HDAC1预测器:一种简单透明的应用程序,用于组蛋白去乙酰化酶1抑制剂的虚拟筛选。

IF 2.3 3区 环境科学与生态学 Q3 CHEMISTRY, MULTIDISCIPLINARY
O V Tinkov, V Y Grigorev, L D Grigoreva, V N Osipov
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引用次数: 0

摘要

组蛋白去乙酰化酶通过修饰组蛋白和改变染色质构象在调节基因表达中发挥重要作用。HDAC失调与许多疾病有关,如癌症、自身免疫性疾病和神经退行性疾病。组蛋白去乙酰化酶1 (HDAC1)抑制剂是一类重要的药物。利用二维RDKit分子描述符建立定量构效关系(QSAR)分类模型;ECPF4(扩展连接指纹)圆形指纹;以及随机森林、梯度增强和支持向量机方法。开发的模型被集成到HDAC1 PREDICTOR应用程序中,该应用程序可在链接https://ovttiras-hdac1-inhibitors-hdac1-predictor-app-z3mrbr.streamlitapp.com上免费获得。HDAC1 PREDICTOR web应用程序允许人们揭示预测抑制HDAC1活性高于参考Vorinostat化合物的化合物(IC50 = 11.08 nM)。在HDAC1 PREDICTOR中实现的用于确定分子片段对抑制活性贡献的算法可以用来找到增加或减少活性的分子片段,使研究人员能够对新的高活性HDAC1抑制剂进行合理的分子设计。开发的QSAR模型及其用Python编程语言构建的代码可以在GitHub平台上免费获得,网址为https://github.com/ovttiras/HDAC1-inhibitors。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
HDAC1 PREDICTOR: a simple and transparent application for virtual screening of histone deacetylase 1 inhibitors.

Histone deacetylases play an important role in regulating gene expression by modifying histones and changing chromatin conformation. HDAC dysregulation is involved in many diseases, such as cancer, autoimmune and neurodegenerative diseases. Histone deacetylase 1 (HDAC1) inhibitors represent an important class of drugs. Quantitative Structure-Activity Relationship (QSAR) classification models were developed using 2D RDKit molecular descriptors; ECPF4 (Extended Connectivity Fingerprint) circular fingerprints; and the Random Forest, Gradient Boosting, and Support Vector Machine methods. The developed models were integrated into the HDAC1 PREDICTOR application, which is freely available at the link https://ovttiras-hdac1-inhibitors-hdac1-predictor-app-z3mrbr.streamlitapp.com. The HDAC1 PREDICTOR web application allows one to reveal the compounds for which the predicted activity to inhibit HDAC1 is higher than that of the reference Vorinostat compound (IC50 = 11.08 nM). The algorithm implemented in HDAC1 PREDICTOR for determining the contributions of molecular fragments to the inhibitory activity can be used to find the molecule segments that increase or decrease the activity, enabling the researcher to conduct a rational molecular design of new highly active HDAC1 inhibitors. The developed QSAR models and the code for their construction in the Python programming language are freely available on the GitHub platform at https://github.com/ovttiras/HDAC1-inhibitors.

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来源期刊
CiteScore
5.20
自引率
20.00%
发文量
78
审稿时长
>24 weeks
期刊介绍: SAR and QSAR in Environmental Research is an international journal welcoming papers on the fundamental and practical aspects of the structure-activity and structure-property relationships in the fields of environmental science, agrochemistry, toxicology, pharmacology and applied chemistry. A unique aspect of the journal is the focus on emerging techniques for the building of SAR and QSAR models in these widely varying fields. The scope of the journal includes, but is not limited to, the topics of topological and physicochemical descriptors, mathematical, statistical and graphical methods for data analysis, computer methods and programs, original applications and comparative studies. In addition to primary scientific papers, the journal contains reviews of books and software and news of conferences. Special issues on topics of current and widespread interest to the SAR and QSAR community will be published from time to time.
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