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A General ANN-Based Multitasking Model for the Discovery of Potent and Safer Antibacterial Agents

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Artificial Neural Networks

Part of the book series: Methods in Molecular Biology ((MIMB,volume 1260))

Abstract

Bacteria have been one of the world’s most dangerous and deadliest pathogens for mankind, nowadays giving rise to significant public health concerns. Given the prevalence of these microbial pathogens and their increasing resistance to existing antibiotics, there is a pressing need for new antibacterial drugs. However, development of a successful drug is a complex, costly, and time-consuming process. Quantitative Structure-Activity Relationships (QSAR)-based approaches are valuable tools for shortening the time of lead compound identification but also for focusing and limiting time-costly synthetic activities and in vitro/vivo evaluations. QSAR-based approaches, supported by powerful statistical techniques such as artificial neural networks (ANNs), have evolved to the point of integrating dissimilar types of chemical and biological data. This chapter reports an overview of the current research and potential applications of QSAR modeling tools toward the rational design of more efficient antibacterial agents. Particular emphasis is given to the setup of multitasking models along with ANNs aimed at jointly predicting different antibacterial activities and safety profiles of drugs/chemicals under diverse experimental conditions.

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Acknowledgments

A. Speck-Planche acknowledges the Portuguese Fundação para a Ciência e a Tecnologia (FCT) and the European Social Fund for financial support (grant SFRH/BD/77690/2011). This work has been further supported by FCT through grant N° Pest-C/EQB/LA0006/2011.

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Authors and Affiliations

  1. Department of Chemistry and Biochemistry, Faculty of Sciences, University of Porto, 4169-007, Porto, Portugal

    A. Speck-Planche & M. N. D. S. Cordeiro

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  1. A. Speck-Planche
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  2. M. N. D. S. Cordeiro
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Correspondence to M. N. D. S. Cordeiro .

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Editors and Affiliations

  1. Chemistry Department, Oxford University, UK, and University of Victoria, Victoria, British Columbia, Canada

    Hugh Cartwright

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Speck-Planche, A., Cordeiro, M.N.D.S. (2015). A General ANN-Based Multitasking Model for the Discovery of Potent and Safer Antibacterial Agents. In: Cartwright, H. (eds) Artificial Neural Networks. Methods in Molecular Biology, vol 1260. Springer, New York, NY. https://doi.org/10.1007/978-1-4939-2239-0_4

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  • DOI: https://doi.org/10.1007/978-1-4939-2239-0_4

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