55 -1.79
-0.11 0.62 -0.05 0.46 -0.49 -0.08
0.03 -0.26 -0.25 0.68 0.04 0.62 0.21
-0.09 -0.15 -0.18 -0.06 -0.42 0.12 0.40 0.04
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-0.64 -0.08 0.39 0.04 -0.48 -0.39 -0.20 0.40 -0.52 -0.71
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//
H MIRL960101
D Statistical potential derived by the maximization of the harmonic mean of Z
scores
R PMID:9000638
A Mirny, L.A. and Shakhnovich, E.I.
T How to derive a protein folding potential? A new approach
to an old problem
J J. Mol. Biol. 264, 1164-1179 (1996)
M rows = ARNDCQEGHILKMFPSTWYV, cols = ARNDCQEGHILKMFPSTWYV
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//
H VENM980101
D Statistical potential derived by the maximization of the perceptron criterion
R
A Vendruscolo, M. and Domany E.
T Pairwise contact potentials are unsuitable for protein folding
J J. Chem. Phys. 109, 11101-11108 (1998)
M rows = ARNDCQEGHILKMFPSTWYV, cols = ARNDCQEGHILKMFPSTWYV
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//
H BASU010101
D Optimization-based potential derived by the modified perceptron criterion
R PMID:11391771
A Bastolla, U., Farwer, J., Knapp, E.W. and Vendruscolo, M.
T How to guarantee optimal stability for most representative
structures in the protein data bank
J Proteins 44, 79-96 (2001)
M rows = ARNDCQEGHILKMFPSTWYV, cols = ARNDCQEGHILKMFPSTWYV
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//
H MIYS850102
D Quasichemical energy of transfer of amino acids from water to the protein
environment
A Miyazawa, S. and Jernigan, R.L.
T Estimation of Effective Interresidue Contact Energies
from Protein Crystal-Structures-Quasi-Chemical Approximation
J Macromolecules 18, 534-552 (1985)
M rows = ARNDCQEGHILKMFPSTWYV, cols = ARNDCQEGHILKMFPSTWYV
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//
H MIYS850103
D Quasichemical energy of interactions in an average buried environment
A Miyazawa, S. and Jernigan, R.L.
T Estimation of Effective Interresidue Contact Energies
from Protein Crystal-Structures-Quasi-Chemical Approximation
J Macromolecules 18, 534-552 (1985)
M rows = ARNDCQEGHILKMFPSTWYV, cols = ARNDCQEGHILKMFPSTWYV
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//
H MIYS960101
D Quasichemical energy of transfer of amino acids from water to the protein
environment
R PMID:8604144
A Miyazawa, S. and Jernigan, R.L.
T Residue-residue potentials with a favorable contact pair term
and an unfavorable high packing density term, for simulation
and threading
J J. Mol. Biol. 256, 623-644 (1996)
M rows = ARNDCQEGHILKMFPSTWYV, cols = ARNDCQEGHILKMFPSTWYV
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//
H MIYS960102
D Quasichemical energy of interactions in an average buried environment
R PMID:8604144
A Miyazawa, S. and Jernigan, R.L.
T Residue-residue potentials with a favorable contact pair term
and an unfavorable high packing density term, for simulation
and threading
J J. Mol. Biol. 256, 623-644 (1996)
M rows = ARNDCQEGHILKMFPSTWYV, cols = ARNDCQEGHILKMFPSTWYV
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//
H MIYS960103
D Number of contacts between side chains derived from 1168 x-ray protein
structures
R PMID:8604144
A Miyazawa, S. and Jernigan, R.L.
T Residue-residue potentials with a favorable contact pair term
and an unfavorable high packing density term, for simulation
and threading
J J. Mol. Biol. 256, 623-644 (1996)
M rows = ARNDCQEGHILKMFPSTWYV, cols = ARNDCQEGHILKMFPSTWYV
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//
H MIYS990106
D Quasichemical energy of transfer of amino acids from water to the protein
environment
R PMID:10336383
A Miyazawa, S. and Jernigan, R.L.
T Self-consistent estimation of inter-residue protein contact energies
based on an equilibrium mixture approximation of residues
J Proteins 34, 49-68 (1999)
M rows = ARNDCQEGHILKMFPSTWYV, cols = ARNDCQEGHILKMFPSTWYV
-0.12
0.24 0.19
0.15 0.10 -0.06
0.27 -0.24 0.02 0.29
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0.22 0.09 0.06 0.24 -0.07 0.20
0.38 -0.22 0.12 0.44 0.20 0.27 0.46
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0.07 0.05 0.00 -0.10 -0.36 0.15 0.00 0.00 -0.40
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0.41 0.66 0.22 -0.01 0.33 0.28 -0.06 0.29 0.38 0.24 0.22 0.76
-0.27 0.03 0.04 0.30 -0.61 -0.06 0.12 -0.17 -0.29 -0.66 -0.70 0.29 -0.70
-0.36 -0.05 -0.01 0.18 -0.67 -0.11 0.14 -0.19 -0.34 -0.73 -0.80 0.19 -0.83 -0.88
0.15 0.17 0.18 0.33 -0.18 0.17 0.37 0.02 0.01 -0.05 -0.12 0.47 -0.13 -0.19 0.11
0.10 0.16 0.09 0.10 -0.13 0.22 0.18 -0.01 0.04 0.03 -0.02 0.36 0.05 -0.12 0.20 0.05
0.04 0.11 0.04 0.11 -0.15 0.12 0.16 -0.04 -0.03 -0.15 -0.15 0.33 -0.11 -0.15 0.13 0.04 0.03
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//
H MIYS990107
D Quasichemical energy of interactions in an average buried environment
R PMID:10336383
A Miyazawa, S. and Jernigan, R.L.
T Self-consistent estimation of inter-residue protein contact energies
based on an equilibrium mixture approximation of residues
J Proteins 34, 49-68 (1999)
M rows = ARNDCQEGHILKMFPSTWYV, cols = ARNDCQEGHILKMFPSTWYV
-0.08
0.18 0.03
0.07 -0.08 -0.26
0.10 -0.51 -0.27 -0.09
0.01 0.32 0.21 0.25 -0.55
0.09 -0.14 -0.19 -0.10 0.10 -0.10
0.19 -0.51 -0.19 0.04 0.31 -0.09 0.04
-0.04 0.03 -0.09 -0.06 0.03 0.00 0.13 -0.25
0.11 -0.01 -0.08 -0.27 -0.02 0.02 -0.19 0.04 -0.36
-0.07 0.20 0.32 0.31 -0.04 0.12 0.24 0.17 0.17 -0.18
-0.04 0.20 0.26 0.40 -0.01 0.13 0.28 0.18 0.16 -0.21 -0.20
0.13 0.28 -0.18 -0.50 0.35 -0.17 -0.57 0.01 0.10 0.22 0.24 0.16
0.00 0.20 0.19 0.36 -0.04 0.04 0.16 0.10 -0.02 -0.13 -0.13 0.24 -0.20
-0.01 0.20 0.22 0.32 -0.02 0.07 0.26 0.16 0.01 -0.12 -0.15 0.22 -0.25 -0.22
0.06 -0.02 -0.03 0.03 0.03 -0.09 0.05 -0.07 -0.08 0.12 0.09 0.06 0.01 0.03 -0.11
0.01 -0.03 -0.12 -0.20 0.08 -0.04 -0.14 -0.10 -0.05 0.20 0.19 -0.05 0.19 0.10 -0.02 -0.17
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0.02 -0.02 0.07 0.15 -0.07 0.10 0.06 0.04 -0.08 -0.05 -0.03 0.06 -0.21 -0.08 -0.21 0.15 0.20 -0.10
0.05 -0.10 0.02 -0.03 0.16 -0.06 -0.06 0.03 -0.05 0.02 0.00 -0.12 -0.08 -0.02 -0.13 0.04 0.09 0.01 0.01
-0.07 0.23 0.25 0.40 -0.04 0.16 0.28 0.10 0.19 -0.16 -0.19 0.22 -0.03 -0.11 0.07 0.16 0.11 -0.01 0.08 -0.19
//
H LIWA970101
D Modified version of the Miyazawa-Jernigan transfer energy
A Liwo, A., Oldziej, S., Pincus, M.R., Wawak, R.J., Rackovsky, S. and Scheraga,
H.A.
T A united-residue force field for off-lattice protein-structure simulations:
1. Functional forms and parameters of long-range side-chain interaction
potentials from protein crystal data.
J J. Comp. Chem. 18, 849-873 (1997)
M rows = ARNDCQEGHILKMFPSTWYV, cols = ARNDCQEGHILKMFPSTWYV
-3.28
-2.56 -2.03
-2.59 -2.19 -2.24
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-3.81 -3.42 -3.23 -3.12 -4.60 -3.25 -3.04 -3.47 -3.94 -4.98 -4.87 -2.84 -4.87 -5.07 -3.60 -3.30 -3.44 -4.74
-3.41 -3.01 -2.82 -2.84 -4.08 -2.90 -2.71 -3.12 -3.42 -4.51 -4.32 -2.58 -4.30 -4.43 -3.23 -2.97 -3.16 -4.20 -3.69
-3.93 -3.00 -3.02 -2.82 -4.53 -3.05 -2.84 -3.42 -3.44 -5.01 -4.85 -2.69 -4.59 -4.89 -3.39 -3.35 -3.58 -4.63 -4.04 -4.64
//
H KESO980101
D Quasichemical transfer energy derived from interfacial regions of
protein-protein complexes
R PMID:9865952
A Keskin, O., Bahar, I., Badretdinov, A.Y., Ptitsyn, O.B. and Jernigan, R.L.
T Empirical solvent-mediated potentials hold for both intra-molecular
and inter-molecular inter-residue interactions
J Protein Science 7, 2578-2586 (1998)
M rows = ARNDCQEGHILKMFPSTWYV, cols = ARNDCQEGHILKMFPSTWYV
-3.51
-3.26 -3.98
-2.06 -2.67 -1.99
-2.74 -3.92 -2.50 -2.47
-3.99 -4.41 -1.76 -3.56 -7.23
-3.65 -4.13 -3.00 -3.15 -4.37 -4.71
-2.69 -4.05 -2.43 -2.35 -3.02 -3.45 -2.85
-2.24 -2.71 -1.63 -1.84 -3.43 -3.02 -1.58 -1.77
-3.29 -3.24 -3.05 -2.93 -4.79 -4.20 -3.15 -2.47 -3.08
-4.45 -4.29 -3.42 -3.46 -5.53 -4.65 -3.99 -3.50 -4.55 -5.97
-5.02 -5.01 -3.94 -4.16 -6.13 -5.36 -4.35 -3.79 -4.85 -6.67 -7.16
-1.91 -2.11 -1.63 -2.47 -2.28 -2.56 -2.83 -1.32 -2.14 -2.88 -3.24 -1.02
-4.42 -4.13 -3.05 -3.69 -5.07 -4.46 -3.76 -3.02 -4.47 -5.37 -6.24 -2.36 -5.89
-4.43 -4.51 -3.89 -3.52 -4.81 -4.89 -4.10 -3.76 -3.82 -6.11 -6.65 -2.70 -5.58 -6.45
-1.78 -2.43 -1.01 -1.24 -2.97 -2.67 -1.70 -1.01 -1.80 -3.09 -3.75 -0.50 -3.11 -3.46 -0.83
-2.49 -2.78 -2.13 -2.34 -3.41 -3.06 -2.57 -1.68 -3.12 -3.47 -4.12 -1.91 -3.33 -4.01 -1.56 -2.14
-2.38 -2.43 -2.05 -2.41 -2.92 -3.44 -2.34 -1.81 -2.73 -3.61 -4.28 -1.64 -3.33 -3.85 -1.24 -2.22 -2.12
-4.66 -4.54 -3.31 -3.81 -4.70 -4.87 -3.84 -3.77 -4.50 -5.79 -6.40 -3.12 -5.49 -5.72 -3.96 -2.86 -3.48 -5.16
-3.96 -4.32 -3.14 -3.63 -4.71 -4.75 -3.62 -3.34 -3.78 -5.39 -5.67 -2.64 -5.01 -5.33 -2.92 -3.43 -3.33 -5.12 -4.58
-3.86 -3.70 -2.76 -3.28 -4.82 -4.29 -3.20 -2.77 -4.14 -5.31 -6.03 -2.19 -5.16 -5.33 -2.43 -2.95 -2.87 -4.70 -4.54 -4.86
//
H KESO980102
D Quasichemical energy in an average protein environment derived from interfacial
regions of protein-protein complexes
R PMID:9865952
A Keskin, O., Bahar, I., Badretdinov, A.Y., Ptitsyn, O.B. and Jernigan, R.L.
T Empirical solvent-mediated potentials hold for both intra-molecular
and inter-molecular inter-residue interactions
J Protein Science 7, 2578-2586 (1998)
M rows = ARNDCQEGHILKMFPSTWYV, cols = ARNDCQEGHILKMFPSTWYV
-0.38
0.16 -0.26
0.31 -0.02 -0.40
0.02 -0.87 -0.51 -0.07
0.00 -0.12 1.46 0.06 -2.38
0.08 -0.11 -0.05 0.21 0.21 -0.38
0.20 -0.87 -0.30 0.17 0.72 0.03 -0.20
0.08 -0.10 -0.09 0.11 -0.26 -0.11 0.50 -0.27
0.01 0.35 -0.52 0.00 -0.64 -0.31 -0.10 0.01 0.38
-0.08 0.37 0.16 0.54 -0.30 0.33 0.13 0.05 -0.02 -0.37
-0.09 0.21 0.23 0.41 -0.34 0.17 0.34 0.33 0.25 -0.50 -0.42
0.06 0.15 -0.44 -0.87 -0.50 0.00 -1.11 -0.17 -0.01 0.32 0.52 -0.22
-0.27 0.30 0.32 0.09 -0.08 0.27 0.13 0.31 -0.17 0.00 -0.30 0.61 -0.74
0.01 0.22 -0.22 0.55 0.49 0.14 0.09 -0.15 0.79 -0.44 -0.40 0.57 -0.14 -0.71
0.19 -0.17 0.19 0.36 -0.15 -0.11 0.01 0.13 0.33 0.11 0.01 0.30 -0.14 -0.19 -0.03
0.08 0.08 -0.32 -0.13 0.02 0.10 -0.25 0.08 -0.38 0.33 0.26 -0.50 0.25 -0.14 -0.15 -0.14
0.14 0.38 -0.30 -0.26 0.46 -0.32 -0.07 -0.11 -0.05 0.14 0.04 -0.29 0.19 -0.02 0.11 -0.27 -0.22
-0.38 0.04 0.20 0.11 0.44 0.01 0.20 -0.31 -0.05 -0.26 -0.31 1.00 -0.20 -0.13 -0.85 0.86 0.18 0.27
0.00 -0.07 0.04 -0.04 0.10 -0.21 0.08 -0.21 0.34 -0.12 0.08 0.14 -0.05 -0.07 -0.13 -0.03 0.00 -0.02 0.20
-0.11 0.35 0.22 0.11 -0.22 0.05 0.30 0.17 -0.23 -0.33 -0.48 0.40 -0.40 -0.27 0.16 0.25 0.27 0.20 0.03 -0.49
//
H MOOG990101
D Quasichemical potential derived from interfacial regions of protein-protein
complexes
R PMID:10328272
A Moont, G., Gabb, H.A. and Sternberg, M.J.E.
T Use of pair potentials across protein interfaces in screening predicted
docked complexes
J Proteins 35, 364-373 (1999)
M rows = ARNDCQEGHILKMFPSTWYV, cols = ARNDCQEGHILKMFPSTWYV
-0.48
-0.20 -0.11
-0.21 0.24 -0.18
-0.39 0.45 -0.12 -0.65
-0.12 0.17 -0.30 -0.49 0.00
-0.16 0.24 0.08 -0.01 0.23 -0.29
-0.39 0.37 -0.01 -0.35 -0.14 -0.05 -0.67
-0.29 0.01 -0.18 -0.24 0.11 0.05 -0.37 -0.39
0.04 0.10 -0.14 0.06 0.00 0.01 0.14 0.08 0.03
-0.10 0.10 -0.05 -0.24 0.00 0.15 -0.28 -0.20 0.24 -0.20
0.01 0.07 -0.29 -0.21 0.09 0.02 -0.29 -0.13 0.13 0.35 -0.06
-0.53 -0.01 -0.17 0.16 -0.03 -0.17 0.16 -0.19 -0.02 -0.21 -0.07 -0.78
0.15 0.37 -0.01 0.02 0.00 0.23 0.10 0.34 0.00 0.33 0.44 0.09 0.00
0.13 0.31 -0.10 -0.01 0.18 0.16 -0.11 -0.12 0.34 0.59 0.41 -0.05 0.58 0.33
-0.56 0.03 0.02 -0.22 -0.28 -0.14 -0.30 -0.27 -0.22 -0.43 -0.06 -0.46 0.39 0.08 -0.57
-0.15 0.19 -0.16 0.00 0.15 -0.10 -0.10 -0.19 0.08 -0.14 -0.19 -0.24 -0.01 0.05 -0.13 -0.63
-0.43 0.00 -0.23 -0.24 -0.17 -0.17 -0.23 -0.21 0.06 -0.05 -0.05 -0.22 0.10 0.03 -0.13 -0.05 -0.58
0.08 0.37 0.04 0.02 0.00 0.22 0.00 0.10 0.00 0.43 0.25 0.06 0.00 0.34 0.35 0.05 0.03 0.00
0.15 0.42 0.26 0.25 0.25 0.26 0.08 0.07 0.47 0.34 0.27 0.26 0.47 0.43 0.24 0.12 0.15 0.59 0.09
-0.01 -0.04 -0.12 -0.29 -0.09 0.08 -0.13 -0.13 -0.10 0.20 0.21 -0.20 0.38 0.23 -0.10 -0.19 -0.13 0.40 0.27 0.00
//
H BETM990101
D Modified version of the Miyazawa-Jernigan transfer energy
R PMID:10048329
A Betancourt,M.R. and Thirumalai,D.
T Pair potentials for protein folding: Choice of reference states
and sensitivity of predicted native states to variations
in the interaction schemes
J Protein Science 8, 361-369 (1999)
M rows = ARNDCQEGHILKMFPSTWYV, cols = ARNDCQEGHILKMFPSTWYV
-0.20
0.27 0.13
0.24 0.02 -0.04
0.30 -0.71 -0.12 0.27
-0.26 0.32 0.28 0.38 -1.34
0.21 -0.12 -0.05 0.12 0.04 0.14
0.43 -0.75 -0.01 0.40 0.46 0.10 0.45
-0.03 0.14 0.10 0.17 -0.09 0.20 0.48 -0.20
0.21 0.04 0.10 -0.22 -0.19 0.22 -0.11 0.23 -0.33
-0.35 0.18 0.55 0.54 -0.48 0.14 0.38 0.21 0.19 -0.60
-0.37 0.09 0.36 0.62 -0.50 0.08 0.37 0.14 0.10 -0.79 -0.81
0.20 0.50 -0.14 -0.69 0.35 -0.20 -0.87 0.12 0.26 0.21 0.16 0.38
-0.23 0.17 0.32 0.62 -0.49 -0.01 0.24 0.08 -0.17 -0.60 -0.68 0.22 -0.56
-0.33 0.08 0.29 0.48 -0.53 -0.04 0.34 0.11 -0.19 -0.65 -0.78 0.11 -0.89 -0.82
0.07 -0.02 0.13 0.25 -0.18 -0.05 0.26 -0.01 -0.05 0.05 -0.08 0.12 -0.16 -0.19 -0.07
0.15 0.12 0.14 0.01 0.09 0.25 0.10 0.10 0.15 0.35 0.26 0.10 0.32 0.10 0.17 0.13
0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00
-0.40 -0.41 -0.09 0.06 -0.74 -0.11 -0.15 -0.24 -0.46 -0.65 -0.70 -0.28 -0.94 -0.78 -0.73 0.07 0.00 -0.74
-0.15 -0.37 0.01 -0.07 -0.16 -0.18 -0.16 -0.04 -0.21 -0.33 -0.44 -0.40 -0.51 -0.49 -0.40 0.07 0.00 -0.55 -0.27
-0.38 0.17 0.39 0.66 -0.51 0.17 0.41 0.04 0.18 -0.68 -0.80 0.16 -0.47 -0.67 -0.08 0.25 0.00 -0.62 -0.27 -0.72
//
H TOBD000101
D Optimization-derived potential obtained for small set of decoys
R PMID:10813832
A Tobi, D., Shafran, G., Linial, N. and Elber, R.
T On the design and analysis of protein folding potentials
J Proteins 40, 71-85 (2000)
M rows = ARNDCQEGHILKMFPSTWYV, cols = ARNDCQEGHILKMFPSTWYV
-0.17
0.03 1.01
0.33 0.82 -0.68
0.58 -0.40 0.28 -0.24
-0.48 0.80 -1.89 -0.32 -2.94
-0.14 0.50 0.87 -0.26 -0.84 0.73
0.29 -0.91 0.78 0.18 0.16 0.48 1.03
0.43 0.12 0.46 -0.55 0.14 -0.08 0.88 -0.30
0.66 -0.62 0.95 0.63 -2.34 0.83 -0.17 0.19 -3.30
-0.79 0.31 0.48 0.19 -0.26 0.31 -0.47 0.31 -0.37 -0.27
-0.13 0.28 1.17 0.41 -0.25 -0.22 -0.05 0.23 -0.17 -0.58 -1.42
0.18 0.56 0.00 -0.71 0.45 0.86 -0.34 0.82 0.79 -0.08 0.43 1.01
-0.82 0.40 1.92 0.08 -1.99 0.16 0.06 0.08 -0.52 0.03 -0.36 0.77 -1.08
-0.49 -0.89 0.36 0.50 -2.52 -0.65 -0.12 0.90 -1.03 -0.72 -0.89 0.32 -1.37 -2.38
0.87 -0.59 0.08 0.20 -0.19 0.24 -0.18 -0.81 -1.01 -0.33 0.08 0.42 -0.75 1.41 0.06
0.18 0.84 -0.78 0.32 0.47 0.18 0.15 -0.05 1.17 0.49 0.80 -0.04 -0.20 -0.79 0.60 0.03
-0.45 -0.19 0.13 0.49 -1.38 -0.20 0.81 0.10 0.80 -0.29 0.30 0.38 -0.40 0.32 0.47 0.32 -0.38
-0.04 0.23 1.45 -0.05 -2.09 -1.14 -0.41 0.51 1.10 -0.63 -0.44 -0.38 -0.33 -0.80 -2.24 -0.08 -0.61 -0.97
-0.08 -1.64 0.43 0.04 -0.65 -0.64 -0.16 -0.56 -1.02 -1.34 0.25 -0.20 -0.19 -0.79 -0.68 -0.83 0.67 -0.85 -2.22
-0.54 0.41 0.71 0.31 -0.46 0.37 0.34 -0.12 0.67 -0.98 -1.03 0.17 -0.93 -0.43 0.32 0.52 0.24 -0.41 -0.50 -0.53
//
H TOBD000102
D Optimization-derived potential obtained for large set of decoys
R PMID:10813832
A Tobi, D., Shafran, G., Linial, N. and Elber, R.
T On the design and analysis of protein folding potentials
J Proteins 40, 71-85 (2000)
M rows = ARNDCQEGHILKMFPSTWYV, cols = ARNDCQEGHILKMFPSTWYV
-0.15
-0.16 0.65
1.01 0.14 -0.45
0.62 -0.57 -0.53 0.89
-0.96 -0.25 0.18 -0.50 -2.11
0.16 1.24 0.57 0.78 -0.54 0.41
-0.02 -0.70 -0.19 0.83 0.65 0.28 1.59
0.23 0.84 0.12 0.37 -0.74 -0.36 0.48 0.01
0.29 0.36 -0.06 -0.07 -0.66 -0.60 1.27 0.42 -2.26
-0.85 -0.22 0.22 -0.18 -1.02 0.66 0.31 -0.04 -0.31 -1.10
-0.72 -0.04 -0.19 1.12 -0.24 0.10 0.99 -0.20 -0.31 -1.15 -1.60
0.96 1.24 0.38 -0.55 -0.38 -0.04 -0.36 0.95 -0.01 -0.01 1.02 2.28
-0.85 0.67 0.66 0.42 -1.30 0.41 0.00 -0.63 0.18 0.07 -1.39 1.66 -1.89
-0.79 0.43 0.50 0.35 -0.96 -0.10 -0.56 -0.10 0.52 -0.76 -1.24 -0.01 -1.04 -1.39
0.08 -0.31 -0.25 0.83 -0.45 -0.07 0.24 0.16 0.93 0.43 -0.27 0.45 -0.22 -0.09 0.41
0.24 0.91 -0.17 0.29 -0.41 0.27 1.14 -0.09 -0.28 -0.14 1.13 0.13 -0.59 -0.01 0.48 1.31
0.33 -0.44 1.23 -0.35 0.00 -0.28 -0.11 0.73 -0.27 -0.18 -0.18 -0.16 -0.62 -0.29 0.34 0.03 -0.41
0.24 -0.14 -0.04 -1.41 -0.32 0.00 1.13 0.87 0.91 -1.90 -0.85 0.33 -0.30 0.58 -2.51 -0.77 0.32 -1.35
-0.50 0.54 0.22 -0.27 -0.23 -0.79 -0.84 -0.62 -1.34 -1.42 -0.53 -1.06 0.02 -1.43 -0.17 -0.86 -0.19 -1.96 -1.35
-0.36 0.53 0.54 0.20 -0.58 -0.06 0.47 -0.43 0.51 -1.46 -0.77 0.75 -1.22 -0.89 0.75 0.14 0.29 -0.18 -0.30 -1.32
//
H PARB960101
D Statistical contact potential derived by the quasichemical approximation
R PMID:8627632
A Park, B. and Levitt, M.
T Energy functions that discriminate X-ray and near-native folds
from well-constructed decoys
J J. Mol. Biol. 258, 367-392 (1996)
* (Glu is not available)
M rows = ARNDCQEGHILKMFPSTWYV, cols = ARNDCQEGHILKMFPSTWYV
0.5
0.2 -0.9
0.3 -0.8 -0.7
0.3 -1.4 -0.6 0.0
0.3 0.0 0.0 0.0 -2.7
0.0 -0.9 -0.7 -0.3 -0.2 -0.5
0.6 -1.5 -0.6 0.0 0.1 -0.4 0.1
NA NA NA NA NA NA NA NA
0.0 -1.0 -0.8 -1.1 -0.6 -0.5 -1.0 NA -1.6
-0.4 -0.7 -0.1 0.0 -0.8 -0.4 -0.2 NA -0.8 -1.5
-0.4 -0.6 -0.1 0.0 -0.8 -0.6 -0.1 NA -0.7 -1.4 -1.4
1.0 0.1 -0.3 -1.0 0.5 -0.4 -1.1 NA 0.0 0.0 0.1 0.7
-0.5 -0.5 -0.3 0.1 -0.8 -0.6 -0.3 NA -0.9 -1.4 -1.3 -0.1 -1.5
-0.8 -0.9 -0.6 -0.3 -1.2 -0.8 -0.5 NA -1.2 -1.7 -1.6 -0.4 -1.9 -2.0
0.6 -0.2 -0.1 0.1 0.0 -0.3 0.1 NA -0.4 -0.1 -0.1 0.6 -0.5 -0.7 0.1
0.5 -0.4 -0.1 -0.3 -0.1 0.0 -0.2 NA -0.6 -0.1 0.0 0.1 -0.1 -0.4 0.2 0.0
0.0 -0.6 -0.4 -0.3 -0.3 -0.5 -0.3 NA -0.7 -0.6 -0.3 0.0 -0.6 -0.7 0.0 -0.2 -0.5
-0.8 -1.3 -0.8 -0.6 -1.3 -1.0 -0.8 NA -1.5 -1.8 -1.7 -0.8 -2.0 -2.0 -1.3 -0.6 -0.9 -2.2
-0.7 -1.4 -0.8 -1.0 -0.8 -1.1 -1.0 NA -1.5 -1.4 -1.4 -1.0 -1.5 -1.7 -1.0 -0.6 -0.8 -1.8 -1.6
-0.3 -0.5 0.0 0.4 -0.5 -0.4 0.0 NA -0.5 -1.2 -1.2 0.1 -1.0 -1.5 0.0 0.0 -0.3 -1.6 -1.2 -1.1
//
H PARB960102
D Modified version of the Miyazawa-Jernigan transfer energy
R PMID:8627632
A Park, B. and Levitt, M.
T Energy functions that discriminate X-ray and near-native folds
from well-constructed decoys
J J. Mol. Biol. 258, 367-392 (1996)
* (Glu is not available)
M rows = ARNDCQEGHILKMFPSTWYV, cols = ARNDCQEGHILKMFPSTWYV
-2.9
-2.4 -2.9
-2.8 -3.2 -3.6
-2.6 -3.7 -3.3 -2.6
-3.1 -2.6 -3.2 -2.9 -6.1
-2.7 -2.9 -3.2 -2.7 -2.9 -2.6
-1.9 -3.2 -2.8 -2.0 -2.4 -2.2 -1.5
NA NA NA NA NA NA NA NA
-2.6 -2.9 -3.2 -3.3 -3.3 -2.5 -2.8 NA -3.5
-3.9 -3.3 -3.2 -2.9 -4.2 -3.2 -2.7 NA -3.4 -4.9
-3.7 -3.0 -3.0 -2.7 -4.0 -3.1 -2.4 NA -3.1 -4.6 -4.3
-1.9 -2.0 -3.0 -3.5 -2.4 -2.7 -3.2 NA -2.2 -2.9 -2.5 -1.7
-3.8 -3.1 -3.3 -2.7 -4.2 -3.3 -2.7 NA -3.5 -4.7 -4.4 -2.9 -4.8
-3.7 -3.0 -3.2 -2.7 -4.1 -3.0 -2.4 NA -3.3 -4.5 -4.2 -2.8 -4.6 -4.3
-2.3 -2.4 -2.7 -2.3 -2.8 -2.5 -1.8 NA -2.6 -3.0 -2.8 -1.8 -3.4 -3.1 -2.2
-2.4 -2.6 -2.8 -2.8 -3.0 -2.3 -2.3 NA -2.7 -3.0 -2.6 -2.3 -3.0 -2.8 -2.2 -2.4
-3.2 -3.1 -3.4 -3.2 -3.5 -3.1 -2.7 NA -3.2 -3.8 -3.3 -2.8 -3.8 -3.4 -2.8 -2.9 -3.5
-3.8 -3.5 -3.5 -3.2 -4.3 -3.3 -2.8 NA -3.6 -4.7 -4.4 -3.3 -4.8 -4.4 -3.7 -3.1 -3.7 -4.7
-3.7 -3.6 -3.5 -3.5 -3.8 -3.4 -3.0 NA -3.7 -4.4 -4.1 -3.5 -4.4 -4.1 -3.5 -3.1 -3.6 -4.3 -4.1
-4.1 -3.5 -3.5 -2.8 -4.3 -3.4 -2.8 NA -3.5 -5.0 -4.7 -3.1 -4.7 -4.6 -3.2 -3.1 -3.9 -4.8 -4.5 -5.1
//
H KOLA930101
D Statistical potential derived by the quasichemical approximation
A Kolinski, A., Godzik, A. and Skolnick, J.
T A general method for the prediction of the three dimensional structure
and folding pathway of globular proteins: Application to designed helical
proteins
J J. Chem. Phys. 98, 7420-7433 (1993)
M rows = ARNDCQEGHILKMFPSTWYV, cols = ARNDCQEGHILKMFPSTWYV
-0.1
0.5 0.2
0.1 0.0 -0.4
0.1 -1.1 -0.6 0.3
0.1 0.4 0.3 0.3 -3.3
0.0 -0.5 -0.4 0.0 0.1 0.0
0.5 -0.9 -0.4 0.3 0.8 0.2 0.6
0.1 0.5 -0.1 -0.4 0.1 -0.1 0.6 0.3
-0.1 -0.4 -0.5 -1.0 -1.2 0.9 -0.9 0.3 -1.4
-0.6 0.4 0.7 0.6 -1.1 0.3 0.4 0.3 -0.2 -0.8
-0.4 0.2 0.5 0.8 -0.5 0.4 0.7 0.5 -0.3 -0.6 -0.6
1.0 1.7 0.1 -0.6 1.6 0.4 -0.7 1.2 0.3 0.8 1.1 1.9
0.1 0.1 0.2 1.0 -1.8 0.2 0.0 0.4 -0.9 -0.7 -0.6 0.5 -1.1
-0.6 -0.4 0.2 0.4 -1.5 0.0 0.1 0.1 -1.0 -0.8 -0.9 0.3 -1.1 -1.5
0.3 0.5 0.4 0.6 0.0 -0.1 0.6 0.4 -0.5 0.3 0.5 1.1 -0.2 -0.2 0.1
-0.1 0.0 -0.3 -0.9 -0.4 0.0 -0.2 0.0 -0.6 0.4 0.4 0.5 0.0 0.0 0.4 -0.6
-0.3 0.1 -0.3 -0.6 0.0 -0.2 -0.2 0.0 -0.6 0.0 0.3 0.6 0.2 0.0 0.3 -0.5 -0.3
-0.7 -0.9 -0.1 -0.2 -0.5 -0.2 0.1 -0.5 -1.2 -0.9 -0.8 0.1 -1.3 -1.3 -0.7 -0.1 0.0 -0.8
-0.5 -0.4 -0.5 -0.3 -0.1 -0.5 0.0 -0.4 -0.8 -0.5 -0.1 -0.2 -0.6 -0.5 -0.9 -0.1 -0.2 -0.5 -0.8
-0.6 0.3 0.2 0.7 -0.8 0.2 0.4 0.2 -0.2 -0.7 -0.6 0.9 -0.5 -0.8 0.1 0.3 0.2 -0.8 -0.3 -0.9
//
H GODA950101
D Quasichemical statistical potential derived from buried contacts
R PMID:8535247
A Godzik, A., Kolinski, A. and Skolnick, J.
T Are Proteins Ideal Mixtures of Amino-Acids-Analysis
of Energy Parameter Sets
J Protein Science 4, 2107-2117 (1995)
* (Glu is not available)
M rows = ARNDCQEGHILKMFPSTWYV, cols = ARNDCQEGHILKMFPSTWYV
0.1
0.3 -0.4
0.1 -0.5 -0.7
0.2 -1.0 -0.6 -0.3
0.1 0.4 -0.1 0.3 -0.9
0.0 -0.4 -0.6 -0.3 0.1 -0.4
0.3 -1.0 -0.5 -0.3 0.4 -0.3 -0.4
NA NA NA NA NA NA NA NA
0.2 -0.2 -0.3 -0.7 0.0 -0.2 -0.6 NA -0.8
-0.1 0.3 0.4 0.5 0.2 0.2 0.5 NA 0.4 -0.1
-0.1 0.3 0.3 0.6 0.1 0.3 0.5 NA 0.4 -0.1 -0.2
0.3 0.3 -0.5 -0.9 0.4 -0.3 -0.8 NA 0.0 0.2 0.3 0.1
0.0 0.3 0.1 0.5 0.1 0.1 0.3 NA 0.2 0.0 0.0 0.2 -0.2
-0.1 0.2 0.1 0.3 0.1 0.1 0.3 NA 0.1 0.0 -0.1 0.1 -0.1 -0.2
0.0 -0.3 -0.3 0.0 -0.1 -0.4 -0.1 NA -0.1 0.2 0.1 0.1 0.0 -0.1 -0.3
0.1 -0.3 -0.4 -0.5 0.1 -0.3 -0.5 NA -0.3 0.4 0.4 -0.3 0.3 0.1 -0.3 -0.4
0.0 -0.1 -0.3 -0.3 0.0 -0.2 -0.2 NA -0.1 0.1 0.2 -0.1 0.1 0.1 -0.2 -0.2 0.0
0.0 -0.1 0.0 0.0 0.2 -0.1 0.0 NA 0.0 0.1 0.1 -0.1 -0.1 -0.1 -0.4 0.2 0.2 0.0
-0.1 -0.3 -0.2 -0.2 0.1 -0.2 -0.3 NA -0.1 0.1 0.0 -0.3 -0.1 0.0 -0.4 -0.1 0.0 0.1 -0.1
-0.1 0.4 0.3 0.6 0.0 0.2 0.4 NA 0.5 -0.1 -0.1 0.4 0.1 0.0 0.1 0.3 0.2 0.1 0.1 -0.2
//
H SKOJ970101
D Statistical potential derived by the quasichemical approximation
R PMID:9070450
A Skolnick, J., Jaroszewski, L., Kolinski, A. and Godzik, A.
T Derivation and testing of pair potentials for protein folding.
When is the quasichemical approximation correct?
J Protein Science 6, 676-688 (1997)
M rows = ARNDCQEGHILKMFPSTWYV, cols = ARNDCQEGHILKMFPSTWYV
0.8
0.6 -0.1
0.9 0.0 0.1
1.2 -0.5 0.4 0.9
0.6 0.7 0.6 0.8 -1.3
0.6 0.2 0.2 0.6 0.3 0.3
1.2 -0.4 0.5 0.9 0.9 0.8 1.2
1.2 0.2 0.7 0.8 1.3 0.8 1.1 1.5
0.4 -0.1 0.2 -0.1 0.1 0.1 0.1 0.7 -0.8
-0.6 -0.2 0.5 0.5 -0.5 0.1 0.4 0.4 -0.1 -1.4
-0.3 -0.1 0.4 0.7 -0.4 0.2 0.6 0.4 -0.1 -1.3 -1.2
1.3 1.1 0.7 0.2 1.3 0.5 0.0 0.9 1.0 0.5 0.5 2.1
-0.3 0.2 0.3 0.6 -0.3 0.1 0.4 0.5 -0.4 -1.0 -1.0 0.6 -1.1
-0.2 -0.4 0.1 0.5 -0.6 -0.1 0.4 0.3 -0.4 -1.3 -1.3 0.4 -1.3 -1.5
0.6 0.1 0.5 0.9 0.4 0.2 0.7 0.8 0.0 0.0 0.0 0.9 -0.2 -0.1 0.4
0.9 0.2 0.7 0.7 0.6 0.6 0.6 0.8 0.0 0.3 0.4 0.9 0.4 0.1 0.6 0.6
0.5 0.0 0.3 0.5 0.5 0.4 0.4 0.5 0.1 -0.3 0.0 0.8 0.0 -0.2 0.2 0.4 0.1
-0.6 -0.6 0.0 0.0 -0.7 -0.4 -0.1 0.0 -0.9 -1.3 -1.4 -0.1 -1.5 -1.5 -0.8 -0.1 -0.2 -1.2
-0.4 -0.7 -0.2 -0.2 -0.1 -0.3 -0.2 0.1 -0.8 -1.0 -0.9 -0.2 -1.1 -1.0 -0.5 0.1 -0.2 -1.2 -0.8
-0.4 0.0 0.5 1.0 -0.6 0.2 0.5 0.5 0.0 -1.2 -1.2 0.7 -0.8 -1.1 -0.1 0.4 -0.2 -1.1 -0.8 -1.2
//
H SKOJ000101
D Statistical quasichemical potential with the partially composition-corrected
pair scale
R PMID:10651034
A Skolnick, J., Kolinski, A. and Ortiz, A.
T Derivation of protein-specific pair potentials based on weak sequence
fragment similarity
J Proteins 38, 3-16 (2000)
M rows = ARNDCQEGHILKMFPSTWYV, cols = ARNDCQEGHILKMFPSTWYV
1.0
0.4 -0.1
0.8 0.0 0.1
1.1 -0.6 0.0 0.6
0.6 0.2 0.5 0.5 -1.7
0.6 0.0 0.0 0.2 0.2 0.0
1.1 -0.5 0.3 0.7 0.8 0.2 1.0
1.4 0.3 0.6 0.8 0.9 0.8 1.1 1.7
0.5 -0.1 0.0 -0.2 -0.2 -0.1 -0.1 0.7 -0.6
-0.3 -0.2 0.4 0.6 -0.5 0.0 0.3 0.5 0.0 -1.1
-0.1 -0.2 0.3 0.6 -0.5 0.0 0.4 0.7 0.0 -1.2 -1.1
1.0 0.6 0.3 -0.2 0.9 0.1 -0.4 0.7 0.6 0.4 0.3 1.6
-0.2 0.0 0.1 0.4 -0.5 -0.1 0.4 0.6 -0.3 -0.8 -1.0 0.3 -1.0
-0.2 -0.4 0.0 0.4 -0.8 -0.1 0.2 0.4 -0.3 -1.1 -1.1 0.3 -1.1 -1.2
0.8 0.1 0.6 0.9 0.4 0.4 0.5 1.1 0.3 0.1 0.1 0.8 0.0 -0.2 0.9
0.9 0.3 0.4 0.3 0.4 0.2 0.4 0.9 0.1 0.4 0.4 0.7 0.3 0.1 0.6 0.5
0.6 0.0 0.2 0.1 0.1 0.1 0.2 0.6 0.0 -0.2 0.0 0.5 -0.1 -0.2 0.5 0.2 0.2
-0.5 -0.6 -0.2 0.0 -0.7 -0.5 -0.2 0.2 -0.7 -1.1 -1.1 -0.1 -1.2 -1.3 -0.7 -0.2 -0.3 -1.1
-0.2 -0.7 -0.2 -0.1 -0.3 -0.3 -0.2 0.3 -0.7 -0.8 -0.9 -0.2 -0.8 -0.9 -0.5 0.1 -0.2 -1.1 -0.7
-0.1 0.1 0.5 0.8 -0.5 0.3 0.5 0.8 -0.1 -1.0 -0.9 0.5 -0.8 -0.9 0.2 0.4 -0.1 -0.9 -0.7 -0.8
//
H SKOJ000102
D Statistical quasichemical potential with the composition-corrected pair scale
R PMID:10651034
A Skolnick, J., Kolinski, A. and Ortiz, A.
T Derivation of protein-specific pair potentials based on weak sequence
fragment similarity
J Proteins 38, 3-16 (2000)
M rows = ARNDCQEGHILKMFPSTWYV, cols = ARNDCQEGHILKMFPSTWYV
0.8
0.3 -0.3
0.7 -0.2 -0.2
0.9 -0.6 0.0 0.2
0.0 -0.6 -0.5 -0.3 -2.4
0.4 -0.2 -0.2 0.0 -0.7 -0.5
1.0 -0.5 0.2 0.5 -0.2 0.1 0.5
1.2 0.2 0.4 0.7 0.1 0.5 0.9 1.1
0.2 -0.4 -0.4 -0.4 -1.4 -0.5 -0.3 0.3 -1.2
-0.3 -0.2 0.2 0.5 -0.8 -0.1 0.3 0.4 -0.3 -1.1
-0.1 -0.2 0.3 0.5 -0.6 0.0 0.4 0.6 -0.2 -1.2 -1.1
0.8 0.4 0.2 -0.2 -0.3 0.0 -0.4 0.6 0.1 0.3 0.3 0.6
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-0.2 -0.4 -0.2 0.2 -1.1 -0.3 0.1 0.3 -0.6 -1.1 -1.1 0.1 -1.2 -1.3
0.7 0.0 0.3 0.6 -0.4 0.0 0.4 0.8 -0.2 0.0 0.1 0.5 -0.4 -0.3 0.3
0.8 0.2 0.2 0.2 -0.4 0.1 0.3 0.8 -0.2 0.3 0.4 0.5 -0.1 0.0 0.4 0.2
0.5 0.0 0.1 0.1 -0.5 0.0 0.1 0.6 -0.2 -0.2 0.0 0.4 -0.3 -0.3 0.3 0.2 0.0
-0.6 -0.9 -0.6 -0.4 -1.5 -0.9 -0.5 -0.2 -1.2 -1.2 -1.2 -0.5 -1.6 -1.4 -0.9 -0.5 -0.6 -1.7
-0.3 -0.7 -0.3 -0.2 -1.0 -0.4 -0.2 0.2 -0.9 -0.9 -0.9 -0.3 -1.0 -1.0 -0.6 0.0 -0.2 -1.3 -0.9
0.0 0.0 0.3 0.6 -0.7 0.1 0.4 0.7 -0.3 -1.0 -0.9 0.4 -0.8 -0.9 0.2 0.4 -0.1 -1.0 -0.7 -0.7
//
H BONM030101
D Quasichemical statistical potential for the antiparallel orientation of
interacting side groups
R PMID:15072433
A Boniecki, M., Rotkiewicz, P., Skolnick, J. and Kolinski, A.
T Protein fragment reconstruction using various modeling techniques
J J. Comput. Aided Mol. Des. 17, 725-738 (2003)
M rows = ARNDCQEGHILKMFPSTWYV, cols = ARNDCQEGHILKMFPSTWYV
-0.1
0.6 0.4
0.7 0.1 0.6
1.0 -0.2 0.8 1.8
-0.3 -0.7 0.2 0.6 -2.3
0.6 0.2 0.8 1.2 0.1 0.8
1.0 -0.1 1.2 2.1 0.7 1.6 2.3
0.1 0.7 0.3 0.5 -0.4 0.6 1.0 0.1
0.4 0.0 -0.2 -0.3 -1.2 -0.1 0.0 0.5 -0.9
-0.4 -0.4 0.7 0.9 -0.2 0.3 0.7 0.2 -0.8 -0.5
-0.4 -0.4 0.8 1.0 -0.4 0.3 0.7 0.3 -0.6 -0.4 -0.4
1.0 1.0 1.4 0.9 0.4 1.5 1.4 1.0 0.3 0.7 0.6 2.5
-0.2 -0.3 0.5 1.1 -0.4 0.3 1.1 0.2 -0.7 -0.3 -0.3 0.7 -0.7
-0.3 -0.5 -0.4 -0.1 -1.4 -0.4 -0.1 0.3 -0.8 -1.4 -1.4 -0.2 -1.4 -1.6
0.4 -0.1 0.6 1.0 -0.1 0.6 1.0 0.4 -0.6 0.4 0.4 1.3 0.3 -0.7 0.4
0.3 -0.2 0.5 0.7 -0.1 0.7 0.9 0.1 -0.6 0.4 0.3 1.3 0.6 -0.7 0.5 0.3
0.2 -0.1 0.5 0.9 -0.1 0.6 1.0 0.2 -0.6 0.3 0.3 1.2 0.5 -0.8 0.6 0.5 0.6
0.1 -0.5 -0.4 -0.2 -1.2 -0.4 -0.2 0.3 -0.9 -1.2 -1.1 0.0 -1.1 -1.2 -0.8 -0.5 -0.8 -1.4
0.0 -0.3 -0.3 -0.2 -1.2 -0.3 -0.1 0.4 -0.6 -1.1 -1.1 0.0 -0.9 -1.2 -0.8 -0.6 -0.6 -1.1 -0.9
-0.5 -0.3 0.7 1.0 -0.3 0.4 0.8 0.1 -0.7 -0.5 -0.4 0.7 -0.2 -1.3 0.3 0.3 0.3 -1.1 -1.0 -0.6
//
H BONM030102
D Quasichemical statistical potential for the intermediate orientation of
interacting side groups
R PMID:15072433
A Boniecki, M., Rotkiewicz, P., Skolnick, J. and Kolinski, A.
T Protein fragment reconstruction using various modeling techniques
J J. Comput. Aided Mol. Des. 17, 725-738 (2003)
M rows = ARNDCQEGHILKMFPSTWYV, cols = ARNDCQEGHILKMFPSTWYV
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0.5 -0.2
0.4 -0.3 0.1
0.6 -0.8 0.2 0.6
-0.2 -0.6 0.3 0.3 -1.7
0.4 -0.4 0.3 0.6 0.3 0.6
0.8 -0.7 0.6 1.1 0.8 0.7 1.2
0.4 0.4 0.2 0.5 -0.3 0.5 0.9 0.1
0.5 -0.4 -0.5 -0.6 -1.1 -0.2 -0.4 0.4 -1.0
-0.1 -0.2 0.7 0.9 -0.2 0.7 0.8 0.3 -0.5 -0.3
-0.2 -0.4 0.6 0.8 -0.4 0.4 0.8 0.3 -0.5 -0.3 -0.5
0.8 0.2 0.6 0.1 0.8 0.8 0.2 0.7 0.0 1.0 0.8 1.6
0.0 -0.4 0.6 0.9 -0.3 0.5 0.9 0.2 -0.6 -0.2 -0.3 1.0 -0.5
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//
H BONM030103
D Quasichemical statistical potential for the parallel orientation of interacting
side groups
R PMID:15072433
A Boniecki, M., Rotkiewicz, P., Skolnick, J. and Kolinski, A.
T Protein fragment reconstruction using various modeling techniques
J J. Comput. Aided Mol. Des. 17, 725-738 (2003)
M rows = ARNDCQEGHILKMFPSTWYV, cols = ARNDCQEGHILKMFPSTWYV
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//
H BONM030104
D Distances between centers of interacting side chains in the antiparallel
orientation
R PMID:15072433
A Boniecki, M., Rotkiewicz, P., Skolnick, J. and Kolinski, A.
T Protein fragment reconstruction using various modeling techniques
J J. Comput. Aided Mol. Des. 17, 725-738 (2003)
M rows = ARNDCQEGHILKMFPSTWYV, cols = ARNDCQEGHILKMFPSTWYV
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//
H BONM030105
D Distances between centers of interacting side chains in the intermediate
orientation
R PMID:15072433
A Boniecki, M., Rotkiewicz, P., Skolnick, J. and Kolinski, A.
T Protein fragment reconstruction using various modeling techniques
J J. Comput. Aided Mol. Des. 17, 725-738 (2003)
M rows = ARNDCQEGHILKMFPSTWYV, cols = ARNDCQEGHILKMFPSTWYV
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5.1 6.0 5.5 5.3 5.5 5.3 5.2 5.5 5.6 5.8 5.8 5.7 5.9 6.1 5.5 5.2 5.4
5.9 5.9 6.5 6.0 6.1 6.2 6.2 5.2 6.0 6.3 6.3 5.7 6.5 6.5 5.8 5.7 6.5 7.5
5.6 6.3 5.9 6.2 6.1 6.7 6.1 4.8 6.2 6.2 6.1 5.7 6.1 6.4 5.6 5.9 6.1 6.9 6.5
5.4 6.0 5.6 5.6 5.7 5.4 5.4 4.6 5.6 6.0 6.0 5.9 5.9 6.0 5.7 5.4 5.7 6.3 6.0 5.8
//
H BONM030106
D Distances between centers of interacting side chains in the parallel
orientation
R PMID:15072433
A Boniecki, M., Rotkiewicz, P., Skolnick, J. and Kolinski, A.
T Protein fragment reconstruction using various modeling techniques
J J. Comput. Aided Mol. Des. 17, 725-738 (2003)
M rows = ARNDCQEGHILKMFPSTWYV, cols = ARNDCQEGHILKMFPSTWYV
4.8
5.5 6.7
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5.3 6.4 5.9 5.5 6.1 6.1
4.8 6.1 5.0 5.0 5.7 6.5 5.7
4.5 6.7 5.3 6.1 5.2 7.2 5.3 4.5
5.3 5.5 5.5 5.5 6.0 6.8 5.8 5.3 6.2
5.5 6.2 5.3 6.0 5.9 6.0 5.9 5.2 6.3 6.4
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5.4 5.3 5.9 5.8 6.5 5.8 6.3 4.9 5.9 5.9 6.0 5.5
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//
H MICC010101
D Optimization-derived potential
R PMID:11151013
A Micheletti, C., Seno, F., Banavar, J.R. and Maritan, A.
T Learning effective amino acid interactions through iterative
stochastic techniques
J Proteins 42, 422-431 (2001)
M rows = ARNDCQEGHILKMFPSTWYV, cols = ARNDCQEGHILKMFPSTWYV
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//
H SIMK990101
D Distance-dependent statistical potential (contacts within 0-5 Angstrooms)
R PMID:10336385
A Simons, K.T., Ruczinski, I., Kooperberg, C., Fox, B.A., Bystroff, C. and Baker,
D.
T Improved recognition of native-like protein structures using
a combination of sequence-dependent and sequence-independent
features of proteins
J Proteins 34, 82-95 (1999)
M rows = ARNDCQEGHILKMFPSTWYV, cols = ARNDCQEGHILKMFPSTWYV
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//
H SIMK990102
D Distance-dependent statistical potential (contacts within 5-7.5 Angstrooms)
R PMID:11782533
A Simons, K.T., Ruczinski, I., Kooperberg, C., Fox, B.A., Bystroff, C. and Baker,
D.
T Improved recognition of native-like protein structures using
a combination of sequence-dependent and sequence-independent
features of proteins
J Proteins 34, 82-95 (1999)
M rows = ARNDCQEGHILKMFPSTWYV, cols = ARNDCQEGHILKMFPSTWYV
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//
H SIMK990103
D Distance-dependent statistical potential (contacts within 7.5-10 Angstrooms)
R PMID:11782533
A Simons, K.T., Ruczinski, I., Kooperberg, C., Fox, B.A., Bystroff, C. and Baker,
D.
T Improved recognition of native-like protein structures using
a combination of sequence-dependent and sequence-independent
features of proteins
J Proteins 34, 82-95 (1999)
M rows = ARNDCQEGHILKMFPSTWYV, cols = ARNDCQEGHILKMFPSTWYV
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//
H SIMK990104
D Distance-dependent statistical potential (contacts within 10-12 Angstrooms)
R PMID:11782533
A Simons, K.T., Ruczinski, I., Kooperberg, C., Fox, B.A., Bystroff, C. and Baker,
D.
T Improved recognition of native-like protein structures using
a combination of sequence-dependent and sequence-independent
features of proteins
J Proteins 34, 82-95 (1999)
M rows = ARNDCQEGHILKMFPSTWYV, cols = ARNDCQEGHILKMFPSTWYV
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//
H SIMK990105
D Distance-dependent statistical potential (contacts longer than 12 Angstrooms)
R PMID:11782533
A Simons, K.T., Ruczinski, I., Kooperberg, C., Fox, B.A., Bystroff, C. and Baker,
D.
T Improved recognition of native-like protein structures using
a combination of sequence-dependent and sequence-independent
features of proteins
J Proteins 34, 82-95 (1999)
M rows = ARNDCQEGHILKMFPSTWYV, cols = ARNDCQEGHILKMFPSTWYV
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//
H ZHAC000101
D Environment-dependent residue contact energies (rows = helix, cols = helix)
R PMID:10706611
A Zhang, C. and Kim, S.H.
T Environment-dependent residue contact energies for proteins
J Proc. Natl. Acad. Sci. USA 97, 2550-2555 (2000)
M rows = ARNDCQEGHILKMFPSTWYV, cols = ARNDCQEGHILKMFPSTWYV
-1.65
0.02 1.08
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//
H ZHAC000102
D Environment-dependent residue contact energies (rows = helix, cols = strand)
R PMID:10706611
A Zhang, C. and Kim, S.H.
T Environment-dependent residue contact energies for proteins
J Proc. Natl. Acad. Sci. USA 97, 2550-2555 (2000)
M rows = ARNDCQEGHILKMFPSTWYV, cols = ARNDCQEGHILKMFPSTWYV
-0.94 1.26 0.55 0.76 -1.54 1.14 1.57 -0.78 0.44 -1.59 -1.64 1.91 -0.90 -1.49 0.28 0.20 -0.04 -0.92 -0.75 -1.45
0.56 1.79 2.31 0.79 -0.67 2.54 0.72 1.09 0.94 -0.01 0.01 3.68 0.89 -0.05 1.37 0.83 1.35 0.00 0.33 0.44
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0.66 0.76 0.76 1.19 -0.21 1.66 2.22 0.29 0.57 0.59 0.79 1.13 1.41 0.49 1.70 1.03 1.19 1.85 0.18 0.86
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0.82 1.05 2.18 2.11 0.01 2.42 2.58 1.15 0.97 0.20 0.31 1.31 1.25 0.12 2.00 1.09 1.13 0.58 0.31 0.39
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//
H ZHAC000103
D Environment-dependent residue contact energies (rows = helix, cols = coil)
R PMID:10706611
A Zhang, C. and Kim, S.H.
T Environment-dependent residue contact energies for proteins
J Proc. Natl. Acad. Sci. USA 97, 2550-2555 (2000)
M rows = ARNDCQEGHILKMFPSTWYV, cols = ARNDCQEGHILKMFPSTWYV
0.12 1.17 0.84 0.90 -0.81 1.16 1.44 0.10 0.69 -0.81 -0.78 1.16 -0.22 -0.67 0.61 0.47 0.36 -0.72 -0.37 -0.43
0.98 1.65 1.16 0.60 -0.21 1.26 1.12 1.09 1.16 -0.04 -0.09 2.37 0.47 -0.04 1.22 1.05 0.92 -0.09 0.06 0.32
0.69 1.16 1.16 1.22 -0.06 1.23 1.45 0.96 0.88 0.26 0.12 1.48 0.32 0.03 1.14 0.73 0.62 0.62 0.53 0.23
0.90 0.40 1.06 1.45 0.58 1.88 2.18 1.13 0.69 0.43 0.65 0.95 0.75 0.33 1.41 0.39 0.54 -0.10 0.12 0.77
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1.13 1.10 1.28 1.37 0.14 1.62 1.84 1.29 1.31 0.05 -0.05 1.50 0.41 0.20 1.14 0.86 0.62 0.45 0.31 0.48
1.33 0.91 1.33 1.60 0.31 1.60 1.93 1.62 1.01 0.33 0.38 1.12 0.82 0.55 1.54 0.78 0.54 0.23 0.52 0.86
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0.78 1.30 1.31 1.27 -0.04 1.44 1.71 0.69 0.84 0.05 0.15 1.68 0.38 0.27 1.05 1.19 0.83 -0.24 0.23 0.12
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0.50 0.90 0.75 0.91 -0.26 1.03 1.25 0.55 0.55 -0.20 -0.26 1.42 0.50 -0.22 0.88 0.69 0.56 0.41 0.11 -0.15
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//
H ZHAC000104
D Environment-dependent residue contact energies (rows = strand, cols = strand)
R PMID:10706611
A Zhang, C. and Kim, S.H.
T Environment-dependent residue contact energies for proteins
J Proc. Natl. Acad. Sci. USA 97, 2550-2555 (2000)
M rows = ARNDCQEGHILKMFPSTWYV, cols = ARNDCQEGHILKMFPSTWYV
-2.52
-1.24 0.03
-1.22 -0.80 -0.48
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-1.17 -0.68 -0.74 -0.71 -1.97 -0.10
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-0.70 0.28 -0.35 -1.00 -0.74 -0.42 -1.06 -0.83 -0.61 -1.3 -1.2 0.47
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//
H ZHAC000105
D Environment-dependent residue contact energies (rows = strand, cols = coil)
R PMID:10706611
A Zhang, C. and Kim, S.H.
T Environment-dependent residue contact energies for proteins
J Proc. Natl. Acad. Sci. USA 97, 2550-2555 (2000)
M rows = ARNDCQEGHILKMFPSTWYV, cols = ARNDCQEGHILKMFPSTWYV
-0.57 0.47 0.30 0.62 -1.60 0.45 0.61 -0.24 0.07 -1.64 -1.63 0.62 -1.03 -1.55 -0.11 -0.10 -0.34 -1.44 -0.39 -1.55
0.23 0.79 0.76 0.39 -0.41 0.92 0.76 0.52 0.51 -0.30 0.13 1.58 0.88 -0.07 0.60 0.65 0.37 0.14 0.32 0.17
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0.15 -0.25 0.46 0.69 -0.46 0.41 1.34 0.56 -0.51 -0.23 0.27 0.59 0.60 -0.38 1.02 0.08 0.05 -0.48 0.02 0.34
-1.19 -0.46 0.21 0.51 -3.30 0.26 0.20 -1.03 -0.72 -1.55 -1.71 0.27 -1.24 -1.70 -0.50 -0.55 -0.97 -0.67 -1.26 -1.62
0.63 1.18 0.92 1.37 -0.30 0.93 1.27 0.56 0.91 -0.28 -0.11 0.98 0.15 -0.30 0.64 0.88 0.68 -0.44 0.66 0.15
0.97 0.89 1.37 1.89 0.30 1.25 2.34 0.98 0.58 0.20 0.50 0.67 1.23 0.58 1.26 0.95 1.06 0.04 0.87 0.48
-0.64 0.12 0.27 0.31 -1.37 0.38 0.98 -0.40 -0.12 -1.58 -1.40 0.78 -0.46 -1.38 -0.21 0.05 -0.26 -1.41 -0.61 -1.13
-0.02 0.75 0.68 0.14 -0.58 0.73 0.84 0.41 -0.64 -0.75 0.03 1.46 -0.16 -0.49 0.52 0.31 -0.11 -1.00 -0.58 0.03
-0.94 -0.14 0.31 0.26 -1.70 0.07 0.46 -0.37 -0.50 -1.88 -1.79 0.84 -0.99 -1.82 -0.47 -0.05 -0.54 -1.65 -1.09 -1.64
-0.76 0.32 0.43 0.25 -1.63 0.22 0.68 -0.17 -0.40 -1.84 -1.70 0.47 -1.06 -1.76 -0.39 0.09 -0.42 -1.81 -1.15 -1.64
1.02 1.99 1.18 0.59 0.08 1.10 0.60 0.61 0.95 0.24 0.34 2.69 0.97 -0.03 1.23 1.07 0.83 0.00 0.26 0.36
-0.16 0.83 0.47 0.92 -1.63 0.36 0.71 -0.20 0.90 -1.00 -1.12 1.55 -0.31 -1.35 -0.01 0.34 0.20 -1.70 -0.60 -0.79
-0.70 0.03 0.63 0.15 -1.26 0.29 0.35 -0.11 -0.36 -1.73 -1.55 0.71 -0.97 -1.55 -0.28 -0.09 -0.32 -1.23 -0.91 -1.30
0.17 0.50 0.60 0.67 -1.31 0.50 0.94 0.02 -0.45 -1.26 -0.91 1.08 0.83 -0.87 0.63 0.31 0.26 -0.50 -0.55 -0.79
-0.06 0.99 0.73 0.86 -0.89 0.85 0.67 0.08 0.06 -0.22 -0.29 0.94 -0.08 -0.41 0.67 0.33 0.13 -1.01 0.13 -0.24
0.26 0.93 0.70 0.87 -0.78 0.58 1.20 0.12 0.52 -0.30 -0.24 1.11 0.01 -0.08 0.65 0.47 0.41 -0.31 0.12 -0.32
-0.03 -0.11 0.27 0.66 -1.50 0.65 0.50 -0.12 -0.32 -1.13 -1.01 0.52 -1.08 -1.04 -0.32 -0.03 -0.10 -0.67 -0.73 -0.64
-0.44 0.20 0.20 0.20 -1.26 0.16 0.10 -0.21 -0.52 -1.26 -1.30 0.60 -0.76 -1.17 -0.42 0.05 -0.27 -1.20 -0.75 -0.84
-0.83 0.20 0.48 0.62 -1.44 0.17 0.73 -0.12 -0.26 -1.64 -1.59 0.52 -0.70 -1.55 -0.28 0.12 -0.17 -1.16 -0.85 -1.42
//
H ZHAC000106
D Environment-dependent residue contact energies (rows = coil, cols = coil)
R PMID:10706611
A Zhang, C. and Kim, S.H.
T Environment-dependent residue contact energies for proteins
J Proc. Natl. Acad. Sci. USA 97, 2550-2555 (2000)
M rows = ARNDCQEGHILKMFPSTWYV, cols = ARNDCQEGHILKMFPSTWYV
0.12
0.56 1.18
0.59 0.83 0.83
0.65 0.33 0.61 1.15
-0.74 -0.25 -0.07 -0.12 -2.42
0.70 0.94 0.87 0.96 -0.05 1.22
1.32 0.54 1.09 1.48 0.20 1.11 2.18
0.11 0.65 0.79 0.75 -0.56 0.73 1.16 0.35
0.35 0.47 0.91 0.29 -0.83 0.83 0.74 0.53 0.28
-0.45 0.05 0.40 0.47 -1.27 0.24 0.70 0.01 -0.21 -1.04
-0.25 0.26 0.37 0.57 -1.25 0.38 0.82 0.13 -0.03 -1.15 -1.04
1.06 1.65 1.11 0.58 0.76 1.29 0.93 1.08 1.23 0.48 0.78 2.23
0.29 0.58 0.68 0.75 -0.74 0.65 1.08 0.54 0.19 -0.52 -0.68 1.15 -0.12
-0.41 0.24 0.46 0.38 -1.44 0.39 0.55 0.09 -0.28 -1.09 -1.05 0.74 -0.60 -1.09
0.48 0.82 1.09 1.26 -0.23 1.09 1.25 0.74 0.59 0.14 0.10 1.59 0.54 -0.04 1.11
0.45 0.55 0.81 0.54 -0.47 0.75 0.87 0.61 0.46 0.09 0.01 1.24 0.56 0.17 0.94 0.87
0.30 0.80 0.54 0.51 -0.37 0.81 0.81 0.38 0.31 -0.28 -0.05 1.10 0.46 0.08 0.67 0.54 0.69
-0.28 -0.04 0.13 0.43 -0.63 -0.01 0.44 -0.17 -0.44 -1.28 -0.98 0.23 -0.50 -1.02 -0.33 0.14 -0.19 -0.46
-0.07 0.22 0.40 0.38 -0.58 0.09 0.47 0.28 -0.18 -0.74 -0.56 0.62 -0.26 -0.63 0.04 0.23 0.27 -0.87 -0.18
-0.18 0.43 0.54 0.59 -1.22 0.23 0.74 0.04 0.09 -0.90 -0.93 0.81 -0.31 -0.77 0.17 0.20 -0.10 -0.57 -0.38 -0.31
//
modules/seq/alg/tests/CMakeLists.txt
+ 1
− 0
View file @ c3ce0b79
......@@ -9,6 +9,7 @@ set(OST_SEQ_ALG_UNIT_TESTS
test_semiglobal_align.py
test_weight_matrix.py
test_alignment_from_chain_view.py
test_aaindex.py
)
if (COMPOUND_LIB)
......
modules/seq/alg/tests/test_aaindex.py 0 → 100644
+ 49
− 0
View file @ c3ce0b79
import sys
import unittest
from ost.seq.alg import aaindex
class TestAAIndex(unittest.TestCase):
def testStuff(self):
index = aaindex.AAIndex()
# test some random aaindex annotations from all three files
# the files themselves are lazy loaded until the required
# annotation is found
# entry from aaindex1
self.assertEqual(index["BHAR880101"].GetScore("C"), 0.346)
# entries from aaindex2
# symmetric one:
self.assertEqual(index["HENS920102"].GetPairScore("C", "A"), -1.0)
self.assertEqual(index["HENS920102"].GetPairScore("A", "C"), -1.0)
# non-symmetric one:
self.assertEqual(index["LINK010101"].GetPairScore("C", "A"), 0.035)
self.assertEqual(index["LINK010101"].GetPairScore("A", "C"), 0.000)
# entries from aaindex3
# symmetric one
self.assertEqual(index["TANS760102"].GetPairScore("H", "R"), 17)
self.assertEqual(index["TANS760102"].GetPairScore("R", "H"), 17)
# non symmetric one
self.assertEqual(index["ZHAC000102"].GetPairScore("H", "R"), 2.19)
self.assertEqual(index["ZHAC000102"].GetPairScore("R", "H"), 0.94)
# depending on annotation type (single amino acids or pairs), we need
# to call the right functions
with self.assertRaises(RuntimeError):
index["TANS760102"].GetScore("H")
with self.assertRaises(RuntimeError):
index["BHAR880101"].GetPairScore("H", "R")
if __name__ == "__main__":
from ost import testutils
# the function below indirectly enables GetSharedDataPath when
# calling stuff from python which is the case in unit tests
testutils.SetDefaultCompoundLib()
testutils.RunTests()
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