Literature DB >> 25894297

The purchasable chemical space: a detailed picture.

Xavier Lucas1, Björn A Grüning1, Stefan Bleher1, Stefan Günther1.   

Abstract

The screening of a reduced yet diverse and synthesizable region of the chemical space is a critical step in drug discovery. The ZINC database is nowadays routinely used to freely access and screen millions of commercially available compounds. We collected ∼125 million compounds from chemical catalogs and the ZINC database, yielding more than 68 million unique molecules, including a large portion of described natural products (NPs) and drugs. The data set was filtered using advanced medicinal chemistry rules to remove potentially toxic, promiscuous, metabolically labile, or reactive compounds. We studied the physicochemical properties of this compilation and identified millions of NP-like, fragment-like, inhibitors of protein-protein interactions (i-PPIs) like, and drug-like compounds. The related focused libraries were subjected to a detailed scaffold diversity analysis and compared to reference NPs and marketed drugs. This study revealed thousands of diverse chemotypes with distinct representations of building block combinations among the data sets. An analysis of the stereogenic and shape complexity properties of the libraries also showed that they present well-defined levels of complexity, following the tendency: i-PPIs-like < drug-like < fragment-like < NP-like. As the collected compounds have huge interest in drug discovery and particularly virtual screening and library design, we offer a freely available collection comprising over 37 million molecules under: http://pbox.pharmaceutical-bioinformatics.org , as well as the filtering rules used to build the focused libraries described herein.

Mesh:

Substances:

Year:  2015        PMID: 25894297     DOI: 10.1021/acs.jcim.5b00116

Source DB:  PubMed          Journal:  J Chem Inf Model        ISSN: 1549-9596            Impact factor:   4.956


  7 in total

1.  Chemoinformatic expedition of the chemical space of fungal products.

Authors:  Mariana González-Medina; Fernando D Prieto-Martínez; J Jesús Naveja; Oscar Méndez-Lucio; Tamam El-Elimat; Cedric J Pearce; Nicholas H Oberlies; Mario Figueroa; José L Medina-Franco
Journal:  Future Med Chem       Date:  2016-08-03       Impact factor: 3.808

2.  In silico prediction of chemical mechanism of action via an improved network-based inference method.

Authors:  Zengrui Wu; Weiqiang Lu; Dang Wu; Anqi Luo; Hanping Bian; Jie Li; Weihua Li; Guixia Liu; Jin Huang; Feixiong Cheng; Yun Tang
Journal:  Br J Pharmacol       Date:  2016-11-01       Impact factor: 8.739

3.  Predicting novel substrates for enzymes with minimal experimental effort with active learning.

Authors:  Dante A Pertusi; Matthew E Moura; James G Jeffryes; Siddhant Prabhu; Bradley Walters Biggs; Keith E J Tyo
Journal:  Metab Eng       Date:  2017-10-10       Impact factor: 9.783

Review 4.  Rethinking drug design in the artificial intelligence era.

Authors:  Petra Schneider; W Patrick Walters; Alleyn T Plowright; Norman Sieroka; Jennifer Listgarten; Robert A Goodnow; Jasmin Fisher; Johanna M Jansen; José S Duca; Thomas S Rush; Matthias Zentgraf; John Edward Hill; Elizabeth Krutoholow; Matthias Kohler; Jeff Blaney; Kimito Funatsu; Chris Luebkemann; Gisbert Schneider
Journal:  Nat Rev Drug Discov       Date:  2019-12-04       Impact factor: 84.694

5.  Chemical Space Expansion of Bromodomain Ligands Guided by in Silico Virtual Couplings (AutoCouple).

Authors:  Laurent Batiste; Andrea Unzue; Aymeric Dolbois; Fabrice Hassler; Xuan Wang; Nicholas Deerain; Jian Zhu; Dimitrios Spiliotopoulos; Cristina Nevado; Amedeo Caflisch
Journal:  ACS Cent Sci       Date:  2018-02-07       Impact factor: 14.553

Review 6.  Accelerators for Classical Molecular Dynamics Simulations of Biomolecules.

Authors:  Derek Jones; Jonathan E Allen; Yue Yang; William F Drew Bennett; Maya Gokhale; Niema Moshiri; Tajana S Rosing
Journal:  J Chem Theory Comput       Date:  2022-06-16       Impact factor: 6.578

7.  StreptomeDB 2.0--an extended resource of natural products produced by streptomycetes.

Authors:  Dennis Klementz; Kersten Döring; Xavier Lucas; Kiran K Telukunta; Anika Erxleben; Denise Deubel; Astrid Erber; Irene Santillana; Oliver S Thomas; Andreas Bechthold; Stefan Günther
Journal:  Nucleic Acids Res       Date:  2015-11-28       Impact factor: 16.971

  7 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.