Literature DB >> 22539148

Structural systems biology and multiscale signaling models.

Shannon E Telesco1, Ravi Radhakrishnan.   

Abstract

We review current advances in experimental as well as computational modeling and simulation approaches to structural systems biology, whose overall aim is to build quantitative models of signaling networks while retaining the crucial elements of molecular specificity. We briefly discuss the current and emerging experimental and computational methods, particularly focusing on hybrid and multiscale methods, and highlight several applications in cell signaling with quantitative and predictive capabilities. The scope of such models range from delineating protein-protein interactions to describing clinical implications.

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Year:  2012        PMID: 22539148      PMCID: PMC4612526          DOI: 10.1007/s10439-012-0576-6

Source DB:  PubMed          Journal:  Ann Biomed Eng        ISSN: 0090-6964            Impact factor:   3.934


  57 in total

Review 1.  Cell signaling by receptor tyrosine kinases.

Authors:  J Schlessinger
Journal:  Cell       Date:  2000-10-13       Impact factor: 41.582

2.  Structures of the tyrosine kinase domain of fibroblast growth factor receptor in complex with inhibitors.

Authors:  M Mohammadi; G McMahon; L Sun; C Tang; P Hirth; B K Yeh; S R Hubbard; J Schlessinger
Journal:  Science       Date:  1997-05-09       Impact factor: 47.728

3.  Comparative study of several algorithms for flexible ligand docking.

Authors:  Badry D Bursulaya; Maxim Totrov; Ruben Abagyan; Charles L Brooks
Journal:  J Comput Aided Mol Des       Date:  2003-11       Impact factor: 3.686

4.  Multiscale computer simulation of the immature HIV-1 virion.

Authors:  Gary S Ayton; Gregory A Voth
Journal:  Biophys J       Date:  2010-11-03       Impact factor: 4.033

5.  Molecular dynamics analysis of conserved hydrophobic and hydrophilic bond-interaction networks in ErbB family kinases.

Authors:  Andrew J Shih; Shannon E Telesco; Sung-Hee Choi; Mark A Lemmon; Ravi Radhakrishnan
Journal:  Biochem J       Date:  2011-06-01       Impact factor: 3.857

Review 6.  EGF-ERBB signalling: towards the systems level.

Authors:  Ami Citri; Yosef Yarden
Journal:  Nat Rev Mol Cell Biol       Date:  2006-07       Impact factor: 94.444

7.  Simulated self-assembly of the HIV-1 capsid: protein shape and native contacts are sufficient for two-dimensional lattice formation.

Authors:  Bo Chen; Robert Tycko
Journal:  Biophys J       Date:  2011-06-22       Impact factor: 4.033

8.  Molecular systems biology of ErbB1 signaling: bridging the gap through multiscale modeling and high-performance computing.

Authors:  Andrew J Shih; Jeremy Purvis; Ravi Radhakrishnan
Journal:  Mol Biosyst       Date:  2008-09-12

9.  Analysis of Somatic Mutations in Cancer: Molecular Mechanisms of Activation in the ErbB Family of Receptor Tyrosine Kinases.

Authors:  Andrew J Shih; Shannon E Telesco; Ravi Radhakrishnan
Journal:  Cancers (Basel)       Date:  2011-03       Impact factor: 6.639

10.  Ligand-dependent responses of the ErbB signaling network: experimental and modeling analyses.

Authors:  Marc R Birtwistle; Mariko Hatakeyama; Noriko Yumoto; Babatunde A Ogunnaike; Jan B Hoek; Boris N Kholodenko
Journal:  Mol Syst Biol       Date:  2007-11-13       Impact factor: 11.429

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  7 in total

Review 1.  Mathematical simulation of membrane protein clustering for efficient signal transduction.

Authors:  Krishnan Radhakrishnan; Ádám Halász; Meghan M McCabe; Jeremy S Edwards; Bridget S Wilson
Journal:  Ann Biomed Eng       Date:  2012-06-06       Impact factor: 3.934

Review 2.  Disentangling biological signaling networks by dynamic coupling of signaling lipids to modifying enzymes.

Authors:  Raymond D Blind
Journal:  Adv Biol Regul       Date:  2013-10-18

3.  Molecular modeling of ErbB4/HER4 kinase in the context of the HER4 signaling network helps rationalize the effects of clinically identified HER4 somatic mutations on the cell phenotype.

Authors:  Shannon E Telesco; Rajanikanth Vadigepalli; Ravi Radhakrishnan
Journal:  Biotechnol J       Date:  2013-12-04       Impact factor: 4.677

Review 4.  Computational algorithms for in silico profiling of activating mutations in cancer.

Authors:  E Joseph Jordan; Keshav Patil; Krishna Suresh; Jin H Park; Yael P Mosse; Mark A Lemmon; Ravi Radhakrishnan
Journal:  Cell Mol Life Sci       Date:  2019-04-13       Impact factor: 9.261

5.  Membrane signalosome: where biophysics meets systems biology.

Authors:  Sreeja K Kandy; Paul A Janmey; Ravi Radhakrishnan
Journal:  Curr Opin Syst Biol       Date:  2021-02-25

6.  Multiscale Cancer Modeling and In Silico Oncology: Emerging Computational Frontiers in Basic and Translational Cancer Research.

Authors:  Georgios S Stamatakos; Norbert Graf; Ravi Radhakrishnan
Journal:  J Bioeng Biomed Sci       Date:  2013-05-25

Review 7.  Integrating Multiscale Modeling with Drug Effects for Cancer Treatment.

Authors:  Xiangfang L Li; Wasiu O Oduola; Lijun Qian; Edward R Dougherty
Journal:  Cancer Inform       Date:  2016-01-13
  7 in total

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