Prediction of Severity of Drug-Drug Interactions Caused by Enzyme Inhibition and Activation
Drug-drug interactions (DDIs) severity assessment is a crucial problem because polypharmacy is increasingly common in modern medical practice. Many DDIs are caused by alterations of the plasma concentrations of one drug due to another drug inhibiting and/or inducing the metabolism or transporter-med...
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ftmdpi:oai:mdpi.com:/1420-3049/24/21/3955/ 2023-08-20T04:09:05+02:00 Prediction of Severity of Drug-Drug Interactions Caused by Enzyme Inhibition and Activation Alexander Dmitriev Dmitry Filimonov Alexey Lagunin Dmitry Karasev Pavel Pogodin Anastasiya Rudik Vladimir Poroikov agris 2019-10-31 application/pdf https://doi.org/10.3390/molecules24213955 EN eng Multidisciplinary Digital Publishing Institute Medicinal Chemistry https://dx.doi.org/10.3390/molecules24213955 https://creativecommons.org/licenses/by/4.0/ Molecules; Volume 24; Issue 21; Pages: 3955 drug interactions DDIs adverse drug reaction ADR Text 2019 ftmdpi https://doi.org/10.3390/molecules24213955 2023-07-31T22:45:03Z Drug-drug interactions (DDIs) severity assessment is a crucial problem because polypharmacy is increasingly common in modern medical practice. Many DDIs are caused by alterations of the plasma concentrations of one drug due to another drug inhibiting and/or inducing the metabolism or transporter-mediated disposition of the victim drug. Accurate assessment of clinically relevant DDIs for novel drug candidates represents one of the significant tasks of contemporary drug research and development and is important for practicing physicians. This work is a development of our previous investigations and aimed to create a model for the severity of DDIs prediction. PASS program and PoSMNA descriptors were implemented for prediction of all five classes of DDIs severity according to OpeRational ClassificAtion (ORCA) system: contraindicated (class 1), provisionally contraindicated (class 2), conditional (class 3), minimal risk (class 4), no interaction (class 5). Prediction can be carried out both for known drugs and for new, not yet synthesized substances using only their structural formulas. Created model provides an assessment of DDIs severity by prediction of different ORCA classes from the first most dangerous class to the fifth class when DDIs do not take place in the human organism. The average accuracy of DDIs class prediction is about 0.75. Text Orca MDPI Open Access Publishing Molecules 24 21 3955 |
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MDPI Open Access Publishing |
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English |
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drug interactions DDIs adverse drug reaction ADR |
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drug interactions DDIs adverse drug reaction ADR Alexander Dmitriev Dmitry Filimonov Alexey Lagunin Dmitry Karasev Pavel Pogodin Anastasiya Rudik Vladimir Poroikov Prediction of Severity of Drug-Drug Interactions Caused by Enzyme Inhibition and Activation |
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drug interactions DDIs adverse drug reaction ADR |
description |
Drug-drug interactions (DDIs) severity assessment is a crucial problem because polypharmacy is increasingly common in modern medical practice. Many DDIs are caused by alterations of the plasma concentrations of one drug due to another drug inhibiting and/or inducing the metabolism or transporter-mediated disposition of the victim drug. Accurate assessment of clinically relevant DDIs for novel drug candidates represents one of the significant tasks of contemporary drug research and development and is important for practicing physicians. This work is a development of our previous investigations and aimed to create a model for the severity of DDIs prediction. PASS program and PoSMNA descriptors were implemented for prediction of all five classes of DDIs severity according to OpeRational ClassificAtion (ORCA) system: contraindicated (class 1), provisionally contraindicated (class 2), conditional (class 3), minimal risk (class 4), no interaction (class 5). Prediction can be carried out both for known drugs and for new, not yet synthesized substances using only their structural formulas. Created model provides an assessment of DDIs severity by prediction of different ORCA classes from the first most dangerous class to the fifth class when DDIs do not take place in the human organism. The average accuracy of DDIs class prediction is about 0.75. |
format |
Text |
author |
Alexander Dmitriev Dmitry Filimonov Alexey Lagunin Dmitry Karasev Pavel Pogodin Anastasiya Rudik Vladimir Poroikov |
author_facet |
Alexander Dmitriev Dmitry Filimonov Alexey Lagunin Dmitry Karasev Pavel Pogodin Anastasiya Rudik Vladimir Poroikov |
author_sort |
Alexander Dmitriev |
title |
Prediction of Severity of Drug-Drug Interactions Caused by Enzyme Inhibition and Activation |
title_short |
Prediction of Severity of Drug-Drug Interactions Caused by Enzyme Inhibition and Activation |
title_full |
Prediction of Severity of Drug-Drug Interactions Caused by Enzyme Inhibition and Activation |
title_fullStr |
Prediction of Severity of Drug-Drug Interactions Caused by Enzyme Inhibition and Activation |
title_full_unstemmed |
Prediction of Severity of Drug-Drug Interactions Caused by Enzyme Inhibition and Activation |
title_sort |
prediction of severity of drug-drug interactions caused by enzyme inhibition and activation |
publisher |
Multidisciplinary Digital Publishing Institute |
publishDate |
2019 |
url |
https://doi.org/10.3390/molecules24213955 |
op_coverage |
agris |
genre |
Orca |
genre_facet |
Orca |
op_source |
Molecules; Volume 24; Issue 21; Pages: 3955 |
op_relation |
Medicinal Chemistry https://dx.doi.org/10.3390/molecules24213955 |
op_rights |
https://creativecommons.org/licenses/by/4.0/ |
op_doi |
https://doi.org/10.3390/molecules24213955 |
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Molecules |
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24 |
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21 |
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3955 |
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1774721781210284032 |