Suppr超能文献

抗癌药物数据库的现状与未来应用

Current situation and future usage of anticancer drug databases.

作者信息

Wang Hongzhi, Yin Yuanyuan, Wang Peiqi, Xiong Chenyu, Huang Lingyu, Li Sijia, Li Xinyi, Fu Leilei

机构信息

College of Mathematics, Tonghua Normal University, Tonghua, 134002, China.

State Key Laboratory of Oral Diseases, West China Hospital of Stomatology, Sichuan University, Chengdu, 610041, China.

出版信息

Apoptosis. 2016 Jul;21(7):778-94. doi: 10.1007/s10495-016-1250-5.

Abstract

Cancer is a deadly disease with increasing incidence and mortality rates and affects the life quality of millions of people per year. The past 15 years have witnessed the rapid development of targeted therapy for cancer treatment, with numerous anticancer drugs, drug targets and related gene mutations been identified. The demand for better anticancer drugs and the advances in database technologies have propelled the development of databases related to anticancer drugs. These databases provide systematic collections of integrative information either directly on anticancer drugs or on a specific type of anticancer drugs with their own emphases on different aspects, such as drug-target interactions, the relationship between mutations in drug targets and drug resistance/sensitivity, drug-drug interactions, natural products with anticancer activity, anticancer peptides, synthetic lethality pairs and histone deacetylase inhibitors. We focus on a holistic view of the current situation and future usage of databases related to anticancer drugs and further discuss their strengths and weaknesses, in the hope of facilitating the discovery of new anticancer drugs with better clinical outcomes.

摘要

癌症是一种发病率和死亡率不断上升的致命疾病,每年影响着数百万人的生活质量。过去15年见证了癌症治疗靶向疗法的迅速发展,众多抗癌药物、药物靶点及相关基因突变已被确定。对抗癌药物的更高需求以及数据库技术的进步推动了抗癌药物相关数据库的发展。这些数据库直接提供有关抗癌药物或特定类型抗癌药物的综合信息系统收集,它们在不同方面有各自的侧重点,如药物-靶点相互作用、药物靶点突变与耐药性/敏感性之间的关系、药物-药物相互作用、具有抗癌活性的天然产物、抗癌肽、合成致死配对以及组蛋白去乙酰化酶抑制剂。我们着眼于抗癌药物相关数据库的现状和未来用途的整体视角,并进一步讨论它们的优缺点,希望有助于发现具有更好临床疗效的新型抗癌药物。

文献AI研究员

20分钟写一篇综述,助力文献阅读效率提升50倍。

立即体验

用中文搜PubMed

大模型驱动的PubMed中文搜索引擎

马上搜索

文档翻译

学术文献翻译模型,支持多种主流文档格式。

立即体验