Kinase Inhibitors and Nucleoside Analogues as Novel Therapies to Inhibit HIV-1 or ZEBOV Replication
Bibliographic record
Abstract
Without a vaccine for Human Immunodeficiency Virus type 1 (HIV-1), or approved therapy for treating Zaire Ebolavirus (ZEBOV) infection, new means to treat either virus during acute infection are under intense investigation. Repurposing tyrosine kinase inhibitors of known specificity may not only inhibit HIV-1 replication, but also treat associated inflammation or neurocognitive disorders caused by chronic HIV-1 infection. Moreover, tyrosine kinase inhibitors may effectively treat other infections, including ZEBOV. In addition, established nucleoside/nucleotide analogues that effectively inhibit HIV-1 infection, could also be repurposed to inhibit ZEBOV replication. In this work the role of two host cell kinases, cellular protoncogene SRC (c-SRC) and Protein Tyrosine Kinase 2 Beta (PTK2B), were found to have key roles during early HIV-1 replication in primary activated CD4+ T-cells ex vivo. siRNA knockdown of either kinase increased intracellular reverse transcripts and decreased nuclear proviral integration, suggesting they act at the level of pre-integration complex (PIC) formation or PIC nuclear translocation. c-SRC siRNA knockdown consistently reduced p24 levels of IIIB(X4) and Ba-L(R5) infection, or luciferase activity of HXB2(X4) or JR-FL(R5) recombinant viruses, prompting further drug inhibition studies of this kinase. Four c-SRC kinase inhibitors (dasatinib, saracatinib, KX2-391 and SRC Inhibitor-1) significantly reduced HXB2 and JR-FL infection in primary CD4+ T-cells. Thus, these potent c-SRC inhibitors should be further evaluated in humanized mouse models of HIV-1 infection. During 2014-16, the Ebola outbreak in West Africa prompted us to rapidly assess whether conventional nucleoside analogs could inhibit in vitro ZEBOV replication. Employing a new lifecycle model of ZEBOV infection in level 2 biocontainment, combinations of nucleoside analogues and interferons were found to synergistically inhibit ZEBOV replication. These included zidovudine, lamivudine and tenofovir, confirmed to show antiviral activity against fully infectious ZEBOV-GFP in level 4 biocontainment. Findings from this thesis provided the rationale for further preclinical development of nucleoside analogue combination treatments, and a phase II EVD trial evaluating recombinant interferon in Guinea. Pre-clinical results using c-SRC kinase inhibitors also suggest that this approach could also be effective in EVD.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".