Sun Choi
Ewha Womans University · 生化学・遺伝学・分子生物学
研究室紹介
Professor Sun Choi's research lab specializes in computational and systems biology-driven drug discovery, with a focus on rational design of therapeutics targeting cancer, metabolic disorders, and neurological diseases. The lab integrates molecular dynamics simulations, machine learning, and big data analytics to investigate protein-ligand interactions, epigenetic regulation, and the mechanisms of drug action. A key emphasis is on developing innovative nanotheranostic platforms and identifying novel drug candidates through in silico screening and structure-based design. The lab also explores the therapeutic potential of natural compounds like capsaicin and epigenetic modulators such as DNMT inhibitors.
Research Overview
Research Output Trend
Figures are computed from collected data and may differ slightly.
Selected Papers
15Albumin is a promising candidate as a biomarker for potential disease diagnostics and has been extensively used as a drug delivery carrier for decades. In these two directions, many albumin-detecting probes and exogenous albumin-based nanocomposite delivery systems have been developed. However, there are only a few cases demonstrating the specific interactions of exogenous probes with albumin in vivo, and nanocomposite delivery systems usually suffer from tedious fabrication processes and potent
Capsaicin is the most predominant and naturally occurring alkamide found in Capsicum fruits. Since its discovery in the 19th century, the therapeutic roles of capsaicin have been well characterized. The potential applications of capsaicin range from food flavorings to therapeutics. Indeed, capsaicin and few of its analogues have featured in clinical research covered by more than a thousand patents. Previous records suggest pleiotropic pharmacological activities of capsaicin such as an analgesic,
Molecular dynamics (MD) simulation is a rigorous theoretical tool that when used efficiently could provide reliable answers to questions pertaining to the structure-function relationship of proteins. Data collated from protein dynamics can be translated into useful statistics that can be exploited to sieve thermodynamics and kinetics crucial for the elucidation of mechanisms responsible for the modulation of biological processes such as protein-ligand binding and protein-protein association. Con
The primary goal of rational drug discovery is the identification of selective ligands which act on single or multiple drug targets to achieve the desired clinical outcome through the exploration of total chemical space. To identify such desired compounds, computational approaches are necessary in predicting their drug-like properties. G Protein-Coupled Receptors (GPCRs) represent one of the largest and most important integral membrane protein families. These receptors serve as increasingly attr
There have been numerous advances in the development of computational and statistical methods and applications of big data and artificial intelligence (AI) techniques for computer-aided drug design (CADD). Drug design is a costly and laborious process considering the biological complexity of diseases. To effectively and efficiently design and develop a new drug, CADD can be used to apply cutting-edge techniques to various limitations in the drug design field. Data pre-processing approaches, whic
DNA methylation is an epigenetic modification that regulates gene expression by DNA methyltransferases (DNMTs). Inhibition of DNMTs is a promising approach for cancer therapy. Recently, novel classes of the quinolone-based compound, SGI-1027, and RG108-procainamide conjugates, CBC12, have been identified as potent DNMT inhibitors. In this work, we report comprehensive studies using induced-fit docking of SGI-1027 and CBC12 with human DNMT1 and DNMT3A. The docking was performed in the C-terminal
G-protein coupled receptors (GPCRs), a major gatekeeper of extracellular signals on plasma membrane, are unarguably one of the most important therapeutic targets. Given the recent discoveries of allosteric modulations, an allosteric wiring diagram of intramolecular signal transductions would be of great use to glean the mechanism of receptor regulation. Here, by evaluating betweenness centrality (CB ) of each residue, we calculate maps of information flow in GPCRs and identify key residues for s
On the basis of the potent inhibitory activity of neplanocin A (1) against S-adenosylhomocysteine (AdoHcy) hydrolase, we analyzed the comprehensive structure-activity relationships by modifying the adenine and carbasugar moiety of 1 to find the pharmacophore in the active site of the enzyme. The introduction of 7-deazaadenine instead of adenine eliminated the inhibitory activity against the AdoHcy hydrolase, while 3-deazaadenine maintained the inhibitory activity of the enzyme, indicating that N
Cancer is considered as one of the world's leading causes of morbidity and mortality. Over the past four decades, spectacular advances in molecular and cellular biology have led to major breakthroughs in the field of cancer research. However, the design and development of anticancer drugs prove to be an intricate, expensive, and time-consuming process. To overcome these limitations and manage large amounts of emerging data, computer- aided drug discovery/design (CADD) methods have been developed