Custommune: a web tool to design personalized and population-targeted vaccine epitopes (preprint)

Computational prediction of immunogenic epitopes is a promising platform for therapeutic and preventive vaccine design. A potential target for this strategy is human immunodeficiency virus (HIV-1), for which, despite decades of efforts, no vaccine is available. In particular, a therapeutic vaccine devised to eliminate infected cells would represent a key component of cure strategies. HIV peptides designed based on individual viro-immunological data from people living with HIV/AIDS have recently shown able to induce post-therapy viral set point abatement. However, the reproducibility and scalability of this method is curtailed by the errors and arbitrariness associated with manual peptide design as well as by the time-consuming process. We herein introduce Custommune, a user-friendly web tool to design personalized and population-targeted vaccines. When applied to HIV-1, Custommune predicted personalized epitopes using patient specific Human Leukocyte Antigen (HLA) alleles and viral sequences, as well as the expected HLA-peptide binding strength and potential immune escape mutations. Of note, Custommune predictions compared favorably with manually designed peptides administered in a recent phase II clinical trial ( NCT02961829 ). Furthermore, we utilized Custommune to design preventive vaccines targeted for populations highly affected by COVID-19. The results allowed the identification of peptides tailored for each population and predicted to elicit both CD8 + T-cell immunity and neutralizing antibodies against structurally conserved epitopes of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). Overall, our data describe a new tool for rapid development of personalized or population-based immunotherapy against chronic and acute viral infections.

Pharmacokinetic bases of the hydroxychloroquine response in COVID-19: implications for therapy and prevention (preprint)

Chloroquine/hydroxychloroquine has recently been the subject of intense debate in regard to its potential antiviral activity against SARS-Cov-2, the etiological agent of COVID-19. Some report possible curative effects, others do not. In order to shed some light on this rather controversial topic, we used mathematical modelling to simulate possible scenarios of response to hydroxychloroquine in COVID-19 patients. Our computer-aided simulations show that hydroxychloroquine may have an impact on the amplitude of the viral load peak but that viral clearance is not significantly accelerated if the drug is not administered early enough (i.e. when viral loads range from 1 to 1,000 copies/mL). Although some authors had used the trough plasma concentrations or the theoretical drug distribution in the lung to model the effect of chloroquine/hydroxychloroquine on COVID-19, the theoretical drug response based on the trough whole blood concentrations of the drug agreed well with the results of the clinical trials so far reported. Moreover, the effects of chloroquine/hydroxychloroquine could be fully explained when taking into account also the capacity of this drug to raise cell-mediated responses against the productively SARS-Cov-2-infected cells. On the whole, the present study suggests that chloroquine/hydroxychloroquine has a narrow therapeutic window, which overlaps with the highest tolerated doses. These considerations may have implications for development of anti-COVID-19 combination therapies and prevention strategies.