Use of parallel validation high-throughput screens to reduce false positives and identify novel dengue NS2B-NS3 protease inhibitors

Abstract

Dengue virus (DENV), a mosquito-borne member of the family Flaviviridae, is a significant global pathogen affecting primarily tropical and subtropical regions of the world and placing tremendous burden on the limited medical infrastructure that exists in many of the developing countries located within these regions. Recent outbreaks in developed countries, including Australia (Hanna et al., 2009), France (La Ruche et al., 2010), Taiwan (Kuan et al., 2010), and the USA (CDC, 2010), lead many researchers to believe that continued emergence into more temperate latitudes is likely. A primary concern is that there are no approved vaccines or antiviral therapies to treat DENV infections. Since the viral NS2B-NS3 protease (DENV NS2B-NS3pro) is required for virus replication, it provides a strategic target for the development of antiviral drugs. In this study, proof-of-concept high-throughput screenings (HTSs) were performed to unambiguously identify dengue 2 virus (DEN2V) NS2B-NS3pro inhibitors from a library of 2000 compounds. Validation screens were performed in parallel to concurrently eliminate insoluble, auto-fluorescing, and/or nonspecific inhibitors. Kinetic analyses of the hits revealed that parallel substrate fluorophore (AMC) interference controls and trypsin inhibition controls were able to reduce false positive rates due to solubility and fluorophore interference while the trypsin inhibition control additionally eliminated non-specific inhibitors. We identified five DEN2V NS2B-NS3pro inhibitors that also inhibited the related West Nile virus (WNV) protease (NS2B-NS3pro), but did not inhibit the trypsin protease. Biochemical analyses revealed various mechanisms of inhibition including competitive and mixed noncompetitive inhibition, with the lowest K(i) values being 12±1.5 μM for DEN2V NS2B-NS3pro and 2±0.2 μM for WNV NS2B-NS3pro.

Figure 1

Relative activity of DEN2V NS2B-NS3pro. The black bars display the averaged relative fluorescence of the protease reaction in the presence of inhibitors. The fluorescence intensity was normalized to the averaged signal produced by the protease reaction without inhibitor (hatched bar, second from the left). The grey bars display the averaged relative fluorescence of AMC in the presence of inhibitors, normalized to the signal produced by AMC alone. The first hatched bar on the left-hand side is a control containing substrate alone.

Figure 2

Relative activity of DEN2V NS2B-NS3pro. The black bars display the averaged relative fluorescence of the protease reaction in the presence of inhibitors. The fluorescence intensity was normalized to the averaged signal produced by the protease reaction without inhibitor. The grey bars display the averaged relative fluorescence of AMC in the presence of inhibitors, normalized to the signal produced by AMC alone.

Figure 3

DEN2V protease reaction with the small peptide substrate Boc-Gly-Arg-Arg-AMC demonstrated Michaelis-Menten kinetics with substrate inhibition. The model curve was produced with the program Dynafit, which optimized the kinetic parameters in a substrate inhibition model (insert) to best fit the data points.

Figure 4

Representative curve for inhibitor MS28 (alexidine hydrochloride), which was modeled as having a mixed inhibition mechanism against DEN2V NS2B-NS3pro. Concentrations of MS28 tested were 0 (circles, top curve), 30 (squares, middle curve), and 100 (pentagons, lower curve) μM. Data were analyzed with the program Dynafit, with curves calculated from global fitting to the data points. Error bars were within the dimensions of the data points.

Figure 5

Chemical structures for lead DEN2V protease inhibitors: (A) ivermectin (MS21), (B) selamectin (MS24), (C) methylbenzethonium chloride (MS22), (D) tyrothricin (MS23), and (E) alexidine hydrochloride (MS28).

Figure 6

Hit rate as a function of replicate number and inclusion of AMC and trypsin internal controls.