Literature DB >> 22573601

From protein interaction networks to novel therapeutic strategies.

Samira Jaeger1, Patrick Aloy.   

Abstract

Cellular mechanisms that sustain health or contribute to disease emerge mostly from the complex interplay among various molecular entities. To understand the underlying relationships between genotype, environment and phenotype, one has to consider the intricate and nonsequential interaction patterns formed between the different sets of cellular players. Biological networks capture a variety of molecular interactions and thus provide an excellent opportunity to consider physiological characteristics of individual molecules within their cellular context. In particular, the concept of network biology and its applications contributed largely to recent advances in biomedical research. In this review, we show (i) how biological networks, i.e., protein-protein interaction networks, facilitate the understanding of pathogenic mechanisms that trigger the onset and progression of diseases and (ii) how this knowledge can be translated into effective diagnostic and therapeutic strategies. In particular, we focus on the impact of network pharmacological concepts that go beyond the classical view on individual drugs and targets aiming for combinational therapies with improved clinical efficacy and reduced safety risks.
Copyright © 2012 Wiley Periodicals, Inc.

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Year:  2012        PMID: 22573601     DOI: 10.1002/iub.1040

Source DB:  PubMed          Journal:  IUBMB Life        ISSN: 1521-6543            Impact factor:   3.885


  12 in total

Review 1.  Identification of protein interactions involved in cellular signaling.

Authors:  Jukka Westermarck; Johanna Ivaska; Garry L Corthals
Journal:  Mol Cell Proteomics       Date:  2013-03-12       Impact factor: 5.911

Review 2.  Structural bioinformatics of the interactome.

Authors:  Donald Petrey; Barry Honig
Journal:  Annu Rev Biophys       Date:  2014       Impact factor: 12.981

3.  Setting Up a Bioluminescence Resonance Energy Transfer High throughput Screening Assay to Search for Protein/Protein Interaction Inhibitors in Mammalian Cells.

Authors:  Cyril Couturier; Benoit Deprez
Journal:  Front Endocrinol (Lausanne)       Date:  2012-09-11       Impact factor: 5.555

4.  Protein interaction network for Alzheimer's disease using computational approach.

Authors:  V Srinivasa Rao; K Srinivas; G N Sunand Kumar; G N Sujin
Journal:  Bioinformation       Date:  2013-12-06

Review 5.  Protein-protein interaction networks (PPI) and complex diseases.

Authors:  Nahid Safari-Alighiarloo; Mohammad Taghizadeh; Mostafa Rezaei-Tavirani; Bahram Goliaei; Ali Asghar Peyvandi
Journal:  Gastroenterol Hepatol Bed Bench       Date:  2014

Review 6.  Revisiting the Role of Plant Transcription Factors in the Battle against Abiotic Stress.

Authors:  Sardar-Ali Khan; Meng-Zhan Li; Suo-Min Wang; Hong-Ju Yin
Journal:  Int J Mol Sci       Date:  2018-05-31       Impact factor: 5.923

Review 7.  Metabolomics and systems pharmacology: why and how to model the human metabolic network for drug discovery.

Authors:  Douglas B Kell; Royston Goodacre
Journal:  Drug Discov Today       Date:  2013-07-26       Impact factor: 7.851

8.  Novel Neuroprotective Multicomponent Therapy for Amyotrophic Lateral Sclerosis Designed by Networked Systems.

Authors:  Mireia Herrando-Grabulosa; Roger Mulet; Albert Pujol; José Manuel Mas; Xavier Navarro; Patrick Aloy; Mireia Coma; Caty Casas
Journal:  PLoS One       Date:  2016-01-25       Impact factor: 3.240

9.  HVint: A Strategy for Identifying Novel Protein-Protein Interactions in Herpes Simplex Virus Type 1.

Authors:  Paul Ashford; Anna Hernandez; Todd Michael Greco; Anna Buch; Beate Sodeik; Ileana Mihaela Cristea; Kay Grünewald; Adrian Shepherd; Maya Topf
Journal:  Mol Cell Proteomics       Date:  2016-07-06       Impact factor: 5.911

10.  A New Methodology for Incorporating Chiral Linkers into Stapled Peptides.

Authors:  Juan C Serrano; James Sipthorp; Wenshu Xu; Laura S Itzhaki; Steven V Ley
Journal:  Chembiochem       Date:  2017-05-18       Impact factor: 3.461

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