Tools for creating machine-learning datasets from macromolecular structure
Project description
Macromolecule Census is a tool for identifying high-quality, non-redundant subsets of the biological assemblies in the protein data bank (PDB). A particular emphasis is to accommodate all kinds of macromolecules; not just proteins. Briefly, this process involves the following steps:
Rank each structure by metrics including clash score, resolution, $R_{free}$, Q-score, NMR restraints.
Rank each assembly by biological relevance, subchain cover, and size.
Cluster protein, DNA, and RNA molecules by sequence similarity.
Cluster small molecules and branched polysaccharides by identity.
The primary use-case for this software is the creation of datasets for machine learning. This typically entails iterating through each assembly in ranked order, adding unique training examples as they appear.
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