Automated identification of crystallographic ligands using sparse-density representations
A novel procedure for identifying ligands in macromolecular crystallographic electron-density maps is introduced. Density clusters in such maps can be rapidly attributed to one of 82 different ligands in an automated manner.
| Main Authors: | , |
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| Format: | Online |
| Language: | English |
| Published: |
International Union of Crystallography
2014
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| Online Access: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4089483/ |