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Advances in QSAR Modeling pp 339–384Cite as

QSAR/QSPR Modeling in the Design of Drug Candidates with Balanced Pharmacodynamic and Pharmacokinetic Properties

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Part of the book series: Challenges and Advances in Computational Chemistry and Physics ((COCH,volume 24))

Abstract

Drug discovery and development is a slow complicated multi-objective and expensive enterprise. Drug candidates are a compromise output of competing pharmacodynamics and pharmacokinetic processes. To facilitate this task and avoid failures in clinical phases, computational techniques and in silico modeling using the endpoints offered by high technology, are extremely valuable. In this chapter, some historical aspects and a background overview for constructing Quantitative Structure-Activity Relationships (QSAR) and Quantitative Structure-Property Relationships (QSPR) are provided. The different goals for the establishment of QSAR/QSPR models are defined. Representative examples and success stories of in silico modeling along the different drug discovery processes are presented. Examples include models for optimizing efficient binding to receptor, using both ligand- and structure-based approaches, for in vitro permeability predictions, predictions for human intestinal absorption and blood brain barrier penetration, as well as for plasma protein binding and drug metabolism. The value of global and local models as well as their interpretability and the criteria for their evaluation and proper use are discussed throughout this chapter.

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Authors and Affiliations

  1. Faculty of Pharmacy, Department of Pharmaceutical Chemistry, National and Kapodistrian University of Athens, Panepistimiopolis, 157 71, Athens, Zografou, Greece

    George Lambrinidis & Anna Tsantili-Kakoulidou

  2. Laboratory of Inorganic and Analytical Chemistry, School of Chemical Engineering, National Technical University of Athens, Athens, Greece

    Fotios Tsopelas

  3. Department of Food Science and Nutrition, School of Environment, University of the Aegean, Limnos, Greece

    Costas Giaginis

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  1. George Lambrinidis
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  2. Fotios Tsopelas
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  3. Costas Giaginis
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  4. Anna Tsantili-Kakoulidou
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Correspondence to Anna Tsantili-Kakoulidou .

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  1. Department of Pharmaceutical Technology, Jadavpur University, Kolkata, India

    Kunal Roy

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Lambrinidis, G., Tsopelas, F., Giaginis, C., Tsantili-Kakoulidou, A. (2017). QSAR/QSPR Modeling in the Design of Drug Candidates with Balanced Pharmacodynamic and Pharmacokinetic Properties. In: Roy, K. (eds) Advances in QSAR Modeling. Challenges and Advances in Computational Chemistry and Physics, vol 24. Springer, Cham. https://doi.org/10.1007/978-3-319-56850-8_9

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