Heat shock factor 1 (HSF1) is a stress-responsive transcription factor that regulates expression of protein chaperones and cell survival factors. In cancer, HSF1 plays a unique role, hijacking the normal stress response to drive a cancer-specific transcriptional program. These observations suggest that HSF1 inhibitors could be promising therapeutics. However, HSF1 is activated through a complex mechanism, which involves release of a negative regulatory domain, leucine zipper 4 (LZ4), from a masked oligomerization domain (LZ1-3), and subsequent binding of the oligomer to heat shock elements (HSEs) in HSF1-responsive genes. Recent crystal structures have suggested that HSF1 oligomers are held together by extensive, buried contact surfaces, making it unclear whether there are any possible binding sites for inhibitors. Here, we have rationally designed a series of peptide-based molecules based on the LZ4 and LZ1-3 motifs. Using a plate-based, fluorescence polarization (FP) assay, we identified a minimal region of LZ4 that suppresses binding of HSF1 to the HSE. Using this information, we converted this peptide into a tracer and used it to understand how binding of LZ4 to LZ1-3 suppresses HSF1 activation. Together, these results suggest a previously unexplored avenue in the development of HSF1 inhibitors. Furthermore, the findings highlight how native interactions can inspire the design of inhibitors for even the most challenging protein-protein interactions (PPIs).

Combining multiple therapeutic strategies in NRAS/BRAF mutant melanoma-namely MEK/BRAF kinase inhibitors, immune checkpoint inhibitors (ICIs), and targeted immunotherapies-may offer an improved survival benefit by overcoming limitations associated with any individual therapy. Still, optimal combination, order, and timing of administration remains under investigation. Here, we measure how MEK inhibition (MEKi) alters anti-tumor immunity by utilizing quantitative immunopeptidomics to profile changes in the peptide major histocompatibility molecules (pMHC) repertoire. These data reveal a collection of tumor antigens whose presentation levels are selectively augmented following therapy, including several epitopes present at over 1,000 copies per cell. We leveraged the tunable abundance of MEKi-modulated antigens by targeting four epitopes with pMHC-specific T cell engagers and antibody drug conjugates, enhancing cell killing in tumor cells following MEK inhibition. These results highlight drug treatment as a means to enhance immunotherapy efficacy by targeting specific upregulated pMHCs and provide a methodological framework for identifying, quantifying, and therapeutically targeting additional epitopes of interest.

Numerous neutralizing antibodies that target SARS-CoV-2 have been reported, and most directly block binding of the viral Spike receptor-binding domain (RBD) to angiotensin-converting enzyme II (ACE2). Here, we deliberately exploit non-neutralizing RBD antibodies, showing they can dramatically assist in neutralization when linked to neutralizing binders. We identified antigen-binding fragments (Fabs) by phage display that bind RBD, but do not block ACE2 or neutralize virus as IgGs. When these non-neutralizing Fabs were assembled into bispecific VH/Fab IgGs with a neutralizing VH domain, we observed a ~ 25-fold potency improvement in neutralizing SARS-CoV-2 compared to the mono-specific bi-valent VH-Fc alone or the cocktail of the VH-Fc and IgG. This effect was epitope-dependent, reflecting the unique geometry of the bispecific antibody toward Spike. Our results show that a bispecific antibody that combines both neutralizing and non-neutralizing epitopes on Spike-RBD is a promising and rapid engineering strategy to improve the potency of SARS-CoV-2 antibodies.

An essential mechanism for severe acute respiratory syndrome coronavirus 1 (SARS-CoV-1) and severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection begins with the viral spike protein binding to the human receptor protein angiotensin-converting enzyme II (ACE2). Here, we describe a stepwise engineering approach to generate a set of affinity optimized, enzymatically inactivated ACE2 variants that potently block SARS-CoV-2 infection of cells. These optimized receptor traps tightly bind the receptor binding domain (RBD) of the viral spike protein and prevent entry into host cells. We first computationally designed the ACE2-RBD interface using a two-stage flexible protein backbone design process that improved affinity for the RBD by up to 12-fold. These designed receptor variants were affinity matured an additional 14-fold by random mutagenesis and selection using yeast surface display. The highest-affinity variant contained seven amino acid changes and bound to the RBD 170-fold more tightly than wild-type ACE2. With the addition of the natural ACE2 collectrin domain and fusion to a human immunoglobulin crystallizable fragment (Fc) domain for increased stabilization and avidity, the most optimal ACE2 receptor traps neutralized SARS-CoV-2-pseudotyped lentivirus and authentic SARS-CoV-2 virus with half-maximal inhibitory concentrations (IC50s) in the 10- to 100-ng/mL range. Engineered ACE2 receptor traps offer a promising route to fighting infections by SARS-CoV-2 and other ACE2-using coronaviruses, with the key advantage that viral resistance would also likely impair viral entry. Moreover, such traps can be predesigned for viruses with known entry receptors for faster therapeutic response without the need for neutralizing antibodies isolated from convalescent patients.

An essential mechanism for SARS-CoV-1 and -2 infection begins with the viral spike protein binding to the human receptor protein angiotensin-converting enzyme II (ACE2). Here we describe a stepwise engineering approach to generate a set of affinity optimized, enzymatically inactivated ACE2 variants that potently block SARS-CoV-2 infection of cells. These optimized receptor traps tightly bind the receptor binding domain (RBD) of the viral spike protein and prevent entry into host cells. We first computationally designed the ACE2-RBD interface using a two-stage flexible protein backbone design process that improved affinity for the RBD by up to 12-fold. These designed receptor variants were affinity matured an additional 14-fold by random mutagenesis and selection using yeast surface display. The highest affinity variant contained seven amino acid changes and bound to the RBD 170-fold more tightly than wild-type ACE2. With the addition of the natural ACE2 collectrin domain and fusion to a human Fc domain for increased stabilization and avidity, the most optimal ACE2 receptor traps neutralized SARS-CoV-2 pseudotyped lentivirus and authentic SARS-CoV-2 virus with half-maximal inhibitory concentrations (IC50) in the 10-100 ng/ml range. Engineered ACE2 receptor traps offer a promising route to fighting infections by SARS-CoV-2 and other ACE2-utilizing coronaviruses, with the key advantage that viral resistance would also likely impair viral entry. Moreover, such traps can be predesigned for viruses with known entry receptors for faster therapeutic response without the need for neutralizing antibodies isolated or generated from convalescent patients.

Although the primary protein sequence of ubiquitin (Ub) is extremely stable over evolutionary time, it is highly tolerant to mutation during selection experiments performed in the laboratory. We have proposed that this discrepancy results from the difference between fitness under laboratory culture conditions and the selective pressures in changing environments over evolutionary timescales. Building on our previous work (Mavor et al., 2016), we used deep mutational scanning to determine how twelve new chemicals (3-Amino-1,2,4-triazole, 5-fluorocytosine, Amphotericin B, CaCl₂, Cerulenin, Cobalt Acetate, Menadione, Nickel Chloride, p-Fluorophenylalanine, Rapamycin, Tamoxifen, and Tunicamycin) reveal novel mutational sensitivities of ubiquitin residues. Collectively, our experiments have identified eight new sensitizing conditions for Lys63 and uncovered a sensitizing condition for every position in Ub except Ser57 and Gln62. By determining the ubiquitin fitness landscape under different chemical constraints, our work helps to resolve the inconsistencies between deep mutational scanning experiments and sequence conservation over evolutionary timescales.