{"title":"揭示 ALS 的治疗生物标志物和药物靶点:微阵列分析、分子对接和结构动力学综合研究","authors":"","doi":"10.1016/j.compbiolchem.2024.108211","DOIUrl":null,"url":null,"abstract":"<div><p>Amyotrophic lateral sclerosis (ALS), commonly known as Lou Gehrig's disease, is a debilitating neurodegenerative disorder characterized by the progressive degeneration of nerve cells in the brain and spinal cord. Despite extensive research, its precise etiology remains elusive, and early diagnosis is challenging due to the absence of specific tests. This study aimed to identify potential blood-based biomarkers for early ALS detection and monitoring using datasets from whole blood samples (GSE112680) and oligodendrocytes, astrocytes, and fibroblasts (GSE87385) obtained from the NCBI-GEO repository. Through bioinformatics analysis, including protein-protein interactions and molecular pathway analyses, we identified differentially expressed genes (DEGs) associated with ALS. Notably, ALS2, ADH7, ALDH8A1, ALDH3B1, ABHD2, ABHD17B, ABHD12, ABHD13, PGAM2, AURKB, ANAPC11, VAPA, UNC45B, and TNNT2 emerged as top-ranked DEGs, implicated in drug metabolism, protein depalmytilation, and the AKT/mTOR signaling pathways. Among these, AurKB established as a potential therapeutic biomarker with relevance to various neurological conditions. Consequently, AurKB was selected for identifying potential therapeutic molecules and utilized for <em>in silico</em> structural characterization studies. Exploration of the IMPATT database led to the discovery of a lead compound similar to Fostamatinib, currently used for AurKB. Initial molecular docking and MMGBSA-based binding energy analysis were followed by molecular dynamics simulation (MDS) and free energy landscape (FEL) analysis to validate the ligand's binding efficacy and understand dynamic processes within the biological system. The identified potential biomarkers and lead molecule provide novel insights into the correlation between blood cell transcripts and ALS pathology, paving the way for blood-based diagnostic tools for early ALS detection and ongoing disease monitoring.</p></div>","PeriodicalId":10616,"journal":{"name":"Computational Biology and Chemistry","volume":null,"pages":null},"PeriodicalIF":2.6000,"publicationDate":"2024-09-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Unveiling therapeutic biomarkers and druggable targets in ALS: An integrative microarray analysis, molecular docking, and structural dynamic studies\",\"authors\":\"\",\"doi\":\"10.1016/j.compbiolchem.2024.108211\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><p>Amyotrophic lateral sclerosis (ALS), commonly known as Lou Gehrig's disease, is a debilitating neurodegenerative disorder characterized by the progressive degeneration of nerve cells in the brain and spinal cord. Despite extensive research, its precise etiology remains elusive, and early diagnosis is challenging due to the absence of specific tests. This study aimed to identify potential blood-based biomarkers for early ALS detection and monitoring using datasets from whole blood samples (GSE112680) and oligodendrocytes, astrocytes, and fibroblasts (GSE87385) obtained from the NCBI-GEO repository. Through bioinformatics analysis, including protein-protein interactions and molecular pathway analyses, we identified differentially expressed genes (DEGs) associated with ALS. Notably, ALS2, ADH7, ALDH8A1, ALDH3B1, ABHD2, ABHD17B, ABHD12, ABHD13, PGAM2, AURKB, ANAPC11, VAPA, UNC45B, and TNNT2 emerged as top-ranked DEGs, implicated in drug metabolism, protein depalmytilation, and the AKT/mTOR signaling pathways. Among these, AurKB established as a potential therapeutic biomarker with relevance to various neurological conditions. Consequently, AurKB was selected for identifying potential therapeutic molecules and utilized for <em>in silico</em> structural characterization studies. Exploration of the IMPATT database led to the discovery of a lead compound similar to Fostamatinib, currently used for AurKB. Initial molecular docking and MMGBSA-based binding energy analysis were followed by molecular dynamics simulation (MDS) and free energy landscape (FEL) analysis to validate the ligand's binding efficacy and understand dynamic processes within the biological system. The identified potential biomarkers and lead molecule provide novel insights into the correlation between blood cell transcripts and ALS pathology, paving the way for blood-based diagnostic tools for early ALS detection and ongoing disease monitoring.</p></div>\",\"PeriodicalId\":10616,\"journal\":{\"name\":\"Computational Biology and Chemistry\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":2.6000,\"publicationDate\":\"2024-09-12\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Computational Biology and Chemistry\",\"FirstCategoryId\":\"99\",\"ListUrlMain\":\"https://www.sciencedirect.com/science/article/pii/S1476927124001993\",\"RegionNum\":4,\"RegionCategory\":\"生物学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q2\",\"JCRName\":\"BIOLOGY\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Computational Biology and Chemistry","FirstCategoryId":"99","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S1476927124001993","RegionNum":4,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"BIOLOGY","Score":null,"Total":0}
引用次数: 0
摘要
肌萎缩性脊髓侧索硬化症(ALS)俗称卢伽雷氏病,是一种使人衰弱的神经退行性疾病,其特征是大脑和脊髓中的神经细胞逐渐退化。尽管进行了广泛的研究,但其确切的病因仍然难以捉摸,而且由于缺乏特定的检测方法,早期诊断也很困难。本研究旨在利用从 NCBI-GEO 数据库中获得的全血样本(GSE112680)和少突胶质细胞、星形胶质细胞和成纤维细胞(GSE87385)数据集,鉴定用于早期 ALS 检测和监测的潜在血液生物标志物。通过生物信息学分析,包括蛋白-蛋白相互作用和分子通路分析,我们确定了与 ALS 相关的差异表达基因(DEGs)。值得注意的是,ALS2、ADH7、ALDH8A1、ALDH3B1、ABHD2、ABHD17B、ABHD12、ABHD13、PGAM2、AURKB、ANAPC11、VAPA、UNC45B 和 TNNT2 成为排名靠前的 DEGs,它们与药物代谢、蛋白质脱钙和 AKT/mTOR 信号通路有关。其中,AurKB 是一个潜在的治疗生物标志物,与各种神经疾病相关。因此,AurKB 被选中用于鉴定潜在的治疗分子,并被用于硅结构特征研究。通过探索 IMPATT 数据库,发现了一种与目前用于 AurKB 的 Fostamatinib 相似的先导化合物。初步的分子对接和基于 MMGBSA 的结合能分析之后,进行了分子动力学模拟(MDS)和自由能谱(FEL)分析,以验证配体的结合效能并了解生物系统内的动态过程。已确定的潜在生物标志物和先导分子为了解血细胞转录本与 ALS 病理学之间的相关性提供了新的视角,为基于血液的诊断工具铺平了道路,从而可用于 ALS 的早期检测和持续疾病监测。
Unveiling therapeutic biomarkers and druggable targets in ALS: An integrative microarray analysis, molecular docking, and structural dynamic studies
Amyotrophic lateral sclerosis (ALS), commonly known as Lou Gehrig's disease, is a debilitating neurodegenerative disorder characterized by the progressive degeneration of nerve cells in the brain and spinal cord. Despite extensive research, its precise etiology remains elusive, and early diagnosis is challenging due to the absence of specific tests. This study aimed to identify potential blood-based biomarkers for early ALS detection and monitoring using datasets from whole blood samples (GSE112680) and oligodendrocytes, astrocytes, and fibroblasts (GSE87385) obtained from the NCBI-GEO repository. Through bioinformatics analysis, including protein-protein interactions and molecular pathway analyses, we identified differentially expressed genes (DEGs) associated with ALS. Notably, ALS2, ADH7, ALDH8A1, ALDH3B1, ABHD2, ABHD17B, ABHD12, ABHD13, PGAM2, AURKB, ANAPC11, VAPA, UNC45B, and TNNT2 emerged as top-ranked DEGs, implicated in drug metabolism, protein depalmytilation, and the AKT/mTOR signaling pathways. Among these, AurKB established as a potential therapeutic biomarker with relevance to various neurological conditions. Consequently, AurKB was selected for identifying potential therapeutic molecules and utilized for in silico structural characterization studies. Exploration of the IMPATT database led to the discovery of a lead compound similar to Fostamatinib, currently used for AurKB. Initial molecular docking and MMGBSA-based binding energy analysis were followed by molecular dynamics simulation (MDS) and free energy landscape (FEL) analysis to validate the ligand's binding efficacy and understand dynamic processes within the biological system. The identified potential biomarkers and lead molecule provide novel insights into the correlation between blood cell transcripts and ALS pathology, paving the way for blood-based diagnostic tools for early ALS detection and ongoing disease monitoring.
期刊介绍:
Computational Biology and Chemistry publishes original research papers and review articles in all areas of computational life sciences. High quality research contributions with a major computational component in the areas of nucleic acid and protein sequence research, molecular evolution, molecular genetics (functional genomics and proteomics), theory and practice of either biology-specific or chemical-biology-specific modeling, and structural biology of nucleic acids and proteins are particularly welcome. Exceptionally high quality research work in bioinformatics, systems biology, ecology, computational pharmacology, metabolism, biomedical engineering, epidemiology, and statistical genetics will also be considered.
Given their inherent uncertainty, protein modeling and molecular docking studies should be thoroughly validated. In the absence of experimental results for validation, the use of molecular dynamics simulations along with detailed free energy calculations, for example, should be used as complementary techniques to support the major conclusions. Submissions of premature modeling exercises without additional biological insights will not be considered.
Review articles will generally be commissioned by the editors and should not be submitted to the journal without explicit invitation. However prospective authors are welcome to send a brief (one to three pages) synopsis, which will be evaluated by the editors.