Systematic analysis to identify novel disease indications and plausible potential chemical leads of glutamate ionotropic receptor NMDA type subunit 1, GRIN1

IF 2.3 4区 生物学 Q3 BIOCHEMISTRY & MOLECULAR BIOLOGY Journal of Molecular Recognition Pub Date : 2022-10-19 DOI:10.1002/jmr.2997
Tulika Bhardwaj, Irshad Ahmad, Pallavi Somvanshi
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引用次数: 3

Abstract

Schizophrenia is a mental illness affecting the normal lifestyle of adults and early adolescents incurring major symptoms as jumbled speech, involvement in everyday activities eventually got reduced, patients always struggle with attention and memory, reason being both the genetic and environmental factors responsible for altered brain chemistry and structure, resulting in schizophrenia and associated orphan diseases. The network biology describes the interactions among genes/proteins encoding molecular mechanisms of biological processes, development, and diseases. Besides, all the molecular networks, protein-protein Interaction Networks have been significant in distinguishing the pathogenesis of diseases and thereby drug discovery. The present meta-analysis prioritizes novel disease indications viz. rare and orphan diseases associated with target Glutamate Ionotropic Receptor NMDA Type Subunit 1, GRIN1 using text mining knowledge-based tools. Furthermore, ZINC database was virtually screened, and binding conformation of selected compounds was performed and resulted in the identification of Narciclasine (ZINC04097652) and Alvespimycin (ZINC73138787) as potential inhibitors. Furthermore, docked complexes were subjected to MD simulation studies which suggests that the identified leads could be a better potential drug to recuperate schizophrenia.

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系统分析谷氨酸嗜离子受体NMDA型亚基1 GRIN1的新疾病适应症和可能的潜在化学线索
精神分裂症是一种影响成年人和早期青少年正常生活方式的精神疾病,其主要症状是言语混乱,日常活动参与度最终减少,患者总是在注意力和记忆力方面挣扎,原因是遗传和环境因素导致大脑化学和结构的改变,导致精神分裂症和相关的孤儿疾病。网络生物学描述了编码生物过程、发育和疾病的分子机制的基因/蛋白质之间的相互作用。此外,所有的分子网络,蛋白质-蛋白质相互作用网络在区分疾病的发病机制从而发现药物方面都具有重要意义。本荟萃分析使用基于文本挖掘知识的工具,优先考虑新的疾病适应症,即与靶谷氨酸离子化受体NMDA型亚单位1 (GRIN1)相关的罕见病和孤儿病。此外,对锌数据库进行虚拟筛选,并对选定的化合物进行结合构象分析,结果发现水仙素(ZINC04097652)和阿尔维霉素(ZINC73138787)是潜在的抑制剂。此外,对接的复合物进行了MD模拟研究,这表明所鉴定的导联物可能是一种更好的潜在治疗精神分裂症的药物。
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来源期刊
Journal of Molecular Recognition
Journal of Molecular Recognition 生物-生化与分子生物学
CiteScore
4.60
自引率
3.70%
发文量
68
审稿时长
2.7 months
期刊介绍: Journal of Molecular Recognition (JMR) publishes original research papers and reviews describing substantial advances in our understanding of molecular recognition phenomena in life sciences, covering all aspects from biochemistry, molecular biology, medicine, and biophysics. The research may employ experimental, theoretical and/or computational approaches. The focus of the journal is on recognition phenomena involving biomolecules and their biological / biochemical partners rather than on the recognition of metal ions or inorganic compounds. Molecular recognition involves non-covalent specific interactions between two or more biological molecules, molecular aggregates, cellular modules or organelles, as exemplified by receptor-ligand, antigen-antibody, nucleic acid-protein, sugar-lectin, to mention just a few of the possible interactions. The journal invites manuscripts that aim to achieve a complete description of molecular recognition mechanisms between well-characterized biomolecules in terms of structure, dynamics and biological activity. Such studies may help the future development of new drugs and vaccines, although the experimental testing of new drugs and vaccines falls outside the scope of the journal. Manuscripts that describe the application of standard approaches and techniques to design or model new molecular entities or to describe interactions between biomolecules, but do not provide new insights into molecular recognition processes will not be considered. Similarly, manuscripts involving biomolecules uncharacterized at the sequence level (e.g. calf thymus DNA) will not be considered.
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