Connecting Neuronal Cell Protective Pathways and Drug Combinations in a Huntington’s Disease Model through the Application of Quantitative Systems Pharmacology

被引:0
|
作者
Fen Pei
Hongchun Li
Mark J. Henderson
Steven A. Titus
Ajit Jadhav
Anton Simeonov
Murat Can Cobanoglu
Seyed H. Mousavi
Tongying Shun
Lee McDermott
Prema Iyer
Michael Fioravanti
Diane Carlisle
Robert M. Friedlander
Ivet Bahar
D. Lansing Taylor
Timothy R. Lezon
Andrew M. Stern
Mark E. Schurdak
机构
[1] Department of Computational and Systems Biology,
[2] University of Pittsburgh,undefined
[3] National Center for Advancing Translational Sciences,undefined
[4] National Institutes of Health,undefined
[5] Department of Neurological Surgery,undefined
[6] University of Pittsburgh,undefined
[7] University of Pittsburgh Drug Discovery Institute,undefined
[8] Department of Pharmaceutical Sciences,undefined
[9] University of Pittsburgh,undefined
[10] University of Pittsburgh Brain Institute,undefined
来源
关键词
D O I
暂无
中图分类号
学科分类号
摘要
Quantitative Systems Pharmacology (QSP) is a drug discovery approach that integrates computational and experimental methods in an iterative way to gain a comprehensive, unbiased understanding of disease processes to inform effective therapeutic strategies. We report the implementation of QSP to Huntington’s Disease, with the application of a chemogenomics platform to identify strategies to protect neuronal cells from mutant huntingtin induced death. Using the STHdhQ111 cell model, we investigated the protective effects of small molecule probes having diverse canonical modes-of-action to infer pathways of neuronal cell protection connected to drug mechanism. Several mechanistically diverse protective probes were identified, most of which showed less than 50% efficacy. Specific combinations of these probes were synergistic in enhancing efficacy. Computational analysis of these probes revealed a convergence of pathways indicating activation of PKA. Analysis of phospho-PKA levels showed lower cytoplasmic levels in STHdhQ111 cells compared to wild type STHdhQ7 cells, and these levels were increased by several of the protective compounds. Pharmacological inhibition of PKA activity reduced protection supporting the hypothesis that protection may be working, in part, through activation of the PKA network. The systems-level studies described here can be broadly applied to any discovery strategy involving small molecule modulation of disease phenotype.
引用
收藏
相关论文
共 50 条
  • [1] Connecting Neuronal Cell Protective Pathways and Drug Combinations in a Huntington's Disease Model through the Application of Quantitative Systems Pharmacology
    Pei, Fen
    Li, Hongchun
    Henderson, Mark J.
    Titus, Steven A.
    Jadhav, Ajit
    Simeonov, Anton
    Cobanoglu, Murat Can
    Mousavi, Seyed H.
    Shun, Tongying
    McDermott, Lee
    Iyer, Prema
    Fioravanti, Michael
    Carlisle, Diane
    Friedlander, Robert M.
    Bahar, Ivet
    Taylor, D. Lansing
    Lezon, Timothy R.
    Stern, Andrew M.
    Schurdak, Mark E.
    SCIENTIFIC REPORTS, 2017, 7
  • [2] Curcumin modulates cell death and is protective in Huntington’s disease model
    Anjalika Chongtham
    Namita Agrawal
    Scientific Reports, 6
  • [3] Curcumin modulates cell death and is protective in Huntington's disease model
    Chongtham, Anjalika
    Agrawal, Namita
    SCIENTIFIC REPORTS, 2016, 6
  • [4] Model innovation in Parkinson's disease drug development: linking Quantitative Systems Pharmacology to the patient voice
    Barrett, J.
    Piccoli, B.
    Muller, M.
    Barrett, K.
    Goncharov, D.
    Kaddi, C.
    Azer, K.
    Romero, K.
    Stephenson, D.
    MOVEMENT DISORDERS, 2021, 36 : S126 - S126
  • [5] A Quantitative Systems Pharmacology Model for the Key Interleukins Involved in Crohn's Disease
    Balbas-Martinez, Violeta
    Asin-Prieto, Eduardo
    Parra-Guillen, Zinnia P.
    Troconiz, Inaki F.
    JOURNAL OF PHARMACOLOGY AND EXPERIMENTAL THERAPEUTICS, 2020, 372 (03): : 299 - 307
  • [6] A quantitative systems pharmacology model for simulating OFF-Time in augmentation trials for Parkinson's disease: application to preladenant
    Rose, Rachel
    Mitchell, Emma
    Van der Graaf, Piet
    Takaichi, Daisuke
    Hosogi, Jun
    Geerts, Hugo
    JOURNAL OF PHARMACOKINETICS AND PHARMACODYNAMICS, 2022, 49 (06) : 593 - 606
  • [7] A quantitative systems pharmacology model for simulating OFF-Time in augmentation trials for Parkinson’s disease: application to preladenant
    Rachel Rose
    Emma Mitchell
    Piet Van Der Graaf
    Daisuke Takaichi
    Jun Hosogi
    Hugo Geerts
    Journal of Pharmacokinetics and Pharmacodynamics, 2022, 49 : 593 - 606
  • [8] A Dynamic Quantitative Systems Pharmacology Model of Inflammatory Bowel Disease: Part 2-Application to Current Therapies in Crohn's Disease
    Rogers, Katharine, V
    Martin, Steven W.
    Bhattacharya, Indranil
    Singh, Ravi Shankar Prasad
    Nayak, Satyaprakash
    CTS-CLINICAL AND TRANSLATIONAL SCIENCE, 2021, 14 (01): : 249 - 259
  • [9] A quantitative systems pharmacology model to describe the immunopathogenesis of inflammatory bowel disease and guide drug development decisions
    Ramakrishnan, Vidya
    Lu, Pinyi
    McBride, Jacqueline
    Fuh, Franklin
    Lekkerkerker, Annemarie
    Tang, Meina
    Leber, Andrew
    Hontecillas, Raquel
    Quartino, Angelica
    Jin, Jin Yan
    Bassaganya-Riera, Josep
    Ramanujan, Saroja
    Gadkar, Kapil
    JOURNAL OF PHARMACOKINETICS AND PHARMACODYNAMICS, 2018, 45 : S85 - S85
  • [10] Compounds blocking mutant huntingtin toxicity identified using a Huntington's disease neuronal cell model
    Wang, WF
    Duan, WZ
    Igarashi, S
    Morita, H
    Nakamura, M
    Ross, CA
    NEUROBIOLOGY OF DISEASE, 2005, 20 (02) : 500 - 508