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Relationships Between Pharmacovigilance, Molecular, Structural, and Pathway Data: Revealing Mechanisms for Immune-Mediated Drug-Induced Liver Injury.

Ho SS, McLachlan AJ, Chen TF, Hibbs DE, Fois RA - CPT Pharmacometrics Syst Pharmacol (2015)

Bottom Line: We present a novel approach that combines the methods of pharmacoepidemiology with in silico molecular modeling to identify specific features in toxic ligands that are associated with clinical features of IMDILI.Specifically, from pharmacovigilance data multivariate logistic regression identified 18 drugs associated with IMDILI (P < 0.00015).Subsequently, this information was combined with information from immune-pathway reviews and genetic-association studies and complemented with ligand-protein docking simulations to support a hypothesis implicating two putative targets within separate, possibly interacting, immune-system pathways: the major histocompatibility complex within the adaptive immune system and Toll-like receptors (TLRs), in particular TLR-7, which represent pattern recognition receptors of the innate immune system.

View Article: PubMed Central - PubMed

Affiliation: Faculty of Pharmacy (A15), University of Sydney Sydney, NSW, Australia.

ABSTRACT
Immune-mediated drug-induced liver injury (IMDILI) can be devastating, irreversible, and fatal in the absence of successful transplantation surgery. We present a novel approach that combines the methods of pharmacoepidemiology with in silico molecular modeling to identify specific features in toxic ligands that are associated with clinical features of IMDILI. Specifically, from pharmacovigilance data multivariate logistic regression identified 18 drugs associated with IMDILI (P < 0.00015). Eleven of these drugs, along with their known and proposed metabolites, constituted a training set used to develop a four-point pharmacophore model (sensitivity 75%; specificity 85%). Subsequently, this information was combined with information from immune-pathway reviews and genetic-association studies and complemented with ligand-protein docking simulations to support a hypothesis implicating two putative targets within separate, possibly interacting, immune-system pathways: the major histocompatibility complex within the adaptive immune system and Toll-like receptors (TLRs), in particular TLR-7, which represent pattern recognition receptors of the innate immune system.

No MeSH data available.


Related in: MedlinePlus

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fig01: Workflow diagram outlining the approach taken in this study.

Mentions: We present an approach to expose relationships between IMDILI and the 3D structural features of toxic drug molecules and their metabolites. We hypothesize that drugs (or their metabolites) that produce similar patterns of toxicity interact with targets within common toxicological pathways and that activation of the underlying mechanisms depends on structural features that are shared among toxic molecules. We chose to focus on immune-mediated DILI since these reactions have defined clinical characteristics that allow us to identify cases from population adverse drug event data. Briefly, drugs with the potential to cause IMDILI were identified from population adverse drug reaction (ADR) data. We then identified similarities in molecular structures between toxic drugs using in silico pharmacophore modeling. Subsequently, we test the hypotheses that these similarities are important in molecular interactions between toxic drugs and the immune system proteins HLA and TLR-7 (Figure1).


Relationships Between Pharmacovigilance, Molecular, Structural, and Pathway Data: Revealing Mechanisms for Immune-Mediated Drug-Induced Liver Injury.

Ho SS, McLachlan AJ, Chen TF, Hibbs DE, Fois RA - CPT Pharmacometrics Syst Pharmacol (2015)

Workflow diagram outlining the approach taken in this study.
© Copyright Policy - open-access
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC4544056&req=5

fig01: Workflow diagram outlining the approach taken in this study.
Mentions: We present an approach to expose relationships between IMDILI and the 3D structural features of toxic drug molecules and their metabolites. We hypothesize that drugs (or their metabolites) that produce similar patterns of toxicity interact with targets within common toxicological pathways and that activation of the underlying mechanisms depends on structural features that are shared among toxic molecules. We chose to focus on immune-mediated DILI since these reactions have defined clinical characteristics that allow us to identify cases from population adverse drug event data. Briefly, drugs with the potential to cause IMDILI were identified from population adverse drug reaction (ADR) data. We then identified similarities in molecular structures between toxic drugs using in silico pharmacophore modeling. Subsequently, we test the hypotheses that these similarities are important in molecular interactions between toxic drugs and the immune system proteins HLA and TLR-7 (Figure1).

Bottom Line: We present a novel approach that combines the methods of pharmacoepidemiology with in silico molecular modeling to identify specific features in toxic ligands that are associated with clinical features of IMDILI.Specifically, from pharmacovigilance data multivariate logistic regression identified 18 drugs associated with IMDILI (P < 0.00015).Subsequently, this information was combined with information from immune-pathway reviews and genetic-association studies and complemented with ligand-protein docking simulations to support a hypothesis implicating two putative targets within separate, possibly interacting, immune-system pathways: the major histocompatibility complex within the adaptive immune system and Toll-like receptors (TLRs), in particular TLR-7, which represent pattern recognition receptors of the innate immune system.

View Article: PubMed Central - PubMed

Affiliation: Faculty of Pharmacy (A15), University of Sydney Sydney, NSW, Australia.

ABSTRACT
Immune-mediated drug-induced liver injury (IMDILI) can be devastating, irreversible, and fatal in the absence of successful transplantation surgery. We present a novel approach that combines the methods of pharmacoepidemiology with in silico molecular modeling to identify specific features in toxic ligands that are associated with clinical features of IMDILI. Specifically, from pharmacovigilance data multivariate logistic regression identified 18 drugs associated with IMDILI (P < 0.00015). Eleven of these drugs, along with their known and proposed metabolites, constituted a training set used to develop a four-point pharmacophore model (sensitivity 75%; specificity 85%). Subsequently, this information was combined with information from immune-pathway reviews and genetic-association studies and complemented with ligand-protein docking simulations to support a hypothesis implicating two putative targets within separate, possibly interacting, immune-system pathways: the major histocompatibility complex within the adaptive immune system and Toll-like receptors (TLRs), in particular TLR-7, which represent pattern recognition receptors of the innate immune system.

No MeSH data available.


Related in: MedlinePlus