Biology subjects

Chun, J.-H.

Publications and source records attributed to Chun, J.-H..

6 recordsLinked to original sources

bioRxiv2026

De novo design of protease-activatable cytokine prodrugs

Cytokines can elicit potent antitumor immunity, but their clinical use is often limited by systemic immune activation and dose-limiting toxicity. Protease-responsive masking offers a way to improve selectivity by linking cytokine activity to disease-associated protease cleavage, but current approaches have faced several challenges. Here we describe a de novo protein design strategy for generating protease-activatable cytokine prodrugs that overcomes these challenges. We use this strategy to design and characterize cytokine prodrugs and well-behaved AND-gated split systems that require both target-dependent colocalization and proteolytic unmasking to generate active cytokines. In challenging syngeneic tumor models, our IL-21 prodrugs reduced treatment-associated toxicity while maintaining antitumor efficacy.

bioengineering↗

bioRxiv2024

Potent antitumor activity of a designed interleukin-21 mimic

Long-standing goals of cancer immunotherapy are to activate cytotoxic antitumor T cells across a broad range of affinities while dampening suppressive regulatory T (Treg) cell responses, but current approaches achieve these goals with limited success. Here, we report a de novo IL-21 mimic, 21h10, designed to have augmented stability and high signaling potency in both humans and mice. In multiple animal models and in ex vivo human melanoma patient derived organotypic tumor spheroids (PDOTS), 21h10 showed robust antitumor activity. 21h10 generates significantly prolonged STAT signaling in vivo compared with native IL-21, and has considerably stronger anti-tumor activity. Toxicities associated with systemic administration of 21h10 could be mitigated by TNF blockade without compromising antitumor efficacy. In the tumor microenvironment, 21h10 induced highly cytotoxic antitumor T cells from clonotypes with a range of affinities for endogenous tumor antigens, robustly expanding low-affinity cytotoxic T cells and driving high expression of interferon- (IFN-) and granzyme B compared to native IL-21, while increasing the frequency of IFN-+ Th1 cells and reducing that of Foxp3+ Tregs. As 21h10 has full human/mouse cross-reactivity, high stability and potency, and potentiates low-affinity antitumor responses, it has considerable translational potential.

biochemistry↗

bioRxiv2024

Computational design of bifaceted protein nanomaterials with tailorable properties

Recent advances in computational methods have led to considerable progress in the design of self-assembling protein nanoparticles. However, nearly all nanoparticles designed to date exhibit strict point group symmetry, with each subunit occupying an identical, symmetrically related environment. This limits the structural diversity that can be achieved and precludes anisotropic functionalization. Here, we describe a general computational strategy for designing multi-component bifaceted protein nanomaterials with two distinctly addressable sides. The method centers on docking pseudosymmetric heterooligomeric building blocks in architectures with dihedral symmetry and designing an asymmetric protein-protein interface between them. We used this approach to obtain an initial 30-subunit assembly with pseudo-D5 symmetry, and then generated an additional 15 variants in which we controllably altered the size and morphology of the bifaceted nanoparticles by designing de novo extensions to one of the subunits. Functionalization of the two distinct faces of the nanoparticles with de novo protein minibinders enabled specific colocalization of two populations of polystyrene microparticles coated with target protein receptors. The ability to accurately design anisotropic protein nanomaterials with precisely tunable structures and functions could be broadly useful in applications that require colocalizing two or more distinct target moieties.

bioengineering↗

bioRxiv2021

Deep learning methods for designing proteins scaffolding functional sites

Current approaches to de novo design of proteins harboring a desired binding or catalytic motif require pre-specification of an overall fold or secondary structure composition, and hence considerable trial and error can be required to identify protein structures capable of scaffolding an arbitrary functional site. Here we describe two complementary approaches to the general functional site design problem that employ the RosettaFold and AlphaFold neural networks which map input sequences to predicted structures. In the first "constrained hallucination" approach, we carry out gradient descent in sequence space to optimize a loss function which simultaneously rewards recapitulation of the desired functional site and the ideality of the surrounding scaffold, supplemented with problem-specific interaction terms, to design candidate immunogens presenting epitopes recognized by neutralizing antibodies, receptor traps for escape-resistant viral inhibition, metalloproteins and enzymes, and target binding proteins with designed interfaces expanding around known binding motifs. In the second "missing information recovery" approach, we start from the desired functional site and jointly fill in the missing sequence and structure information needed to complete the protein in a single forward pass through an updated RoseTTAFold trained to recover sequence from structure in addition to structure from sequence. We show that the two approaches have considerable synergy, and AlphaFold2 structure prediction calculations suggest that the approaches can accurately generate proteins containing a very wide array of functional sites.

biochemistry↗

bioRxiv2021

Visualization of reactive astrocytes in living brain of Alzheimer's disease patient

An early appearance of reactive astrocytes is a hallmark of Alzheimers disease (AD)1,2, providing a substrate for early diagnostic neuroimaging targets. However, there is no clinically validated neuroimaging probe to visualize the reactive astrogliosis in the human brain in vivo. Here, we report that PET/CT imaging with 11C-acetate and 18F-fluorodeoxyglucose (18F-FDG) functionally visualizes the reactive astrocyte-mediated neuronal hypometabolism in the brains with neuroinflammation and AD. We demonstrate that reactive astrocytes excessively absorb acetate through elevated monocarboxylate transporter-1 (MCT1), leading to aberrant GABA synthesis and release which suppresses neuronal glucose uptake through decreased glucose transporter-3 (GLUT3) in both animal and human brains. We propose the non-invasive functional PET/CT imaging for astrocytic acetate-hypermetabolism and neuronal glucose-hypometabolism as an advanced diagnostic strategy for early stages of AD.

neuroscience↗

bioRxiv2021

Visualizing reactive astrogliosis extends survival in glioblastoma patients

Glioblastoma multiforme (GBM) is a devastating brain tumor with dismal prognosis of only 15-month survival regardless of surgical resection. Here, we report an advanced neuroimaging technique combining 11C-acetate PET and MRI (AcePET), visualizing the boundary beyond the MRI-defined tumor. Targeted biopsy of the regions with increased 11C-acetate uptake revealed the presence of reactive astrocytes with enhanced acetate-transporter MCT1, along with cancer stem cells. Reactive astrogliosis and MCT1-dependent 11C-acetate-uptake were recapitulated in U87MG-orthotopic models. Mechanistically, glycolytic tumor cells release excessive acetate causing reactive astrogliosis, leading to the release of aberrant astrocytic GABA and H2O2, which further down-regulate the neuronal glucose uptake through GLUT3. Clincally, AcePET-guided surgery allows complete tumor resection of infiltrating cancer stem cells and extends the overall survival of patients by 5.25 months compared to conventional MRI-guided surgery. We established a new concept of the metabolic interactions between GBM cells and neighboring neurons through reactive astrocytes and developed AcePET-guided surgery to fight against GBM.

cancer biology↗