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Project Description

Mollib is a unified command-line program and Python library for the validation, quality analysis and manipulation of molecular structures with an emphasis on biophysical analysis. Mollib is built on a plugin framework to easily add new tools to manipulate and analyze structures and data, which can then be combined and cross-validated.

Mollib includes tools for:

  • The processing and protonation of molecules.
  • The analysis of hydrogen bonds and hydrogen bond quality compared to the highest-resolution PDB structures. Hydrogen bonds are classified based on their acceptor-donor residues and Ramachandran angles
  • The measurement of geometries within molecules as well as the reporting and classification of Ramachandran angles.
  • The statistical analysis and comparison of structures to high-resolution crystal structures.
  • The analysis of partial alignment data with residual dipolar coupling (RDC) and residual anisotropic chemical shift (RACS, a.k.a RCSA) data.

Release History

This version
History Node

1.0.9

History Node

1.0.8

History Node

1.0.7

History Node

1.0.6

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1.0.5

History Node

1.0.2

History Node

1.0.1

History Node

1.0

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mollib-1.0.9-cp27-cp27m-macosx_10_6_intel.macosx_10_9_intel.macosx_10_9_x86_64.macosx_10_10_intel.macosx_10_10_x86_64.whl
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mollib-1.0.9-cp27-cp27m-manylinux1_i686.whl
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mollib-1.0.9-cp27-cp27m-manylinux1_x86_64.whl
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mollib-1.0.9-cp34-cp34m-macosx_10_6_intel.macosx_10_9_intel.macosx_10_9_x86_64.macosx_10_10_intel.macosx_10_10_x86_64.whl
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mollib-1.0.9-cp34-cp34m-manylinux1_i686.whl
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mollib-1.0.9-cp34-cp34m-manylinux1_x86_64.whl
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mollib-1.0.9-cp35-cp35m-macosx_10_6_intel.macosx_10_9_intel.macosx_10_9_x86_64.macosx_10_10_intel.macosx_10_10_x86_64.whl
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mollib-1.0.9-cp35-cp35m-manylinux1_i686.whl
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mollib-1.0.9-cp35-cp35m-manylinux1_x86_64.whl
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mollib-1.0.9-cp36-cp36m-macosx_10_6_intel.macosx_10_9_intel.macosx_10_9_x86_64.macosx_10_10_intel.macosx_10_10_x86_64.whl
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mollib-1.0.9-cp36-cp36m-manylinux1_i686.whl
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mollib-1.0.9-cp36-cp36m-manylinux1_x86_64.whl
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Wheel cp36 Sep 28, 2017

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