A new stochastic model for subgenomic hepatitis C virus replication considers drug resistant mutants.
As an RNA virus, hepatitis C virus (HCV) is able to rapidly acquire drug resistance, and for this reason the design of effective anti-HCV drugs is a real challenge. The HCV subgenomic replicon-containing cells are widely used for experimental studies of the HCV genome replication mechanisms, for dru...
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2014
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oai:doaj.org-article:cb38672ba80c44689a4dc650e1639ee72021-11-18T08:27:32ZA new stochastic model for subgenomic hepatitis C virus replication considers drug resistant mutants.1932-620310.1371/journal.pone.0091502https://doaj.org/article/cb38672ba80c44689a4dc650e1639ee72014-01-01T00:00:00Zhttps://www.ncbi.nlm.nih.gov/pmc/articles/pmid/24643004/pdf/?tool=EBIhttps://doaj.org/toc/1932-6203As an RNA virus, hepatitis C virus (HCV) is able to rapidly acquire drug resistance, and for this reason the design of effective anti-HCV drugs is a real challenge. The HCV subgenomic replicon-containing cells are widely used for experimental studies of the HCV genome replication mechanisms, for drug testing in vitro and in studies of HCV drug resistance. The NS3/4A protease is essential for virus replication and, therefore, it is one of the most attractive targets for developing specific antiviral agents against HCV. We have developed a stochastic model of subgenomic HCV replicon replication, in which the emergence and selection of drug resistant mutant viral RNAs in replicon cells is taken into account. Incorporation into the model of key NS3 protease mutations leading to resistance to BILN-2061 (A156T, D168V, R155Q), VX-950 (A156S, A156T, T54A) and SCH 503034 (A156T, A156S, T54A) inhibitors allows us to describe the long term dynamics of the viral RNA suppression for various inhibitor concentrations. We theoretically showed that the observable difference between the viral RNA kinetics for different inhibitor concentrations can be explained by differences in the replication rate and inhibitor sensitivity of the mutant RNAs. The pre-existing mutants of the NS3 protease contribute more significantly to appearance of new resistant mutants during treatment with inhibitors than wild-type replicon. The model can be used to interpret the results of anti-HCV drug testing on replicon systems, as well as to estimate the efficacy of potential drugs and predict optimal schemes of their usage.Nikita V IvanisenkoElena L MishchenkoIlya R AkberdinPavel S DemenkovVitaly A LikhoshvaiKonstantin N KozlovDmitry I TodorovVitaly V GurskyMaria G SamsonovaAlexander M SamsonovDiana ClausznitzerLars KaderaliNikolay A KolchanovVladimir A IvanisenkoPublic Library of Science (PLoS)articleMedicineRScienceQENPLoS ONE, Vol 9, Iss 3, p e91502 (2014) |
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Medicine R Science Q Nikita V Ivanisenko Elena L Mishchenko Ilya R Akberdin Pavel S Demenkov Vitaly A Likhoshvai Konstantin N Kozlov Dmitry I Todorov Vitaly V Gursky Maria G Samsonova Alexander M Samsonov Diana Clausznitzer Lars Kaderali Nikolay A Kolchanov Vladimir A Ivanisenko A new stochastic model for subgenomic hepatitis C virus replication considers drug resistant mutants. |
| description |
As an RNA virus, hepatitis C virus (HCV) is able to rapidly acquire drug resistance, and for this reason the design of effective anti-HCV drugs is a real challenge. The HCV subgenomic replicon-containing cells are widely used for experimental studies of the HCV genome replication mechanisms, for drug testing in vitro and in studies of HCV drug resistance. The NS3/4A protease is essential for virus replication and, therefore, it is one of the most attractive targets for developing specific antiviral agents against HCV. We have developed a stochastic model of subgenomic HCV replicon replication, in which the emergence and selection of drug resistant mutant viral RNAs in replicon cells is taken into account. Incorporation into the model of key NS3 protease mutations leading to resistance to BILN-2061 (A156T, D168V, R155Q), VX-950 (A156S, A156T, T54A) and SCH 503034 (A156T, A156S, T54A) inhibitors allows us to describe the long term dynamics of the viral RNA suppression for various inhibitor concentrations. We theoretically showed that the observable difference between the viral RNA kinetics for different inhibitor concentrations can be explained by differences in the replication rate and inhibitor sensitivity of the mutant RNAs. The pre-existing mutants of the NS3 protease contribute more significantly to appearance of new resistant mutants during treatment with inhibitors than wild-type replicon. The model can be used to interpret the results of anti-HCV drug testing on replicon systems, as well as to estimate the efficacy of potential drugs and predict optimal schemes of their usage. |
| format |
article |
| author |
Nikita V Ivanisenko Elena L Mishchenko Ilya R Akberdin Pavel S Demenkov Vitaly A Likhoshvai Konstantin N Kozlov Dmitry I Todorov Vitaly V Gursky Maria G Samsonova Alexander M Samsonov Diana Clausznitzer Lars Kaderali Nikolay A Kolchanov Vladimir A Ivanisenko |
| author_facet |
Nikita V Ivanisenko Elena L Mishchenko Ilya R Akberdin Pavel S Demenkov Vitaly A Likhoshvai Konstantin N Kozlov Dmitry I Todorov Vitaly V Gursky Maria G Samsonova Alexander M Samsonov Diana Clausznitzer Lars Kaderali Nikolay A Kolchanov Vladimir A Ivanisenko |
| author_sort |
Nikita V Ivanisenko |
| title |
A new stochastic model for subgenomic hepatitis C virus replication considers drug resistant mutants. |
| title_short |
A new stochastic model for subgenomic hepatitis C virus replication considers drug resistant mutants. |
| title_full |
A new stochastic model for subgenomic hepatitis C virus replication considers drug resistant mutants. |
| title_fullStr |
A new stochastic model for subgenomic hepatitis C virus replication considers drug resistant mutants. |
| title_full_unstemmed |
A new stochastic model for subgenomic hepatitis C virus replication considers drug resistant mutants. |
| title_sort |
new stochastic model for subgenomic hepatitis c virus replication considers drug resistant mutants. |
| publisher |
Public Library of Science (PLoS) |
| publishDate |
2014 |
| url |
https://doaj.org/article/cb38672ba80c44689a4dc650e1639ee7 |
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