Computer-Aided Prediction of Pharmacokinetic (ADMET) Properties
2018; Elsevier BV; Linguagem: Inglês
10.1016/b978-0-12-814421-3.00021-x
AutoresBalakumar Chandrasekaran, Sara Nidal Abed, Omar Al-Attraqchi, Kaushik Kuche, Rakesh Kumar Tekade,
Tópico(s)Pharmacogenetics and Drug Metabolism
ResumoThe development of new drug candidates is really a very expensive process that consumes time and effort. Hence, there is an urgent need to develop new methods that are capable of predicting the important pharmacokinetic properties of drugs in a rapid and more accurate manner before being synthesized. Various computational models have emerged for the purpose of predicting ADMET (absorption, distribution, mechanism, excretion, and toxicity) parameters of drugs and drug-like compounds. This chapter focuses mainly on the characterization of the modern in silico techniques that predict the behavior of drugs during the early stages of drug discovery and development and the purposes, needs, and objectives of ADMET studies, which in turn facilitates the discovery of new drugs with more desired absorption, distribution, metabolism, and excretion profiles in addition to the least toxic effects. This chapter also provides an insight into the physicochemical parameters affecting the ADMET of drugs including the solubility, lipophilicity, permeability, as well as the hydrogen bonding. The in silico prediction of the active transport of drugs through various transporter types (P-gp, BCRP, nucleoside transporter, hPEPT1, hASBT, OCTs, OATPs, and BBB choline transporter) is also discussed. The recent in silico tools that are used in the modern ADMET software along with the future perspective and challenges are also covered.
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