DNA Along a Protein Filament¶

This tutorial demonstrates how to construct DNA structures along a protein filament, specifically focusing on the lateral H-NS filament assembly process. This technique involves modeling interactions between DNA and protein structures, providing a method to visualize complex biological assemblies.

Scientific Context:¶

• The process starts with a H-NS decamer homodimer, which serves as the initial protein scaffold.
• Four DNA Binding Domains (DBD) are fitted with 12 bp DNA strands using the H-NS DNA complex structures from previous studies (PDB: 1HNS).
• The reference frames of the 4 DNA oligomers are then used as control points to generate new DNA strands spanning the complete H-NS filament.

Objective:¶

• Highlight the capability of the .make() function to create DNA structures by using anchor points of specific domains as control points.
• Demonstrate the flexibility of structure generation where the protein filament serves as a scaffold, enabling the generation of a DNA configuration along a reference structure.

Steps Covered:¶

• Retrieve and process the trajectory object to identify DNA chains.
• Calculate control points based on the reference frames of identified DNA segments and the scientific model.
• Generate DNA along these control points and integrate with the protein structure.
• Visualize and save the new combined structure.

In [ ]:

import mdtraj as md
import numpy as np
import nglview as nv
import matplotlib.pyplot as plt

from tqdm import tqdm
import mdna as mdna 

# Import extra libraries
sys.path.append('./notebooks/data')
from filament import *
%load_ext autoreload
%autoreload 2

import mdtraj as md import numpy as np import nglview as nv import matplotlib.pyplot as plt from tqdm import tqdm import mdna as mdna # Import extra libraries sys.path.append('./notebooks/data') from filament import * %load_ext autoreload %autoreload 2

Load MD data¶

In [ ]:

# Load H-NS s1s1 dimers
loc_dimers = '/path/to/s1s1_dimers/'
short_trajs = [md.load(loc_dimers+f'dry_{i}.xtc',top=loc_dimers+f'dry_{i}.pdb').remove_solvent() for i in range(0,2)]
s1s1 = md.join(short_trajs)

# Load H-NS s2s2 dimers
loc_dimers = '/path/to/s2s2/'
short_trajs = [md.load(loc_dimers+f'dry_{i}.xtc',top=loc_dimers+f'dry_{i}.pdb').remove_solvent() for i in range(0,2)]
s2s2 = md.join(short_trajs)

# Load H-NS dbd to DNA complex
loc_dbd  = '/path/to/dbd_h-ns_dna/'
traj = [md.load(loc_dbd+f'dry_{i}.xtc',top=loc_dbd+f'dry_{i}.pdb').remove_solvent() for i in range(0,2)]
dna_complex = md.join(traj)

# Define segments of the protein
n = 2 # Overlap of residues between segments

segments = {'s1':np.arange(0,41+n),
            'h3':np.arange(41-n,53+n),
            's2':np.arange(53-n,82+n),
            'l2':np.arange(82-n,95+n),
            'dbd':np.arange(95-n,137)}

# Site map contains a dictionary with the (sub)trajectories of different sites of the protein catergorized from the s1s1 and s2s2 dimers
mapper = SiteMapper(s1s1, s2s2, segments=segments, k=100)
site_map = mapper.get_site_map()
site_map['complex'] = dna_complex

# Load H-NS s1s1 dimers loc_dimers = '/path/to/s1s1_dimers/' short_trajs = [md.load(loc_dimers+f'dry_{i}.xtc',top=loc_dimers+f'dry_{i}.pdb').remove_solvent() for i in range(0,2)] s1s1 = md.join(short_trajs) # Load H-NS s2s2 dimers loc_dimers = '/path/to/s2s2/' short_trajs = [md.load(loc_dimers+f'dry_{i}.xtc',top=loc_dimers+f'dry_{i}.pdb').remove_solvent() for i in range(0,2)] s2s2 = md.join(short_trajs) # Load H-NS dbd to DNA complex loc_dbd = '/path/to/dbd_h-ns_dna/' traj = [md.load(loc_dbd+f'dry_{i}.xtc',top=loc_dbd+f'dry_{i}.pdb').remove_solvent() for i in range(0,2)] dna_complex = md.join(traj) # Define segments of the protein n = 2 # Overlap of residues between segments segments = {'s1':np.arange(0,41+n), 'h3':np.arange(41-n,53+n), 's2':np.arange(53-n,82+n), 'l2':np.arange(82-n,95+n), 'dbd':np.arange(95-n,137)} # Site map contains a dictionary with the (sub)trajectories of different sites of the protein catergorized from the s1s1 and s2s2 dimers mapper = SiteMapper(s1s1, s2s2, segments=segments, k=100) site_map = mapper.get_site_map() site_map['complex'] = dna_complex

Construct H-NS filament¶

In [18]:

#  Paramers to make filament
n_dimers = 6
chains_to_dna = [0,4,7,11]
save = True

# Initialize class to assemble the filament
assembler = Assembler(site_map=site_map)

# Add dimers
print(f'Assembling {n_dimers} H-NS dimers:')
for idx in tqdm(range(n_dimers)):
    assembler.add_dimer(segment='fixed',verbose=True)  

# Add DNA oligo's
n_dna = len(chains_to_dna)
if n_dna > 0:
    print(f"Assembling {n_dna} DNA oligo's:")
    for chainid in tqdm(chains_to_dna):
        assembler.add_dna(chainid=chainid)


# Retrieve the trajectory from the assembled complex
traj = assembler.get_traj()

# Paramers to make filament n_dimers = 6 chains_to_dna = [0,4,7,11] save = True # Initialize class to assemble the filament assembler = Assembler(site_map=site_map) # Add dimers print(f'Assembling {n_dimers} H-NS dimers:') for idx in tqdm(range(n_dimers)): assembler.add_dimer(segment='fixed',verbose=True) # Add DNA oligo's n_dna = len(chains_to_dna) if n_dna > 0: print(f"Assembling {n_dna} DNA oligo's:") for chainid in tqdm(chains_to_dna): assembler.add_dna(chainid=chainid) # Retrieve the trajectory from the assembled complex traj = assembler.get_traj()

Assembling 6 H-NS dimers:

100%|██████████| 6/6 [00:10<00:00,  1.71s/it]

Assembling 4 DNA oligo's:

100%|██████████| 4/4 [00:02<00:00,  1.97it/s]

In [ ]:

traj.save('./pdbs/lateral_filament_dbd_oligos.pdb')

traj.save('./pdbs/lateral_filament_dbd_oligos.pdb')

Analyze filament¶

Identify chains associated with DNA based on residue names typical for DNA nucleotides

In [19]:

DNA_residue_names = ['DG','DC','DT','DA']
DNA_chainids = []
for chain in traj.top.chains:
    for res in chain._residues:
        if str(res.name) in DNA_residue_names:
            DNA_chainids.append(res.chain.index)
DNA_chainids = np.unique(DNA_chainids)
DNA_chainids = np.array([DNA_chainids[i:i + 2] for i in range(0, len(DNA_chainids), 2)])

DNA_residue_names = ['DG','DC','DT','DA'] DNA_chainids = [] for chain in traj.top.chains: for res in chain._residues: if str(res.name) in DNA_residue_names: DNA_chainids.append(res.chain.index) DNA_chainids = np.unique(DNA_chainids) DNA_chainids = np.array([DNA_chainids[i:i + 2] for i in range(0, len(DNA_chainids), 2)])

In [ ]:

ids = DNA_chainids.flatten()
print(f'chainids {''.join([f'{id} ' for id in ids])}')
selection = traj.top.select(f'chainid {''.join([f'{id} ' for id in ids])}')
subtraj = traj.atom_slice(selection)
subtraj.save('./pdbs/lateral_filament_dbd_only_oligos.pdb')

ids = DNA_chainids.flatten() print(f'chainids {''.join([f'{id} ' for id in ids])}') selection = traj.top.select(f'chainid {''.join([f'{id} ' for id in ids])}') subtraj = traj.atom_slice(selection) subtraj.save('./pdbs/lateral_filament_dbd_only_oligos.pdb')

chainids 12 13 14 15 16 17 18 19 

Calculate specific control points based on the center of mass and other structural features of identified DNA segments This follows the previously described scientific model for assembling H-NS filaments

In [8]:

COM_primes = []
idx = 0
for chainids in DNA_chainids:
    nuc = mdna.load(traj, chainids=chainids)
    frames = nuc.get_frames()

    # Adding control points based on the specific arrangements in the filament model
    if idx == 0:
        COM_primes.append(frames[0][0][0] - np.array([3, -1, 0]))
        COM_primes.append(frames[0][0][0])
    elif idx == 3:
        COM_primes.append(frames[-1][0][0] + np.array([0, -2, 0]))
        COM_primes.append(frames[-1][0][0] + np.array([10, -3, 0]))
    else:
        COM_primes.append(frames[6][0][0])
    idx += 1

COM_primes = np.array(COM_primes)
points = COM_primes

COM_primes = [] idx = 0 for chainids in DNA_chainids: nuc = mdna.load(traj, chainids=chainids) frames = nuc.get_frames() # Adding control points based on the specific arrangements in the filament model if idx == 0: COM_primes.append(frames[0][0][0] - np.array([3, -1, 0])) COM_primes.append(frames[0][0][0]) elif idx == 3: COM_primes.append(frames[-1][0][0] + np.array([0, -2, 0])) COM_primes.append(frames[-1][0][0] + np.array([10, -3, 0])) else: COM_primes.append(frames[6][0][0]) idx += 1 COM_primes = np.array(COM_primes) points = COM_primes

Generate DNA along filement¶

Generate the DNA along defined control points and integrate with the protein structure This step visualizes the flexibility and utility of the .make() function in creating specified DNA shapes

In [9]:

dna = mdna.make(control_points=points)
dna.draw()

dna = mdna.make(control_points=points) dna.draw()

Random sequence: CCTCGCCCCCGGTTAGTAATCCACATCGGAGGCCAATGATCCACACCTTCTTGTGAAGTTGGATGCCGTCAAGTGATTCGCTAAGGGTAGCGGGTAAGGTGCATCGCCTAGCCTTCGATGCAATGGATCTCACGATCGGGAAAATCTCCGTGGGGGCGTCCTGGCCCGTTCGTGCCCGCCGTGGTTCTACCCGATGATTTGTGGTCGAGGGT 

Save result

In [ ]:

# Save the structures for further analysis
dna_traj = dna.get_traj()
protein = traj.atom_slice(traj.top.select('protein'))
protein.save('./pdbs/lateral_filament_noDNA.pdb')
new_traj = dna_traj.stack(protein)
new_traj.save('./pdbs/lateral_filament_with_DNA.pdb')

# Visualize the final combined structure
view = nv.show_mdtraj(new_traj)
view

# Save the structures for further analysis dna_traj = dna.get_traj() protein = traj.atom_slice(traj.top.select('protein')) protein.save('./pdbs/lateral_filament_noDNA.pdb') new_traj = dna_traj.stack(protein) new_traj.save('./pdbs/lateral_filament_with_DNA.pdb') # Visualize the final combined structure view = nv.show_mdtraj(new_traj) view

NGLWidget()

In [ ]:

dna_traj.save('./pdbs/lateral_filament_DNA_only.pdb')

dna_traj.save('./pdbs/lateral_filament_DNA_only.pdb')

In [ ]: