File: restrained-ensemble.py

package info (click to toggle)
gromacs 2025.4-1
  • links: PTS, VCS
  • area: main
  • in suites: forky, sid
  • size: 287,236 kB
  • sloc: xml: 3,718,478; cpp: 654,820; ansic: 75,282; python: 20,471; sh: 3,471; perl: 2,218; yacc: 644; fortran: 397; lisp: 265; makefile: 171; lex: 125; awk: 68; csh: 39
file content (237 lines) | stat: -rw-r--r-- 6,834 bytes parent folder | download | duplicates (3)
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
117
118
119
120
121
122
123
124
125
126
127
128
129
130
131
132
133
134
135
136
137
138
139
140
141
142
143
144
145
146
147
148
149
150
151
152
153
154
155
156
157
158
159
160
161
162
163
164
165
166
167
168
169
170
171
172
173
174
175
176
177
178
179
180
181
182
183
184
185
186
187
188
189
190
191
192
193
194
195
196
197
198
199
200
201
202
203
204
205
206
207
208
209
210
211
212
213
214
215
216
217
218
219
220
221
222
223
224
225
226
227
228
229
230
231
232
233
234
235
236
237
#!/usr/bin/env python
"""Run restrained-ensemble sampling and biasing workflow.

Irrgang, M. E., Hays, J. M., & Kasson, P. M.
gmxapi: a high-level interface for advanced control and extension of molecular dynamics simulations.
*Bioinformatics* 2018.
DOI: `10.1093/bioinformatics/bty484 <https://doi.org/10.1093/bioinformatics/bty484>`_
"""

# Restrained-ensemble formalism is a variant of that defined by Roux et al., 2013

import os
import sys

# Of course, the location of the Python plugin module is user-specific and could be
# passed by PYTHONPATH instead of programatically here.
sys.path.append("/home/mei2n/sample_restraint/build/src/pythonmodule")

import gmx

import logging

logging.getLogger().setLevel(logging.DEBUG)
# create console handler
ch = logging.StreamHandler()
ch.setLevel(logging.DEBUG)
# create formatter and add it to the handler
formatter = logging.Formatter("%(asctime)s:%(name)s:%(levelname)s: %(message)s")
ch.setFormatter(formatter)
# add the handlers to the logger
logging.getLogger().addHandler(ch)
logger = logging.getLogger()

import myplugin

logger.info("myplugin is {}".format(myplugin.__file__))

if len(sys.argv) > 1:
    size = int(sys.argv[1])
else:
    size = 20
input_dir_list = ["aa_{:02d}".format(i) for i in range(size)]
print("Input directory list: {}".format(input_dir_list))

tpr_list = [
    os.path.abspath(os.path.join(directory, "mRMR.tpr")) for directory in input_dir_list
]

# dt = 0.002
# First restraint applied between atoms 387 and 2569
# Second restraint applied between atom 1330 and 2520
# Restraint site coordinates relative to atom 1735
# Gathers 50 distance samples over 10ps, then averages the histogram across the ensemble to
# get a smooth histogram for the sample window. At each update (10 ps), updates the bias
# potential with the average statistics from the last 20 windows.
params = {
    "sites": [387, 1735, 2569],
    "k": 100.0,
    "sigma": 0.2,
    "nbins": 70,
    "binWidth": 0.1,
    "max_dist": 6.0,
    "min_dist": 1.9,
    "experimental": [
        1.799741371805743e-21,
        1.394386099050501e-19,
        8.502972718446353e-18,
        4.085581973134053e-16,
        1.548764419813057e-14,
        4.638792711370235e-13,
        1.0996581066864261e-11,
        2.0673577567003664e-10,
        3.0896196375481035e-09,
        3.680765701683053e-08,
        3.5071251461730994e-07,
        2.683161946307409e-06,
        1.6559233749685584e-05,
        8.289071953350906e-05,
        0.00033870482482321125,
        0.0011381605345541928,
        0.0031720369601255603,
        0.007403098031042665,
        0.014627984136430199,
        0.024781412546281113,
        0.036538520471987135,
        0.04776926450937005,
        0.056703917249967935,
        0.06290983130284482,
        0.06723680313442071,
        0.07080726976949929,
        0.07402160052652465,
        0.0765402296381977,
        0.07828089499810763,
        0.08047585508402359,
        0.08570745927698609,
        0.09674399700081715,
        0.11510583738691207,
        0.14051216332953817,
        0.17140325711911122,
        0.20554101371952832,
        0.23970384865306096,
        0.2690817283268939,
        0.2883208679737597,
        0.2947929622276882,
        0.2912919631495654,
        0.28445334990710786,
        0.27916526960634136,
        0.2740440567694397,
        0.2627885645671059,
        0.24084583312911054,
        0.2119920710658402,
        0.18961266641719554,
        0.19160148241368294,
        0.23183520488057596,
        0.31258390292452404,
        0.4212625964074282,
        0.5329315503397933,
        0.6177862653849041,
        0.6510130306580447,
        0.621354685844679,
        0.5350130330039692,
        0.4131558700737114,
        0.28383821525616004,
        0.17174126508493523,
        0.0904869618596048,
        0.04102083542122555,
        0.0158113507543527,
        0.00512381828028717,
        0.0013817258262933331,
        0.00030725601604590235,
        5.5898129564429734e-05,
        8.270145724798172e-06,
        1.066958972950409e-06,
        8.525674649177577e-07,
    ],
    "nsamples": 5,  # window size: 100 ps
    "sample_period": 10000 * 0.002,  # 20 ps
    "nwindows": 100,  # averaging period: 10 ns
}

potential1 = gmx.workflow.WorkElement(
    namespace="myplugin", operation="ensemble_restraint", depends=[], params=params
)
potential1.name = "ensemble_restraint_1"

params["sites"] = [1330, 1735, 2520]
params["experimental"] = [
    8.750538172089207e-20,
    4.963054541010076e-18,
    2.2585602895138136e-16,
    8.296295971141421e-15,
    2.4727072025999945e-13,
    6.001704592322284e-12,
    1.188164346191529e-10,
    1.917922517069427e-09,
    2.52033705254017e-08,
    2.691327568605142e-07,
    2.3326113123212396e-06,
    1.641120092881496e-05,
    9.38976910432654e-05,
    0.0004385427322814972,
    0.0016815454179692623,
    0.005334700709331302,
    0.014137960662648396,
    0.03164990069467528,
    0.06058416858044986,
    0.10044829089636065,
    0.1462620702334438,
    0.19008247987025195,
    0.22511473247247643,
    0.2496090827957139,
    0.2672559820151655,
    0.28375718473756745,
    0.3027960501795795,
    0.3245600144118122,
    0.346907132615181,
    0.3674499825469857,
    0.3851742255922683,
    0.40052661472987944,
    0.4135408960076755,
    0.4218337765359014,
    0.42147736029942173,
    0.4107213639593705,
    0.39238589395514606,
    0.37160127657310765,
    0.3512844290946452,
    0.3307655537130543,
    0.30883452118638083,
    0.2868146457416455,
    0.2677676912313197,
    0.2532530719313838,
    0.2417481938021803,
    0.23018156335307405,
    0.21644933221299598,
    0.20050997978961216,
    0.18377185607646654,
    0.16786393271557773,
    0.15362016010974153,
    0.1405238761751657,
    0.12680145743115132,
    0.11034786248372368,
    0.09017088591908493,
    0.06741463593670398,
    0.045069844741355614,
    0.026422842565654883,
    0.013359579997979203,
    0.005742341678209477,
    0.0020723966306519146,
    0.0006212767709345187,
    0.00015329363473072974,
    3.088693304526221e-05,
    5.048219168357052e-06,
    6.655228160961857e-07,
    7.04490968489331e-08,
    6.246463184699169e-09,
    4.5050655561489735e-09,
    4.676670950356501e-08,
]

potential2 = gmx.workflow.WorkElement(
    namespace="myplugin", operation="ensemble_restraint", depends=[], params=params
)
potential2.name = "ensemble_restraint_2"


# Settings for a 20 core HPC node. Use 18 threads for domain decomposition for pair potentials
# and the remaining 2 threads for PME electrostatics.
md = gmx.workflow.from_tpr(
    tpr_list, tmpi=20, grid=[3, 3, 2], ntomp_pme=1, npme=2, ntomp=1
)
md.add_dependency(potential1)
md.add_dependency(potential2)

context = gmx.context.ParallelArrayContext(md)

with context as session:
    session.run()