Hi,

I have been trying to use chiLife to generate distance distribution of my own label on a protein. Unfortunately, when I have a look at the individual label conformation, I could see some conformations which is just not possible (label clashing with itself). Could someone please help me fix this issue.

Example:

The script that I use:

import os
import numpy as np
import matplotlib.pyplot as plt
import chilife as chi
import MDAnalysis as mda

np.random.seed(100)
plt.style.use('chiLife')
plt.rcParams.update({'font.size':15})

os.chdir('C:\Users\uqvbayya\Desktop\Chilife\VBGd1_cysCNP\G147')

MBP = mda.Universe('C:/Users/uqvbayya/Desktop/Chilife/Protein/ERp29.pdb')

SL1 = chi.RotamerEnsemble('label', site=147, chain='A', protein=MBP, sample=10000, eval_clash=True)
SL2 = chi.RotamerEnsemble('label', site=403, chain='B', protein=MBP, sample=10000, eval_clash=True)

chi.save('ERp29_labelled.pdb', SL1, SL2, MBP)

traj, dE = chi.repack(MBP, SL1, SL2,
repetitions=10000, temp=298,
off_rotamer=True,
repack_radius=10)

SL1_repack = chi.SpinLabel.from_trajectory(traj, 147, burn_in=5000, spin_atoms=SL1.spin_atoms)
SL2_repack = chi.SpinLabel.from_trajectory(traj, 403, burn_in=5000, spin_atoms=SL2.spin_atoms)

chi.save('ERp29_labelled_repacked.pdb', SL1_repack, SL2_repack, MBP)

fig, ax = plt.subplots()
ax.plot(np.cumsum(dE))
ax.set_xlabel('step')
ax.set_ylabel(r'$\rm\Delta$ clash energy (kcal/mol)')
ax.spines['top'].set_visible(False)
ax.spines['right'].set_visible(False)
plt.show()

fig.savefig('Trajectory.png', bbox_inches='tight', dpi=1200)

r = np.linspace(0, 100, 256)
P_repack = chi.distance_distribution(SL1_repack, SL2_repack, r)

fig, ax = plt.subplots(figsize=(6, 3))
ax.plot(r, P_repack)
ax.set_yticks([])
ax.set_xlabel('Distance ($\AA$)')

for spine in ['left', 'right', 'top']:
ax.spines[spine].set_visible(False)
plt.show()

fig.savefig('Distance_distributions.png', dpi=1200, bbox_inches='tight')

distancedistribution = np.column_stack((r, P_repack))
np.savetxt('distancedistribution.txt', distancedistribution, header="Distance[nm] Probability")

Kind regards,
Vishal