Evidence map›Paper›PMID 24643004›Full record

ArticlePloS one2014

A new stochastic model for subgenomic hepatitis C virus replication considers drug resistant mutants.

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 and 4 more

Open access · goldAbstract read
In one paragraph

Article in PloS one, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed
1.0field-weighted citation impact, top 24% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

4 citing papers in PubMed, 14 citations in OpenAlex.

  1. Impact of Negative Feedbacks on De Novo Pyrimidines Biosynthesis inInternational journal of molecular sciences · 2023
    Article
  2. Article
  3. HCV Kinetic Models and Their Implications in Drug Development.CPT: pharmacometrics & systems pharmacology · 2015
    Review
  4. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

14 authors at 5 institutions in 2 countries.

Nikita V IvanisenkoDepartment of Systems Biology, Institute of Cytology and Genetics SB RAS, Novosibirsk, Russia.
Elena L MishchenkoDepartment of Systems Biology, Institute of Cytology and Genetics SB RAS, Novosibirsk, Russia.
Ilya R AkberdinDepartment of Systems Biology, Institute of Cytology and Genetics SB RAS, Novosibirsk, Russia.
Pavel S DemenkovDepartment of Systems Biology, Institute of Cytology and Genetics SB RAS, Novosibirsk, Russia.
Vitaly A LikhoshvaiDepartment of Systems Biology, Institute of Cytology and Genetics SB RAS, Novosibirsk, Russia.
Konstantin N KozlovDepartment of Computational Biology, St. Petersburg State Polytechnical University, St. Petersburg, Russia.
Dmitry I TodorovDepartment of Computational Biology, St. Petersburg State Polytechnical University, St. Petersburg, Russia; Chebyshev Laboratory, St. Petersburg State University, St. Petersburg, Russia.
Vitaly V GurskyDepartment of Computational Biology, St. Petersburg State Polytechnical University, St. Petersburg, Russia; Theoretical Department, Ioffe Physical-Technical Institute of the Russian Academy of Sciences, St.Petersburg, Russia.
Maria G SamsonovaDepartment of Computational Biology, St. Petersburg State Polytechnical University, St. Petersburg, Russia.
Alexander M SamsonovDepartment of Computational Biology, St. Petersburg State Polytechnical University, St. Petersburg, Russia; Theoretical Department, Ioffe Physical-Technical Institute of the Russian Academy of Sciences, St.Petersburg, Russia.
Diana ClausznitzerInstitute for Medical Informatics and Biometry, Technische Universität Dresden, Dresden, Germany.
Lars KaderaliInstitute for Medical Informatics and Biometry, Technische Universität Dresden, Dresden, Germany.
Nikolay A KolchanovDepartment of Systems Biology, Institute of Cytology and Genetics SB RAS, Novosibirsk, Russia.
Vladimir A IvanisenkoDepartment of Systems Biology, Institute of Cytology and Genetics SB RAS, Novosibirsk, Russia; PB-soft Llc, Novosibirsk, Russia.
Peter the Great St. Petersburg Polytechnic University · RUSiberian Branch of the Russian Academy of Sciences · RUInstitute of Cytology and Genetics · RUTechnische Universität Dresden · DEIoffe Institute · RU

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

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.

Indexed as

Models, StatisticalRepliconAntiviral AgentsCarbamatesDEAD-box RNA HelicasesDrug Resistance, ViralHepacivirusMacrocyclic CompoundsNucleoside-TriphosphataseOligopeptidesPolymorphism, Single NucleotideProlineProtease InhibitorsQuinolinesRNA, ViralSerine EndopeptidasesAntiviral AgentsBILN 2061CarbamatesDEAD-box RNA HelicasesMacrocyclic CompoundsN-(3-amino-1-(cyclobutylmethyl)-2,3-dioxopropyl)-3-(2-((((1,1-dimethylethyl)amino)carbonyl)amino)-3,3-dimethyl-1-oxobutyl)-6,6-dimethyl-3-azabicyclo(3.1.0)hexan-2-carboxamideNS3 protein, hepatitis C virusNucleoside-TriphosphataseOligopeptidesProlineProtease InhibitorsQuinolinesRNA, ViralSerine EndopeptidasestelaprevirThiazolesViral Nonstructural ProteinsViral Proteases

Identifiers

PMID24643004
PMCPMC3958367
OpenAlexW1988169220

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.