FusOn-pLM: A Fusion Oncoprotein-Specific Language Model via Focused Probabilistic Masking.

Fusion oncoproteins, a class of chimeric proteins arising from chromosomal translocations, drive and sustain various cancers, particularly those impacting children. Unfortunately, due to their intrinsically disordered nature, large size, and lack of well-defined, druggable pockets, they have been historically challenging to target therapeutically: neither small molecule-based methods nor structure-based approaches for binder design are strong options for this class of molecules. Recently, protein language models (pLMs) have demonstrated success at representing protein sequences with information-rich embeddings, enabling downstream design applications from sequence alone. However, no current pLM has been trained on fusion oncoprotein sequences and thus may not produce optimal representations for these proteins. In this work, we introduce FusOn-pLM, a novel pLM that fine-tunes the state-of-the-art ESM-2 model on fusion oncoprotein sequences. We specifically introduce a novel masked language modeling (MLM) strategy, employing a binding-site probability predictor to focus masking on key amino acid residues, thereby generating more optimal fusion oncoprotein-aware embeddings. Our model improves performance on both fusion oncoprotein-specific benchmarks and disorder prediction tasks in comparison to baseline ESM-2 representations, as well as manually-constructed biophysical embeddings, motivating downstream usage of FusOn-pLM embeddings for therapeutic design tasks targeting these fusions. We have made our model publicly available to the community at https://huggingface.co/ChatterjeeLab/FusOn-pLM.

Engineered immunogens to elicit antibodies against conserved coronavirus epitopes.

Immune responses to SARS-CoV-2 primarily target the receptor binding domain of the spike protein, which continually mutates to escape acquired immunity. Other regions in the spike S2 subunit, such as the stem helix and the segment encompassing residues 815-823 adjacent to the fusion peptide, are highly conserved across sarbecoviruses and are recognized by broadly reactive antibodies, providing hope that vaccines targeting these epitopes could offer protection against both current and emergent viruses. Here we employ computational modeling to design scaffolded immunogens that display the spike 815-823 peptide and the stem helix epitopes without the distracting and immunodominant receptor binding domain. These engineered proteins bind with high affinity and specificity to the mature and germline versions of previously identified broadly protective human antibodies. Epitope scaffolds interact with both sera and isolated monoclonal antibodies with broadly reactivity from individuals with pre-existing SARS-CoV-2 immunity. When used as immunogens, epitope scaffolds elicit sera with broad betacoronavirus reactivity and protect as "boosts" against live virus challenge in mice, illustrating their potential as components of a future pancoronavirus vaccine.

PepMLM: Target Sequence-Conditioned Generation of Peptide Binders via Masked Language Modeling.

Target proteins that lack accessible binding pockets and conformational stability have posed increasing challenges for drug development. Induced proximity strategies, such as PROTACs and molecular glues, have thus gained attention as pharmacological alternatives, but still require small molecule docking at binding pockets for targeted protein degradation (TPD). The computational design of protein-based binders presents unique opportunities to access "undruggable" targets, but have often relied on stable 3D structures or predictions for effective binder generation. Recently, we have leveraged the expressive latent spaces of protein language models (pLMs) for the prioritization of peptide binders from sequence alone, which we have then fused to E3 ubiquitin ligase domains, creating a CRISPR-analogous TPD system for target proteins. However, our methods rely on training discriminator models for ranking heuristically or unconditionally-derived "guide" peptides for their target binding capability. In this work, we introduce PepMLM, a purely target sequence-conditioned de novo generator of linear peptide binders. By employing a novel masking strategy that uniquely positions cognate peptide sequences at the terminus of target protein sequences, PepMLM tasks the state-of-the-art ESM-2 pLM to fully reconstruct the binder region, achieving low perplexities matching or improving upon previously-validated peptide-protein sequence pairs. After successful in silico benchmarking with AlphaFold-Multimer, we experimentally verify PepMLM's efficacy via fusion of model-derived peptides to E3 ubiquitin ligase domains, demonstrating endogenous degradation of target substrates in cellular models. In total, PepMLM enables the generative design of candidate binders to any target protein, without the requirement of target structure, empowering downstream programmable proteome editing applications.

Engineered Immunogens to Elicit Antibodies Against Conserved Coronavirus Epitopes.

Immune responses to SARS-CoV-2 primarily target the receptor binding domain of the spike protein, which continually mutates to escape acquired immunity. Other regions in the spike S2 subunit, such as the stem helix and the segment encompassing residues 815-823 adjacent to the fusion peptide, are highly conserved across sarbecoviruses and are recognized by broadly reactive antibodies, providing hope that vaccines targeting these epitopes could offer protection against both current and emergent viruses. Here we employed computational modeling to design scaffolded immunogens that display the spike 815-823 peptide and the stem helix epitopes without the distracting and immunodominant RBD. These engineered proteins bound with high affinity and specificity to the mature and germline versions of previously identified broadly protective human antibodies. Epitope scaffolds interacted with both sera and isolated monoclonal antibodies with broadly reactivity from individuals with pre-existing SARS-CoV-2 immunity. When used as immunogens, epitope scaffolds elicited sera with broad betacoronavirus reactivity and protected as "boosts" against live virus challenge in mice, illustrating their potential as components of a future pancoronavirus vaccine.