Hongsuk Kang

Inha University

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Hwanho Choi

University of Oxford

Ruhong Zhou

Zhejiang University

Hwangseo Park

Sejong University

Changbong Hyeon

Korea Institute for Advanced Study

D. Thirumalai

The University of Texas at Austin

Binquan Luan

IBM (United States)

Young‐Gui Yoon

Chung-Ang University

Leili Zhang

IBM Research - Thomas J. Watson Research Center

John M. Nuss

Ferring Pharmaceuticals (Switzerland)

Francisco X. Vázquez

St. John's University

Cooperative Institutions

Korea Advanced Institute of Science and Technology

University of Alberta

Korea Research Institute of Chemical Technology

Government of the Republic of Korea

Seoul National University

IBM Research - Thomas J. Watson Research Center

Korea University

Yonsei University

Johannes Kepler University of Linz

Soochow University

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Tunable aggregation of short-side-chain perfluorinated sulfonic acid ionomers for the catalyst layer in polymer electrolyte membrane fuel cells

International Journal of Hydrogen Energy (2020)

Soonyong So Hongsuk Kang Choi Da-Hye Keun‐Hwan Oh

Ionomer

Sulfonic acid

Side chain

10.1016/j.ijhydene.2020.05.128

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Citations (14)

Effects of Macromolecular Crowding on the Collapse of Biopolymers

Physical Review Letters (2015)

Hongsuk Kang P. Pincus Changbong Hyeon D. Thirumalai

Experiments show that macromolecular crowding modestly reduces the size of intrinsically disordered proteins (IDPs) even at volume fraction ($\phi$) similar to that in the cytosol whereas DNA undergoes a coil-to-globule transition at very small $\phi$. We show using a combination of scaling arguments and simulations that the polymer size $\overline{R}_g(\phi)$ depends on $x = \overline{R}_g(0)/D$ where $D$ is the $\phi$-dependent distance between the crowders. If $x\lesssim \mathcal{O}(1)$, there is only a small decrease in $\overline{R}_g(\phi)$ as $\phi$ increases. When $x\gg \mathcal{O}(1)$, a cooperative coil-to-globule transition is induced. Our theory quantitatively explains a number of experiments.

Macromolecular Crowding

Intrinsically Disordered Proteins

Scaling law

Volume fraction

10.1103/physrevlett.114.068303

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Citations (129)

Lost in Sequence: Do Large Language Models Understand Sequential Recommendation?

arXiv (Cornell University) (2025)

Sein Kim Hongsuk Kang Kibum Kim Jiwan Kim Donghyun Kim

Large Language Models (LLMs) have recently emerged as promising tools for recommendation thanks to their advanced textual understanding ability and context-awareness. Despite the current practice of training and evaluating LLM-based recommendation (LLM4Rec) models under a sequential recommendation scenario, we found that whether these models understand the sequential information inherent in users' item interaction sequences has been largely overlooked. In this paper, we first demonstrate through a series of experiments that existing LLM4Rec models do not fully capture sequential information both during training and inference. Then, we propose a simple yet effective LLM-based sequential recommender, called LLM-SRec, a method that enhances the integration of sequential information into LLMs by distilling the user representations extracted from a pre-trained CF-SRec model into LLMs. Our extensive experiments show that LLM-SRec enhances LLMs' ability to understand users' item interaction sequences, ultimately leading to improved recommendation performance. Furthermore, unlike existing LLM4Rec models that require fine-tuning of LLMs, LLM-SRec achieves state-of-the-art performance by training only a few lightweight MLPs, highlighting its practicality in real-world applications. Our code is available at https://github.com/Sein-Kim/LLM-SRec.

Sequence (biology)

10.48550/arxiv.2502.13909

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Self-organized ordering in self-assembled quantum dot superlattices

Materials Science and Engineering B (2002)

G. Springholz V. Holý Peter Mayer M. Pinczolits A. Raab

10.1016/s0921-5107(01)00872-8

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Citations (15)

Potential disruption of protein-protein interactions by graphene oxide

The Journal of Chemical Physics (2016)

Mei Feng Hongsuk Kang Zaixing Yang Binquan Luan Ruhong Zhou

Graphene oxide (GO) is a promising novel nanomaterial with a wide range of potential biomedical applications due to its many intriguing properties. However, very little research has been conducted to study its possible adverse effects on protein-protein interactions (and thus subsequent toxicity to human). Here, the potential cytotoxicity of GO is investigated at molecular level using large-scale, all-atom molecular dynamics simulations to explore the interaction mechanism between a protein dimer and a GO nanosheet oxidized at different levels. Our theoretical results reveal that GO nanosheet could intercalate between the two monomers of HIV-1 integrase dimer, disrupting the protein-protein interactions and eventually lead to dimer disassociation as graphene does [B. Luan et al., ACS Nano 9(1), 663 (2015)], albeit its insertion process is slower when compared with graphene due to the additional steric and attractive interactions. This study helps to better understand the toxicity of GO to cell functions which could shed light on how to improve its biocompatibility and biosafety for its wide potential biomedical applications.

Nanosheet

Nanomaterials

Biocompatibility

10.1063/1.4953562

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Citations (27)

Glassy dynamics in mutant huntingtin proteins

The Journal of Chemical Physics (2018)

Hongsuk Kang Binquan Luan Ruhong Zhou

Causative to the neurodegenerative Huntington's disease (HD), a mutational huntingtin (HTT) protein consists of an unusual expansion on the poly-glutamine (polyQ) region in the first exon (exon-1) domain. Despite its significance on HD progression, the structural role of the exon-1 with the polyQ region is still elusive. As HTT is an intrinsically disordered protein (IDP), a large ensemble of various conformations (instead of a mostly single native conformation) is required to characterize its structural properties and to infer biological functions, which is challenging even for the most state-of-the-art experimental techniques. For this reason, molecular dynamics (MD) simulations with enhanced sampling techniques are ideal to compliment experiment on collecting such a large ensemble of thermodynamically accessible structures. Here, we performed large-scale temperature replica-exchange MD (T-REMD) simulations on the exon-1 with an illustration on the necessity of using T-REMD instead of unbiased regular MD. By comparing T-REMD data and unbiased MD data, we discovered that (1) the dynamics of polyQ regions are extremely sluggish and glassy at the room temperature and the relaxation of the system cannot be achieved within a reasonable amount of time without utilizing an enhanced sampling method and (2) an ensemble of protein structures containing the surprising cis-peptide bonds in the proline-rich domain can be obtained at much elevated temperatures. Our results may provide valuable insights for future studies on the HTT as well as other IDPs using the T-REMD method.

Huntingtin Protein

Intrinsically Disordered Proteins

10.1063/1.5029369

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Citations (12)

Extended Morse Function Model for Angle-Dependent Hydrogen Bond in Protein−Protein Interactions

The Journal of Physical Chemistry B (2010)

Hwanho Choi Hongsuk Kang Hwangseo Park

Backbone-backbone, backbone-asparagine, and serine-backbone hydrogen bonds (HBs) are the most abundant interactions at the interface of protein-protein complex. Here, we propose an angle-dependent potential energy function for these HBs constructed by the product of the radial and the angular Morse functions whose various parameters are optimized with high-level density functional theory (DFT) calculations. The new angular variables, the interatomic distance between the donor and the acceptor atoms (R(theta)) and that between the hydrogen and the base atom of the acceptor (R(phi)), are employed to define the angular Morse functions. The angular part in the new potential function is found to be comparable in the magnitude of energy values to the radial one, which is consistent with the significant angular dependence of HBs. The HB binding energies calculated with the new potential function compare well with those obtained by high-level DFT calculations with the associated squared correlation coefficients ranging from 0.82 to 0.85. This agreement indicates the suitability of the new energy functions as a potential function for HB in modeling the protein-protein interactions.

Morse potential

10.1021/jp909983y

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Citations (11)

Lanosterol Disrupts Aggregation of Human γD-Crystallin by Binding to the Hydrophobic Dimerization Interface

Journal of the American Chemical Society (2018)

Hongsuk Kang Zaixing Yang Ruhong Zhou

Cataracts are a leading cause of vision impairment, which stem from the misfolding and aggregation of crystallins in the eye lens. Despite its prevalence and severity, the detailed mechanism by which misfolded crystallins aggregate into cataracts remains elusive. Recently, in vitro and in vivo experiments demonstrated that lanosterol, a steroid-type compound found in human and animal eyes, can not only prevent cataract formation but also reverse the formation. Inspired by these experimental observations, we investigate the preventive activity of lanosterol in the aggregate formation of human γD-crystallins (HγD-Crys) using all atom molecular dynamics (MD) simulation and free energy perturbation (FEP) techniques. Our results reveal that lanosterol preferentially binds to the HγD-Crys hydrophobic dimerization interface, in particular, to the structured C-terminus (near residues 135–165) with a stronger binding affinity than the unfolded N-terminus. Furthermore, we observe that the C-terminal binding is more favorable than lanosterol self-aggregation, further attesting to lanosterol's efficacy. Finally, we compare the binding free energy of lanosterol with cholesterol using alchemical transformation and discuss the possible correlation of the molecular geometry of steroids with binding affinity.

Lanosterol

Crystallin

10.1021/jacs.8b03065

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Citations (42)

MetLigDB: a web-based database for the identification of chemical groups to design metalloprotein inhibitors

Journal of Applied Crystallography (2011)

Hwanho Choi Hongsuk Kang Hwangseo Park

MetLigDB (http://silver.sejong.ac.kr/MetLigDB) is a publicly accessible web-based database through which the interactions between a variety of chelating groups and various central metal ions in the active site of metalloproteins can be explored in detail. Additional information can also be retrieved, including protein and inhibitor names, the amino acid residues coordinated to the central metal ion, and the binding affinity of the inhibitor for the target metalloprotein. Although many metalloproteins have been considered promising targets for drug discovery, it is difficult to discover new inhibitors because of the difficulty in designing a suitable chelating moiety to impair the catalytic activity of the central metal ion. Because both common and specific chelating groups can be identified for varying metal ions and the associated coordination environments, MetLigDB is expected to give users insight into designing new inhibitors of metalloproteins for drug discovery.

Metalloprotein

Moiety

10.1107/s0021889811022503

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Citations (14)

Genetically encoded discovery of perfluoroaryl macrocycles that bind to albumin and exhibit extended circulation in vivo

Nature Communications (2023)

Jeffrey Y. K. Wong Arunika I. Ekanayake Serhii Kharchenko Steven E. Kirberger Ryan Qiu

Peptide-based therapeutics have gained attention as promising therapeutic modalities, however, their prevalent drawback is poor circulation half-life in vivo. In this paper, we report the selection of albumin-binding macrocyclic peptides from genetically encoded libraries of peptides modified by perfluoroaryl-cysteine SNAr chemistry, with decafluoro-diphenylsulfone (DFS). Testing of the binding of the selected peptides to albumin identified SICRFFC as the lead sequence. We replaced DFS with isosteric pentafluorophenyl sulfide (PFS) and the PFS-SICRFFCGG exhibited KD = 4-6 µM towards human serum albumin. When injected in mice, the concentration of the PFS-SICRFFCGG in plasma was indistinguishable from the reference peptide, SA-21. More importantly, a conjugate of PFS-SICRFFCGG and peptide apelin-17 analogue (N3-PEG6-NMe17A2) showed retention in circulation similar to SA-21; in contrast, apelin-17 analogue was cleared from the circulation after 2 min. The PFS-SICRFFC is the smallest known peptide macrocycle with a significant affinity for human albumin and substantial in vivo circulation half-life. It is a productive starting point for future development of compact macrocycles with extended half-life in vivo.

Human serum albumin

Apelin

Serum Albumin

10.1038/s41467-023-41427-y

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Citations (4)