Literature DB >> 16563000

Flux (1): a virtual synthesis scheme for fragment-based de novo design.

Uli Fechner1, Gisbert Schneider.   

Abstract

It is demonstrated that the fragmentation of druglike molecules by applying simplistic pseudo-retrosynthesis results in a stock of chemically meaningful building blocks for de novo molecule generation. A stochastic search algorithm in conjunction with ligand-based similarity scoring (Flux: fragment-based ligand builder reaxions) facilitated the generation of new molecules using a single known reference compound as a template. This molecule assembly method is applicable in the absence of receptor-structure information. In a case study, we used imantinib (Gleevec) and a Factor Xa inhibitor as the reference structures. The algorithm succeeded in redesigning the templates from scratch and suggested several alternative molecular structures. The resulting designed molecules were chemically reasonable and contained essential substructure motifs. A comparison of molecular descriptors suggests that holographic descriptors might be advantageous over binary fingerprints for ligand-based de novo design.

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Year:  2006        PMID: 16563000     DOI: 10.1021/ci0503560

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


  14 in total

Review 1.  Structure-based discovery of antibacterial drugs.

Authors:  Katie J Simmons; Ian Chopra; Colin W G Fishwick
Journal:  Nat Rev Microbiol       Date:  2010-07       Impact factor: 60.633

2.  The concept of template-based de novo design from drug-derived molecular fragments and its application to TAR RNA.

Authors:  Andreas Schüller; Marcel Suhartono; Uli Fechner; Yusuf Tanrikulu; Sven Breitung; Ute Scheffer; Michael W Göbel; Gisbert Schneider
Journal:  J Comput Aided Mol Des       Date:  2007-12-07       Impact factor: 3.686

3.  De novo design by pharmacophore-based searches in fragment spaces.

Authors:  Tobias Lippert; Tanja Schulz-Gasch; Olivier Roche; Wolfgang Guba; Matthias Rarey
Journal:  J Comput Aided Mol Des       Date:  2011-09-16       Impact factor: 3.686

Review 4.  Machine Learning and Computational Chemistry for the Endocannabinoid System.

Authors:  Kenneth Atz; Wolfgang Guba; Uwe Grether; Gisbert Schneider
Journal:  Methods Mol Biol       Date:  2023

5.  Integrated In Silico Fragment-Based Drug Design: Case Study with Allosteric Modulators on Metabotropic Glutamate Receptor 5.

Authors:  Yuemin Bian; Zhiwei Feng; Peng Yang; Xiang-Qun Xie
Journal:  AAPS J       Date:  2017-05-30       Impact factor: 4.009

Review 6.  Computational Fragment-Based Drug Design: Current Trends, Strategies, and Applications.

Authors:  Yuemin Bian; Xiang-Qun Sean Xie
Journal:  AAPS J       Date:  2018-04-09       Impact factor: 4.009

7.  DOGS: reaction-driven de novo design of bioactive compounds.

Authors:  Markus Hartenfeller; Heiko Zettl; Miriam Walter; Matthias Rupp; Felix Reisen; Ewgenij Proschak; Sascha Weggen; Holger Stark; Gisbert Schneider
Journal:  PLoS Comput Biol       Date:  2012-02-16       Impact factor: 4.475

8.  RENATE: A Pseudo-retrosynthetic Tool for Synthetically Accessible de novo Design.

Authors:  Gian Marco Ghiandoni; Michael J Bodkin; Beining Chen; Dimitar Hristozov; James E A Wallace; James Webster; Valerie J Gillet
Journal:  Mol Inform       Date:  2021-11-08       Impact factor: 4.050

9.  Bayesian molecular design with a chemical language model.

Authors:  Hisaki Ikebata; Kenta Hongo; Tetsu Isomura; Ryo Maezono; Ryo Yoshida
Journal:  J Comput Aided Mol Des       Date:  2017-03-09       Impact factor: 3.686

10.  AutoGrow4: an open-source genetic algorithm for de novo drug design and lead optimization.

Authors:  Jacob O Spiegel; Jacob D Durrant
Journal:  J Cheminform       Date:  2020-04-17       Impact factor: 5.514

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