HDAC2 SCAN: An Expert System for Virtual Screening of Histone Deacetylase 2 Inhibitors

被引：0

作者：

Tinkov, O. V. ^{[1
]}

Grigoreva, L. D. ^{[2
]}

Grigorev, V. Y. ^{[3
]}

机构：

[1] Shevchenko Transnistria State Univ, Tiraspol 3300, Moldova

[2] Lomonosov Moscow State Univ, Moscow 119991, Russia

[3] Russian Acad Sci, Fed Res Ctr Problems Chem Phys & Med Chem, Inst Physiol Act Cpds, Chernogolovka 142432, Russia

来源：

RUSSIAN JOURNAL OF GENERAL CHEMISTRY | 2023年 / 93卷 / SUPPL 2期

关键词：

QSAR; molecular descriptors; machine learning; Streamlit; DESIGN; DOCKING; QSAR; DERIVATIVES; PREDICTION;

D O I：

10.1134/S1070363223150021

中图分类号：

O6 [化学];

学科分类号：

0703 ;

摘要：

Histone deacetylase 2 inhibitors (HDAC2) are developed as effective drugs for the treatment of various diseases. Using various types of molecular descriptors, several adequate Quantitative Structure-Activity Relationship regression models for acute toxicity (LD50, rats, orally) of HDAC2 inhibitors have been proposed. The created adequate models are integrated into the developed HDAC2 SCAN application, freely available at https://hdac2scan.streamlit.app/. The HDAC2 SCAN application can be used for virtual screening.

引用

页码：S426 / S437

页数：12

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