Artificial intelligence to predict inhibitors of drug-metabolizing enzymes and transporters for safer drug design.

Journal: Expert opinion on drug discovery
PMID: 40241626

Abstract

INTRODUCTION: Drug-metabolizing enzymes (DMEs) and transporters (DTs) play integral roles in drug metabolism and drug-drug interactions (DDIs) which directly impact drug efficacy and safety. It is well-established that inhibition of DMEs and DTs often leads to adverse drug reactions (ADRs) and therapeutic failure. As such, early prediction of such inhibitors is vital in drug development. In this context, the limitations of the traditional in vitro assays and QSAR models methods have been addressed by harnessing artificial intelligence (AI) techniques.

Authors

  • Arnab Bhattacharjee
    Drug Discovery and Development Laboratory (DDD Lab), Department of Pharmaceutical Technology, Jadavpur University, Kolkata, India.
  • Ankur Kumar
    Drug Discovery and Development Laboratory (DDD Lab), Department of Pharmaceutical Technology, Jadavpur University, Kolkata, India.
  • Probir Kumar Ojha
    Drug Discovery and Development Laboratory (DDD Lab), Department of Pharmaceutical Technology, Jadavpur University, Kolkata, India.
  • Supratik Kar
    Chemometrics and Molecular Modeling Laboratory, Department of Chemistry and Physics, Kean University, Union, NJ, USA.

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