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IMP Reference Guide  2.6.0
The Integrative Modeling Platform
serialPeptideDocker.py
1 import IMP
2 import subprocess
3 import random
4 import IMP.domino
5 import IMP.core
6 import IMP.rmf
7 import RMF
8 import time
9 import IMP.algebra
10 import types
11 import re
12 import sys
13 import operator
14 import os
15 import peptideDocker
16 import atomicDomino
17 
18 parameterFileName = sys.argv[1]
19 
20 startTime = time.time()
21 
22 p = peptideDocker.PeptideDocker(parameterFileName)
23 
24 p.createModel()
25 
26 p.loadHelpers()
27 
28 p.initDof()
29 
30 p.addForceFieldRestraints()
31 p.setInitialPositions()
32 p.addClosePairNonBondedRestraints()
33 
34 d = atomicDomino.AtomicDomino(p.getModel(), p.getProtein(), parameterFileName)
35 
36 d.loadDominoHelpers()
37 
38 d.createSubsets()
39 d.writeVisualization()
40 p.logTime("Created subsets")
41 p.addCompleteNonBondedRestraints()
42 
43 p.logTime("Added complete nonbonded restraints")
44 
45 
46 # p.addExcludedVolume()
47 p.logTime("Setup")
48 
49 p.runMolecularDynamics()
50 
51 p.logTime("Run MD")
52 
53 p.runAllCg()
54 
55 p.logTime("Run CG")
56 
57 d.createGrid()
58 
59 d.discretizeNativeProtein()
60 
61 particleNameList = d.getDominoParticleNames()
62 
63 flexibleAtoms = p.getFlexibleAtoms()
64 
65 d.readMdTrajectory(particleNameList, flexibleAtoms)
66 
67 d.readCgTrajectories(particleNameList, flexibleAtoms)
68 
69 p.logTime("Read Trajectory")
70 
71 d.createParticleStatesTable()
72 
73 p.logTime("create particle states table")
74 
75 d.createAllSubsetAssignments()
76 
77 p.logTime("Create Leaf assignments")
78 
79 d.createSampler()
80 
81 d.runDomino()
82 
83 p.logTime("Ran Domino")
84 
85 p.writeOutput()
86 
87 p.outputTimes()
88 
89 d.writeOutput(flexibleAtoms, startTime)
Basic functionality that is expected to be used by a wide variety of IMP users.
General purpose algebraic and geometric methods that are expected to be used by a wide variety of IMP...
Support for the RMF file format for storing hierarchical molecular data and markup.
Divide-and-conquer inferential optimization in discrete space.