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<!DOCTYPE html PUBLIC "-//W3C//DTD HTML 4.0 Transitional//EN">
<html><head><title>Python: module src.routines</title>
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<table width="100%" cellspacing=0 cellpadding=2 border=0 summary="heading">
<tr bgcolor="#7799ee">
<td valign=bottom> <br>
<font color="#ffffff" face="helvetica, arial"> <br><big><big><strong><a href="src.html"><font color="#ffffff">src</font></a>.routines</strong></big></big> (1 August 2008)</font></td
><td align=right valign=bottom
><font color="#ffffff" face="helvetica, arial"><a href=".">index</a><br><a href="file:/Users/d3y382/workspaces/apbs-pdb2pqr/pdb2pqr/src/routines.py">/Users/d3y382/workspaces/apbs-pdb2pqr/pdb2pqr/src/routines.py</a></font></td></tr></table>
<p><tt><a href="#Routines">Routines</a> for PDB2PQR<br>
<br>
This module contains the protein object used in PDB2PQR and methods<br>
used to correct, analyze, and optimize that protein.<br>
<br>
----------------------------<br>
<br>
PDB2PQR -- An automated pipeline for the setup, execution, and analysis of<br>
Poisson-Boltzmann electrostatics calculations<br>
<br>
Copyright (c) 2002-2011, Jens Erik Nielsen, University College Dublin;<br>
Nathan A. Baker, Battelle Memorial Institute, Developed at the Pacific<br>
Northwest National Laboratory, operated by Battelle Memorial Institute,<br>
Pacific Northwest Division for the U.S. Department Energy.;<br>
Paul Czodrowski & Gerhard Klebe, University of Marburg.<br>
<br>
All rights reserved.<br>
<br>
Redistribution and use in source and binary forms, with or without modification,<br>
are permitted provided that the following conditions are met:<br>
<br>
* Redistributions of source code must retain the above copyright notice,<br>
this list of conditions and the following disclaimer.<br>
* Redistributions in binary form must reproduce the above copyright notice,<br>
this list of conditions and the following disclaimer in the documentation<br>
and/or other materials provided with the distribution.<br>
* Neither the names of University College Dublin, Battelle Memorial Institute,<br>
Pacific Northwest National Laboratory, US Department of Energy, or University<br>
of Marburg nor the names of its contributors may be used to endorse or promote<br>
products derived from this software without specific prior written permission.<br>
<br>
THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" AND<br>
ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED<br>
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IN NO EVENT SHALL THE COPYRIGHT OWNER OR CONTRIBUTORS BE LIABLE FOR ANY DIRECT,<br>
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BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE,<br>
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<br>
----------------------------</tt></p>
<p>
<table width="100%" cellspacing=0 cellpadding=2 border=0 summary="section">
<tr bgcolor="#aa55cc">
<td colspan=3 valign=bottom> <br>
<font color="#ffffff" face="helvetica, arial"><big><strong>Modules</strong></big></font></td></tr>
<tr><td bgcolor="#aa55cc"><tt> </tt></td><td> </td>
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<table width="100%" cellspacing=0 cellpadding=2 border=0 summary="section">
<tr bgcolor="#ee77aa">
<td colspan=3 valign=bottom> <br>
<font color="#ffffff" face="helvetica, arial"><big><strong>Classes</strong></big></font></td></tr>
<tr><td bgcolor="#ee77aa"><tt> </tt></td><td> </td>
<td width="100%"><dl>
<dt><font face="helvetica, arial"><a href="src.routines.html#Cells">Cells</a>
</font></dt><dt><font face="helvetica, arial"><a href="src.routines.html#Routines">Routines</a>
</font></dt></dl>
<p>
<table width="100%" cellspacing=0 cellpadding=2 border=0 summary="section">
<tr bgcolor="#ffc8d8">
<td colspan=3 valign=bottom> <br>
<font color="#000000" face="helvetica, arial"><a name="Cells">class <strong>Cells</strong></a></font></td></tr>
<tr bgcolor="#ffc8d8"><td rowspan=2><tt> </tt></td>
<td colspan=2><tt>The cells object provides a better way to search for nearby atoms. A<br>
pure all versus all search is O(n^2) - for every atom, every other atom<br>
must be searched. This is rather inefficient, especially for large<br>
proteins where cells may be tens of angstroms apart. The cell class<br>
breaks down the xyz protein space into several 3-D cells of desired<br>
size - then by simply examining atoms that fall into the adjacent<br>
cells one can quickly find nearby cells.<br>
<br>
NOTE: Ideally this should be somehow separated from the routines<br>
object...<br> </tt></td></tr>
<tr><td> </td>
<td width="100%">Methods defined here:<br>
<dl><dt><a name="Cells-__init__"><strong>__init__</strong></a>(self, cellsize)</dt><dd><tt>Initialize the cells.<br>
<br>
Parameters<br>
cellsize: The size of each cell (int)</tt></dd></dl>
<dl><dt><a name="Cells-addCell"><strong>addCell</strong></a>(self, atom)</dt><dd><tt>Add an atom to the cell<br>
<br>
Parameters<br>
atom: The atom to add (atom)</tt></dd></dl>
<dl><dt><a name="Cells-assignCells"><strong>assignCells</strong></a>(self, protein)</dt><dd><tt>Place each atom in a virtual cell for easy neighbor comparison</tt></dd></dl>
<dl><dt><a name="Cells-getNearCells"><strong>getNearCells</strong></a>(self, atom)</dt><dd><tt>Find all atoms in bordering cells to an atom<br>
<br>
Parameters<br>
atom: The atom to use (atom)<br>
Returns<br>
closeatoms: A list of nearby atoms (list)</tt></dd></dl>
<dl><dt><a name="Cells-removeCell"><strong>removeCell</strong></a>(self, atom)</dt><dd><tt>Remove the atom from a cell<br>
<br>
Parameters<br>
atom: The atom to add (atom)</tt></dd></dl>
</td></tr></table> <p>
<table width="100%" cellspacing=0 cellpadding=2 border=0 summary="section">
<tr bgcolor="#ffc8d8">
<td colspan=3 valign=bottom> <br>
<font color="#000000" face="helvetica, arial"><a name="Routines">class <strong>Routines</strong></a></font></td></tr>
<tr><td bgcolor="#ffc8d8"><tt> </tt></td><td> </td>
<td width="100%">Methods defined here:<br>
<dl><dt><a name="Routines-__init__"><strong>__init__</strong></a>(self, protein, verbose, definition<font color="#909090">=None</font>)</dt><dd><tt>Initialize the <a href="#Routines">Routines</a> class. The class contains most<br>
of the main routines that run PDB2PQR<br>
<br>
Parameters<br>
protein: The protein to run PDB2PQR on (Protein)<br>
verbose: A flag to determine whether to write to<br>
stdout</tt></dd></dl>
<dl><dt><a name="Routines-addHydrogens"><strong>addHydrogens</strong></a>(self)</dt><dd><tt>Add the hydrogens to the protein. This requires either<br>
the rebuildTetrahedral function for tetrahedral geometries<br>
or the standard quatfit methods. These methods use three<br>
nearby bonds to rebuild the atom; the closer the bonds, the<br>
more accurate the results. As such the peptide bonds are<br>
used when available.</tt></dd></dl>
<dl><dt><a name="Routines-applyForcefield"><strong>applyForcefield</strong></a>(self, forcefield)</dt><dd><tt>Apply the forcefield to the atoms within the protein<br>
<br>
Parameters<br>
forcefield: The forcefield object (forcefield)<br>
Returns<br>
hitlist: A list of atoms that were found in<br>
the forcefield (list)<br>
misslist: A list of atoms that were not found in<br>
the forcefield (list)</tt></dd></dl>
<dl><dt><a name="Routines-applyNameScheme"><strong>applyNameScheme</strong></a>(self, forcefield)</dt><dd><tt>Apply the naming scheme of the given forcefield to the atoms<br>
within the protein<br>
<br>
Parameters<br>
forcefield: The forcefield object (forcefield)</tt></dd></dl>
<dl><dt><a name="Routines-applyPatch"><strong>applyPatch</strong></a>(self, patchname, residue)</dt><dd><tt>Apply a patch to the given residue. This is one of the key<br>
functions in PDB2PQR. A similar function appears in<br>
definitions.py - that version is needed for residue level<br>
subtitutions so certain protonation states (i.e. CYM, HSE)<br>
are detectatble on input.<br>
<br>
This version looks up the particular patch name in the<br>
patchmap stored in the protein, and then applies the<br>
various commands to the reference and actual residue<br>
structures.<br>
<br>
See the inline comments for a more detailed explanation.<br>
<br>
Parameters<br>
patchname: The name of the patch (string)<br>
residue: The residue to apply the patch to (residue)</tt></dd></dl>
<dl><dt><a name="Routines-apply_pka_values"><strong>apply_pka_values</strong></a>(self, ff, ph, pkadic)</dt></dl>
<dl><dt><a name="Routines-assignTermini"><strong>assignTermini</strong></a>(self, chain, neutraln<font color="#909090">=False</font>, neutralc<font color="#909090">=False</font>)</dt><dd><tt>Assign the termini for the given chain by looking at<br>
the start and end residues.</tt></dd></dl>
<dl><dt><a name="Routines-calculateDihedralAngles"><strong>calculateDihedralAngles</strong></a>(self)</dt><dd><tt>Calculate the dihedral angle for every residue within the protein</tt></dd></dl>
<dl><dt><a name="Routines-debumpProtein"><strong>debumpProtein</strong></a>(self)</dt><dd><tt>Make sure that none of the added atoms were rebuilt<br>
on top of existing atoms. See each called function<br>
for more information.</tt></dd></dl>
<dl><dt><a name="Routines-debumpResidue"><strong>debumpResidue</strong></a>(self, residue, conflictnames)</dt><dd><tt>Debump a specific residue. Only should be called<br>
if the residue has been detected to have a conflict.<br>
If called, try to rotate about dihedral angles to<br>
resolve the conflict.<br>
<br>
Parameters<br>
residue: The residue in question<br>
conflictnames: A list of atomnames that were<br>
rebuilt too close to other atoms<br>
Returns<br>
True if successful, False otherwise</tt></dd></dl>
<dl><dt><a name="Routines-findMissingHeavy"><strong>findMissingHeavy</strong></a>(self)</dt><dd><tt>Repair residues that contain missing heavy (non-Hydrogen) atoms</tt></dd></dl>
<dl><dt><a name="Routines-findNearbyAtoms"><strong>findNearbyAtoms</strong></a>(self, atom)</dt><dd><tt>Find nearby atoms for conflict-checking. Uses<br>
neighboring cells to compare atoms rather than an all<br>
versus all O(n^2) algorithm, which saves a great deal<br>
of time. There are several instances where we ignore<br>
potential conflicts; these include donor/acceptor pairs,<br>
atoms in the same residue, and bonded CYS bridges.<br>
<br>
Parameters<br>
atom: Find nearby atoms to this atom (Atom)<br>
Returns<br>
nearatoms: A dictionary of <Atom too close> to <amount of overlap for that atom>.</tt></dd></dl>
<dl><dt><a name="Routines-findResidueConflicts"><strong>findResidueConflicts</strong></a>(self, residue, writeConflictInfo<font color="#909090">=False</font>)</dt></dl>
<dl><dt><a name="Routines-getClosestAtom"><strong>getClosestAtom</strong></a>(self, atom)</dt><dd><tt>Get the closest atom that does not form a donor/acceptor pair.<br>
Used to detect potential conflicts.<br>
<br>
NOTE: <a href="#Cells">Cells</a> must be set before using this function.<br>
<br>
Parameters<br>
atom: The atom in question (Atom)<br>
Returns<br>
bestatom: The closest atom to the input atom that does not<br>
satisfy a donor/acceptor pair.</tt></dd></dl>
<dl><dt><a name="Routines-getMoveableNames"><strong>getMoveableNames</strong></a>(self, residue, pivot)</dt><dd><tt>Return all atomnames that are further away than the<br>
pivot atom.<br>
<br>
Parameters<br>
residue: The residue to use<br>
pivot: The pivot atomname</tt></dd></dl>
<dl><dt><a name="Routines-getWarnings"><strong>getWarnings</strong></a>(self)</dt><dd><tt>Get all warnings generated from routines</tt></dd></dl>
<dl><dt><a name="Routines-getbumpscore"><strong>getbumpscore</strong></a>(self, residue)</dt><dd><tt>Get an bump score for the current structure</tt></dd></dl>
<dl><dt><a name="Routines-getbumpscore_atom"><strong>getbumpscore_atom</strong></a>(self, atom)</dt><dd><tt>Find nearby atoms for conflict-checking. Uses<br>
neighboring cells to compare atoms rather than an all<br>
versus all O(n^2) algorithm, which saves a great deal<br>
of time. There are several instances where we ignore<br>
potential conflicts; these include donor/acceptor pairs,<br>
atoms in the same residue, and bonded CYS bridges.<br>
<br>
Parameters<br>
atom: Find nearby atoms to this atom (Atom)<br>
Returns<br>
bumpscore: a bump score sum((dist-cutoff)**20 for all near atoms<br>
<br>
Jens rewrote this function from findNearbyAtoms to<br>
be usable for detecting bumps for optimzable hydrogens</tt></dd></dl>
<dl><dt><a name="Routines-pickDihedralAngle"><strong>pickDihedralAngle</strong></a>(self, residue, conflictnames, oldnum<font color="#909090">=None</font>)</dt><dd><tt>Choose an angle number to use in debumping<br>
<br>
Algorithm<br>
Instead of simply picking a random chiangle, this function<br>
uses a more intelligent method to improve efficiency.<br>
The algorithm uses the names of the conflicting atoms<br>
within the residue to determine which angle number<br>
has the best chance of fixing the problem(s). The method<br>
also insures that the same chiangle will not be run twice<br>
in a row.<br>
Parameters<br>
residue: The residue that is being debumped (Residue)<br>
conflictnames: A list of atom names that are currently<br>
conflicts (list)<br>
oldnum : The old dihedral angle number (int)<br>
Returns<br>
bestnum : The new dihedral angle number (int)</tt></dd></dl>
<dl><dt><a name="Routines-removeHydrogens"><strong>removeHydrogens</strong></a>(self)</dt></dl>
<dl><dt><a name="Routines-repairHeavy"><strong>repairHeavy</strong></a>(self)</dt><dd><tt>Repair all heavy atoms. Unfortunately the first time we<br>
get to an atom we might not be able to rebuild it - it<br>
might depend on other atoms to be rebuild first (think side<br>
chains). As such a 'seenmap' is used to keep track of what<br>
we've already seen and subsequent attempts to rebuild the<br>
atom.</tt></dd></dl>
<dl><dt><a name="Routines-runPDB2PKA"><strong>runPDB2PKA</strong></a>(self, ph, ff, pdblist, ligand, verbose, pdb2pka_params)</dt></dl>
<dl><dt><a name="Routines-runPROPKA"><strong>runPROPKA</strong></a>(self, ph, ff, rootname, outname, options)</dt><dd><tt>Run PROPKA on the current protein, setting protonation states to<br>
the correct values<br>
<br>
Parameters<br>
ph: The desired pH of the system<br>
ff: The forcefield name to be used<br>
outname: The name of the PQR outfile</tt></dd></dl>
<dl><dt><a name="Routines-scoreDihedralAngle"><strong>scoreDihedralAngle</strong></a>(self, residue, anglenum)</dt></dl>
<dl><dt><a name="Routines-setDihedralAngle"><strong>setDihedralAngle</strong></a>(self, residue, anglenum, angle)</dt><dd><tt>Rotate a residue about a given angle. Uses the quatfit<br>
methods to perform the matrix mathematics.<br>
<br>
Parameters<br>
residue: The residue to rotate<br>
anglenum: The number of the angle to rotate as<br>
listed in residue.dihedrals<br>
angle: The desired angle.</tt></dd></dl>
<dl><dt><a name="Routines-setDonorsAndAcceptors"><strong>setDonorsAndAcceptors</strong></a>(self)</dt><dd><tt>Set the donors and acceptors within the protein</tt></dd></dl>
<dl><dt><a name="Routines-setReferenceDistance"><strong>setReferenceDistance</strong></a>(self)</dt><dd><tt>Set the distance to the CA atom in the residue.<br>
This is necessary for determining which atoms are<br>
allowed to move during rotations. Uses the<br>
shortestPath algorithm found in utilities.py.</tt></dd></dl>
<dl><dt><a name="Routines-setStates"><strong>setStates</strong></a>(self)</dt><dd><tt>Set the state of each residue. This is the last step<br>
before assigning the forcefield, but is necessary so<br>
as to distinguish between various protonation states.<br>
<br>
See aa.py for residue-specific functions.</tt></dd></dl>
<dl><dt><a name="Routines-setTermini"><strong>setTermini</strong></a>(self, neutraln<font color="#909090">=False</font>, neutralc<font color="#909090">=False</font>)</dt><dd><tt>Set the termini for the protein. First set all known<br>
termini by looking at the ends of the chain. Then<br>
examine each residue, looking for internal chain breaks.</tt></dd></dl>
<dl><dt><a name="Routines-updateBonds"><strong>updateBonds</strong></a>(self)</dt><dd><tt>Update the bonding network of the protein. This happens<br>
in 3 steps:<br>
1. Applying the PEPTIDE patch to all Amino residues<br>
so as to add reference for the N(i+1) and C(i-1)<br>
atoms<br>
2. UpdateInternalBonds for inter-residue linking<br>
3. Set the links to the N(i+1) and C(i-1) atoms</tt></dd></dl>
<dl><dt><a name="Routines-updateInternalBonds"><strong>updateInternalBonds</strong></a>(self)</dt><dd><tt>Update the internal bonding network using the reference<br>
objects in each atom.</tt></dd></dl>
<dl><dt><a name="Routines-updateResidueTypes"><strong>updateResidueTypes</strong></a>(self)</dt><dd><tt>Find the type of residue as notated in the Amino Acid definition</tt></dd></dl>
<dl><dt><a name="Routines-updateSSbridges"><strong>updateSSbridges</strong></a>(self)</dt><dd><tt>Check for SS-bridge partners, and if present, set appropriate<br>
partners</tt></dd></dl>
<dl><dt><a name="Routines-write"><strong>write</strong></a>(self, message, indent<font color="#909090">=0</font>)</dt><dd><tt>Write a message to stdout for debugging if verbose<br>
<br>
Parameters<br>
message: The message to write (string)<br>
indent : The indent level (int, default=0)</tt></dd></dl>
<hr>
Static methods defined here:<br>
<dl><dt><a name="Routines-rebuildTetrahedral"><strong>rebuildTetrahedral</strong></a>(residue, atomname)</dt><dd><tt>Rebuild a tetrahedral hydrogen group. This is necessary<br>
due to the shortcomings of the quatfit routine - given a<br>
tetrahedral geometry and two existing hydrogens, the<br>
quatfit routines have two potential solutions. This function<br>
uses basic tetrahedral geometry to fix this issue.<br>
<br>
Parameters<br>
residue: The residue in question (residue)<br>
atomname: The atomname to add (string)<br>
Returns<br>
1 if successful, 0 otherwise</tt></dd></dl>
</td></tr></table></td></tr></table><p>
<table width="100%" cellspacing=0 cellpadding=2 border=0 summary="section">
<tr bgcolor="#55aa55">
<td colspan=3 valign=bottom> <br>
<font color="#ffffff" face="helvetica, arial"><big><strong>Data</strong></big></font></td></tr>
<tr><td bgcolor="#55aa55"><tt> </tt></td><td> </td>
<td width="100%"><strong>AAPATH</strong> = 'dat/AA.xml'<br>
<strong>AAS</strong> = ['ALA', 'ARG', 'ASH', 'ASN', 'ASP', 'CYS', 'CYM', 'GLN', 'GLU', 'GLH', 'GLY', 'HIS', 'HID', 'HIE', 'HIP', 'HSD', 'HSE', 'HSP', 'ILE', 'LEU', ...]<br>
<strong>BACKBONE</strong> = ['N', 'CA', 'C', 'O', 'O2', 'HA', 'HN', 'H', 'tN']<br>
<strong>BONDED_SS_LIMIT</strong> = 2.5<br>
<strong>BUMP_DIST</strong> = 2.0<br>
<strong>BUMP_HDIST</strong> = 1.5<br>
<strong>BUMP_HEAVY_SIZE</strong> = 1.0<br>
<strong>BUMP_HYDROGEN_SIZE</strong> = 0.5<br>
<strong>CELL_SIZE</strong> = 2<br>
<strong>DIHEDRAL</strong> = 57.2958<br>
<strong>INSTALLDIR</strong> = '/Users/d3y382/pdb2pqr/'<br>
<strong>NAPATH</strong> = 'dat/NA.xml'<br>
<strong>NAS</strong> = ['A', 'A5', 'A3', 'C', 'C5', 'C3', 'G', 'G5', 'G3', 'T', 'T5', 'T3', 'U', 'U5', 'U3', 'RA', 'RG', 'RC', 'RU', 'DA', ...]<br>
<strong>PATCHPATH</strong> = 'dat/PATCHES.xml'<br>
<strong>PEPTIDE_DIST</strong> = 1.7<br>
<strong>REPAIR_LIMIT</strong> = 10<br>
<strong>SMALL</strong> = 1e-07<br>
<strong>TMPDIR</strong> = 'tmp/'<br>
<strong>__author__</strong> = 'Jens Erik Nielsen, Todd Dolinsky, Yong Huang'<br>
<strong>__date__</strong> = '1 August 2008'<br>
<strong>lineParsers</strong> = {'ANISOU': <class 'src.pdb.ANISOU'>, 'ATOM': <class 'src.pdb.ATOM'>, 'AUTHOR': <class 'src.pdb.AUTHOR'>, 'CAVEAT': <class 'src.pdb.CAVEAT'>, 'CISPEP': <class 'src.pdb.CISPEP'>, 'COMPND': <class 'src.pdb.COMPND'>, 'CONECT': <class 'src.pdb.CONECT'>, 'CRYST1': <class 'src.pdb.CRYST1'>, 'DBREF': <class 'src.pdb.DBREF'>, 'END': <class 'src.pdb.END'>, ...}</td></tr></table><p>
<table width="100%" cellspacing=0 cellpadding=2 border=0 summary="section">
<tr bgcolor="#7799ee">
<td colspan=3 valign=bottom> <br>
<font color="#ffffff" face="helvetica, arial"><big><strong>Author</strong></big></font></td></tr>
<tr><td bgcolor="#7799ee"><tt> </tt></td><td> </td>
<td width="100%">Jens Erik Nielsen, Todd Dolinsky, Yong Huang</td></tr></table>
</body></html>
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