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Estimation of the protein–ligand interaction energy for model building and validation
Author(s) -
Beshnova Daria A.,
Pereira Joana,
Lamzin Victor S.
Publication year - 2017
Publication title -
acta crystallographica section d
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 7.374
H-Index - 138
ISSN - 2059-7983
DOI - 10.1107/s2059798317003400
Subject(s) - ligand (biochemistry) , identification (biology) , biological system , protein ligand , computer science , protein data bank , macromolecule , algorithm , computational biology , protein structure , chemistry , data mining , biology , biochemistry , botany , receptor
Macromolecular X‐ray crystallography is one of the main experimental techniques to visualize protein–ligand interactions. The high complexity of the ligand universe, however, has delayed the development of efficient methods for the automated identification, fitting and validation of ligands in their electron‐density clusters. The identification and fitting are primarily based on the density itself and do not take into account the protein environment, which is a step that is only taken during the validation of the proposed binding mode. Here, a new approach, based on the estimation of the major energetic terms of protein–ligand interaction, is introduced for the automated identification of crystallographic ligands in the indicated binding site with ARP / wARP . The applicability of the method to the validation of protein–ligand models from the Protein Data Bank is demonstrated by the detection of models that are `questionable' and the pinpointing of unfavourable interatomic contacts.