Computational approaches in assessments of mixture toxicity

Supratik Kar, Jerzy Leszczynski

Research output: Contribution to journalReview articlepeer-review

6 Scopus citations

Abstract

There are various paths of interactions of combination of two or more chemicals with biological systems. The response of chemicals in a mixture can be predicted employing the perceptions of concentration or dose addition for chemicals with identical mode of action (MOA) and/or common target of effect. While response addition can be considered for chemicals acting on diverse biological targets. Both hypotheses are feasible only when there is no interaction between chemicals. On the contrary, if interaction occurs between chemicals in a mixture results in synergism or potentiation if induction of activating enzyme/inhibition of detoxifying enzyme happens. In contrast, competition of individual chemicals at biological target site show antagonism. Experimental models are time-consuming and costly. Diversity of mixtures and the necessity to test multiple organisms covering different ecosystems to avail the toxicity data make the experimentalist job more challenging. There comes the importance of computational approaches, proven and efficient alternatives to fill the toxicity data gaps, prioritization of chemicals, identification of the toxicity mechanism, and risk assessment and management.

Original languageEnglish
Pages (from-to)31-35
Number of pages5
JournalCurrent Opinion in Toxicology
Volume29
DOIs
StatePublished - Mar 2022

Keywords

  • Computational
  • In silico
  • Mixture
  • QSAR
  • Risk assessment
  • Toxicity

Fingerprint

Dive into the research topics of 'Computational approaches in assessments of mixture toxicity'. Together they form a unique fingerprint.

Cite this