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HBCounter.py
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HBCounter.py
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# -*- coding: utf-8 -*-
# Standard imports
import os
import argparse as ap
from multiprocessing import Pool
from functools import partial
from pathlib import Path
from typing import List, Tuple, Set, Dict
# Local imports
from Helpers import SimIt, HBondLinker
from Helpers import hbond_mod as hbm
from Helpers.ReportUtils import extract_metrics
# External imports
import mdtraj as md
import pandas as pd
import numpy as np
# Script information
__author__ = "Marti Municoy, Carles Perez"
__license__ = "GPL"
__version__ = "1.0.1"
__maintainer__ = "Marti Municoy, Carles Perez"
__email__ = "marti.municoy@bsc.es, carles.perez@bsc.es"
def parse_args():
parser = ap.ArgumentParser()
parser.add_argument("sim_paths", metavar="PATH", type=str,
nargs='*',
help="Path to PELE simulation folders")
parser.add_argument("-l", "--ligand_resname",
metavar="LIG", type=str, default='LIG',
help="Ligand residue name")
parser.add_argument("-d", "--distance",
metavar="D", type=float, default='0.25',
help="Hydrogen bonds distance")
parser.add_argument("-a", "--angle",
metavar="A", type=float, default='2.0943951023931953',
help="Hydrogen bonds angle")
parser.add_argument("-p", "--pseudo_hb",
metavar="BOOL", type=bool, default=False,
help="Look for pseudo hydrogen bonds")
parser.add_argument("-n", "--processors_number",
metavar="N", type=int, default=None,
help="Number of processors")
parser.add_argument("-t", "--topology_path",
metavar="PATH", type=str,
default='output/topologies/topology_0.pdb',
help="Relative path to topology")
parser.add_argument("-o", "--output_path",
metavar="PATH", type=str,
default='hbonds.csv',
help="Relative path to output file")
parser.add_argument("--PELE_output_path",
metavar="PATH", type=str, default='output',
help="Relative path to PELE output folder")
parser.add_argument("-r", "--report_name",
metavar="NAME", type=str,
default='report',
help="PELE report name")
parser.add_argument('--include_rejected_steps',
dest='include_rejected_steps',
action='store_true')
parser.add_argument("--alternative_output_path",
metavar="PATH", type=str, default=None,
help="Alternative path to save output results")
parser.set_defaults(include_rejected_steps=False)
args = parser.parse_args()
return args.sim_paths, args.ligand_resname, args.distance, args.angle, \
args.pseudo_hb, args.processors_number, args.topology_path, \
args.output_path, args.report_name, args.PELE_output_path, \
args.include_rejected_steps, args.alternative_output_path
def account_for_ignored_hbonds(hbonds_in_traj: List[List[HBondLinker]],
accepted_steps: List[int]
) -> List[List[HBondLinker]]:
new_hbonds_in_traj = []
for i, s in enumerate(accepted_steps):
new_hbonds_in_traj.append(hbonds_in_traj[s])
return new_hbonds_in_traj
def find_hbonds_in_trajectory(lig_resname: str, distance: float, angle: float,
pseudo: bool, topology_path: Path,
chain_ids: List[str], report_name: str,
include_rejected_steps: bool, traj_path: Path
) -> Tuple[List[List[HBondLinker]],
List[int], List[int],
Set[md.core.topology.Atom],
Set[md.core.topology.Atom]]:
try:
traj = md.load_xtc(str(traj_path), top=str(topology_path))
except OSError:
print(' - Warning: problems loading trajectory '
'{}, it will be ignored'.format(traj_path))
# Return empty data structures
return list(), list(), list(), set(), set()
lig = traj.topology.select('resname {}'.format(lig_resname))
hbonds_in_traj, donors, acceptors = find_ligand_hbonds(traj, lig, distance,
angle, pseudo,
chain_ids)
# Recover corresponding report
num = int(''.join(filter(str.isdigit, traj_path.name)))
path = traj_path.parent
report_path = path.joinpath(report_name + '_{}'.format(num))
metrics = extract_metrics((report_path, ), (2, 3))[0]
total_steps = []
accepted_steps = []
for m in metrics:
total_steps.append(int(m[0]))
accepted_steps.append(int(m[1]))
try:
if (include_rejected_steps):
hbonds_in_traj = account_for_ignored_hbonds(hbonds_in_traj,
accepted_steps)
else:
if (len(hbonds_in_traj) != len(total_steps)
or len(hbonds_in_traj) != len(accepted_steps)):
raise IndexError
except IndexError:
print(' - Warning: inconsistent number of models found in '
+ 'trajectory {} from {}, '.format(num, path)
+ 'this trajectory will be ignored')
# Return empty data structures
return list(), list(), list(), set(), set()
return hbonds_in_traj, total_steps, accepted_steps, donors, acceptors
def find_ligand_hbonds(traj: md.Trajectory, lig: np.ndarray, distance: float,
angle: float, pseudo: bool, chain_ids: List[str]
) -> Tuple[List[List[HBondLinker]],
Set[md.core.topology.Atom],
Set[md.core.topology.Atom]]:
hbonds_list = []
donors = set()
acceptors = set()
for model_id in range(0, traj.n_frames):
results, _donors, _acceptors = find_hbond_in_snapshot(
traj, model_id, lig, distance, angle, pseudo, chain_ids)
hbonds_list.append(results)
for d in _donors:
donors.add(d)
for a in _acceptors:
acceptors.add(a)
return hbonds_list, donors, acceptors
def find_hbond_in_snapshot(traj: md.Trajectory, model_id: int, lig: np.ndarray,
distance: float, angle: float, pseudo: bool,
chain_ids: List[str]
) -> Tuple[List[HBondLinker],
Set[md.core.topology.Atom],
Set[md.core.topology.Atom]]:
hbonds = hbm.baker_hubbard(traj=traj[model_id], distance=distance,
angle=angle, pseudo=pseudo)
results = []
donors = set()
acceptors = set()
for hbond in hbonds:
if (hbond[0] in lig):
donors.add(traj.topology.atom(hbond[0]))
elif (hbond[2] in lig):
acceptors.add(traj.topology.atom(hbond[2]))
if (any(atom in lig for atom in hbond) and not
all(atom in hbond for atom in lig)):
for atom in hbond:
if (atom not in lig):
_atom = traj.topology.atom(atom)
hb_linker = HBondLinker(
chain_ids[_atom.residue.chain.index],
_atom.residue, tuple((_atom.name, )))
results.append(hb_linker)
break
return results, donors, acceptors
def parse_results(results: Tuple[List[HBondLinker],
Set[md.core.topology.Atom],
Set[md.core.topology.Atom]],
trajectories: List[md.Trajectory]
) -> Tuple[pd.DataFrame,
Set[md.core.topology.Atom],
Set[md.core.topology.Atom],
int]:
counter = 0
data = pd.DataFrame()
donors = set()
acceptors = set()
for (r, t_steps, a_steps, _donors, _acceptors), t in zip(results,
trajectories):
counter += len(r)
epoch = int(t.parent.name)
trajectory = int(''.join(filter(str.isdigit, t.name)))
for hbonds, t_s, a_s in zip(r, t_steps, a_steps):
data = data.append(pd.DataFrame(
[(epoch, trajectory, t_s, a_s, hbonds)],
columns=['epoch', 'trajectory', 'step', 'model',
'hbonds']))
for d in _donors:
donors.add(d)
for a in _acceptors:
acceptors.add(a)
return data, donors, acceptors, counter
def main():
# Parse args
PELE_sim_paths, lig_resname, distance, angle, pseudo_hb, proc_number, \
topology_relative_path, output_relative_path, report_name, \
PELE_output_path, include_rejected_steps, alternative_output_path = \
parse_args()
all_sim_it = SimIt(PELE_sim_paths)
print(' - The following PELE simulation paths will be analyzed:')
for PELE_sim_path in all_sim_it:
print(' - {}'.format(PELE_sim_path))
for PELE_sim_path in all_sim_it:
print(' - Analyzing {}'.format(PELE_sim_path))
topology_path = PELE_sim_path.joinpath(topology_relative_path)
if (not topology_path.is_file()):
print(' - Skipping simulation because topology file with '
+ 'connectivity was missing')
continue
# Retrieve chain ids
chain_ids = set()
with open(str(topology_path), 'r') as f:
for line in f:
if (len(line) < 80):
continue
line = line.strip()
chain_ids.add(line[21])
chain_ids = sorted(list(chain_ids))
parallel_function = partial(find_hbonds_in_trajectory, lig_resname,
distance, angle, pseudo_hb, topology_path,
chain_ids, report_name,
include_rejected_steps)
sim_it = SimIt(PELE_sim_path)
sim_it.build_traj_it(PELE_output_path, 'trajectory', 'xtc')
trajectories = [traj for traj in sim_it.traj_it]
with Pool(proc_number) as pool:
results = pool.map(parallel_function,
trajectories)
data, donors, acceptors, counter = parse_results(results, trajectories)
print(' - {} models were found'.format(counter))
print(' - {} ligand donors were found'.format(len(donors)))
print(' - {} ligand acceptors were found'.format(len(acceptors)))
if (alternative_output_path is not None):
output_path = Path(alternative_output_path)
output_path = output_path.joinpath(PELE_sim_path.name)
output_path = output_path.joinpath(output_relative_path)
try:
os.makedirs(str(output_path.parent))
except FileExistsError:
pass
else:
output_path = PELE_sim_path.joinpath(output_relative_path)
output_info_path = Path(output_path.parent).joinpath(
output_path.name.replace(output_path.suffix, '') + '.info')
with open(str(output_info_path), 'w') as file:
file.write(str(PELE_sim_path.name) + '\n')
file.write('{} donors: {}\n'.format(len(donors),
list(donors)))
file.write('{} acceptors: {}\n'.format(len(acceptors),
list(acceptors)))
data.to_csv(output_path, index=False)
if __name__ == "__main__":
main()