Precise epitope determination of therapeutic antibodies is of great value as it allows for further comprehension of mechanism of action, therapeutic responsiveness prediction, avoidance of unwanted cross reactivity, and vaccine design. The golden standard for discontinuous epitope determination is the laborious X-ray crystallography method. Here, we present a combinatorial method for rapid mapping of discontinuous epitopes by mammalian antigen display, eliminating the need for protein expression and purification. The method is facilitated by automated workflows and tailored software for antigen analysis and oligonucleotide design. These oligos are used in automated mutagenesis to generate an antigen receptor library displayed on mammalian cells for direct binding analysis by flow cytometry. Through automated analysis of 33930 primers an optimized single condition cloning reaction was defined allowing for mutation of all surface-exposed residues of the receptor binding domain of SARS-CoV-2. All variants were functionally expressed, and two reference binders validated the method. Furthermore, epitopes of three novel therapeutic antibodies were successfully determined followed by evaluation of binding also towards SARS-CoV-2 Omicron BA.2. We find the method to be highly relevant for rapid construction of antigen libraries and determination of antibody epitopes, especially for the development of therapeutic interventions against novel pathogens.
© 2024. The Author(s).

Allosteric HIV-1 integrase (IN) inhibitors, or ALLINIs, are a new class of antiviral agents that bind at the dimer interface of the IN, away from the enzymatic catalytic site and block viral replication by triggering an aberrant multimerization of the viral enzyme. To further our understanding of the important binding features of multi-substituted quinoline-based ALLINIs, we have examined the IN multimerization and antiviral properties of substitution patterns at the 6 or 8 position. We found that the binding properties of these ALLINIs are negatively impacted by the presence of bulky substitutions at these positions. In addition, we have observed that the addition of bromine at either the 6 (6-bromo) or 8 (8-bromo) position conferred better antiviral properties. Finally, we found a significant loss of potency with the 6-bromo when tested with the ALLINI-resistant IN A128T mutant virus, while the 8-bromo analog retained full effectiveness.

Allosteric integrase inhibitors (ALLINIs) are a class of experimental anti-HIV agents that target the noncatalytic sites of the viral integrase (IN) and interfere with the IN-viral RNA interaction during viral maturation. Here, we report a highly potent and safe pyrrolopyridine-based ALLINI, STP0404, displaying picomolar IC50 in human PBMCs with a >24,000 therapeutic index against HIV-1. X-ray structural and biochemical analyses revealed that STP0404 binds to the host LEDGF/p75 protein binding pocket of the IN dimer, which induces aberrant IN oligomerization and blocks the IN-RNA interaction. Consequently, STP0404 inhibits proper localization of HIV-1 RNA genomes in viral particles during viral maturation. Y99H and A128T mutations at the LEDGF/p75 binding pocket render resistance to STP0404. Extensive in vivo pharmacological and toxicity investigations demonstrate that STP0404 harbors outstanding therapeutic and safety properties. Overall, STP0404 is a potent and first-in-class ALLINI that targets LEDGF/p75 binding site and has advanced to a human trial.

Machine learning plays an important role in ligand-based virtual screening. However, conventional machine learning approaches tend to be inefficient when dealing with such problems where the data are imbalanced and features describing the chemical characteristic of ligands are high-dimensional. We here describe a machine learning algorithm LBS (local beta screening) for ligand-based virtual screening. The unique characteristic of LBS is that it quantifies the generalization ability of screening directly by a refined loss function, and thus can assess the risk of over-fitting accurately and efficiently for imbalanced and high-dimensional data in ligand-based virtual screening without the help of resampling methods such as cross validation. The robustness of LBS was demonstrated by a simulation study and tests on real datasets, in which LBS outperformed conventional algorithms in terms of screening accuracy and model interpretation. LBS was then used for screening potential activators of HIV-1 integrase multimerization in an independent compound library, and the virtual screening result was experimentally validated. Of the 25 compounds tested, six were proved to be active. The most potent compound in experimental validation showed an EC50 value of 0.71 µM.

HIV-1 integrase (IN) inhibitors represent a new class of highly effective anti-AIDS therapeutics. Current FDA-approved IN strand transfer inhibitors (INSTIs) share a common mechanism of action that involves chelation of catalytic divalent metal ions. However, the emergence of IN mutants having reduced sensitivity to these inhibitors underlies efforts to derive agents that antagonize IN function by alternate mechanisms. Integrase along with the 96-residue multifunctional accessory protein, viral protein R (Vpr), are both components of the HIV-1 pre-integration complex (PIC). Coordinated interactions within the PIC are important for viral replication. Herein, we report a 7-mer peptide based on the shortened Vpr (69⁻75) sequence containing a biotin group and a photo-reactive benzoylphenylalanyl residue, and which exhibits low micromolar IN inhibitory potency. Photo-crosslinking experiments have indicated that the peptide directly binds IN. The peptide does not interfere with IN-DNA interactions or induce higher-order, aberrant IN multimerization, suggesting a mode of action for the peptide that is distinct from clinically used INSTIs and developmental allosteric IN inhibitors. This compact Vpr-derived peptide may serve as a valuable pharmacological tool to identify a potential new pharmacologic site.