Fragmentation-tree density representation for crystallographic modelling of bound ligands.

ABSTRACT: The identification and modelling of ligands into macromolecular models is important for understanding molecule's function and for designing inhibitors to modulate its activities. We describe new algorithms for the automated building of ligands into electron density maps in crystal structure determination. Location of the ligand-binding site is achieved by matching numerical shape features describing the ligand to those of density clusters using a "fragmentation-tree" density representation. The ligand molecule is built using two distinct algorithms exploiting free atoms with inter-atomic connectivity and Metropolis-based optimisation of the conformational state of the ligand, producing an ensemble of structures from which the final model is derived. The method was validated on several thou

SUBMITTER: Langer GG 

PROVIDER: S-EPMC3747352 | biostudies-literature | 2012 Jun

REPOSITORIES: biostudies-literature