<divstyle="text-align:center">Copyright 2013 by Peter Eastman and Stanford University</div>
<divstyle="text-align:center">Copyright 2013-2014 by Peter Eastman and Stanford University</div>
<h1>1. Introduction</h1>
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This will install the PDBFixer python package as well as the command line program <tt>pdbfixer</tt>.
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Before running PDBFixer, you must first install <ahref="https://simtk.org/home/openmm">OpenMM</a>5.2 or later. Follow the installation instructions in the OpenMM manual. It is also highly recommended that you install CUDA or OpenCL. In principle PDBFixer can use the OpenMM reference platform, but it will be prohibitively slow. PDBFixer requires that <ahref="http://www.numpy.org">NumPy</a> be installed.
Before running PDBFixer, you must first install <ahref="https://simtk.org/home/openmm">OpenMM</a>6.0 or later. Follow the installation instructions in the OpenMM manual. It is also recommended that you install CUDA or OpenCL, since the performance will usually be faster than when running on the CPU platform. PDBFixer requires that <ahref="http://www.numpy.org">NumPy</a> be installed.
<h1>3. PDBFixer as a Desktop Application</h1>
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To use PDBFixer create a <tt>PDBFixer</tt> object, passing to its constructor a <tt>PdbStructure</tt> object containing the structure to process. You then call a series of methods on it to perform various transformations. When all the transformations are done, you can get the new structure from its <tt>topology</tt> and <tt>positions</tt> fields. The overall outline of your code will look something like this: