Literature DB >> 28124835

A Pareto Algorithm for Efficient De Novo Design of Multi-functional Molecules.

Frits Daeyaert1,2, Micheal W Deem2.   

Abstract

We have introduced a Pareto sorting algorithm into Synopsis, a de novo design program that generates synthesizable molecules with desirable properties. We give a detailed description of the algorithm and illustrate its working in 2 different de novo design settings: the design of putative dual and selective FGFR and VEGFR inhibitors, and the successful design of organic structure determining agents (OSDAs) for the synthesis of zeolites. We show that the introduction of Pareto sorting not only enables the simultaneous optimization of multiple properties but also greatly improves the performance of the algorithm to generate molecules with hard-to-meet constraints. This in turn allows us to suggest approaches to address the problem of false positive hits in de novo structure based drug design by introducing structural and physicochemical constraints in the designed molecules, and by forcing essential interactions between these molecules and their target receptor.
© 2017 Wiley-VCH Verlag GmbH & Co. KGaA, Weinheim.

Entities:  

Keywords:  Drug Design; FGFR; OSDAs; Pareto; Receptors; VEGFR; Zeolites; multi-target drugs

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Year:  2016        PMID: 28124835     DOI: 10.1002/minf.201600044

Source DB:  PubMed          Journal:  Mol Inform        ISSN: 1868-1743            Impact factor:   3.353


  3 in total

1.  Machine-learning approach to the design of OSDAs for zeolite beta.

Authors:  Frits Daeyaert; Fengdan Ye; Michael W Deem
Journal:  Proc Natl Acad Sci U S A       Date:  2019-02-07       Impact factor: 11.205

2.  Design of organic structure directing agents to guide the synthesis of zeolites for the separation of ethylene-ethane mixtures.

Authors:  Frits Daeyaert; Michael W Deem
Journal:  RSC Adv       Date:  2020-05-27       Impact factor: 4.036

3.  Design of organic structure directing agents to control the synthesis of zeolites for carbon capture and storage.

Authors:  Frits Daeyaert; Michael W Deem
Journal:  RSC Adv       Date:  2019-12-17       Impact factor: 4.036

  3 in total

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