Literature DB >> 33589646

Mapping drug-target interactions and synergy in multi-molecular therapeutics for pressure-overload cardiac hypertrophy.

Aparna Rai1, Vikas Kumar2, Gaurav Jerath1,3, C C Kartha4, Vibin Ramakrishnan5.   

Abstract

Advancements in systems biology have resulted in the development of network pharmacology, leading to a paradigm shift from "one-target, one-drug" to "target-network, multi-component therapeutics". We employ a chimeric approach involving in-vivo assays, gene expression analysis, cheminformatics, and network biology to deduce the regulatory actions of a multi-constituent Ayurvedic concoction, Amalaki Rasayana (AR) in animal models for its effect in pressure-overload cardiac hypertrophy. The proteomics analysis of in-vivo assays for Aorta Constricted and Biologically Aged rat models identify proteins expressed under each condition. Network analysis mapping protein-protein interactions and synergistic actions of AR using multi-component networks reveal drug targets such as ACADM, COX4I1, COX6B1, HBB, MYH14, and SLC25A4, as potential pharmacological co-targets for cardiac hypertrophy. Further, five out of eighteen AR constituents potentially target these proteins. We propose a distinct prospective strategy for the discovery of network pharmacological therapies and repositioning of existing drug molecules for treating pressure-overload cardiac hypertrophy.

Entities:  

Year:  2021        PMID: 33589646     DOI: 10.1038/s41540-021-00171-z

Source DB:  PubMed          Journal:  NPJ Syst Biol Appl        ISSN: 2056-7189


  61 in total

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4.  Pharmacological modulation of pressure-overload cardiac hypertrophy: changes in ventricular function, extracellular matrix, and gene expression.

Authors:  K Wong; K R Boheler; M Petrou; M H Yacoub
Journal:  Circulation       Date:  1997-10-07       Impact factor: 29.690

5.  Magnitude of left ventricular hypertrophy and risk of sudden death in hypertrophic cardiomyopathy.

Authors:  P Spirito; P Bellone; K M Harris; P Bernabo; P Bruzzi; B J Maron
Journal:  N Engl J Med       Date:  2000-06-15       Impact factor: 91.245

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Authors:  Ana I Casas; Ahmed A Hassan; Simon J Larsen; Vanessa Gomez-Rangel; Mahmoud Elbatreek; Pamela W M Kleikers; Emre Guney; Javier Egea; Manuela G López; Jan Baumbach; Harald H H W Schmidt
Journal:  Proc Natl Acad Sci U S A       Date:  2019-03-20       Impact factor: 11.205

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Authors:  Jorge Iván Castillo-Quan; Luke S Tain; Kerri J Kinghorn; Li Li; Sebastian Grönke; Yvonne Hinze; T Keith Blackwell; Ivana Bjedov; Linda Partridge
Journal:  Proc Natl Acad Sci U S A       Date:  2019-09-30       Impact factor: 11.205

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Journal:  PLoS One       Date:  2013-04-25       Impact factor: 3.240

9.  Changing Paradigm from one Target one Ligand Towards Multi-target Directed Ligand Design for Key Drug Targets of Alzheimer Disease: An Important Role of In Silico Methods in Multi-target Directed Ligands Design.

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Journal:  Curr Neuropharmacol       Date:  2018       Impact factor: 7.363

10.  Network-based approach to prediction and population-based validation of in silico drug repurposing.

Authors:  Feixiong Cheng; Rishi J Desai; Diane E Handy; Ruisheng Wang; Sebastian Schneeweiss; Albert-László Barabási; Joseph Loscalzo
Journal:  Nat Commun       Date:  2018-07-12       Impact factor: 14.919

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  4 in total

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Authors:  Luigino Calzetta; Cynthia Koziol-White
Journal:  Curr Res Pharmacol Drug Discov       Date:  2021-08-11

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Authors:  Lucía Prieto Santamaría; Eduardo P García Del Valle; Massimiliano Zanin; Gandhi Samuel Hernández Chan; Yuliana Pérez Gallardo; Alejandro Rodríguez-González
Journal:  Sci Rep       Date:  2021-10-26       Impact factor: 4.379

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Journal:  Oxid Med Cell Longev       Date:  2022-09-22       Impact factor: 7.310

4.  A novel graph mining approach to predict and evaluate food-drug interactions.

Authors:  Md Mostafizur Rahman; Srinivas Mukund Vadrev; Arturo Magana-Mora; Jacob Levman; Othman Soufan
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  4 in total

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