Hi all,
I want to do ensemble simulation to search an ensemble to fit the SAXS data
with Xplor-NIH. The relative scripts are as follows:
xplor.requireVersion("2.19")
import protocol
protocol.initRandomSeed()
protocol.topology['nucleic']="nucleic-2.0.top"
protocol.parameters['nucleic']="nucleic-2.0.par"
protocol.initParams("nucleic")
xray_scale = 500
numberOfStructures=10
fn_pdb = "3u_mr.pdb"
fn_saxsData='SAXS_30_121815.dat'
ensembleSize = 3
#by default, all ensemble members have equal weights, but you can change this:
#
#ensWeights=[1.0/ensembleSize for i in range(ensembleSize)]
ensWeights=[0.6,0.2,0.2]
startStructure=0
outFilename = "SCRIPT_%d_STRUCTURE_MEMBER.pdb" % numberOfStructures
rigidRegions=[
'resid 1:142',
'resid 153:321',
'resid 331:423',
]
breakResids=[143,152,322,330]
#
# read in the PSF and initial PDB files
#
import psfGen
####psfGen.pdbToPSF("fix_HAB.pdb")
#
# starting coords
#
#protocol.initCoords("tectoRNA.pdb")
#protocol.loadPDB("fsr0_s0_102.pdb")
#start from a good structure...
protocol.loadPDB(fn_pdb)
#protocol.loadPDB("ref-11-2-2011b_100_0-relocated-d783.pdb")
#protocol.writePDB("/usr/home/schwitrs/t0.pdb")
xplor.simulation.deleteAtoms("not known")
#import regularize
#regularize.fixupCovalentGeomIVM(translateRegions=rigidRegions)
#protocol.covalentMinimize("""not (resid 1:76 or resid 117:156 or resid 173:283
or resid 319:388 or resid 410:617 or resid 769:834 or resid 634:684 or resid
699:750)""")
#protocol.writePDB("/usr/home/schwitrs/t1.pdb")
from ensembleSimulation import EnsembleSimulation
esim=EnsembleSimulation('ens',ensembleSize)
esim.setAveType('sum')
# list of potential terms used in refinement
from potList import PotList
potList = PotList()
crossTerms=PotList('cross terms')
# parameters to ramp up during the simulated annealing protocol
#
from simulationTools import MultRamp, StaticRamp, InitialParams
rampedParams=[]
from xplorPot import XplorPot
from avePot import AvePot
#protocol.initCollapse("resid 1:835",
# Rtarget=38.2)
#potList.append( XplorPot('COLL') )
#SAXS term
from solnXRayPotTools import create_solnXRayPot
import solnXRayPotTools
xray=create_solnXRayPot('xray',experiment=fn_saxsData,
normalizeIndex=-3,preweighted=False)
xrayCorrect=create_solnXRayPot('xray-c',experiment=fn_saxsData,
normalizeIndex=-3,preweighted=False)
solnXRayPotTools.useGlobs(xray)
xray.setNumAngles(50)
xrayCorrect.setNumAngles(500)
#xray.setScale(50)
xray.setScale(xray_scale)
xray.setCmpType("plain")
xray.setEnsWeights( ensWeights )
xrayCorrect.setEnsWeights( ensWeights )
potList.append(xray)
crossTerms.append(xrayCorrect)
print xray.calcEnergy()
from solnScatPotTools import fitParams
But when I run this scripts I find that my ensemble weights are still 0.6, 0.2,
0.2 in the result. I know Xplor-NIH can optimize the ensemble weights in the
running; But how?
Thank you!
Yikan
Ph. D
TsingHua University
School of life Sciences
Beijing, China
tel:010-62773783
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