Case Study - Alanine Dipeptide

** Info about the data **

import numpy as np
import pandas as pd

import matplotlib as mpl
import matplotlib.pyplot as plt

%matplotlib notebook

import nglview

Molecular Visualization using nglview

view = nglview.show_file("ini0.pdb")
view

view = nglview.show_file("ini0.pdb")
view.add_label(label_type="element", color="black")
view

Plotting the Potential Energy Surface

# Set font size
mpl.rcParams['font.size'] = 14
mpl.rcParams['legend.fontsize'] = 'large'

df = pd.read_csv("a1a2ene.csv")

df.head()

	phi	psi	energy
0	-180	-180	-0.120177
1	-180	-160	-0.118642
2	-180	-140	-0.116515
3	-180	-120	-0.115398
4	-180	-100	-0.115198

# Need to prepare data for plotting.
x = df["phi"].unique()
y = df["psi"].unique()
z = df["energy"].values.reshape(19, -1, order="F")

# Get the min and max energy values
pmin = z.min()
pmax = z.max()

fig, ax = plt.subplots()

ticks = np.linspace(pmin, pmax, 5)

CS = ax.contourf(x, y, z, cmap="jet", levels=30)
#ax.contour(x_,y_, values_square, colors='white')
ax.set_aspect('equal')
ax.set_xlabel(r'$\phi$')
ax.set_ylabel(r'$\psi$')


fig.colorbar(CS, format="%.3f", ticks=ticks)

<matplotlib.colorbar.Colorbar at 0x7f6ebe151280>

Low and High Energy

import matplotlib.image as mpimg
import nglview

min_loc = np.argwhere(z == np.min(z))
max_loc = np.argwhere(z == np.max(z))

print(max_loc)
print(min_loc)

[[0 9]]
[[14  5]]

max_view = nglview.show_file("pdb/opt.0.9.pdb")
max_view

min_view = nglview.show_file("pdb/opt.14.5.pdb")
min_view

min_v = min_view.render_image()

with open('low_energy.png', 'wb') as t:
    t.write(min_v.value)

max_v = max_view.render_image()

max_v

with open('high_energy.png', 'wb') as t:
    t.write(max_v.value)

im = mpimg.imread("low_energy.png")
crop = im[:1200, 1500:2500 , :4]

im2 = mpimg.imread("high_energy.png")
crop2 = im2[:1200, 1500:2500 , :4]

fig, ax = plt.subplots(1, 3, figsize=(10,6))

ticks = np.linspace(pmin, pmax, 5)

CS = ax[0].contourf(x, y, z, cmap="jet", levels=30)
ax[0].contour(x,y, z, colors='white')
ax[0].set_aspect('equal')
ax[0].set_xlabel(r'$\phi$')
ax[0].set_ylabel(r'$\psi$')

ax[1].imshow(crop)
ax[1].axis("off")

ax[2].imshow(crop2)
ax[2].axis("off")

fig.colorbar(CS, format="%.3f", ticks=ticks, location="bottom", ax=ax[:])

<matplotlib.colorbar.Colorbar at 0x7f6e8f569f70>