Department of Biophysics, University of Delhi South Campus, New Delhi 110021, India.
Bioinformatics. 2023 Nov 1;39(11). doi: 10.1093/bioinformatics/btad677.
Fungal pathogens are known to cause life threatening invasive infections with rising global mortality rates. Besides, the indiscriminate use of antifungals in both clinics and agriculture has promoted antifungal drug resistance in the last decade. Fungi can show drug resistance by a variety of mechanisms. But primary driver in all these hitherto documented mechanisms is stable and heritable point mutations in the key proteins. Therefore, cataloguing mutations that can confer resistance is the first step toward understanding the mechanisms leading to the emergence of antifungal resistance.
In the present, work we have described a database of all the mutations responsible for antifungal resistance. Named as antifungal resistance database (AFRbase), it is better than the existing databases of antifungal resistance namely, FunResDB and MARDy which have a limited scope and inadequate information. Data of AFRbase was collected using both text mining and manual curation. AFRbase provides a separate window for visualization of mutations in the 2D and 3D formats making it easy for researchers to analyze the mutation data and ensures interoperability with other standard molecular biology databases like NCBI and UniProtKB. We hope AFRbase can be useful to both clinicians and basic biomedical scientists as we envision it as an important resource for genotypic susceptibility testing of fungi and to study/predict the course of evolution of antifungal resistance. The current version of AFRbase contains manually curated 3691 unique mutations present in 29 proteins of 32 fungal species along with the information of drugs against which resistance is caused.
AFRbase is an open access database available at http://proteininformatics.org/mkumar/afrbase/.
真菌病原体已知会导致危及生命的侵袭性感染，全球死亡率不断上升。此外，在临床和农业中不分青红皂白地使用抗真菌药物，在过去十年中促进了抗真菌药物耐药性的产生。真菌可以通过多种机制表现出耐药性。但在迄今为止所有记录的机制中，主要驱动因素是关键蛋白中的稳定和可遗传的点突变。因此，编目可导致耐药性的突变是理解导致抗真菌耐药性出现的机制的第一步。
在目前的工作中，我们描述了一个负责抗真菌耐药性的所有突变的数据库。命名为抗真菌耐药性数据库 (AFRbase)，它优于现有的抗真菌耐药性数据库，即 FunResDB 和 MARDy，它们的范围有限，信息不足。AFRbase 数据是使用文本挖掘和手动策展收集的。AFRbase 为在 2D 和 3D 格式中可视化突变提供了一个单独的窗口，使研究人员更容易分析突变数据，并确保与其他标准分子生物学数据库（如 NCBI 和 UniProtKB）的互操作性。我们希望 AFRbase 对临床医生和基础生物医学科学家都有用，因为我们设想它是真菌基因型药敏试验的重要资源，并研究/预测抗真菌耐药性的进化过程。当前版本的 AFRbase 包含手动策展的 3691 个独特突变，存在于 32 种真菌物种的 29 种蛋白质中，以及引起耐药性的药物信息。
AFRbase 是一个开放获取的数据库，可在 http://proteininformatics.org/mkumar/afrbase/ 访问。
