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Artificial Chemical Neural Network for Drug Discovery Applications

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Artificial Life and Evolutionary Computation (WIVACE 2021)

Part of the book series: Communications in Computer and Information Science ((CCIS,volume 1722))

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Abstract

The drug design aims to generate chemical species that meet specific criteria, in-cluding efficacy against a pharmacological target, good safety profile, appropriate chemical and biological properties, sufficient novelty to ensure intellectual proper-ty rights for commercial success, etc. Using new algorithms to design and evalu-ate molecules in silicon de novo drug design is increasingly seen as an effective means of reducing the size of the chemical space to something more manageable for identifying chemogenomic research tool compounds and for use as starting points for hit-to-lead optimization.

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Author information

Authors and Affiliations

  1. Department of Pharmacy, University of Salerno, Via Giovanni Paolo II, 132, 84084, Fisciano, SA, Italy

    Stefano Piotto, Lucia Sessa, Jacopo Santoro & Luigi Di Biasi

  2. Bionam Research Center for Biomaterials, University of Salerno, Via Giovanni Paolo II, 132, 84084, Fisciano, SA, Italy

    Stefano Piotto & Lucia Sessa

  3. Department of Computer Sciences, University of Salerno, Via Giovanni Paolo II, 132, 84084, Fisciano, SA, Italy

    Luigi Di Biasi

Authors
  1. Stefano Piotto
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  2. Lucia Sessa
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  3. Jacopo Santoro
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  4. Luigi Di Biasi
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Corresponding author

Correspondence to Stefano Piotto .

Editor information

Editors and Affiliations

  1. Zurich University of Applied Sciences, Winterthur, Switzerland

    Johannes Josef Schneider

  2. School of Engineering, Cardiff University, Cardiff, UK

    Mathias Sebastian Weyland

  3. Zurich University of Applied Sciences, Winterthur, Switzerland

    Dandolo Flumini

  4. Zurich University of Applied Sciences, Winterthur, Switzerland

    Rudolf Marcel Füchslin

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Piotto, S., Sessa, L., Santoro, J., Di Biasi, L. (2022). Artificial Chemical Neural Network for Drug Discovery Applications. In: Schneider, J.J., Weyland, M.S., Flumini, D., Füchslin, R.M. (eds) Artificial Life and Evolutionary Computation. WIVACE 2021. Communications in Computer and Information Science, vol 1722. Springer, Cham. https://doi.org/10.1007/978-3-031-23929-8_21

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  • DOI: https://doi.org/10.1007/978-3-031-23929-8_21

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-031-23928-1

  • Online ISBN: 978-3-031-23929-8

  • eBook Packages: Computer ScienceComputer Science (R0)

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