Development of a Covalent Inhibitor of c-Jun N-Terminal Protein Kinase (JNK) 2/3 with Selectivity over JNK1.

The c-Jun N-terminal kinases (JNKs) are members of the mitogen-activated protein kinase (MAPK) family, which includes JNK1-JNK3. Interestingly, JNK1 and JNK2 show opposing functions, with JNK2 activity favoring cell survival and JNK1 stimulating apoptosis. Isoform-selective small molecule inhibitors of JNK1 or JNK2 would be useful as pharmacological probes but have been difficult to develop due to the similarity of their ATP binding pockets. Here, we describe the discovery of a covalent inhibitor YL5084, the first such inhibitor that displays selectivity for JNK2 over JNK1. We demonstrated that YL5084 forms a covalent bond with Cys116 of JNK2, exhibits a 20-fold higher Kinact/KI compared to that of JNK1, and engages JNK2 in cells. However, YL5084 exhibited JNK2-independent antiproliferative effects in multiple myeloma cells, suggesting the existence of additional targets relevant in this context. Thus, although not fully optimized, YL5084 represents a useful chemical starting point for the future development of JNK2-selective chemical probes.

A collaborative approach to improving representation in viral genomic surveillance.

The lack of routine viral genomic surveillance delayed the initial detection of SARS-CoV-2, allowing the virus to spread unfettered at the outset of the U.S. epidemic. Over subsequent months, poor surveillance enabled variants to emerge unnoticed. Against this backdrop, long-standing social and racial inequities have contributed to a greater burden of cases and deaths among minority groups. To begin to address these problems, we developed a new variant surveillance model geared toward building 'next generation' genome sequencing capacity at universities in or near rural areas and engaging the participation of their local communities. The resulting genomic surveillance network has generated more than 1,000 SARS-CoV-2 genomes to date, including the first confirmed case in northeast Louisiana of Omicron, and the first and sixth confirmed cases in Georgia of the emergent BA.2.75 and BQ.1.1 variants, respectively. In agreement with other studies, significantly higher viral gene copy numbers were observed in Delta variant samples compared to those from Omicron BA.1 variant infections, and lower copy numbers were seen in asymptomatic infections relative to symptomatic ones. Collectively, the results and outcomes from our collaborative work demonstrate that establishing genomic surveillance capacity at smaller academic institutions in rural areas and fostering relationships between academic teams and local health clinics represent a robust pathway to improve pandemic readiness.

Structure-Based Design of Y-Shaped Covalent TEAD Inhibitors.

Transcriptional enhanced associate domain (TEAD) proteins together with their transcriptional coactivator yes-associated protein (YAP) and transcriptional coactivator with the PDZ-binding motif (TAZ) are important transcription factors and cofactors that regulate gene expression in the Hippo pathway. In mammals, the TEAD families have four homologues: TEAD1 (TEF-1), TEAD2 (TEF-4), TEAD3 (TEF-5), and TEAD4 (TEF-3). Aberrant expression and hyperactivation of TEAD/YAP signaling have been implicated in a variety of malignancies. Recently, TEADs were recognized as being palmitoylated in cells, and the lipophilic palmitate pocket has been successfully targeted by both covalent and noncovalent ligands. In this report, we present the medicinal chemistry effort to develop MYF-03-176 (compound 22) as a selective, cysteine-covalent TEAD inhibitor. MYF-03-176 (compound 22) significantly inhibits TEAD-regulated gene expression and proliferation of the cell lines with TEAD dependence including those derived from mesothelioma and liposarcoma.

Direct observation of peptide hydrogel self-assembly.

The characterization of self-assembling molecules presents significant experimental challenges, especially when associated with phase separation or precipitation. Transparent window infrared (IR) spectroscopy leverages site-specific probes that absorb in the "transparent window" region of the biomolecular IR spectrum. Carbon-deuterium (C-D) bonds are especially compelling transparent window probes since they are non-perturbative, can be readily introduced site selectively into peptides and proteins, and their stretch frequencies are sensitive to changes in the local molecular environment. Importantly, IR spectroscopy can be applied to a wide range of molecular samples regardless of solubility or physical state, making it an ideal technique for addressing the solubility challenges presented by self-assembling molecules. Here, we present the first continuous observation of transparent window probes following stopped-flow initiation. To demonstrate utility in a self-assembling system, we selected the MAX1 peptide hydrogel, a biocompatible material that has significant promise for use in drug delivery and medical applications. C-D labeled valine was synthetically introduced into five distinct positions of the twenty-residue MAX1 ß-hairpin peptide. Consistent with current structural models, steady-state IR absorption frequencies and linewidths of C-D bonds at all labeled positions indicate that these side chains occupy a hydrophobic region of the hydrogel and that the motion of side chains located in the middle of the hairpin is more restricted than those located on the hairpin ends. Following a rapid change in ionic strength to initiate self-assembly, the peptide absorption spectra were monitored as function of time, allowing determination of site-specific time constants. We find that within the experimental resolution, MAX1 self-assembly occurs as a cooperative process. These studies suggest that stopped-flow transparent window FTIR can be extended to other time-resolved applications, such as protein folding and enzyme kinetics.

A collaborative approach to improve representation in viral genomic surveillance.

The lack of routine viral genomic surveillance delayed the initial detection of SARS-CoV-2, allowing the virus to spread unfettered at the outset of the U.S. epidemic. Over subsequent months, poor surveillance enabled variants to emerge unnoticed. Against this backdrop, long-standing social and racial inequities have contributed to a greater burden of cases and deaths among minority groups. To begin to address these problems, we developed a new variant surveillance model geared toward building microbial genome sequencing capacity at universities in or near rural areas and engaging the participation of their local communities. The resulting genomic surveillance network has generated more than 1,000 SARS-CoV-2 genomes to date, including the first confirmed case in northeast Louisiana of Omicron, and the first and sixth confirmed cases in Georgia of the emergent BA.2.75 and BQ.1.1 variants, respectively. In agreement with other studies, significantly higher viral gene copy numbers were observed in Delta variant samples compared to those from Omicron BA.1 variant infections, and lower copy numbers were seen in asymptomatic infections relative to symptomatic ones. Collectively, the results and outcomes from our collaborative work demonstrate that establishing genomic surveillance capacity at smaller academic institutions in rural areas and fostering relationships between academic teams and local health clinics represent a robust pathway to improve pandemic readiness. Author summary: Genomic surveillance involves decoding a pathogen’s genetic code to track its spread and evolution. During the pandemic, genomic surveillance programs around the world provided valuable data to scientists, doctors, and public health officials. Knowing the complete SARS-CoV-2 genome has helped detect the emergence of new variants, including ones that are more transmissible or cause more severe disease, and has supported the development of diagnostics, vaccines, and therapeutics. The impact of genomic surveillance on public health depends on representative sampling that accurately reflects the diversity and distribution of populations, as well as rapid turnaround time from sampling to data sharing. After a slow start, SARS-CoV-2 genomic surveillance in the United States grew exponentially. Despite this, many rural regions and ethnic minorities remain poorly represented, leaving significant gaps in the data that informs public health responses. To address this problem, we formed a network of universities and clinics in Louisiana, Georgia, and Mississippi with the goal of increasing SARS-CoV-2 sequencing volume, representation, and equity. Our results demonstrate the advantages of rapidly sequencing pathogens in the same communities where the cases occur and present a model that leverages existing academic and clinical infrastructure for a powerful decentralized genomic surveillance system.