Systematic Extraction of Analogue Series from Large Compound Collections Using a New Computational Compound-Core Relationship Method
Por:
Naveja J.J., Vogt, Martin, Stumpfe, Dagmar, Medina-Franco, Jose L., Bajorath, Juergen
Publicada:
1 ene 2019
Resumen:
Chemical optimization of organic compounds produces a series of
analogues. In addition to considering an analogue series (AS) or
multiple series on a case-by-case basis, which is often done in the
practice of chemistry, the extraction of analogues from compound
repositories is of high interest in organic and medicinal chemistry. In
organic chemistry, ASs are a source of alternative synthetic routes and
also aid in exploring relationships between compounds from different
sources including synthetic vs. naturally occurring molecules. In
medicinal chemistry, ASs are the major source of structure-activity
relationship information and of hits or leads for drug development. ASs
might be identified in different ways. For a given reference compound, a
substructure search can be carried out using its scaffold.
Alternatively, matched molecular pairs can be calculated to retrieve
analogues from a compound repository. However, if no query compounds are
used, the identification of ASs in databases is a difficult task.
Herein, we introduce a computational approach to systematically identify
ASs in collections of organic compounds. The approach involves compound
decomposition on the basis of well-established retrosynthetic rules,
organization of compound-core relationships, and identification of
analogues sharing the same core. The method was applied on a large scale
to extract ASs from the ChEMBL database, yielding more than 30 000
distinct series.
Filiaciones:
Naveja J.J.:
Department of Life Science Informatics, B-IT, LIMES Program Unit Chemical Biology and Medicinal Chemistry, Rheinische Friedrich-Wilhelms-Universität, Endenicher Allee 19c, Bonn, D-53115, Germany
PECEM, Faculty of Medicine, School of Chemistry, Universidad Nacional Autónoma de México, Mexico City, 04510, Mexico
Department of Pharmacy, School of Chemistry, Universidad Nacional Autónoma de México, Mexico City, 04510, Mexico
Vogt, Martin:
Department of Life Science Informatics, B-IT, LIMES Program Unit Chemical Biology and Medicinal Chemistry, Rheinische Friedrich-Wilhelms-Universität, Endenicher Allee 19c, Bonn, D-53115, Germany
Rheinische Friedrich Wilhelms Univ, Dept Life Sci Informat, B IT, LIMES Program Unit Chem Biol & Med Chem, Endenicher Allee 19c, D-53115 Bonn, Germany
Stumpfe, Dagmar:
Department of Life Science Informatics, B-IT, LIMES Program Unit Chemical Biology and Medicinal Chemistry, Rheinische Friedrich-Wilhelms-Universität, Endenicher Allee 19c, Bonn, D-53115, Germany
Rheinische Friedrich Wilhelms Univ, Dept Life Sci Informat, B IT, LIMES Program Unit Chem Biol & Med Chem, Endenicher Allee 19c, D-53115 Bonn, Germany
Medina-Franco, Jose L.:
PECEM, Faculty of Medicine, School of Chemistry, Universidad Nacional Autónoma de México, Mexico City, 04510, Mexico
Univ Nacl Autonoma Mexico, Sch Chem, Dept Pharm, Mexico City 04510, DF, Mexico
Bajorath, Juergen:
Department of Life Science Informatics, B-IT, LIMES Program Unit Chemical Biology and Medicinal Chemistry, Rheinische Friedrich-Wilhelms-Universität, Endenicher Allee 19c, Bonn, D-53115, Germany
Rheinische Friedrich Wilhelms Univ, Dept Life Sci Informat, B IT, LIMES Program Unit Chem Biol & Med Chem, Endenicher Allee 19c, D-53115 Bonn, Germany
Univ Nacl Autonoma Mexico, Fac Med, PECEM, Mexico City 04510, DF, Mexico
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