Accelerated Discovery of Potent Fusion Inhibitors for Respiratory Syncytial Virus

被引：11

作者：

Pribut, Nicole ^{[1
]}

Kaiser, Thomas M. ^{[1
]}

Wilson, Robert J. ^{[1
]}

Jecs, Edgars ^{[1
]}

Dentmon, Zackery W. ^{[1
]}

Pelly, Stephen C. ^{[1
]}

Sharma, Savita ^{[1
]}

Bartsch, Perry W., III ^{[1
]}

Burger, Pieter B. ^{[1
]}

Hwang, Soyon S. ^{[1
]}

Le, Thalia ^{[1
]}

Sourimant, Julien ^{[2
]}

Yoon, Jeong-Joong ^{[2
]}

Plemper, Richard K. ^{[2
]}

Liotta, Dennis C. ^{[1
]}

机构：

[1] Emory Univ, Dept Chem, Atlanta, GA 30322 USA

[2] Georgia State Univ, Inst Biomed Sci, Atlanta, GA 30303 USA

来源：

ACS INFECTIOUS DISEASES | 2020年 / 6卷 / 05期

关键词：

RSV; fusion inhibitor; benzimidazole; machine learning; INFECTION; INFLUENZA; MECHANISM;

D O I：

10.1021/acsinfecdis.9b00524

中图分类号：

R914 [药物化学];

学科分类号：

100701 ;

摘要：

A series of five benzimidazole-based compounds were identified using a machine learning algorithm as potential inhibitors of the respiratory syncytial virus (RSV) fusion protein. These compounds were synthesized, and compound 2 in particular exhibited excellent in vitro potency with an EC50 value of 5 nM. This new scaffold was then further refined leading to the identification of compound 44, which exhibited a 10-fold improvement in activity with an EC50 value of 0.5 nM.

引用

页码：922 / 929

页数：8

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