Dataset Information

Drug connectivity mapping and functional analysis reveal therapeutic small molecules that differentially modulate myelination.

ABSTRACT: Disruption or loss of oligodendrocytes (OLs) and myelin has devastating effects on CNS function and integrity, which occur in diverse neurological disorders, including Multiple Sclerosis (MS), Alzheimer's disease and neuropsychiatric disorders. Hence, there is a need to develop new therapies that promote oligodendrocyte regeneration and myelin repair. A promising approach is drug repurposing, but most agents have potentially contrasting biological actions depending on the cellular context and their dose-dependent effects on intracellular pathways. Here, we have used a combined systems biology and neurobiological approach to identify compounds that exert positive and negative effects on oligodendroglia, depending on concentration. Notably, next generation pharmacogenomic analysis identified the PI3K/Akt modulator LY294002 as the most highly ranked small molecule with both pro- and anti-oligodendroglial concentration-dependent effects. We validated these in silico findings using multidisciplinary approaches to reveal a profoundly bipartite effect of LY294002 on the generation of OPCs and their differentiation into myelinating oligodendrocytes in both postnatal and adult contexts. Finally, we employed transcriptional profiling and signalling pathway activity assays to determine cell-specific mechanisms of action of LY294002 on oligodendrocytes and resolve optimal in vivo conditions required to promote myelin repair. These results demonstrate the power of multidisciplinary strategies in determining the therapeutic potential of small molecules in neurodegenerative disorders.

SUBMITTER: Rivera AD

PROVIDER: S-EPMC8664715 | biostudies-literature |

REPOSITORIES: biostudies-literature

ACCESS DATA

Similar Datasets

Project description:Patients with esophageal carcinoma (ESCA) have a poor prognosis and high mortality rate. Although standard therapies have had effect, there is an urgent requirement to develop novel options, as increasing drug tolerance has been identified in clinical practice. In the present study, differentially expressed genes (DEGs) of ESCA were identified in The Cancer Genome Atlas and Genotype?Tissue Expression databases. Functional and protein?protein interaction (PPI) analyses were performed. The Connectivity Map (CMAP) was selected to predict drugs for the treatment of ESCA, and their target genes were acquired from the Search Tool for Interactions of Chemicals (STITCH) by uploading the Simplified Molecular?Input Line?Entry System structure. Additionally, significant target genes and ESCA?associated hub genes were extracted using another PPI analysis, and the corresponding drugs were added to construct a network. Furthermore, the binding affinity between predicted drug candidates and ESCA?associated hub genes was calculated using molecular docking. Finally, 827 DEGs (|log2 fold?change|?2; q?value <0.05), which are principally involved in protein digestion and absorption (P<0.005), the plasminogen?activating cascade (P<0.01), as well as the 'biological regulation' of the Biological Process, 'membrane' of the Cellular Component and 'protein binding' of the Molecular Function categories, were obtained. Additionally, 11 hub genes were obtained from the PPI network (all degrees ?30). Furthermore, the 15 first screen drugs were extracted from CMAP (score <?0.85) and the 9 second screen drugs with 70 target genes were extracted from STITCH. Furthermore, another PPI analysis extracted 51 genes, and apigenin, baclofen, Prestwick?685, menadione, butyl hydroxybenzoate, gliclazide and valproate were selected as drug candidates for ESCA. Those molecular docking results with a docking score of >5.52 indicated the significance of apigenin, Prestwick?685 and menadione. The results of the present study may lead to novel drug candidates for ESCA, among which Prestwick?685 and menadione were identified to be significant new drug candidates.

Dataset Information

Drug connectivity mapping and functional analysis reveal therapeutic small molecules that differentially modulate myelination.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets