Gwang Lee

Integrated omics-driven discovery reveals synphilin-1-mediated anoikis resistance through p53 down-regulation

Seok Gi Kim, Ye Eun Sim, Abdurazak Aman Ketebo, Ji Su Hwang et autres

Synphilin-1 is a protein that interacts with α-synuclein and has been implicated in Parkinson's disease (PD). However, the cellular and molecular mechanisms underlying the effect of synphilin-1 in PD remain poorly understood. The present study aimed to elucidate the molecular function of …

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Unraveling the Intricacies of G‐Protein‐Coupled Receptor Signaling in Cardiovascular Diseases: Novel Perspectives From Regulation to Therapeutic Targeting

Shaherin Basith, Gwang Lee

G-protein-coupled receptors (GPCRs) represent a compelling intersection of structural biology, systems pharmacology, and clinical medicine. They function as essential molecular regulators of cardiovascular physiology, governing processes from the initiation of cardiac rhythm in the sinoatrial node to the regulation of vascular tone. …

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Submicron traction-force mapping reveals mitochondrial regulation of nanoscale force coordination during rigidity sensing under oxidative stress

Muhammad Hassan, Seok Gi Kim, Dan Bi Im, Jung Seung Lee et autres

Oxidative stress is closely associated with aging, fibrosis, and cancer progression, yet how oxidative stress affects rigidity sensing remains poorly understood. Here, we employed submicron micropillar-based traction-force microscopy to investigate oxidative stress-associated mechanotransduction dysfunction in mouse embryonic fibroblasts (MEFs). Sublethal H 2 …

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SSEL ‐ CPP : A SHAP ‐based feature‐selection ensemble learning framework identifies molecular properties of cell‐penetrating peptides

Chan Kwon, Minjun Kwon, Shaherin Basith, Sampa Misra et autres

Cell-penetrating peptides (CPPs) facilitate the intracellular delivery of therapeutic molecules. However, their accurate identification and design remain challenging because of the complexity of their structural and physicochemical characteristics. This study aimed to develop an interpretable predictive model that enables reliable CPP discovery …

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Submicron traction-force mapping reveals mitochondrial regulation of nanoscale force coordination during rigidity sensing under oxidative stress

Muhammad Hassan, Seok Gi Kim, Dan Bi Im, Jung Seung Lee et autres

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CONTRA-IL6: an interpretable hybrid convolutional neural network and Transformer framework for accurate prediction of interleukin-6-inducing peptides using protein language models

Duong Thanh Tran, Nhat Truong Pham, Gwang Lee, Shaherin Basith et autres

Interleukin-6 (IL-6) is a key immunomodulatory cytokine implicated in diverse physiological processes and pathological conditions, including autoimmune diseases, cancers, and cytokine storms. Immunogenic peptides capable of inducing IL-6 expression are key modulators of host immune responses and represent promising candidates for therapeutic …

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Integrative Peptide Drug Development: Chemical Engineering, AI-Driven Design, and Cell-Penetrating Peptides

Yong Eun Jang, Minjun Kwon, Chan Kwon, Seok Gi Kim et autres

Peptide therapeutics occupy a unique chemical space between small molecules and biologics, combining high target specificity with structural programmability and favorable safety profiles. Recent regulatory approvals and expanding clinical pipelines underscore the growing therapeutic and commercial relevance of peptide-based drugs. This review …

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EnsemPred-ACP: Combining machine and deep learning to improve anticancer peptide prediction

Minjun Kwon, Yong Eun Jang, Ji Su Hwang, Seok Gi Kim et autres

Anticancer peptide (ACP) has emerged as potent therapeutic agents owing to its ability to selectively target cancer cells while minimising toxicity to healthy cells. However, the accurate computational prediction of ACP remains challenging because of the complex molecular mechanisms underlying cancer. In …

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CPPpred-En: Ensemble framework integrating a protein language model and conventional features for highly accurate cell-penetrating peptide prediction

Yong Eun Jang, Minjun Kwon, Seok Gi Kim, Nimisha Pradeep George et autres

Cell-penetrating peptides (CPPs) have gained significant attention for biomedical applications, including drug delivery and therapeutic development, due to their ability to penetrate cell membranes. The accurate prediction of CPPs is critical for accelerating the design and development of novel peptide-based therapies. Approaches …

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1879-LB: Predicting Diabetic Peripheral Neuropathy in Type 2 Diabetes Using a Multimodal Model Integrating Foot Radiograph and Electronic Medical Records

JOON HO MOON, K.-H. Kim, Gwang Lee, Jaetaek Kim

Introduction and Objective: The global rise in diabetes has led to increased chronic complications, with diabetic peripheral neuropathy (DPN) being the most common. Undiagnosed DPN can progress to diabetic foot ulcers, making early screening at type 2 diabetes (T2D) diagnosis crucial. However, …

Optimizing image format piping and instrumentation diagram recognition: Integrating symbol and text recognition with a single backbone architecture

Junhyung Byun, Duhwan Mun, Gwang Lee, Hyungki Kim

Abstract Recent studies propose deep learning-based methods to recognize symbols and text in Piping and Instrumentation Diagrams (P&ID). However, existing approaches use complex processes with separate models for symbol detection, text detection, and text recognition. We propose an integrated model combining symbol-text …

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Synphilin-1 regulates mechanotransduction in rigidity sensing through interaction with zyxin

Seok Gi Kim, Jinyan Li, Ji Su Hwang, Mohamed F. Y. Hassan et autres

BACKGROUND: Synphilin-1 has been studied extensively in the context of Parkinson's disease pathology. However, the biophysical functions of synphilin-1 remain unexplored. To investigate its novel functionalities herein, cellular traction force and rigidity sensing ability are analyzed based on synphilin-1 overexpression using elastomeric …

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