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Biology subjects

Yoon, M. J.

Publications and source records attributed to Yoon, M. J..

3 recordsLinked to original sources

Accurate antibody loop structure prediction enables zero-shot design of target-specific antibodies

Protein loops, characterized by their versatile structures with varying sizes and shapes, can recognize a wide range of targets with high specificity and affinity. The variable loops of the antibody complementarity-determining region (CDR) are particularly crucial for immune responses and therapeutic applications due to their effective target recognition capabilities. Accurate structure prediction of these antibody loops is essential for the efficient in silico design of target-binding antibodies for therapeutic or industrial use. However, predicting antibody loop structures is challenging due to the lack of evolutionary information from related proteins. Thus, a successful ab initio structure prediction method, which operates without structural templates or related sequences, is crucial for the effective design of antibody loop-mediated interactions. This study demonstrates that highly accurate antibody loop structure prediction enables the effective zero-shot design of target-binding antibody loops. The performance of loop design has been shown to depend on the accuracy of ab initio loop structure prediction, as tested with two versions of our design model. The high affinity, diversity, novelty, and specificity of the antibody loops designed with these new methods were validated experimentally on four target proteins.

bioengineering↗

Engineering a Single Extracellular Vesicle Protein and RNA Assay (siEVPRA) via In Situ Fluorescence Microscopy in a UV Micropatterned Array

The physical and molecular heterogeneity of extracellular vesicles (EVs) confounds bulk biomarker characterization, thus encouraging the development of novel assays capable of profiling EVs at a single-vesicle resolution. Here, we present a single EV (siEV) protein and RNA assay (siEVPRA) to simultaneously detect proteins, messenger RNAs (mRNAs), and microRNAs (miRNAs) in siEVs. The siEVPRA consists of an array of microdomains embedded on a polyethylene glycol (PEG)-coated glass surface produced via UV photopatterning, functionalized with antibodies to target siEV subpopulations. Fluorescently labeled antibodies and RNA-targeting molecular beacons (MBs) were used to generate signals for proteins, mRNAs, and miRNAs on siEVs detected by total internal reflection fluorescence microscopy (TIRFM), outperforming the sensitivities of ELISA and PCR by three orders of magnitude. Using the siEVPRA, we analyzed EVs harvested from glioblastoma (GBM) cell lines and demonstrated vesicular heterogeneity in protein, mRNA, and miRNA expression through colocalization analyses, and validated the results by bulk RNA sequencing. We further demonstrated the clinical utility of the siEVPRA by detecting different mRNAs and miRNAs associated with GBM in patient samples. Together, these results indicate that the siEVPRA provides an effective platform to investigate the heterogeneity of proteins and RNAs in subpopulations of EVs.

bioengineering↗

An Immunogold Single Extracellular Vesicular RNA and Protein (AuSERP) Biochip to Predict Responses to Immunotherapy in Non-Small Cell Lung Cancer Patients

Conventional PD-L1 immunohistochemical tissue biopsies only predict 20~40% of non-small cell lung cancer (NSCLC) patients that will respond positively to anti-PD-1/PD-L1 immunotherapy. Herein, we present an immunogold biochip to quantify single extracellular vesicular RNA and protein (AuSERP) as a non-invasive alternative. With only 3 L of serum, PD-1/PD-L1 proteins on the surface of extracellular vesicles (EVs) and EV PD-1/PD-L1 messenger RNA (mRNA) cargo were detected at a single-vesicle resolution and exceeded the sensitivities of ELISA and qRT-PCR by 1000 times. By testing a cohort of 27 non-responding and 27 responding NSCLC patients, AuSERP indicated that the single-EV mRNA biomarkers surpass the single-EV protein biomarkers at predicting patient responses to immunotherapy. Dual single-EV PD-1/PD-L1 mRNA detection differentiated responders from non-responders with an accuracy of 72.2% and achieved an NSCLC diagnosis accuracy of 93.2%, suggesting the potential for AuSERP to provide enhanced immunotherapy predictions and cancer diagnoses within the clinical setting.

immunology↗