IRed Analysis of MD Simulations

Calculating order parameters from MD Simulations

The analysis utilizes iRed software provided by the Dr. Rafael Bruschweiler Group. All iRed calculations were completed on the HCC cluster.

1. Create a pdb file of the trajectory in the same manner as the .xtc file.
2. After the pdb file is created (will be very large), use the following scripts to extract the N and H coordinates for each atom at each time point in the trajectory
   1. awk ‘{if (($3 == “N”) && ($4 != “PRO”)) {print $6, $7, $8, $9:}} xxx.pdb > N-HCoor.dat
   2. awk ‘{if (($3 == “H”) && ($4 != “H1”)) {print $6, $7, $8, $9:}} xxx.pdb > H-NCoor.dat
3. Once .dat files are created, use the python script below to run the iRed calculation
   1. In command line, run “ired_1vec_block.py --coor1 N-HCoor.dat --coor2 H-NCoor.dat --block 100

       ! /usr/bin/env python
       from __future__ import division
       import numpy as np
       from optparse import OptionParser
       import sys
       def setupParserOptions():
               parser=OptionParser()
               parser.add_option('--coor1', dest='coor1',default='H-NCoor.dat',help = "Input coordinate file 1")
               parser.add_option('--coor2', dest='coor2',default='N-HCoor.dat',help = "Input coordinate file 2")
               parser.add_option('--block', dest='block', default = 1, help = 'Number of blocks')
               return parser
       def ired(hCoor_file, nCoor_file, block):
           try:
               h_all = np.loadtxt(hCoor_file)
           except IOError:
               print 'cannot open ', hCoor_file
           try:
               n_all = np.loadtxt(nCoor_file)
           except IOError:
               print 'cannot open ', nCoor_file
           numLines = len(h_all)
           numRes = len(set(h_all[:,0]))
           numSnapshot = numLines // numRes
           blockNum = int(block)
          blockSize = numSnapshot // blockNum
           if numLines != len(n_all):
               print 'Error: The two coordinate files do not have same length.'
               return
           if np.mod(numLines, numRes) != 0:
               print 'Error: Coordinate files do not formatted correctly.'
               return
           # initialize s2
           s2_sum = np.zeros([1, numRes])
           for i in range(blockNum):
               hC = h_all[i*numRes*blockSize:(i+1)*numRes*blockSize, :]
               nC = n_all[i*numRes*blockSize:(i+1)*numRes*blockSize, :]
              # Calculate the bond vector orientations over the trajectory
               hnC = hC[:,1:] - nC[:,1:]
                # residue index
               resNum = hC[0:numRes, 0]
               # Construct matrix m
               mMat = np.zeros([numRes, numRes])
               #print numRes, numSnapshot, blockNum, blockSize
               for a in range(0, numRes*blockSize, numRes):
                   # N-H vectors for the current snapshot
                   hnTemp = hnC[a:a+numRes, :]
                   # normalize the vectors
                   for b in range(numRes):
                       hnTemp[b,:] = hnTemp[b,:] / np.linalg.norm(hnTemp[b,:])
                   # Construct Rank 2 Legendre polynomial
                  c = np.dot(hnTemp, hnTemp.T)
                   mMat = mMat + (3*np.multiply(c, c)-1)/2
               # Ensemble averaging
               mMat = mMat / blockSize
               #print np.shape(hnTemp), np.shape(hnTemp.T), np.shape(c), np.shape(mMat)
               # Diagonalize matrix
               dVals, v = np.linalg.eig(mMat)
               Ind = dVals.argsort()[::-1] # sort eigenvalues in descending order
               dSort = dVals[Ind]
               eigVal = np.diag(dSort)
               eigVec = v[:, Ind]
               # Calculate the squared order parameters
               s2_block = np.zeros(numRes)
               for b in range(numRes):
                   sumOverModes = 0;
                   for a in range(5,numRes):
                       sumOverModes += eigVal[a,a] * (eigVec[b,a])**2
                   s2_block[b] = 1 - sumOverModes
               s2_sum += s2_block
           s2 = s2_sum / blockNum
           # output
           out = np.concatenate(([resNum], s2), axis = 0)
           with open('ired_s2_1vec_%dblock.out' %(block), 'wb') as f:
               np.savetxt(f, np.transpose(out), fmt='%i %.3f')
       if __name__ == '__main__':
           parser = setupParserOptions()
           if len(sys.argv) <2:
               parser.print_help()
               sys.exit()
           options, args=parser.parse_args()
           print "**************************************************\nMD Block-averaged iRED S2 Calculation"
           print "Input coordinate file:  %s"%(options.coor1)
           print "Input coordinate file:  %s"%(options.coor2)
           print "Number of MD block(s):  %s"%(options.block)
           f1 = options.coor1
           f2 = options.coor2
           try:
               bn = int(options.block)
           except ValueError:
               print "Error: Number of block should be an integer."
           ired(f1, f2, bn)

1. Python script will output a .out file that contains the order parameter values for each amino acid residue.