Molecular mechanism matters: Benefits of mechanistic computational models for drug development

Clegg, Lindsay E.; Gabhann, Feilim Mac

doi:10.1016/j.phrs.2015.06.002

Cited by 34 publications

(28 citation statements)

References 45 publications

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“…The lack of approved pro-angiogenic therapies to date makes it clear that a better understanding of the molecular mechanisms driving disease is critical to identify more effective drug targets, optimize drug properties (e.g. affinity), and avoid off-target effects leading to toxicity and drug failure [55]. This work can be extended to disease applications with changes in VEGF splicing, and to compare results in humans versus mice, to aid in translation of therapeutics targeting the VEGF system and to further validate the model against data obtained in mice.…”

Section: Discussionmentioning

confidence: 99%

“…Compared to in vitro studies, physiological ligand concentrations are very low, many different growth factors are constantly being produced, consumed, and transported throughout the body, and the time-scales of interest are far longer [55]. Computational models provide a key tool to study the combined effects of many forms of regulation within a single framework, and to scale between model systems and human patients.…”

Section: Introductionmentioning

confidence: 99%

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A computational analysis of in vivo VEGFR activation by multiple co-expressed ligands

Clegg

Gabhann

2017

PLoS Comput Biol

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The splice isoforms of vascular endothelial growth A (VEGF) each have different affinities for the extracellular matrix (ECM) and the coreceptor NRP1, which leads to distinct vascular phenotypes in model systems expressing only a single VEGF isoform. ECM-immobilized VEGF can bind to and activate VEGF receptor 2 (VEGFR2) directly, with a different pattern of site-specific phosphorylation than diffusible VEGF. To date, the way in which ECM binding alters the distribution of isoforms of VEGF and of the related placental growth factor (PlGF) in the body and resulting angiogenic signaling is not well-understood. Here, we extend our previous validated cell-level computational model of VEGFR2 ligation, intracellular trafficking, and site-specific phosphorylation, which captured differences in signaling by soluble and immobilized VEGF, to a multi-scale whole-body framework. This computational systems pharmacology model captures the ability of the ECM to regulate isoform-specific growth factor distribution distinctly for VEGF and PlGF, and to buffer free VEGF and PlGF levels in tissue. We show that binding of immobilized growth factor to VEGF receptors, both on endothelial cells and soluble VEGFR1, is likely important to signaling in vivo. Additionally, our model predicts that VEGF isoform-specific properties lead to distinct profiles of VEGFR1 and VEGFR2 binding and VEGFR2 site-specific phosphorylation in vivo, mediated by Neuropilin-1. These predicted signaling changes mirror those observed in murine systems expressing single VEGF isoforms. Simulations predict that, contrary to the ‘ligand-shifting hypothesis,’ VEGF and PlGF do not compete for receptor binding at physiological concentrations, though PlGF is predicted to slightly increase VEGFR2 phosphorylation when over-expressed by 10-fold. These results are critical to design of appropriate therapeutic strategies to control VEGF availability and signaling in regenerative medicine applications.

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Section: Discussionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

A computational analysis of in vivo VEGFR activation by multiple co-expressed ligands

Clegg

Gabhann

2017

PLoS Comput Biol

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“…15 Computational models provide a unique potential to examine this signaling complexity, bridging observations in cell culture experiments, animal models that recapitulate human disease only to a limited extent, and human patients with PAD. 16 The VEGF family is complex, consisting of five ligand genes, including VEGFA and placental growth factor (PlGF), three receptors (vascular endothelial growth factor receptors (VEGFR)1-3), and multiple co-receptors, including neuropilin-1 (NRP1). 17 The VEGFRs can be alternatively spliced, producing soluble isoforms (e.g., soluble VEGFR1 (sVEGFR1)) that bind to VEGF, PlGF, and heparin sulfate proteoglycans (HSPGs).…”

mentioning

confidence: 99%

Systems Pharmacology of VEGF165b in Peripheral Artery Disease

Clegg

Ganta

Annex

et al. 2017

CPT Pharmacom & Syst Pharma

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We built a whole‐body computational model to study the role of the poorly understood vascular endothelial growth factor (VEGF)165b splice isoform in peripheral artery disease (PAD). This model was built and validated using published and new experimental data from cells, mice, and humans, and explicitly accounts for known properties of VEGF165b: lack of extracellular matrix (ECM)‐binding and weak phosphorylation of vascular endothelial growth factor receptor‐2 (VEGFR2) in vitro. The resulting model captures all known information about VEGF165b distribution and signaling in human PAD, and provides novel, nonintuitive insight into VEGF165b mechanism of action in vivo. Although VEGF165a and VEGF165b compete for VEGFR2 in vitro, simulations show that these isoforms do not compete for VEGFR2 at much lower physiological concentrations. Instead, reduced VEGF165a may drive impaired VEGFR2 signaling. The model predicts that VEGF165b does compete for binding to VEGFR1, supporting a VEGFR1‐mediated response to anti‐VEGF165b. The model predicts a key role for VEGF165b in PAD, but in a different way than previously hypothesized.

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“…This is particularly applicable in cancer care, wherein the clinical successes of anticancer therapies are often limited by the marginal efficacy of the therapeutics and their various side effects. Prediction of the distribution, metabolism, absorption, excretion and toxicity of potential new drugs in early stages of development has attracted much attention 59,60 . The therapeutic efficiency of nanomedicine is determined by the proper concentration of drug at the lesion site.…”

Section: Introductionmentioning

confidence: 99%

“…Mechanistic mathematical and computational modeling at multiple scales, from gene to protein to tissue and organ, and eventually the whole body is becoming an effective if not a required tool for examining the impact of various biophysical features of the tumor tissue and biochemical properties of drug compounds on drug delivery efficacy 59,60,70–73 . Numerical simulations are well-suited and cheaper, compared to laboratory experiments, for testing combinations of multiple parameters that can be varied simultaneously in a controlled manner and over a wide range of values.…”

Section: Introductionmentioning

confidence: 99%

Multiscale Modeling in the Clinic: Drug Design and Development

Clancy

Cannon

et al. 2016

Ann Biomed Eng

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A wide range of length and time scales are relevant to pharmacology, especially in drug development, drug design and drug delivery. Therefore, multiscale computational modeling and simulation methods and paradigms that advance the linkage of phenomena occurring at these multiple scales have become increasingly important. Multiscale approaches present in silico opportunities to advance laboratory research to bedside clinical applications in pharmaceuticals research. This is achievable through the capability of modeling to reveal phenomena occurring across multiple spatial and temporal scales, which are not otherwise readily accessible to experimentation. The resultant models, when validated, are capable of making testable predictions to guide drug design and delivery. In this review we describe the goals, methods, and opportunities of multiscale modeling in drug design and development. We demonstrate the impact of multiple scales of modeling in this field. We indicate the common mathematical and computational techniques employed for multiscale modeling approaches used in pharmacometric and systems pharmacology models in drug development and present several examples illustrating the current state-of-the-art models for (i) excitable systems and applications in cardiac disease; (ii) stem cell driven complex biosystems; (iii) nanoparticle delivery, with applications to angiogenesis and cancer therapy; (iv) host-pathogen interactions and their use in metabolic disorders, inflammation and sepsis; and (v) computer-aided design of nanomedical systems. We conclude with a focus on barriers to successful clinical translation of drug development, drug design and drug delivery multiscale models.

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Molecular mechanism matters: Benefits of mechanistic computational models for drug development

Cited by 34 publications

References 45 publications

A computational analysis of in vivo VEGFR activation by multiple co-expressed ligands

A computational analysis of in vivo VEGFR activation by multiple co-expressed ligands

Systems Pharmacology of VEGF165b in Peripheral Artery Disease

Multiscale Modeling in the Clinic: Drug Design and Development

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