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. 2020 Jul;34(7):747-765.
doi: 10.1007/s10822-019-00234-8. Epub 2019 Oct 21.

BRADSHAW: a system for automated molecular design

Darren V S Green  1 , Stephen Pickett  2 , Chris Luscombe  2 , Stefan Senger  2 , David Marcus  2 , Jamel Meslamani  3 , David Brett  4 , Adam Powell  4 , Jonathan Masson  4
Affiliations

BRADSHAW: a system for automated molecular design

Darren V S Green et al. J Comput Aided Mol Des. 2020 Jul.

Erratum in

Abstract

This paper introduces BRADSHAW (Biological Response Analysis and Design System using an Heterogenous, Automated Workflow), a system for automated molecular design which integrates methods for chemical structure generation, experimental design, active learning and cheminformatics tools. The simple user interface is designed to facilitate access to large scale automated design whilst minimising software development required to introduce new algorithms, a critical requirement in what is a very fast moving field. The system embodies a philosophy of automation, best practice, experimental design and the use of both traditional cheminformatics and modern machine learning algorithms.

Keywords: Active learning; Automated design; Cheminformatics; Experimental design.

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Figures

Fig. 1
Fig. 1
Overview of the BRADSHAW system
Fig. 2
Fig. 2
The BRADSHAW User Interface. Available Tasks are on the left, and are coloured if they can be added to the current workflow
Fig. 3
Fig. 3
Example of a sparse array design for a two component library
Scheme 1
Scheme 1
Molecule generation for Adenosine A2A antagonists
Scheme 2
Scheme 2
The core template for a 50 × 50 array targeted against MMP12
Fig. 4
Fig. 4
MMP12 activity distribution across the MMP12 data set (yellow), the sparse design (red) and the Fit and Predict selections (blue)
See this image and copyright information in PMC

References

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