A New in Silico Antibody Similarity Measure Both Identifies Large Sets of Epitope Binders with Distinct CDRs and Accurately Predicts Off-Target Reactivity

Integrating artificial intelligence-based epitope prediction in a SARS-CoV-2 antibody discovery pipeline: caution is warranted

BACKGROUND

SARS-CoV-2-neutralizing antibodies (nABs) showed great promise in the early phases of the COVID-19 pandemic. The emergence of resistant strains, however, quickly rendered the majority of clinically approved nABs ineffective. This underscored the imperative to develop nAB cocktails targeting non-overlapping epitopes.

METHODS

Undertaking a nAB discovery program, we employed a classical workflow, while integrating artificial intelligence (AI)-based prediction to select non-competing nABs very early in the pipeline. We identified and in vivo validated (in female Syrian hamsters) two highly potent nABs.

FINDINGS

Despite the promising results, in depth cryo-EM structural analysis demonstrated that the AI-based prediction employed with the intention to ensure non-overlapping epitopes was inaccurate. The two nABs in fact bound to the same receptor-binding epitope in a remarkably similar manner.

INTERPRETATION

Our findings indicate that, even in the Alphafold era, AI-based predictions of paratope-epitope interactions are rough and experimental validation of epitopes remains an essential cornerstone of a successful nAB lead selection.

FUNDING

Full list of funders is provided at the end of the manuscript.

Combined Multiplexed Phage Display, High-Throughput Sequencing, and Functional Assays as a Platform for Identifying Modulatory VHHs Targeting the FSHR

Developing modulatory antibodies against G protein-coupled receptors is challenging. In this study, we targeted the follicle-stimulating hormone receptor (FSHR), a significant regulator of reproduction, with variable domains of heavy chain-only antibodies (VHHs). We built two immune VHH libraries and submitted them to multiplexed phage display approaches. We used next-generation sequencing to identify 34 clusters of specifically enriched sequences that were functionally assessed in a primary screen based on a cAMP response element (CRE)-dependent reporter gene assay. In this assay, 23 VHHs displayed negative or positive modulation of FSH-induced responses, suggesting a high success rate of the multiplexed strategy. We then focused on the largest cluster identified (i.e., PRC1) that displayed positive modulation of FSH action. We demonstrated that PRC1 specifically binds to the human FSHR and human FSHR/FSH complex while potentiating FSH-induced cAMP production and Gs recruitment. We conclude that the improved selection strategy reported here is effective for rapidly identifying functionally active VHHs and could be adapted to target other challenging membrane receptors. This study also led to the identification of PRC1, the first potential positive modulator VHH reported for the human FSHR.

The High-Resolution Structure Reveals Remarkable Similarity in PD-1 Binding of Cemiplimab and Dostarlimab, the FDA-Approved Antibodies for Cancer Immunotherapy

Multiple tumors have responded well to immunotherapies, which use monoclonal antibodies to block the immune checkpoint proteins and reactivate the T-cell immune response to cancer cells. Significantly, the anti-PD-1 antibodies pembrolizumab and nivolumab, which were approved in 2014, have revolutionized cancer therapy, demonstrating dramatic improvement and longer duration. The US FDA authorized the third anti-PD-1 medication, cemiplimab, in 2018 for use in patients with cutaneous squamous cell carcinoma. To further understand the molecular mechanism of the antibody drug, we now reveal the intricate structure of PD-1 in complex with the cemiplimab Fab at a resolution of 1.98 Å. The cemiplimab-PD-1 interaction preoccupies the space for PD-L1 binding with a greater binding affinity than the PD-1/PD-L1 interaction, which is the basis for the PD-1 blocking mechanism. The structure reveals that cemiplimab and dostarlimab are significantly similar in PD-1 binding, although the precise interactions differ. A comparative investigation of PD-1 interactions with the four FDA-approved antibodies reveals that the BC, C'D, and FG loops of PD-1 adopt distinct conformations for optimal interaction with the antibodies. The structural characteristics in this work could be helpful information for developing more potent anti-PD-1 biologics against cancer.