PDF(Pubmed)
Abstract：
Due to the similarity and diversity among kinases, small molecule kinase inhibitors (SMKIs) often display multi-target effects or selectivity, which have a strong correlation with the efficacy and safety of these inhibitors. However, due to the limited number of well-known popular databases and their restricted data mining capabilities, along with the significant scarcity of databases focusing on the pharmacological similarity and diversity of SMIKIs, researchers find it challenging to quickly access relevant information. The KLIFS database is representative of specialized application databases in the field, focusing on kinase structure and co-crystallised kinase-ligand interactions, whereas the KLSD database in this paper emphasizes the analysis of SMKIs among all reported kinase targets. To solve the current problem of the lack of professional application databases in kinase research and to provide centralized, standardized, reliable and efficient data resources for kinase researchers, this paper proposes a research program based on the ChEMBL database. It focuses on kinase ligands activities comparisons. This scheme extracts kinase data and standardizes and normalizes them, then performs kinase target difference analysis to achieve kinase activity threshold judgement. It then constructs a specialized and personalized kinase database platform, adopts the front-end and back-end separation technology of SpringBoot architecture, constructs an extensible WEB application, handles the storage, retrieval and analysis of the data, ultimately realizing data visualization and interaction. This study aims to develop a kinase database platform to collect, organize, and provide standardized data related to kinases. By offering essential resources and tools, it supports kinase research and drug development, thereby advancing scientific research and innovation in kinase-related fields. It is freely accessible at: http://ai.njucm.edu.cn:8080.
摘要：
由于激酶之间的相似性和多样性，小分子激酶抑制剂(SMKIs)通常表现出多靶点效应或选择性，与这些抑制剂的疗效和安全性有很强的相关性。然而,由于著名的流行数据库数量有限，数据挖掘能力有限，随着专注于SMIKIs药理学相似性和多样性的数据库的显著稀缺，研究人员发现快速访问相关信息具有挑战性。KLIFS数据库是该领域专业应用数据库的代表，专注于激酶结构和共晶激酶-配体相互作用，而本文中的KLSD数据库强调了SMKIs在所有报道的激酶靶标中的分析。为解决目前激酶研究缺乏专业应用数据库的问题,标准化，激酶研究人员的可靠和有效的数据资源，本文提出了一种基于ChEMBL数据库的研究方案。它侧重于激酶配体活性比较。该方案提取激酶数据并对其进行标准化和规范化，然后进行激酶靶点差异分析,实现激酶活性阈值判断。然后，它构建了一个专门的和个性化的激酶数据库平台，采用SpringBoot架构的前端和后端分离技术，构造一个可扩展的WEB应用程序，处理存储，检索和分析数据，最终实现数据的可视化和交互。本研讨旨在开辟一个激酶数据库收集平台，组织,并提供与激酶相关的标准化数据。通过提供必要的资源和工具，它支持激酶研究和药物开发，从而推进激酶相关领域的科学研究和创新。它可以在http://ai免费访问。njucm.edu.cn:8080。
