High Throughput Assay for Identification of Novel HIV-1 Autoprocessing Inhibitors

Opportunity

Available for Licensing

IP Status

US Utility Patent Pending (Not Yet Published)

Inventors

Chaoping Chen
Liangqun Huang

At A Glance

Researchers at Colorado State University have developed a cell-based functional assay for high-throughput drug discovery of HIV-1 autoprocessing inhibitors and drug resistance assessment. 

Identification of these novel inhibitors will initiate an unprecedent combinational therapy by targeting a vital enzyme (HIV-1 protease) at two distinct functional states (precursor and mature protease) and at different regions (non-catalytic and catalytic site).  Such a strategy is expected to drastically decrease the likelihood (i.e., increase genetic barrier) for HIV to evolve viable strains resistant to both classes of inhibitor.  Furthermore, the assay provides an easy and reliable phenotypic tool to analyze drug resistance.

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Licensing Director

Steve Foster
Steve.Foster@colostate.edu
970-491-7100

Reference No.:  19-039

Background

​HIV-1 protease (PR) is one of the three viral encoded enzymes essential for productive viral replication. In the infected cell, the unspliced genomic RNA functions as the mRNA to mediate translation of two polyprotein precursors with the ratio between the two controlled by a regulated ribosomal frameshift. These polyproteins co-assemble into viral particles, which bud off from the infected cell. Upon or shortly after virion release, one polyprotein is triggered to undergo autoproteolysis resulting in the liberation of the free mature PR; a process generally referred to as PR autoprocessing. There are at least 10 cleavage sites within the polyproteins that can be processed by the mature PR at various rates and modulations. Concerted proteolysis of these sites is required for proper virion maturation that in turn determines viral infectivity.

HIV-1 protease autoprocessing is a complicated process in which a polyprotein precursor must function as both the catalyst and substrate before any mature PR becomes available. Extensive research efforts have focused on structural and enzymatic characterization of the mature PR, which has led to successful development of ten FDA-approved Protease Inhibitors (PIs). All PIs share the same mechanism of action and bind to the catalytic site of the mature PR with high affinities.  However, the protease autoprocessing mechanism remains largely undefined.

Technology Overview

To enable identification of novel inhibitors that selectively target the precursor-mediated autoproteolysis, amplified luminescent proximity homogeneous assay (AlphaLISA) was employed for quantification of autoprocessing efficiency using crude cell lysates for high throughput screening (HTS) drug discovery. The group: (1) compared quantification results from conventional western blotting and AlphaLISA analyses evaluating known HIV PIs for their efficacies at suppressing precursor autoprocessing; (2) carried out HTS of ~23,000 diverse small molecule compounds; and (3) examined autoprocessing of fusion precursors carrying mutations identified from patients experiencing PI resistance to determine the role of precursor autoprocessing in drug resistance development.  Results of these analyses collectively validated this newly developed AlphaLISA assay as a useful tool for HTS drug discovery targeting precursor autoproteolysis and to quantify PI resistance. (Published in Nature)

Benefits
  • High selectivity (advantageous for large-scale HTS campaigns)
  • Offers quantification of protease inhibitor (PI) resistance
  • Precursor autoprocessing is a critical step contributing to drug resistance
  • Inhibitors selectively targeting precursor autoprocessing will compensate the current cART in combating drug resistance
  • Inhibitors prevent essential HIV maturation, and prevent HIV resistance
Benefits
  • Identification of autoprocessing inhibitors of HIV-1 protease
  • HIV Drug Discovery
Publications

​Huang, L., Li, L., Tien, C. et al. Targeting HIV-1 Protease Autoprocessing for High-throughput Drug Discovery and Drug Resistance AssessmentSci Rep 9, 301 (2019). https://doi.org/10.1038/s41598-018-36730-4

Last updated: September 2020

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