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In Silico Tools and Software to Predict ADMET of New Drug Candidates

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In Silico Methods for Predicting Drug Toxicity

Part of the book series: Methods in Molecular Biology ((MIMB,volume 2425))

Abstract

Implication of computational techniques and in silico tools promote not only reduction of animal experimentations but also save time and money followed by rational designing of drugs as well as controlled synthesis of those “Hits” which show drug-likeness and possess suitable absorption, distribution, metabolism, excretion, and toxicity (ADMET) profile. With globalization of diseases, resistance of drugs over the time and modification of viruses and microorganisms, computational tools, and artificial intelligence are the future of drug design and one of the important areas where the principles of sustainability and green chemistry (GC) perfectly fit. Most of the new drug entities fail in the clinical trials over the issue of drug-associated human toxicity. Although ecotoxicity related to new drugs is rarely considered, but this is the high time when ecotoxicity prediction should get equal importance along with human-associated drug toxicity. Thus, the present book chapter discusses the available in silico tools and software for the fast and preliminary prediction of a series of human-associated toxicity and ecotoxicity of new drug entities to screen possibly safer drugs before going into preclinical and clinical trials.

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Acknowledgments

SK and JL want to acknowledge the National Science Foundation (Grant: NSF/CREST HRD-1547754) to support the research.

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Correspondence to Kunal Roy .

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Kar, S., Roy, K., Leszczynski, J. (2022). In Silico Tools and Software to Predict ADMET of New Drug Candidates. In: Benfenati, E. (eds) In Silico Methods for Predicting Drug Toxicity. Methods in Molecular Biology, vol 2425. Humana, New York, NY. https://doi.org/10.1007/978-1-0716-1960-5_4

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  • DOI: https://doi.org/10.1007/978-1-0716-1960-5_4

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  • Publisher Name: Humana, New York, NY

  • Print ISBN: 978-1-0716-1959-9

  • Online ISBN: 978-1-0716-1960-5

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