PyPAT: Python-based Protein Analysis Tools

PyPAT (Python-based Protein Analysis Tools) is a collection of tools that build upon the ptraj module of AMBER and the PyMOL visualization package to aid in the analysis of protein structures and molecular dynamics trajectories. They allow for the evaluation of the convergence of trajectories, as well as the examination of correlated dynamics, hydrogen bonds, and bridging-water molecules throughout a trajectory. Our tools are written in Python and released under an open-source license.

Lerner, M.G.; Spronk, S.A.; Carlson, H.A. PyPAT: a Python-based toolset to aid in the analysis of protein structures and trajectories. (2008) *submitted to Bioinformatics*.

 

Automated clustering of probe molecules from solvent mapping of protein surfaces

In an effort to understand protein binding and function, researchers will often create a reciprocal map of a protein surface. Multiple-copy methods (MCM) use probe molecules to define these complementary maps. These techniques flood the protein surface with hundreds of small molecule probes. The probes are then simultaneously and independently minimized to the protein’s potential energy surface. Clusters of probes on the protein surface can define the most important among these interactions. Most MCMs that cluster molecules in physical space do so via RMSD-based methods. We find that significantly improved results may be obtained by Jarvis-Patrick clustering in physical space. This package contains programs for flooding a protein surface with probe molecules, as well as programs to group the probe molecules into clusters.

Lerner, M.G.; Meagher, K.L.; Carlson H.A. Automated clustering of probe molecules from solvent mapping of protein surfaces: New algorithms applied to hot-spot mapping and structure-based drug design. J Comput. Aided Mol. Des. 2008, 10, 727-736.

 

Gaussian-weighted RMSD superposition of proteins

wRMSD Fitting

Many proteins contain flexible structures such as loops and hinged domains. A standard RMSD (sRMSD) alignment of two different conformations of the same protein can be skewed by the difference between the mobile regions. To overcome this problem, we have developed a novel method to overlay two protein conformations by their atomic coordinates using a Gaussian-weighted RMSD (wRMSD) fit. The algorithm is based on the Kabsch least-squares method and determines an optimal transformation between two molecules by calculating the minimal weighted deviation between the two coordinate sets.

 

Our second technique, a local wRMSD fit, uses subsets of the protein sequence for an initial, local sRMSD alignment and then performs a wRMSD fit of the entire protein, keeping the Gaussian scaling factor set to 2 Ų to maintain the local bias in the fit. The optimal solution is identified by the largest %wSUM. Using this second method, we were able to achieve multiple alignments based on different domains of the protein, and the solutions could be ranked by %wSUM.

Damm, K.L. and Carlson, H.A. Gaussian-Weighted RMSD Superposition of Proteins: A Structural Comparison for Flexible Proteins and Predicted Protein Structures. Biophys. J. 2006, 90, 4558-4573.

 

PyMOL Rendering Plug-in

Written by Dr. Michael Lerner, this plug-in allows you to capture molecular image using standard or ray-trace formats. It also allows you to adjust the size and resolution of the image. Put the python source files in "/DeLano Scientific/PyMOL/modules/pmg_tk/startup"

Listing Row

Friday, June 26, 2015
Friday, June 26, 2015