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Large-scale prediction and testing of drug activity on side-effect targets.

Lounkine E, Keiser MJ, Whitebread S, Mikhailov D, Hamon J, Jenkins JL, Lavan P, Weber E, Doak AK, Côté S, Shoichet BK, Urban L - Nature (2012)

Bottom Line: Drugs can act on several protein targets, some of which can be unrelated by conventional molecular metrics, and hundreds of proteins have been implicated in side effects.Here we use a computational strategy to predict the activity of 656 marketed drugs on 73 unintended 'side-effect' targets.Among these new associations was the prediction that the abdominal pain side effect of the synthetic oestrogen chlorotrianisene was mediated through its newly discovered inhibition of the enzyme cyclooxygenase-1.

View Article: PubMed Central - PubMed

Affiliation: Novartis Institutes for Biomedical Research, Cambridge, Massachusetts 02139, USA.

ABSTRACT
Discovering the unintended 'off-targets' that predict adverse drug reactions is daunting by empirical methods alone. Drugs can act on several protein targets, some of which can be unrelated by conventional molecular metrics, and hundreds of proteins have been implicated in side effects. Here we use a computational strategy to predict the activity of 656 marketed drugs on 73 unintended 'side-effect' targets. Approximately half of the predictions were confirmed, either from proprietary databases unknown to the method or by new experimental assays. Affinities for these new off-targets ranged from 1 nM to 30 μM. To explore relevance, we developed an association metric to prioritize those new off-targets that explained side effects better than any known target of a given drug, creating a drug-target-adverse drug reaction network. Among these new associations was the prediction that the abdominal pain side effect of the synthetic oestrogen chlorotrianisene was mediated through its newly discovered inhibition of the enzyme cyclooxygenase-1. The clinical relevance of this inhibition was borne out in whole human blood platelet aggregation assays. This approach may have wide application to de-risking toxicological liabilities in drug discovery.

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Off-target networks(a–c) Off-target networks for three drugs. Known targets of the drugs are grey while newly predicted targets are blue; the adverse events associated with each are orange and red, respectively. Red adverse events are significantly (ef > 1, q-Value < 0.05) associated with the new off-targets. Targets related by sequence are connected by grey edges. (d) Chlorotrianisene inhibits platelet aggregation. Two independent experiments (red and blue) shown for chlorotrianisene and indomethacin. Vehicle: negative control; ASA: Acetylsalicylic acid (positive control). Asterisks indicate significant (*: paired student t-test p-Value < 0.05) and highly significant (**: p-Value < 0.01) differences to vehicle control with s.d.
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Figure 2: Off-target networks(a–c) Off-target networks for three drugs. Known targets of the drugs are grey while newly predicted targets are blue; the adverse events associated with each are orange and red, respectively. Red adverse events are significantly (ef > 1, q-Value < 0.05) associated with the new off-targets. Targets related by sequence are connected by grey edges. (d) Chlorotrianisene inhibits platelet aggregation. Two independent experiments (red and blue) shown for chlorotrianisene and indomethacin. Vehicle: negative control; ASA: Acetylsalicylic acid (positive control). Asterisks indicate significant (*: paired student t-test p-Value < 0.05) and highly significant (**: p-Value < 0.01) differences to vehicle control with s.d.

Mentions: Network graphs help visualize the new and known drug-target links, and the adverse events with which they are associated (Figure 2a–c). For example, the estrogen receptor (ESR1) modulator chlorotrianisene was found to inhibit PTGS1 (COX-1), indeed with an affinity substantially better than its affinity for ESR1. Drugs that modulate the two proteins can share two of chlorotrianisene’s adverse reactions, “erythema multiforme” and “oedema”, but “rash” and “abdominal pain upper” link only to drugs inhibiting COX-1, and both of these are associated with chlorotrianisene almost uniquely among the estrogen receptor modulators (Figure 2a, Supplementary TableS5). For prenylamine, a new G protein-coupled receptor (GPCR) cluster (HRH1, OPRM1, ADRB2) emerges that is unrelated to the drugs primary ion channel activity but uniquely link to its sedative and myocardial infarction ADRs (Figure 2a). For domperidone, its known activity at dopamine receptors is associated with a Parkinsonism-like phenotype (“hyperprolactinaemia” and “extrapyramidal disorder”), while “somnolence” only associates with the newly discovered opioid activity (Figure 2b).


Large-scale prediction and testing of drug activity on side-effect targets.

Lounkine E, Keiser MJ, Whitebread S, Mikhailov D, Hamon J, Jenkins JL, Lavan P, Weber E, Doak AK, Côté S, Shoichet BK, Urban L - Nature (2012)

Off-target networks(a–c) Off-target networks for three drugs. Known targets of the drugs are grey while newly predicted targets are blue; the adverse events associated with each are orange and red, respectively. Red adverse events are significantly (ef > 1, q-Value < 0.05) associated with the new off-targets. Targets related by sequence are connected by grey edges. (d) Chlorotrianisene inhibits platelet aggregation. Two independent experiments (red and blue) shown for chlorotrianisene and indomethacin. Vehicle: negative control; ASA: Acetylsalicylic acid (positive control). Asterisks indicate significant (*: paired student t-test p-Value < 0.05) and highly significant (**: p-Value < 0.01) differences to vehicle control with s.d.
© Copyright Policy
Related In: Results  -  Collection

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getmorefigures.php?uid=PMC3383642&req=5

Figure 2: Off-target networks(a–c) Off-target networks for three drugs. Known targets of the drugs are grey while newly predicted targets are blue; the adverse events associated with each are orange and red, respectively. Red adverse events are significantly (ef > 1, q-Value < 0.05) associated with the new off-targets. Targets related by sequence are connected by grey edges. (d) Chlorotrianisene inhibits platelet aggregation. Two independent experiments (red and blue) shown for chlorotrianisene and indomethacin. Vehicle: negative control; ASA: Acetylsalicylic acid (positive control). Asterisks indicate significant (*: paired student t-test p-Value < 0.05) and highly significant (**: p-Value < 0.01) differences to vehicle control with s.d.
Mentions: Network graphs help visualize the new and known drug-target links, and the adverse events with which they are associated (Figure 2a–c). For example, the estrogen receptor (ESR1) modulator chlorotrianisene was found to inhibit PTGS1 (COX-1), indeed with an affinity substantially better than its affinity for ESR1. Drugs that modulate the two proteins can share two of chlorotrianisene’s adverse reactions, “erythema multiforme” and “oedema”, but “rash” and “abdominal pain upper” link only to drugs inhibiting COX-1, and both of these are associated with chlorotrianisene almost uniquely among the estrogen receptor modulators (Figure 2a, Supplementary TableS5). For prenylamine, a new G protein-coupled receptor (GPCR) cluster (HRH1, OPRM1, ADRB2) emerges that is unrelated to the drugs primary ion channel activity but uniquely link to its sedative and myocardial infarction ADRs (Figure 2a). For domperidone, its known activity at dopamine receptors is associated with a Parkinsonism-like phenotype (“hyperprolactinaemia” and “extrapyramidal disorder”), while “somnolence” only associates with the newly discovered opioid activity (Figure 2b).

Bottom Line: Drugs can act on several protein targets, some of which can be unrelated by conventional molecular metrics, and hundreds of proteins have been implicated in side effects.Here we use a computational strategy to predict the activity of 656 marketed drugs on 73 unintended 'side-effect' targets.Among these new associations was the prediction that the abdominal pain side effect of the synthetic oestrogen chlorotrianisene was mediated through its newly discovered inhibition of the enzyme cyclooxygenase-1.

View Article: PubMed Central - PubMed

Affiliation: Novartis Institutes for Biomedical Research, Cambridge, Massachusetts 02139, USA.

ABSTRACT
Discovering the unintended 'off-targets' that predict adverse drug reactions is daunting by empirical methods alone. Drugs can act on several protein targets, some of which can be unrelated by conventional molecular metrics, and hundreds of proteins have been implicated in side effects. Here we use a computational strategy to predict the activity of 656 marketed drugs on 73 unintended 'side-effect' targets. Approximately half of the predictions were confirmed, either from proprietary databases unknown to the method or by new experimental assays. Affinities for these new off-targets ranged from 1 nM to 30 μM. To explore relevance, we developed an association metric to prioritize those new off-targets that explained side effects better than any known target of a given drug, creating a drug-target-adverse drug reaction network. Among these new associations was the prediction that the abdominal pain side effect of the synthetic oestrogen chlorotrianisene was mediated through its newly discovered inhibition of the enzyme cyclooxygenase-1. The clinical relevance of this inhibition was borne out in whole human blood platelet aggregation assays. This approach may have wide application to de-risking toxicological liabilities in drug discovery.

Show MeSH
Related in: MedlinePlus