Recognizing and validating ligands with CheckMyBlob. Issue Volume 49:Issue W1(2021) (27th April 2021)

• Record Type: Journal Article
• Authors: Brzezinski, Dariusz; Porebski, Przemyslaw J; Kowiel, Marcin; Macnar, Joanna M; Minor, Wladek
• Is Part Of: Nucleic acids research. Volume 49:Issue W1(2021)
• Page Start: W86
• Page End: W92
• Publication Date: 2021-04-27
• Subjects: Nucleic acids -- Periodicals; Molecular biology -- Periodicals; 572.805
• DOI: 10.1093/nar/gkab296
• Languages: English
• ISSNs: 0305-1048

Abstract

Abstract: Structure-guided drug design depends on the correct identification of ligands in crystal structures of protein complexes. However, the interpretation of the electron density maps is challenging and often burdened with confirmation bias. Ligand identification can be aided by automatic methods such as CheckMyBlob, a machine learning algorithm that learns to generalize ligand descriptions from sets of moieties deposited in the Protein Data Bank. Here, we present the CheckMyBlob web server, a platform that can identify ligands in unmodeled fragments of electron density maps or validate ligands in existing models. The server processes PDB/mmCIF and MTZ files and returns a ranking of 10 most likely ligands for each detected electron density blob along with interactive 3D visualizations. Additionally, for each prediction/validation, a plugin script is generated that enables users to conduct a detailed analysis of the server results in Coot. The CheckMyBlob web server is available at https://checkmyblob.bioreproducibility.org . Graphical Abstract: