Publication:
Systematic Identification of Synergistic Drug Pairs Targeting HIV

Thumbnail Image

Open/View Files

Date

2012

Published Version

Journal Title

Journal ISSN

Volume Title

Publisher

The Harvard community has made this article openly available. Please share how this access benefits you.

Research Projects

Organizational Units

Journal Issue

Citation

Tan, Xu, Long Hu, Lovelace J. Luquette, Geng Gao, Yifang Liu, Hongjing Qu, Ruibin Xi, Zhi John Lu, Peter J. Park, and Stephen J. Elledge. 2012. Systematic identification of synergistic drug pairs targeting hiv. Nature biotechnology 30(11): 1125-1130.

Research Data

Abstract

The systematic identification of effective drug combinations has been hindered by the unavailability of methods that can explore the large combinatorial search space of drug interactions. Here we present a multiplex screening method named MuSIC (Multiplex Screening for Interacting Compounds), which expedites the comprehensive assessment of pair-wise compound interactions. We examined ~500,000 drug pairs from 1000 FDA-approved or clinically tested drugs and identified drugs that synergize to inhibit HIV replication. Our analysis reveals an enrichment of anti-inflammatory drugs in drug combinations that synergize against HIV, indicating HIV benefits from inflammation that accompanies its infection. Multiple drug pairs identified in this study, including glucocorticoid and nitazoxanide, synergize by targeting different steps of the HIV life cycle. As inflammation accompanies HIV infection, our findings indicate that inhibiting inflammation could curb HIV propagation. MuSIC can be applied to a wide variety of disease-relevant screens to facilitate efficient identification of compound combinations.

Description

Keywords

Combination therapy, FDA-approved drug library, HIV

Terms of Use

This article is made available under the terms and conditions applicable to Other Posted Material (LAA), as set forth at Terms of Service

Endorsement

Review

Supplemented By

Referenced By

Related Stories