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ADMET Prediction of Dual PPARα/γ Agonists for Identification of Potential Anti-diabetic Agents

  • Neha VermaEmail author
  • Usha Chouhan
Conference paper
Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 748)

Abstract

Since last 15 years, ex vivo experimental tools to describe ADME–Tox profiles of molecules have been exercised in initial stages of the drug development process to enhance the success percentage of discovery index and to ameliorate better candidates into drug discovery. Implementation of in silico ADMET prediction has further improved discovery support, allowing virtual screening of chemical compounds and therefore, application of ADMET property prediction at each phase of the drug development process. Recently there have been advancements in the approaches used to determine the accurateness of the prediction as well as application domain of the absorption, metabolism, distribution, excretion, and toxicity models. Developments also seen in the methods used to anticipate the physiochemical properties of leads in the initial steps of drug development. Absorption, distribution, metabolism, and excretion, ADME parameters, were calculated to investigate pharmacokinetic properties of hit compounds for the screening of new and potent anti-diabetic agents. ADME studies on a set of ligand molecules were performed by DruLiTo software. This study would permit chemists and drug-metabolism researchers to focus on compounds having maximum likelihoods of meeting the essential ADME criteria, also would add to a fall in compound attrition at late-stage.

Keywords

ADMET Pharmacokinetic properties Anti-diabetic agents 

Notes

Acknowledgements

Author Neha Verma would like to acknowledge the UGC, Delhi for providing RGNFSC fellowship.

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Copyright information

© Springer Nature Singapore Pte Ltd. 2019

Authors and Affiliations

  1. 1.Department of Mathematics, Bioinformatics and Computer ApplicationsMANITBhopalIndia

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