Institute of Bioinformatics and Applied Biotechnology (IBAB), Biotech Park, Electronics City Phase I, Bengaluru, Karnataka, India.
Manipal Academy of Higher Education, Manipal, Karnataka, India.
PLoS One. 2018 Jun 21;13(6):e0199530. doi: 10.1371/journal.pone.0199530. eCollection 2018.
Rheumatoid arthritis (RA) is a chronic inflammatory disease of the synovial joints. Though the current RA therapeutics such as disease-modifying antirheumatic drugs (DMARDs), nonsteroidal anti-inflammatory drugs (NSAIDs) and biologics can halt the progression of the disease, none of these would either dramatically reduce or cure RA. So, the identification of potential therapeutic targets and new therapies for RA are active areas of research. Several studies have discovered the involvement of cytokines in the pathogenesis of this disease. These cytokines induce signal transduction pathways in RA synovial fibroblasts (RASF). These pathways share many signal transducers and their interacting proteins, resulting in the formation of a signaling network. In order to understand the involvement of this network in RA pathogenesis, it is essential to identify the key transducers and their interacting proteins that are part of this network. In this study, based on a detailed literature survey, we have identified a list of 12 cytokines that induce signal transduction pathways in RASF. For these cytokines, we have built a signaling network using the protein-protein interaction (PPI) data that was obtained from public repositories such as HPRD, BioGRID, MINT, IntAct and STRING. By combining the network centrality measures with the gene expression data from the RA related microarrays that are available in the open source Gene Expression Omnibus (GEO) database, we have identified 24 key proteins of this signaling network. Two of these 24 are already drug targets for RA, and of the remaining, 12 have direct PPI links to some of the current drug targets of RA. Therefore, these key proteins seem to be crucial in the pathogenesis of RA and hence might be treated as potential drug targets.
类风湿关节炎(RA)是一种慢性炎症性疾病的滑膜关节。虽然目前的类风湿关节炎的治疗,如改善病情抗风湿药(DMARDs)、非甾体抗炎药(NSAIDs)和生物制剂可以阻止疾病的进展,但是没有一种药物可以显著减少或治愈 RA。因此,寻找潜在的治疗靶点和新的治疗方法是类风湿关节炎研究的活跃领域。一些研究已经发现细胞因子在这种疾病的发病机制中的作用。这些细胞因子在 RA 滑膜成纤维细胞(RASF)中诱导信号转导途径。这些途径共享许多信号转导器及其相互作用的蛋白质,从而形成一个信号网络。为了了解该网络在 RA 发病机制中的作用,识别该网络中的关键转导器及其相互作用的蛋白质是非常重要的。在这项研究中,我们根据详细的文献调查,确定了一组 12 种细胞因子,这些细胞因子可诱导 RASF 中的信号转导途径。对于这些细胞因子,我们使用从 HPRD、BioGRID、MINT、IntAct 和 STRING 等公共数据库中获得的蛋白质-蛋白质相互作用(PPI)数据构建了一个信号网络。通过将网络中心性度量与可从开放源代码基因表达综合数据库(GEO)中获得的 RA 相关微阵列的基因表达数据相结合,我们确定了这个信号网络的 24 个关键蛋白质。这 24 个关键蛋白质中有 2 个是 RA 的药物靶点,其余的 12 个与 RA 的一些现有药物靶点有直接的 PPI 联系。因此,这些关键蛋白质在 RA 的发病机制中似乎是至关重要的,因此可能被视为潜在的药物靶点。