Next-generation bNAbs for HIV-1 cure strategies

Schriek, A.I.; Aldon, Y.L.T.; van Gils, M.J.; de Taeye, S.W.

doi:10.1016/j.antiviral.2023.105788

Cited by 2 publications

(1 citation statement)

References 247 publications

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“…Still, the number of identi ed HIV bNAbs remains relatively low, with only 250 of them reported 3,20 . Some bNAbs have been investigated in registered clinical trials, for prevention, as a component of long-acting antiretroviral therapy (ART), or as a component of intervention aimed at long-term drug-free remission of HIV 17,21,22 .…”

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confidence: 99%

RAIN: a Machine Learning-based identification for HIV-1 bNAbs

Perez,

Foglierini

2024

Preprint

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Broadly neutralizing antibodies (bNAbs) are promising candidates for the treatment and prevention of HIV-1 infection. Despite their critical importance, automatic detection of HIV-1 bNAbs from immune repertoire is still lacking. Here, we developed a straightforward computational method for Rapid Automatic Identification of bNAbs (RAIN) based on Machine Learning methods. In contrast to other approaches using one-hot encoding amino acid sequences or structural alignment for prediction, RAIN uses a combination of selected sequence-based features for accurate prediction of HIV-1 bNAbs. We demonstrate the performance of our approach on non-biased, experimentally obtained sequenced BCR repertoires from HIV-1 immune donors. RAIN processing leads to the successful identification of novel HIV-1 bNAbs targeting the CD4-binding site of the envelope glycoprotein. In addition, we validate the identified bNAbs using in vitro neutralization assay and we solve the structure of one of them in complex with the soluble native-like heterotrimeric envelope glycoprotein by single-particle cryo-electron microscopy (cryo-EM). Overall, we propose a method to facilitate and accelerate HIV-1 bNAbs discovery from non-selected immune repertoires.

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confidence: 99%

RAIN: a Machine Learning-based identification for HIV-1 bNAbs

Perez,

Foglierini

2024

Preprint

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The Use of Broadly Neutralizing Antibodies (bNAbs) in HIV-1 Treatment and Prevention

Thavarajah,

Hønge,

Wejse

2024

Viruses

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Background: Although antiretroviral therapy (ART) effectively halts disease progression in HIV infection, the complete eradication of the virus remains elusive. Additionally, challenges such as long-term ART toxicity, drug resistance, and the demanding regimen of daily and lifelong adherence required by ART highlight the imperative need for alternative therapeutic and preventative approaches. In recent years, broadly neutralizing antibodies (bNAbs) have emerged as promising candidates, offering potential for therapeutic, preventative, and possibly curative interventions against HIV infection. Objective: This review aims to provide a comprehensive overview of the current state of knowledge regarding the passive immunization of bNAbs in HIV-1-infected individuals. Main findings: Recent findings from clinical trials have highlighted the potential of bNAbs in the treatment, prevention, and quest for an HIV-1 cure. While monotherapy with a single bNAb is insufficient in maintaining viral suppression and preventing viral escape, ultimately leading to viral rebound, combination therapy with potent, non-overlapping epitope-targeting bNAbs have demonstrated prolonged viral suppression and delayed time to rebound by effectively restricting the emergence of escape mutations, albeit largely in individuals with bNAb-sensitive strains. Additionally, passive immunization with bNAb has provided a “proof of concept” for antibody-mediated prevention against HIV-1 acquisition, although complete prevention has not been obtained. Therefore, further research on the use of bNAbs in HIV-1 treatment and prevention remains imperative.

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Next-generation bNAbs for HIV-1 cure strategies

Cited by 2 publications

References 247 publications

RAIN: a Machine Learning-based identification for HIV-1 bNAbs

RAIN: a Machine Learning-based identification for HIV-1 bNAbs

The Use of Broadly Neutralizing Antibodies (bNAbs) in HIV-1 Treatment and Prevention

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