Literature DB >> 28712298

The Fragment Network: A Chemistry Recommendation Engine Built Using a Graph Database.

Richard J Hall1, Christopher W Murray1, Marcel L Verdonk1.   

Abstract

The hit validation stage of a fragment-based drug discovery campaign involves probing the SAR around one or more fragment hits. This often requires a search for similar compounds in a corporate collection or from commercial suppliers. The Fragment Network is a graph database that allows a user to efficiently search chemical space around a compound of interest. The result set is chemically intuitive, naturally grouped by substitution pattern and meaningfully sorted according to the number of observations of each transformation in medicinal chemistry databases. This paper describes the algorithms used to construct and search the Fragment Network and provides examples of how it may be used in a drug discovery context.

Entities:  

Mesh:

Substances:

Year:  2017        PMID: 28712298     DOI: 10.1021/acs.jmedchem.7b00809

Source DB:  PubMed          Journal:  J Med Chem        ISSN: 0022-2623            Impact factor:   7.446


  7 in total

1.  Knowledge discovery through chemical space networks: the case of organic electronics.

Authors:  Christian Kunkel; Christoph Schober; Harald Oberhofer; Karsten Reuter
Journal:  J Mol Model       Date:  2019-03-07       Impact factor: 1.810

2.  SAMPL7 protein-ligand challenge: A community-wide evaluation of computational methods against fragment screening and pose-prediction.

Authors:  Harold Grosjean; Mehtap Işık; Anthony Aimon; David Mobley; John Chodera; Frank von Delft; Philip C Biggin
Journal:  J Comput Aided Mol Des       Date:  2022-04-15       Impact factor: 4.179

3.  Galaxy workflows for fragment-based virtual screening: a case study on the SARS-CoV-2 main protease.

Authors:  Simon Bray; Tim Dudgeon; Rachael Skyner; Rolf Backofen; Björn Grüning; Frank von Delft
Journal:  J Cheminform       Date:  2022-04-12       Impact factor: 5.514

4.  FGDB: a comprehensive graph database of ligand fragments from the Protein Data Bank.

Authors:  Daniele Toti; Gabriele Macari; Enrico Barbierato; Fabio Polticelli
Journal:  Database (Oxford)       Date:  2022-06-27       Impact factor: 4.462

Review 5.  In silico Strategies to Support Fragment-to-Lead Optimization in Drug Discovery.

Authors:  Lauro Ribeiro de Souza Neto; José Teófilo Moreira-Filho; Bruno Junior Neves; Rocío Lucía Beatriz Riveros Maidana; Ana Carolina Ramos Guimarães; Nicholas Furnham; Carolina Horta Andrade; Floriano Paes Silva
Journal:  Front Chem       Date:  2020-02-18       Impact factor: 5.221

6.  Frag4Lead: growing crystallographic fragment hits by catalog using fragment-guided template docking.

Authors:  Alexander Metz; Jan Wollenhaupt; Steffen Glöckner; Niki Messini; Simon Huber; Tatjana Barthel; Ahmed Merabet; Hans Dieter Gerber; Andreas Heine; Gerhard Klebe; Manfred S Weiss
Journal:  Acta Crystallogr D Struct Biol       Date:  2021-08-23       Impact factor: 7.652

Review 7.  Fragment-based drug discovery: opportunities for organic synthesis.

Authors:  Jeffrey D St Denis; Richard J Hall; Christopher W Murray; Tom D Heightman; David C Rees
Journal:  RSC Med Chem       Date:  2020-12-24
  7 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.