View source for 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.
#Create a pdb file of the trajectory in the same manner as the .xtc file. 
#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
##awk ‘{if (($3 == “N”) && ($4 != “PRO”)) {print $6, $7, $8, $9:}} xxx.pdb > N-HCoor.dat
## awk ‘{if (($3 == “H”) && ($4 != “H1”)) {print $6, $7, $8, $9:}} xxx.pdb > H-NCoor.dat
#Once .dat files are created, use the python script below to run the iRed calculation
##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)

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