Filter.py: - Revision history

Frodo at 16:12, 14 February 2014

2014-02-14T16:12:42Z

← Older revision		Revision as of 16:12, 14 February 2014
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	Thanks to Nir for sharing this script and to OpenEye of course.		Thanks to Nir for sharing this script and to OpenEye of course.

	[[Category:~~Tutorial~~]]		[[Category:Tutorials]]
	[[Category:Docking]]		[[Category:Docking]]

Frodo at 03:35, 14 February 2014

2014-02-14T03:35:48Z

← Older revision		Revision as of 03:35, 14 February 2014
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	==Acknowledgments==		==Acknowledgments==
	Thanks to Nir for sharing this script and to OpenEye of course.		Thanks to Nir for sharing this script and to OpenEye of course.

			[[Category:Tutorial]]
			[[Category:Docking]]

Oliv Eidam at 23:30, 6 May 2013

2013-05-06T23:30:36Z

← Older revision		Revision as of 23:30, 6 May 2013
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	3. Find the x,y,z coordinates of the reference point, e.g.: -36.457 9.996 6.888		3. Find the x,y,z coordinates of the reference point, e.g.: -36.457 9.996 6.888

	Then run filter.py providing coordinates and coordinates of the reference point:		Then run filter.py providing pdb coordinates and coordinates of the reference point:
	filter.py topdock.pdb -36.457 9.996 6.888 > filter.log		filter.py topdock.pdb -36.457 9.996 6.888 > filter.log

Line 73:		Line 73:
	print mol.GetTitle(),d		print mol.GetTitle(),d
	ifs.close()		ifs.close()


			==Acknowledgments==
			Thanks to Nir for sharing this script and to OpenEye of course.

Oliv Eidam at 23:05, 6 May 2013

2013-05-06T23:05:11Z

← Older revision		Revision as of 23:05, 6 May 2013
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	=Filter.py: search a substructure in DOCK poses and calculate atom distances=		=Filter.py: search a substructure in DOCK poses and calculate atom distances=

	Sometimes it is interesting to search for a substructure in your DOCK output poses and calculate distances to a reference point. This is what filter.py (courtesy from Nir) can do for you.		[[File:Piperidine opioid coords.png\|thumb\|upright=1.35\|right\|alt=Opioid ligands exhibit a piperdine substructure and the charged nitrogen forms a salt bridge with Asp[3.32]. \|Opioid ligands exhibit a piperdine substructure and the charged nitrogen forms a salt bridge with Asp[3.32].]]
	For example, lots of opioid ligands exhibit a piperidine ring. The charged nitrogen of the piperidine ring forms a salt bridge with the conserved Asp[3.32] in the delta, mu and ~~kappa~~ opioid receptor crystal structures, and you may be interested to interrogate how many of your docked opioid ligands place the piperidine nitrogen within salt bridge distance of the conserved Aspartate.
			Sometimes it is interesting to search for a substructure in your DOCK output poses and calculate distances to a reference point. This is what filter.py (courtesy from Nir) can do for you. <br>
			For example, lots of opioid ligands exhibit a piperidine ring. The charged nitrogen of the piperidine ring forms a salt bridge with the conserved Asp[3.32] in the delta, mu and nociceptin opioid receptor crystal structures, and you may be interested to interrogate how many of your docked opioid ligands place the piperidine nitrogen within salt bridge distance of the conserved Aspartate.

	==Edit filter.py==		==Edit filter.py==
	Edit filter.py (see code below): <br>		Edit filter.py (see code below): <br>
	1. Define a substructure for your ligand(s) by providing smiles or smarts for your substructure (variable ss); <br>		1. Define a substructure for your ligand(s) by providing smiles or smarts for your substructure (variable ss); <br>
	2. Define an atom within that substructure to calculate distance from a reference point (variable attack_site); the first atom in your smiles or smarts is 0, the second is 1, the third is 2, etc.		2. Define an atom within that substructure to calculate distance from a reference point (variable attack_site); the first atom in your smiles or smarts is 0, the second is 1, the third is 2, etc. <br>
			3. Find the x,y,z coordinates of the reference point, e.g.: -36.457 9.996 6.888

	Then run filter.py providing coordinates and coordinates of the reference point:		Then run filter.py providing coordinates and coordinates of the reference point:

Oliv Eidam: Created page with "=Filter.py: search a substructure in DOCK poses and calculate atom distances= Sometimes it is interesting to search for a substructure in your DOCK output poses and calculate..."

2013-05-06T22:54:01Z

Created page with "=Filter.py: search a substructure in DOCK poses and calculate atom distances= Sometimes it is interesting to search for a substructure in your DOCK output poses and calculate..."

New page

=Filter.py: search a substructure in DOCK poses and calculate atom distances=

Sometimes it is interesting to search for a substructure in your DOCK output poses and calculate distances to a reference point. This is what filter.py (courtesy from Nir) can do for you.
For example, lots of opioid ligands exhibit a piperidine ring. The charged nitrogen of the piperidine ring forms a salt bridge with the conserved Asp[3.32] in the delta, mu and kappa opioid receptor crystal structures, and you may be interested to interrogate how many of your docked opioid ligands place the piperidine nitrogen within salt bridge distance of the conserved Aspartate.

==Edit filter.py==
Edit filter.py (see code below): <br>
1. Define a substructure for your ligand(s) by providing smiles or smarts for your substructure (variable ss); <br>
2. Define an atom within that substructure to calculate distance from a reference point (variable attack_site); the first atom in your smiles or smarts is 0, the second is 1, the third is 2, etc.

Then run filter.py providing coordinates and coordinates of the reference point:
filter.py topdock.pdb -36.457 9.996 6.888 > filter.log

This outputs a line for each ligand that is within a the defined vicinity threshold t, which is 15.5 Angstrom in the example below. The last number in the output (filter.log) is the distance (4.59A below).

Example output in filter.log:
1 cmpd24 -55.98 -45.59 -29.67 24.45 -5.17 4.5911097889

==filter.py code==

#!/usr/bin/env python
import os
import sys
import math

from openeye.oechem import *
from openeye.oeomega import *

#usage ./filter.py topdock.pdb -36.457 9.996 6.888

def calc_dist(p1,p2):
return math.sqrt((p1[0]-p2[0])**2+(p1[1]-p2[1])**2+(p1[2]-p2[2])**2)

#main program
#input file is the first argument
infile = sys.argv[1]
#x y z coords of target cys are the next 3 args
cov_xyz = [0,0,0]
cov_xyz[0] = float(sys.argv[2])
cov_xyz[1] = float(sys.argv[3])
cov_xyz[2] = float(sys.argv[4])

ifs = oemolistream(infile)
mol = OEGraphMol()
lig_xyz = OEDoubleArray(3)

#define the vicinity threashold
t = 15.5
#define the reactive warhead and identify the attack site

#piperidine smiles; distance to nitrogen measured
ss = OESubSearch("CN1CCCCC1")
attack_site = 1

#amide smarts, distance to oxygen measured
#ss = OESubSearch("[NX3H1][CX3](=[OX1])[#6]")
#attack_site = 2

while OEReadMolecule(ifs, mol):
for count,match in enumerate(ss.Match(mol,"true")):
for ma in match.GetAtoms():
#starting count from zero and target carbon is 5
if (ma.pattern.GetIdx()==attack_site):
mol.GetCoords(ma.target,lig_xyz)
#print mol.GetTitle(),calc_dist(lig_xyz,cov_xyz)
d=calc_dist(lig_xyz,cov_xyz)
if d<t:
print mol.GetTitle(),d
ifs.close()