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Recognizing and validating ligands with CheckMyBlob.
Brzezinski, Dariusz; Porebski, Przemyslaw J; Kowiel, Marcin; Macnar, Joanna M; Minor, Wladek.
Afiliação
  • Brzezinski D; Department of Molecular Physiology and Biological Physics, University of Virginia, Charlottesville, VA 22908, USA.
  • Porebski PJ; Institute of Computing Science, Poznan University of Technology, Poznan, 60-965, Poland.
  • Kowiel M; Center for Biocrystallographic Research, Institute of Bioorganic Chemistry, Polish Academy of Sciences, Poznan, 61-704, Poland.
  • Macnar JM; Department of Molecular Physiology and Biological Physics, University of Virginia, Charlottesville, VA 22908, USA.
  • Minor W; Center for Biocrystallographic Research, Institute of Bioorganic Chemistry, Polish Academy of Sciences, Poznan, 61-704, Poland.
Nucleic Acids Res ; 49(W1): W86-W92, 2021 07 02.
Article em En | MEDLINE | ID: mdl-33905501
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.
Assuntos

Texto completo: 1 Base de dados: MEDLINE Assunto principal: Software / Ligantes Tipo de estudo: Prognostic_studies Idioma: En Ano de publicação: 2021 Tipo de documento: Article

Texto completo: 1 Base de dados: MEDLINE Assunto principal: Software / Ligantes Tipo de estudo: Prognostic_studies Idioma: En Ano de publicação: 2021 Tipo de documento: Article