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癌症药物信息学:数据库和分析工具。

Cancer pharmacoinformatics: Databases and analytical tools.

机构信息

Department of Pharmacoinformatics, National Institute of Pharmaceutical Education and Research, S.A.S. Nagar, Punjab, India.

Center of Biomedical Engineering, Indian Institute of Technology Ropar, Rupnagar, Punjab, India.

出版信息

Funct Integr Genomics. 2024 Sep 19;24(5):166. doi: 10.1007/s10142-024-01445-5.

Abstract

Cancer is a subject of extensive investigation, and the utilization of omics technology has resulted in the generation of substantial volumes of big data in cancer research. Numerous databases are being developed to manage and organize this data effectively. These databases encompass various domains such as genomics, transcriptomics, proteomics, metabolomics, immunology, and drug discovery. The application of computational tools into various core components of pharmaceutical sciences constitutes "Pharmacoinformatics", an emerging paradigm in rational drug discovery. The three major features of pharmacoinformatics include (i) Structure modelling of putative drugs and targets, (ii) Compilation of databases and analysis using statistical approaches, and (iii) Employing artificial intelligence/machine learning algorithms for the discovery of novel therapeutic molecules. The development, updating, and analysis of databases using statistical approaches play a pivotal role in pharmacoinformatics. Multiple software tools are associated with oncoinformatics research. This review catalogs the databases and computational tools related to cancer drug discovery and highlights their potential implications in the pharmacoinformatics of cancer.

摘要

癌症是一个广泛研究的课题,组学技术的应用使得癌症研究产生了大量的大数据。目前正在开发许多数据库来有效地管理和组织这些数据。这些数据库涵盖了基因组学、转录组学、蛋白质组学、代谢组学、免疫学和药物发现等多个领域。将计算工具应用于药物科学的各个核心组成部分构成了“药物信息学”,这是合理药物发现的一个新兴范例。药物信息学的三个主要特点包括:(i)假定药物和靶点的结构建模,(ii)使用统计方法编译数据库和进行分析,以及(iii)使用人工智能/机器学习算法发现新的治疗分子。使用统计方法开发、更新和分析数据库在药物信息学中起着关键作用。与癌症药物发现相关的多个软件工具都与癌症药物发现相关联。本综述列出了与癌症药物发现相关的数据库和计算工具,并强调了它们在癌症药物信息学中的潜在意义。

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