Revilla2003 - Controlling HIV infection using recombinant viruses

  public model
Model Identifier
BIOMD0000000707
Short description

This a model from the article:
Fighting a virus with a virus: a dynamic model for HIV-1 therapy.
Revilla T, Garcia-Ramos G. Math Biosci 2003 Oct;185(2):191-203 12941536 ,
Abstract:
A mathematical model examined a potential therapy for controlling viral infections using genetically modified viruses. The control of the infection is an indirect effect of the selective elimination by an engineered virus of infected cells that are the source of the pathogens. Therefore, this engineered virus could greatly compensate for a dysfunctional immune system compromised by AIDS. In vitro studies using engineered viruses have been shown to decrease the HIV-1 load about 1000-fold. However, the efficacy of this potential treatment for reducing the viral load in AIDS patients is unknown. The present model studied the interactions among the HIV-1 virus, its main host cell (activated CD4+ T cells), and a therapeutic engineered virus in an in vivo context; and it examined the conditions for controlling the pathogen. This model predicted a significant drop in the HIV-1 load, but the treatment does not eradicate HIV. A basic estimation using a currently engineered virus indicated an HIV-1 load reduction of 92% and a recovery of host cells to 17% of their normal level. Greater success (98% HIV reduction, 44% host cells recovery) is expected as more competent engineered viruses are designed. These results suggest that therapy using viruses could be an alternative to extend the survival of AIDS patients.

This model was taken from the CellML repository and automatically converted to SBML.
The original model was: Revilla T, Garcia-Ramos G. (2003) - version=1.0
The original CellML model was created by:
Catherine Lloyd
c.lloyd@auckland.ac.nz
The University of Auckland

This model originates from BioModels Database: A Database of Annotated Published Models (http://www.ebi.ac.uk/biomodels/). It is copyright (c) 2005-2011 The BioModels.net Team.
To the extent possible under law, all copyright and related or neighbouring rights to this encoded model have been dedicated to the public domain worldwide. Please refer to CC0 Public Domain Dedication for more information.

In summary, you are entitled to use this encoded model in absolutely any manner you deem suitable, verbatim, or with modification, alone or embedded it in a larger context, redistribute it, commercially or not, in a restricted way or not..

To cite BioModels Database, please use: Li C, Donizelli M, Rodriguez N, Dharuri H, Endler L, Chelliah V, Li L, He E, Henry A, Stefan MI, Snoep JL, Hucka M, Le Novère N, Laibe C (2010) BioModels Database: An enhanced, curated and annotated resource for published quantitative kinetic models. BMC Syst Biol., 4:92.

Format
SBML (L2V4)
Related Publication
  • Fighting a virus with a virus: a dynamic model for HIV-1 therapy.
  • Revilla T, García-Ramos G
  • Mathematical biosciences , 10/ 2003 , Volume 185 , pages: 191-203 , PubMed ID: 12941536
  • Instituto de Zoología Tropical, Universidad Central de Venezuela, Apdo. Postal 47058, Caracas 1041-A, Venezuela.
  • A mathematical model examined a potential therapy for controlling viral infections using genetically modified viruses. The control of the infection is an indirect effect of the selective elimination by an engineered virus of infected cells that are the source of the pathogens. Therefore, this engineered virus could greatly compensate for a dysfunctional immune system compromised by AIDS. In vitro studies using engineered viruses have been shown to decrease the HIV-1 load about 1000-fold. However, the efficacy of this potential treatment for reducing the viral load in AIDS patients is unknown. The present model studied the interactions among the HIV-1 virus, its main host cell (activated CD4+ T cells), and a therapeutic engineered virus in an in vivo context; and it examined the conditions for controlling the pathogen. This model predicted a significant drop in the HIV-1 load, but the treatment does not eradicate HIV. A basic estimation using a currently engineered virus indicated an HIV-1 load reduction of 92% and a recovery of host cells to 17% of their normal level. Greater success (98% HIV reduction, 44% host cells recovery) is expected as more competent engineered viruses are designed. These results suggest that therapy using viruses could be an alternative to extend the survival of AIDS patients.
Contributors
Submitter of the first revision: Camille Laibe
Submitter of this revision: Rahuman Sheriff
Modellers: Camille Laibe, Rahuman Sheriff

Metadata information

is (2 statements)
BioModels Database BIOMD0000000707
BioModels Database MODEL1006230047

isDescribedBy (1 statement)
PubMed 12941536

hasTaxon (2 statements)
hasProperty (3 statements)
Mathematical Modelling Ontology Ordinary differential equation model
Experimental Factor Ontology HIV infection
Experimental Factor Ontology treatment

occursIn (1 statement)
Brenda Tissue Ontology helper T-lymphocyte


Curation status
Curated


Tags

Connected external resources

SBGN view in Newt Editor

Name Description Size Actions

Model files

MODEL1006230047.xml SBML L2V4 representation of Revilla2003 - Controlling HIV infection using recombinant viruses 45.62 KB Preview | Download

Additional files

MODEL1006230047-biopax2.owl Auto-generated BioPAX (Level 2) 1.04 KB Preview | Download
MODEL1006230047-biopax3.owl Auto-generated BioPAX (Level 3) 1.98 KB Preview | Download
MODEL1006230047.m Auto-generated Octave file 2.93 KB Preview | Download
MODEL1006230047.pdf Auto-generated PDF file 136.13 KB Preview | Download
MODEL1006230047.png Auto-generated Reaction graph (PNG) 5.04 KB Preview | Download
MODEL1006230047.sci Auto-generated Scilab file 245.00 Bytes Preview | Download
MODEL1006230047.svg Auto-generated Reaction graph (SVG) 851.00 Bytes Preview | Download
MODEL1006230047.vcml Auto-generated VCML file 900.00 Bytes Preview | Download
MODEL1006230047.xpp Auto-generated XPP file 1.73 KB Preview | Download
MODEL1006230047_curated_annotated.cps COPASI file to reproduce Figure 2b of the reference publication 66.89 KB Preview | Download
MODEL1006230047_urn.xml Auto-generated SBML file with URNs 13.14 KB Preview | Download

  • Model originally submitted by : Camille Laibe
  • Submitted: Jun 23, 2010 10:12:12 AM
  • Last Modified: Aug 30, 2018 4:40:10 PM
Revisions
  • Version: 5 public model Download this version
    • Submitted on: Aug 30, 2018 4:40:10 PM
    • Submitted by: Rahuman Sheriff
    • With comment: Automatically added model identifier BIOMD0000000707
  • Version: 2 public model Download this version
    • Submitted on: Jun 25, 2010 2:13:26 PM
    • Submitted by: Camille Laibe
    • With comment: Current version of Revilla2003_HIV1therapy
  • Version: 1 public model Download this version
    • Submitted on: Jun 23, 2010 10:12:12 AM
    • Submitted by: Camille Laibe
    • With comment: Original import of Revilla2003_HIV1therapy

(*) You might be seeing discontinuous revisions as only public revisions are displayed here. Any private revisions unpublished model revision of this model will only be shown to the submitter and their collaborators.

Legends
: Variable used inside SBML models


Species
Species Initial Concentration/Amount
Single Infected Th Cells

helper T-lymphocyte ; infected cell
6.0 mol
Recombinant Virus

Genetically Modified Organism ; Viruses
1.0 mol
Double Infected Th Cells

infected cell ; helper T-lymphocyte
0.0 mol
Normal Th cells

helper T-lymphocyte
3.0 mol
Pathogen Virus

Human immunodeficiency virus 1
149.0 mol
Reactions
Reactions Rate Parameters
Normal_Th_cells => Single_Infected_Th_Cells; Pathogen_Virus Plasma*beta*Normal_Th_cells*Pathogen_Virus beta = 0.004
=> Recombinant_Virus; Double_Infected_Th_Cells Plasma*c*Double_Infected_Th_Cells c = 2000.0
Recombinant_Virus => Plasma*q*Recombinant_Virus q = 2.0
Single_Infected_Th_Cells => Double_Infected_Th_Cells; Recombinant_Virus Plasma*alpha*Recombinant_Virus*Single_Infected_Th_Cells alpha = 0.004
Normal_Th_cells => Plasma*d*Normal_Th_cells d = 0.01
Pathogen_Virus => Plasma*u*Pathogen_Virus u = 2.0
Double_Infected_Th_Cells => Plasma*b*Double_Infected_Th_Cells b = 2.0
=> Normal_Th_cells Plasma*lamda lamda = 2.0
Curator's comment:
(added: 29 Aug 2018, 16:27:28, updated: 29 Aug 2018, 16:27:28)
Figure 2b of the reference publication has been reproduced. Simulation of the model with double infection. Infection rates are set to be equal. ie alpha=beta . Initial conditions are x(0)=3, y(0)=6, v(0)=149 and w(0)=1. The model was simulated using Copasi 4.22 and the figure was generated using Python 2.7.