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Applications of Metaheuristics in Process Engineering pp 325–342Cite as

Genetic Algorithms in Drug Design: A Not-So-Old Story in a Newer Bottle

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Abstract

The application of computational tools can alleviate the challenges (viz. time consumption and cost intensiveness) in drug design. Metaheuristics, a collection of such diverse computational and mathematical tools, whose first application was dated back to the early 1970s, caters to several expectations of rational drug designing. Among the population-based metaheuristics, genetic algorithms most closely mimic natural selection. As a consequence, they are rapidly garnering popularity over other members of evolutionary computation as the most preferred simulation processes for drug trials and designing. This chapter discusses various applications of genetic algorithms in drug design, from designing a combinatorial library, QSAR/QSPR study, and designing lead candidacy in drug discovery to solutions for genetic disease. Genetic algorithms find their place in all.

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Authors and Affiliations

  1. Department of Chemistry, School of Natural Sciences, Shiv Nadar University, Tehsil Dadri, District Gautam Buddha Nagar, UP, India

    Subhabrata Sen

  2. Department of Mathematics, School of Natural Sciences, Shiv Nadar University, Tehsil Dadri, District Gautam Buddha Nagar, UP, 201314, India

    Sudeepto Bhattacharya

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  1. Subhabrata Sen
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Correspondence to Subhabrata Sen .

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Editors and Affiliations

  1. Evol. Comput. & Image Proc. Group, Center for Develop. of Adv. Computing, Pune, India

    Jayaraman Valadi

  2. Lab. LiSSi (EA 3956), Université Paris-Est Créteil, Créteil, France

    Patrick Siarry

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Sen, S., Bhattacharya, S. (2014). Genetic Algorithms in Drug Design: A Not-So-Old Story in a Newer Bottle. In: Valadi, J., Siarry, P. (eds) Applications of Metaheuristics in Process Engineering. Springer, Cham. https://doi.org/10.1007/978-3-319-06508-3_14

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  • DOI: https://doi.org/10.1007/978-3-319-06508-3_14

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