Aaron Diamond AIDS Research Center

Venezuelan equine encephalitis virus (VEEV) is an arbovirus that causes a disease in which 4%-14% of individuals can develop neurological symptoms. Prior to 1970, VEEV was developed as a biological threat agent due to its stability and high morbidity when administered by aerosol. Currently, no FDA-licensed vaccines nor therapeutics for VEEV exist. Single-domain antibodies (sdAbs) may provide a therapeutic option due to their small size and ability to bind recessed epitopes not recognized by conventional antibodies. This study identified two bivalent sdAbs that were able to protect mice from a lethal challenge against both epizootic and enzootic subtypes of VEEV. Cryo-EM structures of sdAb-VEEV complexes revealed the sdAbs that comprised the bivalent sdAbs to recognize a mixture of conserved and non-conserved regions of the VEEV envelope proteins. While all three of the cryo-EM-characterized epitopes were unique in terms of their recognized VEEV residues, two sdAbs, V2B3 and V2C3, overlapped sterically, explaining why only their combinations with the non-sterically overlapping sdAb V3A8f, which composed the bivalent sdAbs described here, were so particularly effective. Binding and neutralization studies found that the bivalent sdAbs have the potential to be broad-spectrum anti-alphavirus therapeutics as they cross-neutralize multiple alphaviruses.IMPORTANCEAlphaviruses are no longer geographically constrained to one region of the world but are expanding to be of global concern. In many regions of the world, multiple alphaviruses co-circulate; therefore, having a therapeutic that is pan-alphavirus is important. A cocktail of multiple pan-alphavirus binding/neutralizing antibodies (Abs) may provide optimal coverage against alphaviruses while decreasing the prevalence of viral escape mutants, which could cause the therapeutic to no longer be efficacious. Structures of these Abs, defining their recognition, could assist in identifying optimal combinations. A bivalent pan-alphavirus single-domain antibody could be used in a cocktail with already identified alphavirus IgG antibodies.

Amino acid substitutions in or near the drug-binding pockets of biological targets are critical drivers of drug resistance in viral infections. Despite advances in deep learning-based methods for predicting drug-target binding affinity (DTA) and the effects of amino acid substitutions, their practical application remains limited. This limitation stems from these methods' failure to consider the susceptibility of proteins to mutations under selective pressure and the challenges posed by data scarcity. In this study, we introduce MutDTA, a transfer learning model designed to predict the impact of mutations on DTA and to elucidate resistance mechanisms effectively. MutDTA utilizes protein sequences and drug molecular graphs to embed targets and drugs, respectively, enhancing the model's utility. A cross-attention module not only improves prediction accuracy but also aids in identifying critical interaction sites, thereby enhancing model interpretability. Fine-tuning on the Platinum dataset enables MutDTA to effectively capture mutation-specific insights, overcoming issues of data sparsity. Experimental results from both pre-training and fine-tuning phases show that MutDTA significantly outperforms existing methods, displaying exceptional generalization capabilities in cold-start scenarios. Furthermore, an interpretability analysis involving the HIV-1 protease and the drug TMC114, with and without the V32I mutation, demonstrates MutDTA's precision in pinpointing key sites of resistance. Source code and datasets can be available at https://github.com/altriavin/MutDTA.

Background/Objectives: Vaccine elicitation of antibodies with high HIV-1 neutralization breadth is a long-standing goal. Recently, the induction of such antibodies has been achieved at the fusion peptide site of vulnerability. Questions remain, however, as to how much anti-fusion peptide antibodies can be improved and whether their neutralization breadth and potency are sufficient to prevent HIV-1 infection. Methods: Here, we use yeast display coupled with deep mutational screening and biochemical and structural analyses to study the improvement of the best fusion peptide-directed, vaccine-elicited antibody, DFPH_a.01, with an initial 59% breadth. Results: Yeast display identified both single and double mutations that improved recognition of HIV-1 envelope trimers. We characterized two paratope-distal light chain (LC) mutations, S10R and S59P, which together increased breadth to 63%. Biochemical analysis demonstrated DFPH-a.01_10R59P-LC, and its component mutations, to have increased affinity and stability. Cryo-EM structural analysis revealed elbow-angle influencing by S10R-LC and isosteric positioning by S59P-LC as explanations for enhanced breadth, affinity, and stability. Conclusions: These results, along with another antibody with enhanced performance (DFPH-a.01_1G10A56K-LC with 64% breadth), suggest that mutations improving DFPH_a.01 are plentiful, an important vaccine insight.

Noroviruses infect millions each year, and while effective countermeasures are eagerly sought, none have been reported for the GI genogroup, first described more than 50 years ago. Here, to provide insight into GI norovirus neutralization, we isolated a broad GI antibody, 16E10, from a human blood donor and showed it neutralizes noroviruses in human enteroid cultures and abrogates or reduces infection in rhesus macaques. The cryogenic electron microscopy reconstruction of 16E10 with a norovirus protruding-domain dimer at 2.56-Å resolution reveals an exceptionally large binding surface, overlapping an antibody supersite, distal from host receptor-binding or cofactor-binding sites. Cryogenic electron microscopy reconstructions with virus-like particles (VLPs) showed that 16E10 disrupts protruding domains on the VLP surface and disassembles VLPs, altering viral organization required for avidity. While its epitope was generally conserved, 16E10 recognized multiple sequence-divergent residues, binding to which was enabled by corresponding cavities in the 16E10-norovirus interface. Broad recognition of noroviruses can thus incorporate sequence-divergent residues, through a cavity-based mechanism of diversity tolerance.

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) continues to evolve and spread, and it remains critical to understand the functional consequences of mutations in dominant viral variants. The recombinant JN.1 subvariant XEC recently replaced KP.3.1.1 to become the most prevalent subvariant worldwide. Here, we measure the invitro neutralization of KP.3.1.1 and XEC by human sera, monoclonal antibodies, and the soluble human ACE2 (hACE2) receptor relative to the parental subvariants KP.3 and JN.1. KP.3.1.1 and XEC are slightly more resistant (1.3- to 1.6-fold) than KP.3 to serum neutralization and antigenically similar. Both also demonstrate greater resistance to neutralization by select monoclonal antibodies and soluble hACE2, all of which target the top of the viral spike. Our findings suggest that the upward motion of the receptor-binding domain in the spike may be partially hindered by the N-terminal domain mutations in KP.3.1.1 and XEC, allowing these subvariants to better evade serum antibodies that target the viral spike in the up position and to have a growth advantage.

Effective implementation of evidence-based HIV prevention interventions continues to be a challenge in the United States, and the field is increasingly turning to implementation science for solutions. As such, it is critical to expand the current implementation science vocabulary-and its taxonomy of implementation strategies-to increase its relevance and utility for front-line implementers. Community-based health centers providing HIV prevention services in the southeastern United States. We conducted a collective case-study analysis, combining document review and qualitative interviews with program directors, clinicians, and other providers (N = 30) at 5 sites. We used an inductive and iterative analytic approach to specify and categorize strategies, and then conducted in-depth cross-case analysis to derive a practice-driven taxonomy of HIV prevention implementation strategies. From an initial matrix of 264 activities, we identified 50 strategies common across sites. In contrast to existing implementation science frameworks, most (68%, n = 34) strategies were designed to affect implementation outcomes (eg, acceptability, adoption, feasibility) for patients. We present a practice-driven taxonomy of these strategies, operationalized according to implementation science literature, but with terminology that more directly relates to implementers. Findings demonstrate the feasibility and utility of this method for developing a practice-driven implementation science vocabulary for HIV prevention. Our evidence-based taxonomy provides a framework for implementers seeking data about the universe of strategies they might consider for their own programs, and increases researchers' ability to measure and evaluate the effectiveness of implementation strategies being enacted in practice settings.