Python Macromolecular Library
The Python Macromolecular Library (mmLib/pymmlib) is a software toolkit and library of routines for the analysis and manipulation of macromolecular structural models, implemented in the Python programming language.[1] It is accessed via a layered, object-oriented application programming interface, and provides a range of useful software components for parsing mmCIF, and PDB files, a library of atomic elements and monomers, an object-oriented data structure describing biological macromolecules, and an OpenGL molecular viewer.[2] The mmLib data model is designed to provide easy access to the various levels of detail needed to implement high-level application programs for macromolecular crystallography, NMR, modeling, and visualization. This includes specialized classes for proteins, DNA, amino acids, and nucleic acids. Also included is a extensive monomer library, element library, and specialized classes for performing unit cell calculations combined with a full space group library.
I was the lead developer and maintainer of the Python Macromolecular Library from 2006 to 2010. I contributed 20,590 lines of code to pymmlib (27.8% in Python and 25.5% in Fortran). I added hundreds of new features, including Skittles,[3] which was added to the CCP4 codebase.
Version 1.2.0 was released (with tarball) in June 2011.
Contents
Keywords
macromolecular crystallography; computer programs; Python; mmCIF; PDB; TLSView; TLS models; pymmlib
See also
References
- ↑ Painter J, Merritt EA (2004). "mmLib Python toolkit for manipulating annotated structural models of biological macromolecules". J Appl Cryst 37(1):174-178. DOI:10.1107/S0021889803025639
- ↑ Painter J, Merritt EA (2005). "mmLib A molecular viewer for the analysis of TLS rigid-body motion in macromolecules". Acta Cryst D61(4):465-471. DOI:10.1107/S0907444905001897
- ↑ Zucker F, Champ PC, Merritt EA (2010). "Validation of crystallographic models containing TLS or other descriptions of anisotropy". Acta Cryst. D66, 889-900. DOI:10.1107/S0907444910020421