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DoldánMartelli2013 - A Mathematical Model for the Rational Design of Chimeric Ligands in Selective Drug Therapies Lab

About lab

DoldánMartelli2013 - A Mathematical Model for the Rational Design of Chimeric Ligands in Selective Drug Therapies

This Biosimulant lab wraps DoldánMartelli2013 - A Mathematical Model for the Rational Design of Chimeric Ligands in Selective Drug Therapies as a runnable pharmacology model with a companion visualization module. This model attempts to provide a mathematical framework for describing the dynamics of receptor-drug complex formation of chimeric drugs. It can be used to explore drug-exposure and pathway-response dynamics and compare scenario outcomes across configurations.

What You'll See

The lab asks: Does the chimeric ligand preferentially engage target 1 or target 2? It runs for 60.0 time units with a communication step of 2.0. The run uses the model defaults declared by the curated SBML wrapper. The generated visualizations focus on Target 1 Drug Complex, Target 2 Drug Complex, Target 1 Drug Effector Complex, Target 2 Drug Effector Complex, Selectivity Complex 1, and Selectivity Complex 2, and related outputs, combining trajectory, endpoint-comparison, and summary-table views from one completed dark-mode run.

In this captured run, R 1 D peaked at 5640.0 and R 1 D moved by 4791.0 native units across 60.0 simulation windows.

Output Visualizations

DoldánMartelli2013 - A Mathematical Model for the Rational Design of Chimeric Ligands in Selective Drug Therapies - run interpretation

Summary table for DoldánMartelli2013 - A Mathematical Model for the Rational Design of Chimeric Ligands in Selective Drug Therapies, reporting the scientific question, observed answer (largest change: R 1 D at 4791.0 native units), evidence (peak observable: R 1 D), dominant module, and caveat.

DoldánMartelli2013 - A Mathematical Model for the Rational Design of Chimeric Ligands in Selective Drug Therapies - timeseries visualization

Trajectories of R 1 D, R 2 D, C 1, C 2, C 3, and R 1 DE across the 60.0 simulation. In this run C 2 climbed from 0 to 461.3 and R 1 D fell from 5640.0 to 848.5 — the largest movements among the focused observables.

DoldánMartelli2013 - A Mathematical Model for the Rational Design of Chimeric Ligands in Selective Drug Therapies - excursions bar

Largest-excursion ranking of the focused observables — the absolute movement magnitude during the run. Top 3: R 1 D = 4791.5, R 2 D = 2142.8, C 1 = 928.3, with 2 more observables below.

DoldánMartelli2013 - A Mathematical Model for the Rational Design of Chimeric Ligands in Selective Drug Therapies - endpoint snapshot bar

Endpoint snapshot of the focused observables — final values from the captured run. Top 3 by value: R 1 DE = 5640.0, R 2 DE = 3600.0, R 2 D = 1457.2, with 4 more observables below.

Model Context

  • Core model: models/core
  • Visualization model: models/visualisation
  • Standard: sbml
  • Upstream source: biomodels_ebi:MODEL1907310001
  • License: CC0

Inputs

InputMaps ToDefaultNotes
Ligand Concentrationpharmacology_sbml_dold_nmartelli2013_a_mathematical_model_for_the_model1907310001_model.ligand_concentrationUses the model default unless overridden at run time.
Target 1 Association Ratepharmacology_sbml_dold_nmartelli2013_a_mathematical_model_for_the_model1907310001_model.target_1_association_rateUses the model default unless overridden at run time.
Target 1 Dissociation Ratepharmacology_sbml_dold_nmartelli2013_a_mathematical_model_for_the_model1907310001_model.target_1_dissociation_rateUses the model default unless overridden at run time.
Target 2 Association Ratepharmacology_sbml_dold_nmartelli2013_a_mathematical_model_for_the_model1907310001_model.target_2_association_rateUses the model default unless overridden at run time.
Target 2 Dissociation Ratepharmacology_sbml_dold_nmartelli2013_a_mathematical_model_for_the_model1907310001_model.target_2_dissociation_rateUses the model default unless overridden at run time.

Outputs

OutputMaps ToRole
statepharmacology_sbml_dold_nmartelli2013_a_mathematical_model_for_the_model1907310001_model.stateAvailable to the visualization model and downstream workflows.
summarypharmacology_sbml_dold_nmartelli2013_a_mathematical_model_for_the_model1907310001_model.summaryAvailable to the visualization model and downstream workflows.
species_labelspharmacology_sbml_dold_nmartelli2013_a_mathematical_model_for_the_model1907310001_model.species_labelsAvailable to the visualization model and downstream workflows.
target_1_drug_complexpharmacology_sbml_dold_nmartelli2013_a_mathematical_model_for_the_model1907310001_model.target_1_drug_complexAvailable to the visualization model and downstream workflows.
target_2_drug_complexpharmacology_sbml_dold_nmartelli2013_a_mathematical_model_for_the_model1907310001_model.target_2_drug_complexAvailable to the visualization model and downstream workflows.
target_1_drug_effector_complexpharmacology_sbml_dold_nmartelli2013_a_mathematical_model_for_the_model1907310001_model.target_1_drug_effector_complexAvailable to the visualization model and downstream workflows.
target_2_drug_effector_complexpharmacology_sbml_dold_nmartelli2013_a_mathematical_model_for_the_model1907310001_model.target_2_drug_effector_complexAvailable to the visualization model and downstream workflows.
selectivity_complex_1pharmacology_sbml_dold_nmartelli2013_a_mathematical_model_for_the_model1907310001_model.selectivity_complex_1Available to the visualization model and downstream workflows.
selectivity_complex_2pharmacology_sbml_dold_nmartelli2013_a_mathematical_model_for_the_model1907310001_model.selectivity_complex_2Available to the visualization model and downstream workflows.
selectivity_complex_3pharmacology_sbml_dold_nmartelli2013_a_mathematical_model_for_the_model1907310001_model.selectivity_complex_3Available to the visualization model and downstream workflows.

Runtime

  • Duration: 60.0
  • Communication step: 2.0

Running Locally

biosimulant labs serve .

This model attempts to provide a mathematical framework for describing the dynamics of receptor-drug complex formation of chimeric drugs. It can be used to explore dose-response dynamics and compare treatment scenarios across conditions.

Runtime

Duration60
Comms Step2

Runs

Total0
Completed0
Failed0

Metadata

Packagedold-nmartelli2013-a-mathematical-model-for-the-rational-design
Created2026-05-16
Updated2026-05-16
pharmacologydrug-discoveryreceptor-bindingsystems-biologysbmltelluriumfaithfulbiomodels_ebivisualisation

Manifest

{
  "io": {
    "inputs": [
      {
        "name": "ligand_concentration",
        "label": "Ligand Concentration",
        "maps_to": "pharmacology_sbml_dold_nmartelli2013_a_mathematical_model_for_the_model1907310001_model.ligand_concentration"
      },
      {
        "name": "target_1_association_rate",
        "label": "Target 1 Association Rate",
        "maps_to": "pharmacology_sbml_dold_nmartelli2013_a_mathematical_model_for_the_model1907310001_model.target_1_association_rate"
      },
      {
        "name": "target_1_dissociation_rate",
        "label": "Target 1 Dissociation Rate",
        "maps_to": "pharmacology_sbml_dold_nmartelli2013_a_mathematical_model_for_the_model1907310001_model.target_1_dissociation_rate"
      },
      {
        "name": "target_2_association_rate",
        "label": "Target 2 Association Rate",
        "maps_to": "pharmacology_sbml_dold_nmartelli2013_a_mathematical_model_for_the_model1907310001_model.target_2_association_rate"
      },
      {
        "name": "target_2_dissociation_rate",
        "label": "Target 2 Dissociation Rate",
        "maps_to": "pharmacology_sbml_dold_nmartelli2013_a_mathematical_model_for_the_model1907310001_model.target_2_dissociation_rate"
      }
    ],
    "outputs": [
      {
        "name": "state",
        "label": "Tracked source state",
        "maps_to": "pharmacology_sbml_dold_nmartelli2013_a_mathematical_model_for_the_model1907310001_model.state"
      },
      {
        "name": "summary",
        "label": "Simulation summary",
        "maps_to": "pharmacology_sbml_dold_nmartelli2013_a_mathematical_model_for_the_model1907310001_model.summary"
      },
      {
        "name": "species_labels",
        "label": "Observable labels",
        "maps_to": "pharmacology_sbml_dold_nmartelli2013_a_mathematical_model_for_the_model1907310001_model.species_labels"
      },
      {
        "name": "target_1_drug_complex",
        "label": "Target 1 Drug Complex",
        "maps_to": "pharmacology_sbml_dold_nmartelli2013_a_mathematical_model_for_the_model1907310001_model.target_1_drug_complex"
      },
      {
        "name": "target_2_drug_complex",
        "label": "Target 2 Drug Complex",
        "maps_to": "pharmacology_sbml_dold_nmartelli2013_a_mathematical_model_for_the_model1907310001_model.target_2_drug_complex"
      },
      {
        "name": "target_1_drug_effector_complex",
        "label": "Target 1 Drug Effector Complex",
        "maps_to": "pharmacology_sbml_dold_nmartelli2013_a_mathematical_model_for_the_model1907310001_model.target_1_drug_effector_complex"
      },
      {
        "name": "target_2_drug_effector_complex",
        "label": "Target 2 Drug Effector Complex",
        "maps_to": "pharmacology_sbml_dold_nmartelli2013_a_mathematical_model_for_the_model1907310001_model.target_2_drug_effector_complex"
      },
      {
        "name": "selectivity_complex_1",
        "label": "Selectivity Complex 1",
        "maps_to": "pharmacology_sbml_dold_nmartelli2013_a_mathematical_model_for_the_model1907310001_model.selectivity_complex_1"
      },
      {
        "name": "selectivity_complex_2",
        "label": "Selectivity Complex 2",
        "maps_to": "pharmacology_sbml_dold_nmartelli2013_a_mathematical_model_for_the_model1907310001_model.selectivity_complex_2"
      },
      {
        "name": "selectivity_complex_3",
        "label": "Selectivity Complex 3",
        "maps_to": "pharmacology_sbml_dold_nmartelli2013_a_mathematical_model_for_the_model1907310001_model.selectivity_complex_3"
      }
    ]
  },
  "tags": [
    "pharmacology",
    "drug-discovery",
    "receptor-binding",
    "systems-biology",
    "sbml",
    "tellurium",
    "faithful",
    "biomodels_ebi"
  ],
  "title": "DoldánMartelli2013 - A Mathematical Model for the Rational Design of Chimeric Ligands in Selective Drug Therapies Lab",
  "models": [
    {
      "path": "owned/models/pharmacology_sbml_dold_nmartelli2013_a_mathematical_model_for_the_model1907310001_model",
      "alias": "pharmacology_sbml_dold_nmartelli2013_a_mathematical_model_for_the_model1907310001_model",
      "parameters": {
        "model_path": "data/MODEL1907310001.xml",
        "integration_step": 0.2
      },
      "provenance": {
        "owned_path": "owned/models/pharmacology_sbml_dold_nmartelli2013_a_mathematical_model_for_the_model1907310001_model"
      }
    },
    {
      "path": "owned/models/visualisation",
      "alias": "visualisation",
      "provenance": {
        "owned_path": "owned/models/visualisation"
      }
    }
  ],
  "wiring": [
    {
      "to": [
        "visualisation.pharmacology_sbml_dold_nmartelli2013_a_mathematical_model_for_the_model1907310001_model_state"
      ],
      "from": "pharmacology_sbml_dold_nmartelli2013_a_mathematical_model_for_the_model1907310001_model.state"
    },
    {
      "to": [
        "visualisation.pharmacology_sbml_dold_nmartelli2013_a_mathematical_model_for_the_model1907310001_model_summary"
      ],
      "from": "pharmacology_sbml_dold_nmartelli2013_a_mathematical_model_for_the_model1907310001_model.summary"
    },
    {
      "to": [
        "visualisation.pharmacology_sbml_dold_nmartelli2013_a_mathematical_model_for_the_model1907310001_model_species_labels"
      ],
      "from": "pharmacology_sbml_dold_nmartelli2013_a_mathematical_model_for_the_model1907310001_model.species_labels"
    }
  ],
  "runtime": {
    "duration": 60,
    "initial_inputs": {},
    "communication_step": 2
  },
  "description": "This model attempts to provide a mathematical framework for describing the dynamics of receptor-drug complex formation of chimeric drugs. It can be used to explore dose-response dynamics and compare treatment scenarios across conditions.",
  "schema_version": "2.0"
}

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