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Is systems pharmacology ready to impact upon therapy development? A study on the cholesterol biosynthesis pathway.

ABSTRACT: BACKGROUND AND PURPOSE:An ever-growing wealth of information on current drugs and their pharmacological effects is available from online databases. As our understanding of systems biology increases, we have the opportunity to predict, model and quantify how drug combinations can be introduced that outperform conventional single-drug therapies. Here, we explore the feasibility of such systems pharmacology approaches with an analysis of the mevalonate branch of the cholesterol biosynthesis pathway. EXPERIMENTAL APPROACH:Using open online resources, we assembled a computational model of the mevalonate pathway and compiled a set of inhibitors directed against targets in this pathway. We used computational optimization to identify combination and dose options that show not only maximal efficacy of inhibition on the cholesterol producing branch but also minimal impact on the geranylation branch, known to mediate the side effects of pharmaceutical treatment. KEY RESULTS:We describe serious impediments to systems pharmacology studies arising from limitations in the data, incomplete coverage and inconsistent reporting. By curating a more complete dataset, we demonstrate the utility of computational optimization for identifying multi-drug treatments with high efficacy and minimal off-target effects. CONCLUSION AND IMPLICATIONS:We suggest solutions that facilitate systems pharmacology studies, based on the introduction of standards for data capture that increase the power of experimental data. We propose a systems pharmacology workflow for the refinement of data and the generation of future therapeutic hypotheses.

SUBMITTER: Benson HE

PROVIDER: S-EPMC5715582 | biostudies-literature | 2017 Dec

REPOSITORIES: biostudies-literature

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Is systems pharmacology ready to impact upon therapy development? A study on the cholesterol biosynthesis pathway.

Benson Helen E HE Watterson Steven S Sharman Joanna L JL Mpamhanga Chido P CP Parton Andrew A Southan Christopher C Harmar Anthony J AJ Ghazal Peter P

British journal of pharmacology 20171126 23

<h4>Background and purpose</h4>An ever-growing wealth of information on current drugs and their pharmacological effects is available from online databases. As our understanding of systems biology increases, we have the opportunity to predict, model and quantify how drug combinations can be introduced that outperform conventional single-drug therapies. Here, we explore the feasibility of such systems pharmacology approaches with an analysis of the mevalonate branch of the cholesterol biosynthesis ...[more]

PMID: 28910500

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Project description:BensonWattersonetal_SystemsPharmacology_Multidrug This model is described in the article: Is systems pharmacology ready to impact upon therapy development? A study on the cholesterol biosynthesis pathway. Benson H, Watterson S, Sharman J, Mpamhanga C, Parton A, Southan C, Harmar A, Ghazal P. Br. J. Pharmacol. 2017 Sep; : Abstract: An ever-growing wealth of information on current drugs and their pharmacological effects is available from online databases. As our understanding of systems biology increases, we have the opportunity to predict, model and quantify how drug combinations can be introduced that outperform conventional single-drug therapies. Here, we explore the feasibility of such systems pharmacology approaches with an analysis of the mevalonate branch of the cholesterol biosynthesis pathway.Using open online resources, we assembled a computational model of the mevalonate pathway and compiled a set of inhibitors directed against targets in this pathway. We used computational optimisation to identify combination and dose options that show not only maximal efficacy of inhibition on the cholesterol producing branch but also minimal impact on the geranylation branch, known to mediate the side effects of pharmaceutical treatment.We describe serious impediments to systems pharmacology studies arising from limitations in the data, incomplete coverage and inconsistent reporting. By curating a more complete dataset, we demonstrate the utility of computational optimization for identifying multi-drug treatments with high efficacy and minimal off-target effects.We suggest solutions that facilitate systems pharmacology studies, based on the introduction of standards for data capture that increase the power of experimental data. We propose a systems pharmacology work-flow for the refinement of data and the generation of future therapeutic hypotheses. This model is hosted on BioModels Database and identified by: MODEL1506220000. To cite BioModels Database, please use: Chelliah V et al. BioModels: ten-year anniversary. Nucl. Acids Res. 2015, 43(Database issue):D542-8. 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.

Project description:BackgroundRecent evidence associates prostate cancer with high cholesterol levels, with cholesterol being an important raw material for cell-growth. Within the cell, cholesterol homeostasis is maintained by two master transcription factors: sterol-regulatory element-binding protein 2 (SREBP-2) and liver X receptor (LXR). We previously showed that the androgen receptor, a major player in prostate cell physiology, toggles these transcription factors to promote cholesterol accumulation. Given that prostate cancer therapy targets the androgen receptor, selecting for cells with altered androgen receptor activity, how would this affect SREBP-2 and LXR activity? Using a novel prostate cancer progression model, we explored how this crosstalk between the androgen receptor and cholesterol homeostasis changes during prostate cancer development.Methodology/principal findingsFirstly, we characterised our progression model, which involved 1) culturing LNCaP cells at physiological testosterone levels to generate androgen-tolerant LNCaP-305 cells, and 2) culturing LNCaP-305 with the anti-androgen casodex to generate castration-resistant LNCaP-364 cells. This progression was accompanied by upregulated androgen receptor expression, typically seen clinically, and a reduction in androgen receptor activity. Although this influenced how SREBP-2 and LXR target genes responded to androgen treatment, cellular cholesterol levels and their response to changing sterol status was similar in all LNCaP sub-lines.Conclusion/significanceOverall cholesterol homeostasis is unaffected by changing androgen receptor activity in prostate cancer cells. This does not negate the relationship between androgens and cholesterol homeostasis, but rather suggests that other factors compensate for altered androgen receptor activity. Given that cholesterol regulation is maintained during progression, this supports the growing idea that cholesterol metabolism is a suitable target for prostate cancer.

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Is systems pharmacology ready to impact upon therapy development? A study on the cholesterol biosynthesis pathway.

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Is systems pharmacology ready to impact upon therapy development? A study on the cholesterol biosynthesis pathway.

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