Literature DB >> 24705245

Protein-drug interactome analysis of SSRI-mediated neurorecovery following stroke.

Hong-Fang Chen1, Xiao-Ling Pan1, Jian-Wei Wang1, Hui-Mei Kong1, Ya-Ming Fu2.   

Abstract

Serotonin selective reuptake inhibitors (SSRIs) have been widely used as first-line drugs in the treatment of a range of depressive and anxiety disorders. Recently, clinical studies found that this class of agents also shows significant efficacy in promoting neurogenesis, neuroplasticity and neurorecovery following stroke. Here, we attempt to elucidate molecular mechanism and biological implication underlying the SSRI-mediated neurorecovery. In the procedure, a comprehensive protein-drug interactome (PDI) was constructed for various SSRIs and their major metabolites as well as a group of control drugs across a large panel of human neuroproteins via a high-throughput molecular docking approach. The obtained PDI was then analyzed at systematic level to extract unexpected targets for SSRIs/metabolites. Biological network analysis and gene ontology (GO) enrichment solidified that the inferred targets have high potential to be directly or indirectly involved in diverse neural events, and further molecular dynamics (MD) simulation and post molecular mechanics-Poisson Boltzmann/surface area (MM-PB/SA) characterization revealed a stable complex architecture and high-affinity interaction between the targets and SSRIs/metabolites. Specifically, two human proteins, i.e. neurogenic locus notch homolog protein 1 (NOTCH 1) and Rho-associated protein kinase 1 (ROCK 1), were suggested as promising regulators in the SSRI-mediated neurorecovery, which can be targeted efficiently by fluoxetine and paroxetine, respectively, as well as other SSRIs and metabolites.
Copyright © 2014 Elsevier Ireland Ltd. All rights reserved.

Entities:  

Keywords:  Neurorecovery; Protein–drug interactome; Serotonin selective reuptake inhibitor; Stroke

Mesh:

Substances:

Year:  2014        PMID: 24705245     DOI: 10.1016/j.biosystems.2014.03.007

Source DB:  PubMed          Journal:  Biosystems        ISSN: 0303-2647            Impact factor:   1.973


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