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The rapid evolution of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) underscores the need for antivirals that are resilient to resistance. Current Food and Drug Administration (FDA)-approved therapies primarily target single viral mechanisms, leaving gaps in efficacy. Here, we developed a Deep Learning-based Activity Screening Model (DLASM), which integrates graph convolutional network with machine learning to identify SARS-CoV-2 inhibitors, using experimental 3-chymotrypsin-like (3CL) main protease assay data. The optimized DLASMs virtually screened ~170,000 compounds from diverse in-house collections and yielded novel hits, several of which not only inhibited the 3CL protease but also blocked viral entry by interfering with heparan sulfate-mediated host interactions. These activities were validated through multiple assays, including 3CL enzymatic inhibition, SARS-CoV-2 pseudotyped particle entry, α-synuclein fibril uptake as a proxy for endocytosis, live virus cytopathic effect, heparan sulfate-dependent entry assay, and a 3D human lung mucociliary tissue model. Molecular docking studies elucidated binding modes at the 3CL protease active site, while molecular dynamics simulations provided insights into compound–heparan sulfate interactions. The identified compounds represent early-stage hits with moderate potency that demonstrate dual-mechanism antiviral activity. Together, these findings establish dual-target inhibition as a promising antiviral strategy, offering not only enhanced potency but also reduced risk of resistance. Moreover, our DLASM framework provides a generalizable pipeline for identifying chemically diverse scaffolds and for broader applications beyond SARS-CoV-2.

The ability to model human neurological tissues in vitro has been a major hurdle to effective drug development for neurological disorders. iPSC-derived brain organoids have emerged as a compelling solution to this problem as they have the potential to relevantly model the protein expression pattern and physiology of specific brain regions. Although many protocols now exist for the production of brain organoids, few attempts have been made to do an in-depth kinetic evaluation of expression of mature regiospecific markers of brain organoids. To address this, we differentiated midbrain-specific brain organoids from iPSC-lines derived from three apparently healthy individuals using a matrix-free, bioreactor method. We monitored the expression of midbrain-specific neuronal markers from 7 to 90-days using immunofluorescence and immunohistology. The organoids were further characterized using electron microscopy and RNA-seq. In addition to serving as a potential benchmark for the future evaluation of other differentiation protocols, the markers observed in this study can be useful as control parameters to identify and evaluate the disease phenotypes in midbrain organoid derived from patient iPSC-lines with genetic neurological disorders.

SARS-CoV-2 infection causes spike-dependent fusion of infected cells with ACE2 positive neighboring cells, generating multi-nuclear syncytia that are often associated with severe COVID. To better elucidate the mechanism of spike-induced syncytium formation, we combine chemical genetics with 4D confocal imaging to establish the cell surface heparan sulfate (HS) as a critical stimulator for spike-induced cell-cell fusion. We show that HS binds spike and promotes spike-induced ACE2 clustering, forming synapse-like cell-cell contacts that facilitate fusion pore formation between ACE2-expresing and spike-transfected human cells. Chemical or genetic inhibition of HS mitigates ACE2 clustering, and thus, syncytium formation, whereas in a cell-free system comprising purified HS and lipid-anchored ACE2, HS stimulates ACE2 clustering directly in the presence of spike. Furthermore, HS-stimulated syncytium formation and receptor clustering require a conserved ACE2 linker distal from the spike-binding site. Importantly, the cell fusion-boosting function of HS can be targeted by an investigational HS-binding drug, which reduces syncytium formation in vitro and viral infection in mice. Thus, HS, as a host factor exploited by SARS-CoV-2 to facilitate receptor clustering and a stimulator of infection-associated syncytium formation, may be a promising therapeutic target for severe COVID. The molecular mechanism of syncytium formation during SARS-CoV-2 infection is not fully understood. Zhang et al. now show that cell surface heparan sulfate enhances spike-induced ACE2 clustering and cell-cell fusion, which depends on a conserved ACE2 linker and is blocked by a heparan sulfate binding drug.

The global pandemic caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has led to an urgent need for effective therapeutic options. SARS-CoV-2 is a novel coronavirus responsible for the COVID-19 pandemic that has resulted in significant morbidity and mortality worldwide. The virus is known to enter host cells by binding to the angiotensin-converting enzyme 2 (ACE2) receptor, and emerging evidence suggests that heparan sulfate proteoglycans (HSPGs) play a crucial role in facilitating this process. HSPGs are abundant cell surface proteoglycan present in many tissues, including the lung, and have been shown to interact directly with the spike protein of SARS-CoV-2. This review aims to summarize the current understanding of the role of HSPGs in SARS-CoV-2 infection and the potential of developing new therapies targeting HSPGs.

Advancements in treatment for the rare genetic disorder known as Alagille Syndrome (ALGS) have been regrettably slow. The large variety of mutations to the JAG1 and NOTCH2 genes which lead to ALGS pose a unique challenge for developing targeted treatments. Due to the central role of the Notch signaling pathway in several cancers, traditional treatment modalities which compensate for the loss in activity caused by mutation are rightly excluded. Unfortunately, current treatment plans for ALGS focus on relieving symptoms of the disorder and do not address the underlying causes of disease. Here we review several of the current and potential key technologies and strategies which may yield a significant leap in developing targeted therapies for this disorder.

NGLY1 deficiency is an ultra-rare, autosomal recessive genetic disease caused by mutations in the NGLY1 gene encoding N-glycanase one that removes N-linked glycan. Patients with pathogenic mutations in NGLY1 have complex clinical symptoms including global developmental delay, motor disorder and liver dysfunction. To better understand the disease pathogenesis and the neurological symptoms of the NGLY1 deficiency we generated and characterized midbrain organoids using patient-derived iPSCs from two patients with distinct disease-causing mutations–one homozygous for p. Q208X, the other compound heterozygous for p. L318P and p. R390P and CRISPR generated NGLY1 knockout iPSCs. We demonstrate that NGLY1 deficient midbrain organoids show altered neuronal development compared to one wild type (WT) organoid. Both neuronal (TUJ1) and astrocytic glial fibrillary acid protein markers were reduced in NGLY1 patient-derived midbrain organoids along with neurotransmitter GABA. Interestingly, staining for dopaminergic neuronal marker, tyrosine hydroxylase, revealed a significant reduction in patient iPSC derived organoids. These results provide a relevant NGLY1 disease model to investigate disease mechanisms and evaluate therapeutics for treatments of NGLY1 deficiency.

The current generation of high-throughput screening (HTS) involves the parallel processing of hundreds of thousands of molecules. Despite such large-scale efforts, low hit rates for challenging targets slow the overall rate of novel therapeutic discovery. The success of future screening campaigns for unmet needs can be supported by advances in the quantification of the biological performance diversity and the prediction of chemical features that enhance this diversity. Compound libraries that are biologically performance-diverse contain molecules that have broad, nonredundant coverage of a large set of biological targets. These libraries would accelerate drug discovery by increasing hit rates while reducing the overall footprint of HTS. In this work we present the profiling of two flavonoid-based libraries using the Cell Painting assay to establish which types of chemical and physical features are most relevant for the composition of biologically performance-diverse libraries. We conclude that the impact of varying features is highly dependent on the scaffold around which a library is based further emphasizing the need to screen libraries as they are synthesized to inform synthetic efforts. Autophagy is a catabolic process implicated in a variety of human diseases due to its role in the maintenance of cellular homeostasis. During autophagy, cellular cargo is sequestered within double-membrane autophagosomes which traffic these contents to the lysosome for recycling. Many autophagy modulators exist, but these modulators lack overall specificity, either impacting autophagy at several points within the pathway or affecting other pathways within the cell. To better understand the role of autophagy in various diseases, we need to develop autophagy-specific probes that can be used to evaluate the underlying biology and serve as the starting points for the creation of effective therapies. We approached this problem by targeting two protein-protein interactions (PPIs) found within the autophagy pathway, the ATG14L-Beclin 1 PPI and the ATG5-ATG16L1 PPI. To target these interfaces, we developed two HTS-compatible assays utilizing NanoBRET and fluorescence polarization, respectively. We successfully implemented the NanoBRET HTS to discover a novel molecule that inhibits the formation of VPS34 Complex I and disrupts autophagy more selectively than known autophagy inhibitors that target the VPS34 kinase directly.