scholarly journals Targeting HIV-1 Protease Autoprocessing for High-throughput Drug Discovery and Drug Resistance Assessment

2019 ◽  
Vol 9 (1) ◽  
Author(s):  
Liangqun Huang ◽  
Linfeng Li ◽  
ChihFeng Tien ◽  
Daniel V. LaBarbera ◽  
Chaoping Chen
Viruses ◽  
2019 ◽  
Vol 11 (9) ◽  
pp. 806
Author(s):  
Shambhu G. Aralaguppe ◽  
Anoop T. Ambikan ◽  
Manickam Ashokkumar ◽  
Milner M. Kumar ◽  
Luke Elizabeth Hanna ◽  
...  

The detection of drug resistance mutations (DRMs) in minor viral populations is of potential clinical importance. However, sophisticated computational infrastructure and competence for analysis of high-throughput sequencing (HTS) data lack at most diagnostic laboratories. Thus, we have proposed a new pipeline, MiDRMpol, to quantify DRM from the HIV-1 pol region. The gag-vpu region of 87 plasma samples from HIV-infected individuals from three cohorts was amplified and sequenced by Illumina HiSeq2500. The sequence reads were adapter-trimmed, followed by analysis using in-house scripts. Samples from Swedish and Ethiopian cohorts were also sequenced by Sanger sequencing. The pipeline was validated against the online tool PASeq (Polymorphism Analysis by Sequencing). Based on an error rate of <1%, a value of >1% was set as reliable to consider a minor variant. Both pipelines detected the mutations in the dominant viral populations, while discrepancies were observed in minor viral populations. In five HIV-1 subtype C samples, minor mutations were detected at the <5% level by MiDRMpol but not by PASeq. MiDRMpol is a computationally as well as labor efficient bioinformatics pipeline for the detection of DRM from HTS data. It identifies minor viral populations (<20%) of DRMs. Our method can be incorporated into large-scale surveillance of HIV-1 DRM.


2020 ◽  
Vol 75 (12) ◽  
pp. 3510-3516 ◽  
Author(s):  
Jessica M Fogel ◽  
David Bonsall ◽  
Vanessa Cummings ◽  
Rory Bowden ◽  
Tanya Golubchik ◽  
...  

Abstract Objectives To evaluate the performance of a high-throughput research assay for HIV drug resistance testing based on whole genome next-generation sequencing (NGS) that also quantifies HIV viral load. Methods Plasma samples (n = 145) were obtained from HIV-positive MSM (HPTN 078). Samples were analysed using clinical assays (the ViroSeq HIV-1 Genotyping System and the Abbott RealTime HIV-1 Viral Load assay) and a research assay based on whole-genome NGS (veSEQ-HIV). Results HIV protease and reverse transcriptase sequences (n = 142) and integrase sequences (n = 138) were obtained using ViroSeq. Sequences from all three regions were obtained for 100 (70.4%) of the 142 samples using veSEQ-HIV; results were obtained more frequently for samples with higher viral loads (93.5% for 93 samples with &gt;5000 copies/mL; 50.0% for 26 samples with 1000–5000 copies/mL; 0% for 23 samples with &lt;1000 copies/mL). For samples with results from both methods, drug resistance mutations (DRMs) were detected in 33 samples using ViroSeq and 42 samples using veSEQ-HIV (detection threshold: 5.0%). Overall, 146 major DRMs were detected; 107 were detected by both methods, 37 were detected by veSEQ-HIV only (frequency range: 5.0%–30.6%) and two were detected by ViroSeq only. HIV viral loads estimated by veSEQ-HIV strongly correlated with results from the Abbott RealTime Viral Load assay (R2 = 0.85; n = 142). Conclusions The NGS-based veSEQ-HIV method provided results for most samples with higher viral loads, was accurate for detecting major DRMs, and detected mutations at lower levels compared with a method based on population sequencing. The veSEQ-HIV method also provided HIV viral load data.


2003 ◽  
Vol 47 (2) ◽  
pp. 501-508 ◽  
Author(s):  
Martin E. Adelson ◽  
Annmarie L. Pacchia ◽  
Malvika Kaul ◽  
Robert F. Rando ◽  
Yacov Ron ◽  
...  

ABSTRACT The emergence of human immunodeficiency virus type 1 (HIV-1) strains resistant to highly active antiretroviral therapy necessitates continued drug discovery for the treatment of HIV-1 infection. Most current drug discovery strategies focus upon a single aspect of HIV-1 replication. A virus-cell-based assay, which can be adapted to high-throughput screening, would allow the screening of multiple targets simultaneously. HIV-1-based vector systems mimic the HIV-1 life cycle without yielding replication-competent virus, making them potentially important tools for the development of safe, wide-ranging, rapid, and cost-effective assays amenable to high-throughput screening. Since replication of vector virus is typically restricted to a single cycle, a crucial question is whether such an assay provides the needed sensitivity to detect potential HIV-1 inhibitors. With a stable, inducible vector virus-producing cell line, the inhibitory effects of four reverse transcriptase inhibitors (zidovudine, stavudine, lamivudine, and didanosine) and one protease inhibitor (indinavir) were assessed. It was found that HIV-1 vector virus titer was inhibited in a single cycle of replication up to 300-fold without affecting cell viability, indicating that the assay provides the necessary sensitivity for identifying antiviral molecules. Thus, it seems likely that HIV-1-derived vector systems can be utilized in a novel fashion to facilitate the development of a safe, efficient method for screening compound libraries for anti-HIV-1 activity.


2007 ◽  
Vol 12 (7) ◽  
pp. 946-955 ◽  
Author(s):  
Nicholas L. Mills ◽  
Anang A. Shelat ◽  
R. Kiplin Guy

The lack of lead compounds that specifically recognize and manipulate the function of RNA molecules limits our ability to consider RNA targets valid for drug discovery. Herein is reported a high-throughput biochemical screen for inhibitors of RNA-protein interactions based on AlphaScreen technology that incorporates several layers of specificity measurements into the primary screen. This screen was used to analyze approximately 5500 compounds from a collection of bioactive small molecules to detect inhibitors of the HIV-1 Rev-RRE and BIV Tat-TAR interactions. This proof-of-concept screen validates the assay as one that accurately identifies hit molecules and determines the selectivity of those hits. ( Journal of Biomolecular Screening 2007: 946-955)


2021 ◽  
Vol 21 (1) ◽  
Author(s):  
Adetayo Emmanuel Obasa ◽  
Anoop T. Ambikan ◽  
Soham Gupta ◽  
Ujjwal Neogi ◽  
Graeme Brendon Jacobs

Abstract Background HIV-1C has been shown to have a greater risk of virological failure and reduced susceptibility towards boosted protease inhibitors (bPIs), a component of second-line combination antiretroviral therapy (cART) in South Africa. This study entailed an evaluation of HIV-1 drug resistance-associated mutations (RAMs) among minor viral populations through high-throughput sequencing genotypic resistance testing (HTS-GRT) in patients on the South African national second-line cART regimen receiving bPIs. Methods During 2017 and 2018, 67 patient samples were sequenced using high-throughput sequencing (HTS), of which 56 samples were included in the final analysis because the patient’s treatment regimen was available at the time of sampling. All patients were receiving bPIs as part of their cART. Viral RNA was extracted, and complete pol genes were amplified and sequenced using Illumina HiSeq2500, followed by bioinformatics analysis to quantify the RAMs according to the Stanford HIV Drug Resistance Database. Results Statistically significantly higher PI RAMs were observed in minor viral quasispecies (25%; 14/56) compared to non-nucleoside reverse transcriptase inhibitors (9%; 5/56; p = 0.042) and integrase inhibitor RAM (4%; 2/56; p = 0.002). The majority of the drug resistance mutations in the minor viral quasispecies were observed in the V82A mutation (n = 13) in protease and K65R (n = 5), K103N (n = 7) and M184V (n = 5) in reverse transcriptase. Conclusions HTS-GRT improved the identification of PI and reverse transcriptase inhibitor (RTI) RAMs in second-line cART patients from South Africa compared to the conventional GRT with ≥20% used in Sanger-based sequencing. Several RTI RAMs, such as K65R, M184V or K103N and PI RAM V82A, were identified in < 20% of the population. Deep sequencing could be of greater value in detecting acquired resistance mutations early.


2009 ◽  
Vol 14 (2) ◽  
Author(s):  
Sandra R. R. Simonetti ◽  
Dirce B. De Lima ◽  
Hermann G. Schatzmayr ◽  
Bruno R. Simonetti ◽  
Denise C. N. Sztajnbok ◽  
...  

2009 ◽  
Vol 14 (1) ◽  
Author(s):  
Sandra R. R. Simonetti ◽  
Dirce B. De Lima ◽  
Hermann G. Schatzmayr ◽  
Bruno R. Simonetti ◽  
Denise C. N. Sztajnbok ◽  
...  

AIDS ◽  
2021 ◽  
Vol 35 (2) ◽  
pp. 227-234
Author(s):  
Emmi Andersson ◽  
Anoop Ambikan ◽  
Johanna Brännström ◽  
Shambhu G. Aralaguppe ◽  
Aylin Yilmaz ◽  
...  

2016 ◽  
Author(s):  
Steven K. Albanese ◽  
Daniel L. Parton ◽  
Mehtap Işık ◽  
Lucelenie Rodríguez-Laureano ◽  
Sonya M. Hanson ◽  
...  

AbstractKinases play a critical role in many cellular signaling pathways and are dysregulated in a number of diseases, such as cancer, diabetes, and neurodegeneration. Since the FDA approval of imatinib in 2001, therapeutics targeting kinases now account for roughly 50% of current cancer drug discovery efforts. The ability to explore human kinase biochemistry, biophysics, and structural biology in the laboratory is essential to making rapid progress in understanding kinase regulation, designing selective inhibitors, and studying the emergence of drug resistance. While insect and mammalian expression systems are frequently used for the expression of human kinases, bacterial expression systems are superior in terms of simplicity and cost-effectiveness but have historically struggled with human kinase expression. Following the discovery that phosphatase coexpression could produce high yields of Src and Abl kinase domains in bacterial expression systems, we have generated a library of 52 His-tagged human kinase domain constructs that express above 2 µg/mL culture in a simple automated bacterial expression system utilizing phosphatase coexpression (YopH for Tyr kinases, Lambda for Ser/Thr kinases). Here, we report a structural bioinformatics approach to identify kinase domain constructs previously expressed in bacteria likely to express well in a simple high-throughput protocol, experiments demonstrating our simple construct selection strategy selects constructs with good expression yields in a test of 84 potential kinase domain boundaries for Abl, and yields from a high-throughput expression screen of 96 human kinase constructs. Using a fluorescence-based thermostability assay and a fluorescent ATP-competitive inhibitor, we show that the highest-expressing kinases are folded and have well-formed ATP binding sites. We also demonstrate how the resulting expressing constructs can be used for the biophysical and biochemical study of clinical mutations by engineering a panel of 48 Src mutations and 46 Abl mutations via single-primer mutagenesis and screening the resulting library for expression yields. The wild-type kinase construct library is available publicly via Addgene, and should prove to be of high utility for experiments focused on drug discovery and the emergence of drug resistance.


2021 ◽  
Author(s):  
Adetayo Emmanuel Obasa ◽  
Anoop T Ambikan ◽  
Soham Gupta ◽  
Ujjwal Neogi ◽  
Graeme Brendon Jacobs

Abstract Background: HIV-1C has been shown to have a greater risk of virological failure and reduced susceptibility towards boosted protease inhibitors (bPIs), a component of second-line combination antiretroviral therapy (cART) in South Africa. This study entailed an evaluation of HIV-1 drug resistance-associated mutations (RAMs) among minor viral populations through high-throughput sequencing genotypic resistance testing (HTS-GRT) in patients on the South African national second-line cART regimen receiving bPIs.Methods: During 2017 and 2018, 67 patient samples were sequenced using high throughput sequencing (HTS), of which 56 samples were included in the analysis because the patient’s treatment regimen were available at the time of sampling. All patients were receiving bPIs as part of their cART. Viral RNA was extracted, and complete pol genes were amplified and sequenced using Illumina HiSeq2500, followed by bioinformatics analysis to quantify the RAMs according to the Stanford HIV Drug Resistance Database.Results: Statistically significantly higher PI RAMs were observed in minor viral quasispecies (25%; 14/56) compared to non-nucleoside reverse transcriptase inhibitors (9%; 5/56; p=0.042) and integrase inhibitor RAM (4%; 2/56; p=0.002). The majority of the drug resistance mutations in the minor viral quasispecies were observed in the V82A mutation (n=13) in protease and K65R (n=5), K103N (n=7) and M184V (n=5) in reverse transcriptase.Conclusions: HTS-GRT improved the identification of PI and reverse transcriptase inhibitor (RTI) RAMs in second-line cART patients from South Africa compared to the conventional GRT with ≥20% used in Sanger-based sequencing. Several RTI RAMs, such as K65R, M184V or K103N and PI RAM V82A, were identified in <20% of the population. Deep sequencing could be of greater value in detecting acquired resistance mutations early.


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