Abstract
Drug discovery and development is a costly and time-consuming endeavor (Calcoen et al. Nat Rev Drug Discov 14(3):161–162, 2015; The truly staggering cost of inventing new drugs. Forbes. http://www.forbes.com/sites/matthewherper/2012/02/10/the-truly-staggering-cost-of-inventing-new-drugs/, 2012; Scannell et al. Nat Rev Drug Discov 11(3):191–200, 2012). Over the last two decades, computational tools and in silico models to predict ADMET (Adsorption, Distribution, Metabolism, Excretion, and Toxicity) profiles of molecules have been incorporated into the drug discovery process mainly in an effort to avoid late-stage failures due to poor pharmacokinetics and toxicity. It is now widely recognized that ADMET issues should be addressed as early as possible in drug discovery. Here, we describe in detail how ADMET models can be developed and applied using a commercially available package, ADMET Predictor™ 7.2 (ADMET Predictor v7.2. Simulations Plus, Inc., Lancaster, CA, USA).
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References
Calcoen D, Elias L, Yu X (2015) What does it take to produce a breakthrough drug? Nat Rev Drug Discov 14(3):161–162
The truly staggering cost of inventing new drugs (2012) Forbes. http://www.forbes.com/sites/matthewherper/2012/02/10/the-truly-staggering-cost-of-inventing-new-drugs/
Scannell JW, Blanckley A, Boldon H, Warrington B (2012) Diagnosing the decline in pharmaceutical R&D efficiency. Nat Rev Drug Discov 11(3):191–200
ADMET Predictor v7.2, Simulations Plus, Inc.: Lancaster, CA, USA
Directory of computer-aided Drug Design tools. (2014) http://www.click2drug.org/directory_ADMET.html
Dalby A, Nourse JG, Hounshell WD, Gushurst AKI, Grier DL, Leland BA, Laufer J (1991) Description of Several Chemical Structure File Formats Used by Computer Programs Developed at Molecular Design Limited. J Chem Inf Comput Sci 32(3):245–260
Weininger D (1988) SMILES, a chemical language and information system. 1. Introduction to methodology and encoding rules. J Chem Inf Comp Sci 28:31–36
Weininger D, Weininger A, Weininger JL (1989) SMILES. 2. Algorithm for generation of unique SMILES notation. J Chem Inf Comp Sci 29:97–101
SMILES (2007) Daylight Chemical Information Systems. Inc, www.daylight.com/smiles/index.html
MedChem Designer v3.0, Simulations Plus, Inc.: Lancaster, CA, USA
ChemDraw v15.0, PerkinElmer: Waltham, MA, USA
Accelrys Draw v4.1, Biovia: San Diego, CA, USA
Biovia Insight v1.0, Biovia: San Diego, CA, USA
Pipeline Pilot v9.0, Biovia: San Diego, CA, USA
Michaelis L, Menten M (1913) Die Kinetik der Invertinwirkung. Biochem Z 49:333–339
GastroPlus v9.0, Simulations Plus, Inc.: Lancaster, CA, USA
Kohonen T (1982) Self-Organized Formation of Topologically Correct Feature Maps. Biol Cybern 43:59–69
World Drug Index v2007/04, Thomson Scientific: London, UK
Yoshii K, Kobayashi K, Tsumuji M, Tani M, Shimada N, Chiba K (2000) Identification of human cytochrome P450 isoforms involved in the 7-hydroxylation of chlorpromazine by human liver microsomes. Life Sci 67:175–184
Wójcikowski J, Pichard-Garcia L, Maurel P, Daniel WA (2003) Contribution of human cytochrome P-450 isoforms to the metabolism of the simplest phenothiazine neuroleptic promazine. Br J Pharmacol 138(8):1465–1474
Wójcikowski J, Pichard-Garcia L, Maurel P, Daniel WA (2004) The metabolism of the piperazine-type phenothiazine neuroleptic perazine by the human cytochrome P-450 isoenzymes. Eur Neuropsychopharmacol 14(3):199–208
Wojcikowski J, Boksa J, Daniel WA (2010) Main contribution of the cytochrome P450 isoenzyme 1A2 (CYP1A2) to N-demethylation and 5-sulfoxidation of the phenothiazine neuroleptic chlorpromazine in human liver—A comparison with other phenothiazines. Biochem Pharmacol 80:1252–1259
Cashman JR, Yang Z, Yang L, Wrighton SA (1993) Stereo- and regioselective N- and S-oxidation of tertiary amines and sulfides in the presence of adult human liver microsomes. Drug Metab Dispos 21(3):492–501
Morel E, Lloyd KG, Dahl SG (1987) Anti-apomorphine effects of phenothiazine drug metabolites. Psychopharmacology (Berl) 92(1):68–72
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Ghosh, J., Lawless, M.S., Waldman, M., Gombar, V., Fraczkiewicz, R. (2016). Modeling ADMET. In: Benfenati, E. (eds) In Silico Methods for Predicting Drug Toxicity. Methods in Molecular Biology, vol 1425. Humana Press, New York, NY. https://doi.org/10.1007/978-1-4939-3609-0_4
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DOI: https://doi.org/10.1007/978-1-4939-3609-0_4
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