BRADSHAW: a system for automated molecular design

• DOI: 10.1007/s10822-019-00234-8
• Publication Date: 2019-10-21T10:52:29Z
• Authors: Darren V. S. Green; Stephen Pickett; Chris Luscombe; Stefan Senger; David Marcus; Jamel Meslamani; David Brett; Adam Powell; Jonathan Masson
• Keywords: 0303 health sciences; Cheminformatics; Quantitative Structure-Activity Relationship; Matrix Metalloproteinase Inhibitors; Article; Adenosine A2 Receptor Antagonists; Workflow; Machine Learning; Small Molecule Libraries; User-Computer Interface; 03 medical and health sciences; Deep Learning; Drug Design; Drug Discovery; Computer-Aided Design; Humans; Algorithms; Software

AbstractThis paper introduces BRADSHAW (BiologicalResponseAnalysis andDesignSystem using anHeterogenous,AutomatedWorkflow), 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.