논문

2026

1. 53. Analysis of University Students’ Perceptions of the Importance of Chemical Knowledge in Chemistry-Related Occupations

   H Kim, JM Choi, M Kim, and J Park^†

   Journal of Research in Curriculum & Instruction 30 (2): 190–202 (2026)

   Abs 초록 DOI

   While the importance of the chemical industry continues to grow, avoidance of chemistry in educational settings has also intensified. In this context, understanding how university students perceive the importance of chemical knowledge across chemistry-related occupations can provide significant implications for chemistry education and career guidance. This study surveyed 429 university students to investigate their perceptions of the importance of chemical knowledge across 24 chemistry-related occupations. In-depth interviews were also conducted with 7 of the survey participants. The collected data were categorized and compared by occupational type, academic major, and gender. The results indicated that students perceived chemical knowledge as more important in occupations whose core professional identity is closely associated with chemistry, and less important in occupations where the functional link to chemistry is less explicit. Furthermore, as the relevance to chemistry became more distal, perceptions of importance declined more sharply among male students and non-chemistry majors. Based on these findings, this study suggests the need to strengthen career-linked education in chemistry education and to design educational approaches that foster chemistry-literate citizens.

   화학 산업의 중요성이 증대되고 있으나 교육 현장에서는 화학 기피 현상이 심화되는 상황에서, 대학생들이 화학 관련 직업에서 화학 지식의 중요도를 어떻게 인식하는지 파악하는 것은 화학 교육과 진로 지도에 중요한 시사점을 제공할 수 있다. 이 연구는 대학생 429명을 대상으로 설문을 시행하여 24개 화학 관련 직업에 대해 이들이 인식하는 화학 지식 중요도를 조사하였고, 설문에 참여한 학생 중 7명을 대상으로 심층 인터뷰하였다. 수집된 자료는 직업 유형, 전공 계열, 성별에 따라 구분하여 비교하였다. 연구 결과, 대학생들은 직업의 핵심 정체성이 화학과 가까울수록 화학 지식의 중요도를 높게 인식하였으며, 외연적 연결이 덜 명시적인 직업에서는 중요도를 낮게 인식하였다. 또한 화학과의 관련성이 덜 명시적인 직업일수록 남학생과 비화학 계열 학생에서 중요도 인식이 더 빠르게 감소하였다. 이러한 결과를 바탕으로 화학 교육에서의 진로 연계 교육 강화와 화학적 소양을 갖춘 시민 양성을 위한 교육적 설계의 필요성을 제언하였다.

2. 52. Mechanistic Elucidation of Solution-Processable n-type Doping via Rhodamine B for Photoresponsive Neuromorphic Organic Semiconductors

   Y Kim, MH Kim, SB Woo, M Kim, JM Choi^†, and EK Lee^†

   Macromolecular Research 34 (4): 493–506 (2026)

   Note Abs DOI

   Featured on the Cover

   While organic semiconductors (OSCs) offer potential for next-generation electronics, n-type doping in solution-processed OSCs consistently lags behind p-type doping in efficiency, stability, and reproducibility. A fundamental limitation is the lack of a comprehensive understanding of specific molecular interactions between OSCs and dopants at the structural level. This study addresses this challenge by investigating leuco-Rhodamine B (leuco-RhoB) as an n-type dopant for two polymer OSCs of DPP-DTT and N2200. Combining experimental methods with density functional theory calculations, we elucidate the molecular interactions governing OSC-dopant binding preferences and their impact on electrical performance. Spatial overlap between the van der Waals volumes of the OSCs and leuco-RhoB correlates with binding energy, with N2200 exhibiting stronger binding than DPP-DTT. This enhanced interaction is consistent with improved spatial complementarity, contributing to the improved doping efficiency observed in N2200. Atomic force microscopy and x-ray diffraction analyses confirm better miscibility of leuco-RhoB with N2200, while electrical characterization demonstrates typical n-type doping effects. Leuco-RhoB-doped OSCs exhibit enhanced photoresponsive behavior with improved responsivity, external quantum efficiency, and detectivity, along with faster response times of 0.08 s. These findings advance the rational design of n-type dopants by highlighting the importance of specific structural interactions with OSC beyond energy level alignment.

3. 51. Unveiling the Intramolecular Thermodynamics of Multivalent Proteins: Exploratory Study on Engineered Protein Model

   Yn Kim^*, BH Choi^*, H Park^*, CG Kim^*, Y Eom, Y Jung^†, and JM Choi^†

   Biomacromolecules 27 (4): 2489–2501 (2026)

   Abs DOI

   Multivalent interactions mediated by multidomain proteins are pivotal in numerous biological processes. However, the thermodynamic intricacies of the domain interactions within such complexes remain elusive. In this study, we employed surface plasmon resonance to explore the temperature-dependent kinetics of multidomain protein interactions across various valences from monomers to tetramers. Rigorous screening of protein–peptide binding pairs fused with discrete multivalent protein scaffolds facilitated the selection of candidates with minimal nonspecific interactions and suitable monomer binding kinetics that could be extended to higher valences. We developed a theoretical model to extract the thermodynamic quantities for both inter- and intramolecular interactions. By employing initial rate analysis, we could extract thermodynamic quantities describing complicated interactions between multivalent proteins. Our analysis provides novel insights into the thermodynamics of intramolecular interactions in multivalent protein complexes with implications for protein design and engineering.

2025

1. 50. Supersaturation, Nucleation, and Phase Separation of Mesoscopic Systems

   J Kang^*, D Kim^*, S Song^*, J Han, Y Jung, S Yoon, Y Ryu, S Kim, BH Kim, JM Choi, M Yang, J Jang, T Hyeon, J Park^†, JH Kim^†, and J Sung^†

   Journal of the American Chemical Society 147 (51): 46976–46985 (2025)

   Abs DOI

   Supersaturation, nucleation, and phase separation are ubiquitous phenomena of great interest in both science and industry. However, a unified, quantitative understanding of these phenomena has yet to be achieved for mesoscopic systems. Here, we present a set of general equations that determine the monomer saturation degree, the size distribution, and the free energy of mesoscopic systems, as well as their phase-transition conditions. These equations reveal that, under supersaturation, the largest cluster size (LCS) is an important state variable; the supersaturation degree decreases with the LCS, approaching unity in the macroscopic limit. We identify the critical supersaturation, at which the nuclei undergo the phase transition to form large crystals. Below this critical supersaturation, the nucleus size distribution is either a unimodal function or a monotonically decreasing function of size, depending on the system and temperature. We also predict the most probable nucleus size and the direction of spontaneous changes of the LCS. Our theory provides a unified, quantitative explanation of the nucleus-size-distribution across six different systems, including nanoparticles and biological condensates. This work serves as a general theoretical framework useful for understanding and designing nucleation and phase transitions of mesoscopic systems.

2. 49. DFT Investigation of Metal Coordination and Reactivity in Minimal Metalloenzyme Models

   R Kumar, Y Kim, and JM Choi^†

   Journal of Inorganic Biochemistry 272: 113018 (2025)

   Abs DOI

   Metalloenzymes achieve catalytic functionality by precisely controlling their metal coordination environments through structural constraints. However, the influence of structural rigidity on metal substitution and its impact on enzyme structure and reactivity has not been fully elucidated. To address this, we investigated how structural constraints affect metal coordination geometry, energetics, and reactivity within the active site of human carbonic anhydrase II (CA II) using DFT. We constructed semi-constrained models of metal substituted CA II from their X-ray crystal structures containing Zn²⁺ (native), Cu²⁺, Ni²⁺, and Co²⁺. Semi-constrained models were constructed to mimic the microenvironment of the protein active site, and multiple DFT methods were benchmarked to identify an accurate and efficient computational approach. Structural constraints lead to a rugged energy landscape with multiple local minima, and we found that upon metal substitutions, the competition between the structural constraints and the intrinsic coordination chemistry leads to diverse consequences in final geometry. We also found that the native metal ion (Zn²⁺) in metalloenzymes CA II does not always exhibit the strongest binding among the metal ions tested; instead, the trends follow the Irving-Williams series. However, electrophilicity analysis revealed that constrained geometries modulate the electronic reactivity of the metal center, with Zn²⁺ consistently exhibiting the highest electrophilicity, and this explains the evolutionary optimization of the metalloenzyme. These findings enhance our understanding of metal coordination under structural constraints and provide a computational basis for exploring metal substitutions in artificial metalloenzymes.

3. 48. Single-Molecule Tweezers Decode Hidden Dimerization Patterns of Membrane Proteins within Lipid Bilayers

   VW Sadongo^*, E Kim^*, S Kim^*, WCB Wijesinghe, T Lee, JM Choi, and D Min^†

   Nature Communications 16: 7366 (2025)

   Abs DOI

   Dimerization of transmembrane (TM) proteins is a fundamental process in cellular membranes, central to numerous physiological and pathological pathways, and increasingly recognized as a promising therapeutic target. Although often described as a simple two-state transition from monomers to dimers, the process following monomer diffusion—referred to as post-diffusion dimerization—is likely more intricate due to complex inter-residue interactions. Here, we present a single-molecule tweezer platform that directly profiles these post-diffusion transitions during TM protein dimerization. This approach captures reversible dimerization events of individual TM dimers, revealing previously hidden intermediate states that emerge after monomer diffusion. By integrating measurements of intermediates, kinetics, and energy landscapes with molecular dynamics simulations, we delineate the dimerization pathway and dissect how residue interactions and lipid bilayers influence the process. Furthermore, our platform allows for the targeted analysis of localized perturbations—such as those induced by peptide binding or site-directed mutagenesis—demonstrating its utility for probing the mechanisms of TM dimer-targeting therapeutics at single-molecule resolution.

4. 47. Design Principles of Protein–Protein Interfaces

   CG Kim, TH Kim, and JM Choi^†

   Bulletin of the Korean Chemical Society 46 (8): 791–795 (2025)

   Abs DOI

   We investigated the energy landscape of protein–protein complexes using a customizable energy model. Our findings highlight the crucial role of contact differences in distinguishing between authentic proteins and decoys, emphasizing the importance of accurately capturing favorable contacts. These insights contribute to the development of computational models for protein–protein interactions.

5. 46. Investigating the Nature of PRM:SH3 Interactions Using Artificial Intelligence and Molecular Dynamics

   SJ Kim, DE Hwang, H Kim, and JM Choi^†

   Journal of Chemical Information and Modeling 65 (11): 5662–5671 (2025)

   Abs DOI

   Understanding the binding interactions within protein–peptide complexes is crucial for elucidating key physicochemical phenomena in biological systems. Among the outcomes of these interactions, biomolecular condensates have recently emerged as vital players in various cellular functions including signaling. Complexes such as PRM:SH3 are known to undergo condensation, yet the chemical interactions and governing factors driving these behaviors remain poorly understood. In this study, we combine AlphaFold2 and molecular dynamics simulations to investigate the binding nature of PRM:SH3. Our findings reveal that proline-to-alanine mutations enhance flexibility, weakening the binding affinity, while charge-altering mutations modify the binding mode and influence the binding strength. Notably, the PRM(H) series shows that binding is primarily driven by local flexibility and the hydrophobic effect. Furthermore, we demonstrate that the root-mean-square deviation and dendrogram height are correlated to experimental dissociation constants. These insights provide a framework for understanding the binding behaviors of protein–peptide complexes and offer an effective approach for studying similar systems.

6. 45. Fast Product Release Requires Active-Site Water Dynamics in Carbonic Anhydrase

   JK Kim, SW Lim, H Jeong, C Lee, S Kim, DW Son, R Kumar, JT Andring, C Lomelino, JL Wierman, AE Cohen, TJ Shin, CM Ghim, R McKenna, BH Jo, D Min, JM Choi, and CU Kim^†

   Nature Communications 16: 4404 (2025)

   Abs DOI

   Water plays an essential role in enzyme structure, stability, and the substantial rate enhancement of enzyme catalysis. However, direct observations linking enzyme catalysis and active-site water dynamics pose a significant challenge due to experimental difficulties. By integrating an ultraviolet (UV) photolysis technique with temperature-controlled X-ray crystallography, we track the catalytic pathway of carbonic anhydrase II (CAII) at 1.2 Å resolution. This approach enables us to construct molecular movies of CAII catalysis, encompassing substrate (CO₂) binding, conversion from substrate to product (bicarbonate), and product release. In the catalytic pathway, we identify an unexpected configuration in product binding and correlate it with sub-nanosecond rearrangement of active-site water. Based on these experimental observations, we propose a comprehensive mechanism of CAII and describe the detailed structure and dynamics of active-site water in CAII. Our findings suggest that CAII has evolved to utilize the structure and fast dynamics of the active-site waters for its diffusion-limited catalytic efficiency.

7. 44. A Single Amino Acid Model for Hydrophobically Driven Liquid–Liquid Phase Separation

   HJ Jeon, JH Lee, AJ Park, JM Choi^†, and K Kang^†

   Biomacromolecules 26 (2): 1075–1085 (2025)

   Abs DOI

   This study proposes fluorenylmethoxycarbonyl (Fmoc)-protected single amino acids (Fmoc-AAs) as a minimalistic model system to investigate liquid–liquid phase separation (LLPS) and the elusive liquid-to-solid transition of condensates. We demonstrated that Fmoc-AAs exhibit LLPS depending on the pH and ionic strength, primarily driven by hydrophobic interactions. Systematic examination of the conditions under which each Fmoc-AA undergoes LLPS revealed distinct residue-dependent trends in the critical concentrations and phase behavior. Importantly, we elucidated the liquid-to-solid transition process, suggesting that it may be driven by a molecular mechanism different from that of LLPS. Fmoc-AA condensates showed promise for biomolecular enrichment and catalytic applications. This work provides significant insights into the molecular mechanisms of LLPS and the subsequent liquid-to-solid transition, offering a robust platform for future studies related to protocells and protein aggregation diseases.

2024

1. 43. Hidden Route of Protein Damage through Oxygen-Confined Photooxidation

   S Kim^*, E Kim^*, M Park^*, SH Kim^*, BG Kim, S Na, VW Sadongo, WCB Wijesinghe, YG Eom, G Yoon, H Jeong, E Hwang, C Lee, K Myung, CU Kim, JM Choi, SK Min^†, TH Kwon^†, and D Min^†

   Nature Communications 15: 10873 (2024)

   Abs DOI

   Oxidative modifications can disrupt protein folds and functions, and are strongly associated with human aging and diseases. Conventional oxidation pathways typically involve the free diffusion of reactive oxygen species (ROS), which primarily attack the protein surface. Yet, it remains unclear whether and how internal protein folds capable of trapping oxygen (O₂) contribute to oxidative damage. Here, we report a hidden pathway of protein damage, which we refer to as O₂-confined photooxidation. In this process, O₂ is captured in protein cavities and subsequently converted into multiple ROS, primarily mediated by tryptophan residues under blue light irradiation. The generated ROS then attack the protein interior through constrained diffusion, causing protein damage. The effects of this photooxidative reaction appear to be extensive, impacting a wide range of cellular proteins, as supported by whole-cell proteomic analysis. This photooxidative mechanism may represent a latent oxidation pathway in human tissues directly exposed to visible light, such as skin and eyes.

2. 42. Accelerated Amyloid Aggregation Dynamics of Intrinsically Disordered Proteins in Heavy Water

   MK Son, D Im, DG Hyun, S Kim, SY Chun, JM Choi, TS Choi, M Cho^†, K Kwak^†, and HI Kim^†

   The Journal of Physical Chemistry Letters 15 (47): 11823–11829 (2024)

   Abs DOI

   We explored the influence of D₂O on the fibrillation kinetics and structural dynamics of amyloid intrinsically disordered proteins (IDPs), including α-synuclein, amyloid-β 1–42, and K18. Our findings revealed that fibrillation of IDPs was accelerated in D₂O compared to that in H₂O, exhibiting faster kinetics in contrast to the structured protein, insulin. Structural investigations using electrospray ionization ion mobility mass spectrometry and small-angle X-ray scattering combined with molecular dynamics simulations demonstrated that IDPs did not show significant structural changes that could influence accelerated fibrillation in D₂O. Umbrella sampling of protein protofibrils verified that an increased level of hydrogen bonding of D₂O and enhanced hydrophobic interactions stabilized β-sheet structured fibrils in D₂O. These findings indicate that stabilizing β-sheet fibrils and a more hydrophobic microenvironment in D₂O result in enhanced and faster fibrillation of IDPs. The study highlights the importance of considering D₂O’s differential impact on protein interactions when conducting structural and kinetic analyses, particularly for native peptides and proteins.

3. 41. n-Type Doping Effect of Anthracene-Based Cationic Dyes in Organic Electronics

   Y Kim, M Jung, R Kumar, JM Choi, EK Lee^†, and J Lee^†

   ACS Applied Materials & Interfaces 16 (33): 43774–43785 (2024)

   Abs DOI

   n-Type doping for improving the electrical characteristics and air stability of n-type organic semiconductors (OSCs) is important for realizing advanced future electronics. Herein, we report a selection method for an effective n-type dopant with an optimized structure and thickness based on anthracene cationic dyes with high miscibility induced by a molecular structure similar to that of OSCs. Among the doped OSCs evaluated, rhodamine B (RhoB)-doped OSC exhibits the highest density, a smallest roughness of 2.69 nm, a phase deviation of 0.85° according to atomic force microscopy measurements, and the highest electron mobility (μ), showing its high miscibility. Surface doping of RhoB affords the lowest contact resistance of 2.01 × 10⁵ Ω cm compared to bulk and contact doping, resulting in an effective doping structure. The RhoB-doped OSC retains 81.63% of the original μ value of 6.13 × 10^–2 cm² V^–1 s^–1 after 15 days, whereas pristine OSC shows a lower μ of 2.33 × 10^–2 cm² V^–1 s^–1 and maintains only 4.41% of the original value after 15 days. Our findings demonstrate that this methodology is effective for the selection of a high-performance n-type dopant for OSCs toward the development of high-performance and air-stable n-type organic electronics.

4. 40. Combinatorial Entropy Determines the Early Stages of Nucleation

   DH Koo^*, HJ Park^*, and JM Choi^†

   Bulletin of the Korean Chemical Society 45 (6): 526–529 (2024)

   Abs DOI

   Biomolecular phase separation, a complex phenomenon within living systems, has garnered significant interest due to its diverse roles in cellular organization and function. Despite its importance, studying phase separation dynamics experimentally, particularly in the early stages, poses challenges. Our study investigates the dynamics of biomolecular phase separation using a graph-based simulation module, particularly emphasizing its early stages. Through a simplified model, we dissect the influences of various factors on collective behavior, highlighting the crucial role of combinatorial entropy in percolation dynamics. This study offers valuable insights into the fundamental principles governing biomolecular phase separation, with implications for understanding cellular processes and disease mechanisms.

5. 39. Biomolecular Phase Separation through Theoretical and Computational Microscope

   R Kumar^*, DH Koo^*, YG Eom^*, and JM Choi^†

   Bulletin of the Korean Chemical Society 45 (5): 420–434 (2024)

   Abs DOI

   Biomolecular phase separation is a vital mechanism for orchestrating biomolecules within living cells. This crucial role has spurred an intense pursuit to comprehend the molecular underpinnings governing and regulating these processes. Computational methodologies offer a unique perspective, augmenting experimental techniques by providing detailed information that cannot be obtained otherwise. In this review, we briefly overview the theoretical and computational approaches to investigate biomolecular phase separation. As a short primer, we explain the factors driving and affecting phase separation of biomolecules, and then we delve into analytical and simulation methods used to study phase separation. We explain how analytical methods like the Flory–Huggins theory, random phase approximation, and graph-based methods have been used to study phase behaviors of various proteins. We also discuss principles and applications of all-atom simulations, coarse-grained simulations, and field-theoretical approaches. Additionally, we explore the recent advances in machine learning approach to predict phase separation of biomolecules.

6. 38. Intermolecular Interactions between Cysteine and Aromatic Amino Acids with a Phenyl Moiety in the DNA-Binding Domain of Heat Shock Factor 1 Regulate Thermal Stress-Induced Trimerization

   CJ Lee, BH Choi, SS Kim, DNJ Kim, TH Kim, JM Choi, Y Pak^†, and JS Park^†

   Biochemistry 63 (10): 1307–1321 (2024)

   Abs DOI

   In this study, we investigated the trimerization mechanism and structure of heat shock factor 1 (HSF1) using western blotting, tryptophan (Trp) fluorescence spectroscopy, and molecular modeling. First, we examined the DNA-binding domains of human (Homo sapiens), goldfish (Carassius auratus), and walleye pollock (Gadus chalcogrammus) HSF1s by mutating key residues (36 and 103) that are thought to directly affect trimer formation. Human, goldfish, and walleye pollock HSF1s contain cysteine at residue 36 but cysteine (C), tyrosine (Y), and phenylalanine (F), respectively, at residue 103. The optimal trimerization temperatures for the wild-type HSF1s of each species were found to be 42, 37, and 20 °C, respectively. Interestingly, a mutation experiment revealed that trimerization occurred at 42 °C when residue 103 was cysteine, at 37 °C when it was tyrosine, and at 20 °C when it was phenylalanine, regardless of the species. In addition, it was confirmed that when residue 103 of the three species was mutated to alanine, trimerization did not occur. This suggests that in addition to trimerization via disulfide bond formation between the cysteine residues in human HSF1, trimerization can also occur via the formation of a different type of bond between cysteine and aromatic ring residues such as tyrosine and phenylalanine. We also confirmed that at least one cysteine is required for the trimerization of HSF1s, regardless of its position (residue 36 or 103). Additionally, it was shown that the trimer formation temperature is related to growth and survival in fish.

7. 37. Biomolecular Condensates Form Spatially Inhomogeneous Network Fluids

   F Dar^*, SR Cohen^*, DM Mitrea, AH Phillips, G Nagy, WC Leite, CB Stanley, JM Choi^*†, RW Kriwacki^†, and RV Pappu^†

   Nature Communications 15: 3413 (2024)

   Abs DOI

   The functions of biomolecular condensates are thought to be influenced by their material properties, and these will be determined by the internal organization of molecules within condensates. However, structural characterizations of condensates are challenging, and rarely reported. Here, we deploy a combination of small angle neutron scattering, fluorescence recovery after photobleaching, and coarse-grained molecular dynamics simulations to provide structural descriptions of model condensates that are formed by macromolecules from nucleolar granular components (GCs). We show that these minimal facsimiles of GCs form condensates that are network fluids featuring spatial inhomogeneities across different length scales that reflect the contributions of distinct protein and peptide domains. The network-like inhomogeneous organization is characterized by a coexistence of liquid- and gas-like macromolecular densities that engenders bimodality of internal molecular dynamics. These insights suggest that condensates formed by multivalent proteins share features with network fluids formed by systems such as patchy or hairy colloids.

8. 36. pH Dependence of HSF1 Trimerization is Shaped by Intramolecular Interactions

   BH Choi^*, CJ Lee^*, TH Kim, DNJ Kim, YS Pak, JM Choi^†, and JS Park^†

   Biochemical and Biophysical Research Communications 709: 149824 (2024)

   Abs DOI

   Heat shock factor 1 (HSF1) primarily regulates various cellular stress responses. Previous studies have shown that low pH within the physiological range directly activates HSF1 function in vitro. However, the detailed molecular mechanisms remain unclear. This study proposes a molecular mechanism based on the trimerization behavior of HSF1 at different pH values. Extensive mutagenesis of human and goldfish HSF1 revealed that the optimal pH for trimerization depended on the identity of residue 103. In particular, when residue 103 was occupied by tyrosine, a significant increase in the optimal pH was observed, regardless of the rest of the sequence. This behavior can be explained by the protonation state of the neighboring histidine residues, His101 and His110. Residue 103 plays a key role in trimerization by forming disulfide or non-covalent bonds with Cys36. If tyrosine resides at residue 103 in an acidic environment, its electrostatic interactions with positively charged histidine residues prevent effective trimerization. His101 and His110 are neutralized at a higher pH, which releases Tyr103 to interact with Cys36 and drives the effective trimerization of HSF1. This study showed that the protonation state of a histidine residue can regulate the intramolecular interactions, which consequently leads to a drastic change in the oligomerization behavior of the entire protein.

9. 35. Thermodynamic Modulation of Gephyrin Condensation by Inhibitory Synapse Components

   G Lee, S Kim, DE Hwang, YG Eom, G Jang, HY Park, JM Choi^†, J Ko^†, and Y Shin^†

   Proceedings of the National Academy of Sciences of the United States of America 121 (12): e2313236121 (2024)

   Abs DOI

   Phase separation drives compartmentalization of intracellular contents into various biomolecular condensates. Individual condensate components are thought to differentially contribute to the organization and function of condensates. However, how intermolecular interactions among constituent biomolecules modulate the phase behaviors of multicomponent condensates remains unclear. Here, we used core components of the inhibitory postsynaptic density (iPSD) as a model system to quantitatively probe how the network of intra- and intermolecular interactions defines the composition and cellular distribution of biomolecular condensates. We found that oligomerization-driven phase separation of gephyrin, an iPSD-specific scaffold, is critically modulated by an intrinsically disordered linker region exhibiting minimal homotypic attractions. Other iPSD components, such as neurotransmitter receptors, differentially promote gephyrin condensation through distinct binding modes and affinities. We further demonstrated that the local accumulation of scaffold-binding proteins at the cell membrane promotes the nucleation of gephyrin condensates in neurons. These results suggest that in multicomponent systems, the extent of scaffold condensation can be fine-tuned by scaffold-binding factors, a potential regulatory mechanism for self-organized compartmentalization in cells.

2023

1. 34. Mendeleev’s Cards: Educational Game to Learn Mendeleev’s Idea on the Periodic Table of Elements

   SH Yang^*† and JM Choi^*†

   Journal of Chemical Education 100 (12): 4925–4932 (2023)

   Abs DOI

   The periodic table is a fundamental tool used in chemistry classes that allows students to systematically understand different types of elements and their physical and chemical properties. While many textbooks emphasize the historical process of classifying substances, they often superficially elucidate the achievements of chemists such as Dmitry Mendeleev. To motivate students to learn the periodic table and characteristics of elements, various pedagogical methods using games have been developed. However, none have focused on reproducing Mendeleev’s table based on his perspective. In this study, the authors developed a card game for students to follow the logical process behind the development of the periodic table. They presented a survey analysis that measures usage intention and learning effectiveness as well as student feedback on the meaningfulness of the learning activities. The students remembered the essential features of Mendeleev’s table, even after 7 and 60 days. The results show that the game is an engaging tool that helps students learn the basic concepts of the periodic table and its historical development.

2. 33. Probabilistic Establishment of Speckle-Associated Inter-Chromosomal Interactions

   J Joo^*, S Cho^*, S Hong, S Min, K Kim, R Kumar, JM Choi, Y Shin^†, and I Jung^†

   Nucleic Acids Research 51 (11): 5377–5395 (2023)

   Abs DOI

   Inter-chromosomal interactions play a crucial role in genome organization, yet the organizational principles remain elusive. Here, we introduce a novel computational method to systematically characterize inter-chromosomal interactions using in situ Hi-C results from various cell types. Our method successfully identifies two apparently hub-like inter-chromosomal contacts associated with nuclear speckles and nucleoli, respectively. Interestingly, we discover that nuclear speckle-associated inter-chromosomal interactions are highly cell-type invariant with a marked enrichment of cell-type common super-enhancers (CSEs). Validation using DNA Oligopaint fluorescence in situ hybridization (FISH) shows a strong but probabilistic interaction behavior between nuclear speckles and CSE-harboring genomic regions. Strikingly, we find that the likelihood of speckle-CSE associations can accurately predict two experimentally measured inter-chromosomal contacts from Hi-C and Oligopaint DNA FISH. Our probabilistic establishment model well describes the hub-like structure observed at the population level as a cumulative effect of summing individual stochastic chromatin-speckle interactions. Lastly, we observe that CSEs are highly co-occupied by MAZ binding and MAZ depletion leads to significant disorganization of speckle-associated inter-chromosomal contacts. Taken together, our results propose a simple organizational principle of inter-chromosomal interactions mediated by MAZ-occupied CSEs.

3. 32. Decoding the Roles of Amyloid-β (1-42)’s Key Oligomerization Domains Toward Designing Epitope-Specific Aggregation Inhibitors

   D Im, S Kim, G Yoon, DG Hyun, YG Eom, YE Lee, CH Sohn, JM Choi^†, and HI Kim^†

   JACS Au 3 (4): 1065–1075 (2023)

   Abs DOI

   Fibrillar amyloid aggregates are the pathological hallmarks of multiple neurodegenerative diseases. The amyloid-β (1–42) protein, in particular, is a major component of senile plaques in the brains of patients with Alzheimer’s disease and a primary target for disease treatment. Determining the essential domains of amyloid-β (1–42) that facilitate its oligomerization is critical for the development of aggregation inhibitors as potential therapeutic agents. In this study, we identified three key hydrophobic sites (17LVF19, 32IGL34, and 41IA42) on amyloid-β (1–42) and investigated their involvement in the self-assembly process of the protein. Based on these findings, we designed candidate inhibitor peptides of amyloid-β (1–42) aggregation. Using the designed peptides, we characterized the roles of the three hydrophobic regions during amyloid-β (1–42) fibrillar aggregation and monitored the consequent effects on its aggregation property and structural conversion. Furthermore, we used an amyloid-β (1–42) double point mutant (I41N/A42N) to examine the interactions between the two C-terminal end residues with the two hydrophobic regions and their roles in amyloid self-assembly. Our results indicate that interchain interactions in the central hydrophobic region (17LVF19) of amyloid-β (1–42) are important for fibrillar aggregation, and its interaction with other domains is associated with the accessibility of the central hydrophobic region for initiating the oligomerization process. Our study provides mechanistic insights into the self-assembly of amyloid-β (1–42) and highlights key structural domains that facilitate this process. Our results can be further applied toward improving the rational design of candidate amyloid-β (1–42) aggregation inhibitors.

4. 31. Conformational Landscapes of Artificial Peptides Predicted by Various Force Fields: Are We Ready to Simulate β-Amino Acids?

   J Park, HS Lee, H Kim^†, and JM Choi^†

   Physical Chemistry Chemical Physics 25: 7466–7476 (2023)

   Abs DOI

   With the introduction of artificial peptides as antimicrobial agents and organic catalysts, numerous efforts have been made to design foldamers with desirable structures and functions. Computational tools are a helpful proxy for revealing the dynamic structures at atomic resolution and understanding foldamer’s complex structure–function relationships. However, the performance of conventional force fields in predicting the structures of artificial peptides has not been systematically evaluated. In this study, we critically assessed three popular force fields, AMBER ff14SB, CHARMM36m, and OPLS-AA/L, in predicting conformational propensities of a β-peptide foldamer at monomer and hexamer levels. Simulation results were compared to those obtained from quantum chemistry calculations and experimental data. We also utilised replica exchange molecular dynamics simulations to investigate the energy landscape of each force field and assess the similarities and differences between force fields. We compared different solvent systems in the AMBER ff14SB and CHARMM36m frameworks and confirmed the unanimous role of hydrogen bonds in shaping energy landscapes. We anticipate that our data will pave the way for further improvements to force fields and for understanding the role of solvents in peptide folding, crystallisation, and engineering.

2022

1. 30. Recent Trends in Studies of Biomolecular Phase Separation

   CG Kim^*, DE Hwang^*, R Kumar, M Chung, YG Eom, H Kim, DH Koo, and JM Choi^†

   BMB Reports 55 (8): 363–369 (2022)

   Abs DOI

   Biomolecular phase separation has recently attracted broad interest, due to its role in the spatiotemporal compartmentalization of living cells. It governs the formation, regulation, and dissociation of biomolecular condensates, which play multiple roles in vivo, from activating specific biochemical reactions to organizing chromatin. Interestingly, biomolecular phase separation seems to be a mainly passive process, which can be explained by relatively simple physical principles and reproduced in vitro with a minimal set of components. This Mini review focuses on our current understanding of the fundamental principles of biomolecular phase separation and the recent progress in the research on this topic.

2. 29. Thermodynamics of π–π Interactions of Benzene and Phenol in Water

   D Paik^*, H Lee^*, H Kim^†, and JM Choi^†

   International Journal of Molecular Sciences 23 (17): 9811 (2022)

   Abs DOI

   The π–π interaction is a major driving force that stabilizes protein assemblies during protein folding. Recent studies have additionally demonstrated its involvement in the liquid–liquid phase separation (LLPS) of intrinsically disordered proteins (IDPs). As the participating residues in IDPs are exposed to water, π–π interactions for LLPS must be modeled in water, as opposed to the interactions that are often established at the hydrophobic domains of folded proteins. Thus, we investigated the association of free energies of benzene and phenol dimers in water by integrating van der Waals (vdW)-corrected density functional theory (DFT) and DFT in classical explicit solvents (DFT-CES). By comparing the vdW-corrected DFT and DFT-CES results with high-level wavefunction calculations and experimental solvation free energies, respectively, we established the quantitative credibility of these approaches, enabling a reliable prediction of the benzene and phenol dimer association free energies in water. We discovered that solvation influences dimer association free energies, but not significantly when no direct hydrogen-bond-type interaction exists between two monomeric units, which can be explained by the enthalpy–entropy compensation. Our comprehensive computational study of the solvation effect on π–π interactions in water could help us understand the molecular-level driving mechanism underlying the IDP phase behaviors.

3. 28. Kinetic Modulation of Amyloid-β (1–42) Aggregation and Toxicity by Structure-Based Rational Design

   D Im, CE Heo, MK Son, CR Park, HI Kim^†, and JM Choi^†

   Journal of the American Chemical Society 144 (4): 1603–1611 (2022)

   Abs DOI

   Several point mutations can modulate protein structure and dynamics, leading to different natures. Especially in the case of amyloidogenic proteins closely related to neurodegenerative diseases, structural changes originating from point mutations can affect fibrillation kinetics. Herein, we rationally designed mutant candidates to inhibit the fibrillation process of amyloid-β with its point mutants through multistep in silico analyses. Our results showed that the designed mutants induced kinetic self-assembly suppression and reduced the toxicity of the aggregate. A multidisciplinary biophysical approach with small-angle X-ray scattering, ion mobility-mass spectrometry, mass spectrometry, and additional in silico experiments was performed to reveal the structural basis associated with the inhibition of fibril formation. The structure-based design of the mutants with suppressed self-assembly performed in this study could provide a different perspective for modulating amyloid aggregation based on the structural understanding of the intrinsically disordered proteins.

2021

1. 27. Spatiotemporal and Microscopic Analysis of Asymmetric Liesegang Bands: Diffusion-limited Crystallization of Calcium Phosphate in a Hydrogel

   Mk Jo, YS Cho, G Holló, JM Choi, I Lagzi^†, and SH Yang^†

   Crystal Growth & Design 21 (11): 6119–6128 (2021)

   Abs DOI

   In the more than 100 years since the Liesegang phenomenon was discovered, intensive studies have been conducted to understand and control the characteristics of the periodic precipitation patterns in which the outer electrolyte diffuses into a hydrogel containing the inner electrolyte. Between fields of physics and chemistry, the periodicity of the precipitate has been investigated restrictively by spatial analyses and numerical simulations at macroscopic scales and it has been considered as a result of simple precipitation. In this work, calcium ion diffusion into gelatin hydrogels containing phosphate ions, a biomimetic system for bone formation, resulted in typical Liesegang patterns at macroscopic scales, but the asymmetric growth of the crystal was found in every single band at microscopic scales, which has not been observed or overlooked in the previous reports. The pattern consists of three characteristic bands: a continuous band, a split-fin band, and an intact-fin band. While the continuous band has a uniform crystal density, the split-fin and intact-fin bands have asymmetric crystal densities along the single band. We investigate the formation process of individual bands as well as the whole pattern by combining microscopic and spatiotemporal analyses based on the nucleation theory. Formation processes of asymmetric bands are explained by the unique stability and the diffusive property of amorphous precursors depending on the rate of calcium ion delivery. This is the first study to focus on the inhomogeneity of a single band in Liesegang patterns and the time-dependent mechanism of its growth.

2. 26. Current Understanding of Molecular Phase Separation in Chromosomes

   JK Ryu^†, DE Hwang, and JM Choi^†

   International Journal of Molecular Sciences 22 (19): 10736 (2021)

   Abs DOI

   Biomolecular phase separation denotes the demixing of a specific set of intracellular components without membrane encapsulation. Recent studies have found that biomolecular phase separation is involved in a wide range of cellular processes. In particular, phase separation is involved in the formation and regulation of chromosome structures at various levels. Here, we review the current understanding of biomolecular phase separation related to chromosomes. First, we discuss the fundamental principles of phase separation and introduce several examples of nuclear/chromosomal biomolecular assemblies formed by phase separation. We also briefly explain the experimental and computational methods used to study phase separation in chromosomes. Finally, we discuss a recent phase separation model, termed bridging-induced phase separation (BIPS), which can explain the formation of local chromosome structures.

3. 25. Microbially Guided Discovery and Biosynthesis of Biologically Active Natural Products

   A Sarkar, EY Kim, T Jang, A Hongdusit, H Kim, JM Choi, and JM Fox^†

   ACS Synthetic Biology 10 (6): 1505–1519 (2021)

   Abs DOI

   The design of small molecules that inhibit disease-relevant proteins represents a longstanding challenge of medicinal chemistry. Here, we describe an approach for encoding this challenge—the inhibition of a human drug target—into a microbial host and using it to guide the discovery and biosynthesis of targeted, biologically active natural products. This approach identified two previously unknown terpenoid inhibitors of protein tyrosine phosphatase 1B (PTP1B), an elusive therapeutic target for the treatment of diabetes and cancer. Both inhibitors appear to target an allosteric site, which confers selectivity, and can inhibit PTP1B in living cells. A screen of 24 uncharacterized terpene synthases from a pool of 4464 genes uncovered additional hits, demonstrating a scalable discovery approach, and the incorporation of different PTPs into the microbial host yielded alternative PTP-specific detection systems. Findings illustrate the potential for using microbes to discover and build natural products that exhibit precisely defined biochemical activities yet possess unanticipated structures and/or binding sites.

2020

1. 24. Client Proximity Enhancement inside Cellular Membrane-less Compartments Governed by Client-Compartment Interactions

   D Song, Y Jo, JM Choi, and Y Jung^†

   Nature Communications 11: 5642 (2020)

   Abs DOI

   Membrane-less organelles or compartments are considered to be dynamic reaction centers for spatiotemporal control of diverse cellular processes in eukaryotic cells. Although their formation mechanisms have been steadily elucidated via the classical concept of liquid–liquid phase separation, biomolecular behaviors such as protein interactions inside these liquid compartments have been largely unexplored. Here we report quantitative measurements of changes in protein interactions for the proteins recruited into membrane-less compartments (termed client proteins) in living cells. Under a wide range of phase separation conditions, protein interaction signals were vastly increased only inside compartments, indicating greatly enhanced proximity between recruited client proteins. By employing an in vitro phase separation model, we discovered that the operational proximity of clients (measured from client–client interactions) could be over 16 times higher than the expected proximity from actual client concentrations inside compartments. We propose that two aspects should be considered when explaining client proximity enhancement by phase separation compartmentalization: (1) clients are selectively recruited into compartments, leading to concentration enrichment, and more importantly, (2) recruited clients are further localized around compartment-forming scaffold protein networks, which results in even higher client proximity.

2. 23. Multivalent-Interaction-Driven Assembly of Discrete, Flexible, and Asymmetric Supramolecular Protein Nano-Prisms

   S Han^*, Yn Kim^*, G Jo, YE Kim, HM Kim, JM Choi^†, and Y Jung^†

   Angewandte Chemie International Edition 59 (51): 23244–23251 (2020)

   Abs DOI

   Current approaches to design monodisperse protein assemblies require rigid, tight, and symmetric interactions between oligomeric protein units. Herein, we introduce a new multivalent-interaction-driven assembly strategy that allows flexible, spaced, and asymmetric assembly between protein oligomers. We discovered that two polygonal protein oligomers (ranging from triangle to hexagon) dominantly form a discrete and stable two-layered protein prism nanostructure via multivalent interactions between fused binding pairs. We demonstrated that protein nano-prisms with long flexible peptide linkers (over 80 amino acids) between protein oligomer layers could be discretely formed. Oligomers with different structures could also be monodispersely assembled into two-layered but asymmetric protein nano-prisms. Furthermore, producing higher-order architectures with multiple oligomer layers, for example, 3-layered nano-prisms or nanotubes, was also feasible.

3. 22. Generalized Models for Bond Percolation Transitions of Associative Polymers

   JM Choi, AA Hyman, and RV Pappu^†

   Physical Review E 102: 042403 (2020)

   Abs DOI

   Polymers with stickers-and-spacers architectures can drive phase-separation-aided bond percolation transitions. Here, we present a generalized mean-field model to enable the calculation of bond percolation thresholds for polymers with multiple types of stickers. Further, using graph-based Monte Carlo simulations we demonstrate how cooperativity in bond formation can give rise to reentrant phase behavior. When combined with recent advances for modeling phase separation, our approaches for calculating percolation lines could be useful for modeling hardening transitions for multivalent proteins.

4. 21. Physical Principles Underlying the Complex Biology of Intracellular Phase Transitions

   JM Choi, AS Holehouse, and RV Pappu^†

   Annual Review of Biophysics 49: 107–133 (2020)

   Note Abs DOI

   Highly Downloaded Articles in 2020: Physical Sciences

   Many biomolecular condensates appear to form via spontaneous or driven processes that have the hallmarks of intracellular phase transitions. This suggests that a common underlying physical framework might govern the formation of functionally and compositionally unrelated biomolecular condensates. In this review, we summarize recent work that leverages a stickers-and-spacers framework adapted from the field of associative polymers for understanding how multivalent protein and RNA molecules drive phase transitions that give rise to biomolecular condensates. We discuss how the valence of stickers impacts the driving forces for condensate formation and elaborate on how stickers can be distinguished from spacers in different contexts. We touch on the impact of sticker- and spacer-mediated interactions on the rheological properties of condensates and show how the model can be mapped to known drivers of different types of biomolecular condensates.

2019

1. 20. LASSI: A Lattice Model for Simulating Phase Transitions of Multivalent Proteins

   JM Choi^*, F Dar^*, and RV Pappu^†

   PLOS Computational Biology 15 (10): e1007028 (2019)

   Abs DOI

   Many biomolecular condensates form via spontaneous phase transitions that are driven by multivalent proteins. These molecules are biological instantiations of associative polymers that conform to a so-called stickers-and-spacers architecture. The stickers are protein-protein or protein-RNA interaction motifs and / or domains that can form reversible, non-covalent crosslinks with one another. Spacers are interspersed between stickers and their preferential interactions with solvent molecules determine the cooperativity of phase transitions. Here, we report the development of an open source computational engine known as LASSI (LAttice simulation engine for Sticker and Spacer Interactions) that enables the calculation of full phase diagrams for multicomponent systems comprising of coarse-grained representations of multivalent proteins. LASSI is designed to enable computationally efficient phenomenological modeling of spontaneous phase transitions of multicomponent mixtures comprising of multivalent proteins and RNA molecules. We demonstrate the application of LASSI using simulations of linear and branched multivalent proteins. We show that dense phases are best described as droplet-spanning networks that are characterized by reversible physical crosslinks among multivalent proteins. We connect recent observations regarding correlations between apparent stoichiometry and dwell times of condensates to being proxies for the internal structural organization, specifically the convolution of internal density and extent of networking, within condensates. Finally, we demonstrate that the concept of saturation concentration thresholds does not apply to multicomponent systems where obligate heterotypic interactions drive phase transitions. This emerges from the ellipsoidal structures of phase diagrams for multicomponent systems and it has direct implications for the regulation of biomolecular condensates in vivo.

2. 19. Covalently-Assembled Single-Chain Protein Nanostructures with Ultra-High Stability

   W Bai, CJ Sargent, JM Choi, RV Pappu, and F Zhang^†

   Nature Communications 10: 3317 (2019)

   Abs DOI

   Protein nanostructures with precisely defined geometries have many potential applications in catalysis, sensing, signal processing, and drug delivery. While many de novo protein nanostructures have been assembled via non-covalent intramolecular and intermolecular interactions, a largely unexplored strategy is to construct nanostructures by covalently linking multiple individually folded proteins through site-specific ligations. Here, we report the synthesis of single-chain protein nanostructures with triangular and square shapes made using multiple copies of a three-helix bundle protein and split intein chemistry. Coarse-grained simulations confirm the experimentally observed flexibility of these nanostructures, which is optimized to produce triangular structures with high regularity. These single-chain nanostructures also display ultra-high thermostability, resist denaturation by chaotropes and organic solvents, and have applicability as scaffolds for assembling materials with nanometer resolution. Our results show that site-specific covalent ligation can be used to assemble individually folded proteins into single-chain nanostructures with bespoke architectures and high stabilities.

3. 18. Improvements to the ABSINTH Forcefield for Proteins Based on Experimentally Derived Amino-Acid Specific Backbone Conformational Statistics

   JM Choi and RV Pappu^†

   Journal of Chemical Theory and Computation 15 (2): 1367–1382 (2019)

   Abs DOI

   We present an improved version of the ABSINTH implicit solvation model and force field paradigm (termed ABSINTH-C) by incorporating a grid-based term that bootstraps against experimentally derived and computationally optimized conformational statistics for blocked amino acids. These statistics provide high-resolution descriptions of the intrinsic backbone dihedral angle preferences for all 20 amino acids. The original ABSINTH model generates Ramachandran plots that are too shallow in terms of the basin structures and too permissive in terms of dihedral angle preferences. We bootstrap against the reference optimized landscapes and incorporate CMAP-like residue-specific terms that help us reproduce the intrinsic dihedral angle preferences of individual amino acids. These corrections that lead to ABSINTH-C are achieved by balancing the incorporation of the new residue-specific terms with the accuracies inherent to the original ABSINTH model. We demonstrate the robustness of ABSINTH-C through a series of examples to highlight the preservation of accuracies as well as examples that demonstrate the improvements. Our efforts show how the recent experimentally derived and computationally optimized coil-library landscapes can be used as a touchstone for quantifying errors and making improvements to molecular mechanics force fields.

2018

1. 17. Experimentally Derived and Computationally Optimized Backbone Conformational Statistics for Blocked Amino Acids

   JM Choi and RV Pappu^†

   Journal of Chemical Theory and Computation 15 (2): 1355–1366 (2018)

   Abs DOI

   Experimentally derived, amino acid specific backbone dihedral angle distributions are invaluable for modeling data-driven conformational equilibria of proteins and for enabling quantitative assessments of the accuracies of molecular mechanics force fields. The protein coil library that is extracted from analysis of high-resolution structures of proteins has served as a useful proxy for quantifying intrinsic and context-dependent conformational distributions of amino acids. However, data that go into coil libraries will have hidden biases, and ad hoc procedures must be used to remove these biases. Here, we combine high-resolution biased information from protein structural databases with unbiased low-resolution information from spectroscopic measurements of blocked amino acids to obtain experimentally derived and computationally optimized coil-library landscapes for each of the 20 naturally occurring amino acids. Quantitative descriptions of conformational distributions require parsing of data into conformational basins with defined envelopes, centers, and statistical weights. We develop and deploy a numerical method to extract conformational basins. The weights of conformational basins are optimized to reproduce quantitative inferences drawn from spectroscopic experiments for blocked amino acids. The optimized distributions serve as touchstones for assessments of intrinsic conformational preferences and for quantitative comparisons of molecular mechanics force fields.

2. 16. ProteomeVis: a Web App for Exploration of Protein Properties from Structure to Sequence Evolution across Organisms’ Proteomes

   RM Razban^*, AI Gilson^*, N Durfee^*, H Strobelt, K Dinkla, JM Choi, H Pfister, and EI Shakhnovich^†

   Bioinformatics 34 (20): 3557–3565 (2018)

   Abs DOI

   Motivation: Protein evolution spans time scales and its effects span the length of an organism. A web app named ProteomeVis is developed to provide a comprehensive view of protein evolution in the Saccharomyces cerevisiae and Escherichia coli proteomes. ProteomeVis interactively creates protein chain graphs, where edges between nodes represent structure and sequence similarities within user-defined ranges, to study the long time scale effects of protein structure evolution. The short time scale effects of protein sequence evolution are studied by sequence evolutionary rate (ER) correlation analyses with protein properties that span from the molecular to the organismal level.
   Results: We demonstrate the utility and versatility of ProteomeVis by investigating the distribution of edges per node in organismal protein chain universe graphs (oPCUGs) and putative ER determinants. S. cerevisiae and E. coli oPCUGs are scale-free with scaling constants of 1.79 and 1.56, respectively. Both scaling constants can be explained by a previously reported theoretical model describing protein structure evolution. Protein abundance most strongly correlates with ER among properties in ProteomeVis, with Spearman correlations of −0.49 (P-value < 10⁻¹⁰) and −0.46 (P-value < 10⁻¹⁰) for S. cerevisiae and E. coli, respectively. This result is consistent with previous reports that found protein expression to be the most important ER determinant.
   Availability and implementation: ProteomeVis is freely accessible at http://proteomevis.chem.harvard.edu.

3. 15. Evolution on the Biophysical Fitness Landscape of an RNA Virus

   A Rotem^*, AWR Serohijos^*, CB Chang, JT Wolfe, AE Fischer, TS Mehoke, H Zhang, Y Tao, WL Ung, JM Choi, JV Rodrigues, AO Kolawole, SA Koehler, S Wu, PM Thielen, N Cui, PA Demirev, NS Giacobbi, TR Julian, K Schwab, JS Lin, TJ Smith, JM Pipas, CE Wobus, AB Feldman, DA Weitz^†, and EI Shakhnovich^†

   Molecular Biology and Evolution 35 (10): 2390–2400 (2018)

   Abs DOI

   Viral evolutionary pathways are determined by the fitness landscape, which maps viral genotype to fitness. However, a quantitative description of the landscape and the evolutionary forces on it remain elusive. Here, we apply a biophysical fitness model based on capsid folding stability and antibody binding affinity to predict the evolutionary pathway of norovirus escaping a neutralizing antibody. The model is validated by experimental evolution in bulk culture and in a drop-based microfluidics that propagates millions of independent small viral subpopulations. We demonstrate that along the axis of binding affinity, selection for escape variants and drift due to random mutations have the same direction, an atypical case in evolution. However, along folding stability, selection and drift are opposing forces whose balance is tuned by viral population size. Our results demonstrate that predictable epistatic tradeoffs between molecular traits of viral proteins shape viral evolution.

4. 14. A Molecular Grammar Governing the Driving Forces for Phase Separation of Prion-like RNA Binding Proteins

   J Wang, JM Choi, AS Holehouse, HO Lee, X Zhang, M Jahnel, S Maharana, R Lemaitre, A Pozniakovsky, D Drechsel, I Poser, RV Pappu, S Alberti^†, and AA Hyman^†

   Cell 174 (3): 688–699 (2018)

   Abs DOI

   Summary Proteins such as FUS phase separate to form liquid-like condensates that can harden into less dynamic structures. However, how these properties emerge from the collective interactions of many amino acids remains largely unknown. Here, we use extensive mutagenesis to identify a sequence-encoded molecular grammar underlying the driving forces of phase separation of proteins in the FUS family and test aspects of this grammar in cells. Phase separation is primarily governed by multivalent interactions among tyrosine residues from prion-like domains and arginine residues from RNA-binding domains, which are modulated by negatively charged residues. Glycine residues enhance the fluidity, whereas glutamine and serine residues promote hardening. We develop a model to show that the measured saturation concentrations of phase separation are inversely proportional to the product of the numbers of arginine and tyrosine residues. These results suggest it is possible to predict phase-separation properties based on amino acid sequences.

5. 13. Measuring NDC80 Binding Reveals the Molecular Basis of Tension-Dependent Kinetochore-Microtubule Attachments

   TY Yoo^†, JM Choi, W Conway, CH Yu, RV Pappu, and DJ Needleman

   eLife 7: e36392 (2018)

   Abs DOI

   Proper kinetochore-microtubule attachments, mediated by the NDC80 complex, are required for error-free chromosome segregation. Erroneous attachments are corrected by the tension dependence of kinetochore-microtubule interactions. Here, we present a method, based on fluorescence lifetime imaging microscopy and Förster resonance energy transfer, to quantitatively measure the fraction of NDC80 complexes bound to microtubules at individual kinetochores in living human cells. We found that NDC80 binding is modulated in a chromosome autonomous fashion over prometaphase and metaphase, and is predominantly regulated by centromere tension. We show that this tension dependency requires phosphorylation of the N-terminal tail of Hec1, a component of the NDC80 complex, and the proper localization of Aurora B kinase, which modulates NDC80 binding. Our results lead to a mathematical model of the molecular basis of tension-dependent NDC80 binding to kinetochore microtubules in vivo.

6. 12. Stability of the Influenza Virus Hemagglutinin Protein Correlates with Evolutionary Dynamics

   EY Klein^*†, D Blumenkrantz^*, A Serohijos, E Shakhnovich, JM Choi, JV Rodrigues, BD Smith, AP Lane, A Feldman, and A Pekosz

   mSphere 3: e00554-17 (2018)

   Abs DOI

   Protein thermodynamics are an integral determinant of viral fitness and one of the major drivers of protein evolution. Mutations in the influenza A virus (IAV) hemagglutinin (HA) protein can eliminate neutralizing antibody binding to mediate escape from preexisting antiviral immunity. Prior research on the IAV nucleoprotein suggests that protein stability may constrain seasonal IAV evolution; however, the role of stability in shaping the evolutionary dynamics of the HA protein has not been explored. We used the full coding sequence of 9,797 H1N1pdm09 HA sequences and 16,716 human seasonal H3N2 HA sequences to computationally estimate relative changes in the thermal stability of the HA protein between 2009 and 2016. Phylogenetic methods were used to characterize how stability differences impacted the evolutionary dynamics of the virus. We found that pandemic H1N1 IAV strains split into two lineages that had different relative HA protein stabilities and that later variants were descended from the higher-stability lineage. Analysis of the mutations associated with the selective sweep of the higher-stability lineage found that they were characterized by the early appearance of highly stabilizing mutations, the earliest of which was not located in a known antigenic site. Experimental evidence further suggested that H1N1 HA stability may be correlated with in vitro virus production and infection. A similar analysis of H3N2 strains found that surviving lineages were also largely descended from viruses predicted to encode more-stable HA proteins. Our results suggest that HA protein stability likely plays a significant role in the persistence of different IAV lineages. IMPORTANCE One of the constraints on fast-evolving viruses, such as influenza virus, is protein stability, or how strongly the folded protein holds together. Despite the importance of this protein property, there has been limited investigation of the impact of the stability of the influenza virus hemagglutinin protein—the primary antibody target of the immune system—on its evolution. Using a combination of computational estimates of stability and experiments, our analysis found that viruses with more-stable hemagglutinin proteins were associated with long-term persistence in the population. There are two potential reasons for the observed persistence. One is that more-stable proteins tolerate destabilizing mutations that less-stable proteins could not, thus increasing opportunities for immune escape. The second is that greater stability increases the fitness of the virus through increased production of infectious particles. Further research on the relative importance of these mechanisms could help inform the annual influenza vaccine composition decision process.

2017

1. 11. The Role of Evolutionary Selection in the Dynamics of Protein Structure Evolution

   AI Gilson, A Marshall-Christensen, JM Choi, and EI Shakhnovich^†

   Biophysical Journal 112 (7): 1350–1365 (2017)

   Abs DOI

   Homology modeling is a powerful tool for predicting a protein’s structure. This approach is successful because proteins whose sequences are only 30% identical still adopt the same structure, while structure similarity rapidly deteriorates beyond the 30% threshold. By studying the divergence of protein structure as sequence evolves in real proteins and in evolutionary simulations, we show that this nonlinear sequence-structure relationship emerges as a result of selection for protein folding stability in divergent evolution. Fitness constraints prevent the emergence of unstable protein evolutionary intermediates, thereby enforcing evolutionary paths that preserve protein structure despite broad sequence divergence. However, on longer timescales, evolution is punctuated by rare events where the fitness barriers obstructing structure evolution are overcome and discovery of new structures occurs. We outline biophysical and evolutionary rationale for broad variation in protein family sizes, prevalence of compact structures among ancient proteins, and more rapid structure evolution of proteins with lower packing density.

2. 10. Graph’s Topology and Free Energy of a Spin Model on the Graph

   JM Choi^†, AI Gilson, and EI Shakhnovich^†

   Physical Review Letters 118: 088302 (2017)

   Abs DOI

   In this Letter we investigate a direct relationship between a graph’s topology and the free energy of a spin system on the graph. We develop a method of separating topological and energetic contributions to the free energy, and find that considering the topology is sufficient to qualitatively compare the free energies of different graph systems at high temperature, even when the energetics are not fully known. This method was applied to the metal lattice system with defects, and we found that it partially explains why point defects are more stable than high-dimensional defects. Given the energetics, we can even quantitatively compare free energies of different graph structures via a closed form of linear graph contributions. The closed form is applied to predict the sequence-space free energy of lattice proteins, which is a key factor determining the designability of a protein structure.

2016

1. 9. Acetylation of Surface Lysine Groups of a Protein Alters the Organization and Composition of Its Crystal Contacts

   K Kang^*, JM Choi^*, JM Fox, PW Snyder, DT Moustakas, and GM Whitesides^†

   The Journal of Physical Chemistry B 120 (27): 6461–6468 (2016)

   Abs DOI

   This paper uses crystals of bovine carbonic anhydrase (CA) and its acetylated variant to examine (i) how a large negative formal charge can be accommodated in protein–protein interfaces, (ii) why lysine residues are often excluded from them, and (iii) how changes in the surface charge of a protein can alter the structure and organization of protein–protein interfaces. It demonstrates that acetylation of lysine residues on the surface of CA increases the participation of polar residues (particularly acetylated lysine) in protein–protein interfaces, and decreases the participation of nonpolar residues in those interfaces. Negatively charged residues are accommodated in protein–protein interfaces via (i) hydrogen bonds or van der Waals interactions with polar residues or (ii) salt bridges with other charged residues. The participation of acetylated lysine in protein–protein interfaces suggests that unacetylated lysine tends to be excluded from interfaces because of its positive charge, and not because of a loss in conformational entropy. Results also indicate that crystal contacts in acetylated CA become less constrained geometrically and, as a result, more closely packed (i.e., more tightly clustered spatially) than those of native CA. This study demonstrates a physical-organic approach—and a well-defined model system—for studying the role of charges in protein–protein interactions.

2. 8. Evolutionary Dynamics of Viral Escape under Antibodies Stress: A Biophysical Model

   N Chéron^*, AWR Serohijos^*, JM Choi, and EI Shakhnovich^†

   Protein Science 25 (7): 1332–1340 (2016)

   Abs DOI

   Viruses constantly face the selection pressure of antibodies, either from innate immune response of the host or from administered antibodies for treatment. We explore the interplay between the biophysical properties of viral proteins and the population and demographic variables in the viral escape. The demographic and population genetics aspect of the viral escape have been explored before; however one important assumption was the a priori distribution of fitness effects (DFE). Here, we relax this assumption by instead considering a realistic biophysics-based genotype-phenotype relationship for RNA viruses escaping antibodies stress. In this model the DFE is itself an evolvable property that depends on the genetic background (epistasis) and the distribution of biophysical effects of mutations, which is informed by biochemical experiments and theoretical calculations in protein engineering. We quantitatively explore in silico the viability of viral populations under antibodies pressure and derive the phase diagram that defines the fate of the virus population (extinction or escape from stress) in a range of viral mutation rates and antibodies concentrations. We find that viruses are most resistant to stress at an optimal mutation rate (OMR) determined by the competition between supply of beneficial mutation to facilitate escape from stressors and lethal mutagenesis caused by excess of destabilizing mutations. We then show the quantitative dependence of the OMR on genome length and viral burst size. We also recapitulate the experimental observation that viruses with longer genomes have smaller mutation rate per nucleotide.

2015

1. 7. Protein Homeostasis Imposes a Barrier on Functional Integration of Horizontally Transferred Genes in Bacteria

   S Bershtein^*, AWR Serohijos^*, S Bhattacharyya, M Manhart, JM Choi, W Mu, J Zhou, and EI Shakhnovich^†

   PLOS Genetics 11 (10): e1005612 (2015)

   Abs DOI

   Author Summary Horizontal gene transfer (HGT) is central to bacterial evolution. The outcome of an HGT event (fixation in a population, elimination, or separation as a subdominant clone) depends not only on the availability of a new gene but crucially on the fitness cost or benefit of the genomic incorporation of the foreign gene and its expression in recipient bacteria. Here we studied the fitness landscape for inter-species chromosomal replacement of an essential protein, dihydrofolate reductase (DHFR) encoded by the folA gene, by its orthologs from other mesophilic bacteria. We purified and biochemically characterized 33 out of 35 orthologous DHFRs and found that most of them are stable and more catalytically active than E. coli DHFR. However, the inter-species replacement of DHFR caused significant fitness loss for most transgenic strains due to low abundance of orthologous DHFRs in E. coli cytoplasm. Laboratory evolution resulted in an increase in orthologous DHFR abundance leading to a dramatic fitness improvement. Genomic and proteomic analyses of “naive” and evolved strains suggest a new function of protein homeostasis to discriminate between “self” and “non-self” proteins, thus creating fitness barriers to HGT.

2. 6. Systems-Level Response to Point Mutations in a Core Metabolic Enzyme Modulates Genotype-Phenotype Relationship

   S Bershtein^*, JM Choi^*, S Bhattacharyya, B Budnik, and E Shakhnovich^†

   Cell Reports 11 (4): 645–656 (2015)

   Abs DOI

   Summary Linking the molecular effects of mutations to fitness is central to understanding evolutionary dynamics. Here, we establish a quantitative relation between the global effect of mutations on the E. coli proteome and bacterial fitness. We created E. coli strains with specific destabilizing mutations in the chromosomal folA gene encoding dihydrofolate reductase (DHFR) and quantified the ensuing changes in the abundances of 2,000+ E. coli proteins in mutant strains using tandem mass tags with subsequent LC-MS/MS. mRNA abundances in the same E. coli strains were also quantified. The proteomic effects of mutations in DHFR are quantitatively linked to phenotype: the SDs of the distributions of logarithms of relative (to WT) protein abundances anticorrelate with bacterial growth rates. Proteomes hierarchically cluster first by media conditions, and within each condition, by the severity of the perturbation to DHFR function. These results highlight the importance of a systems-level layer in the genotype-phenotype relationship.

3. 5. Minimalistic Predictor of Protein Binding Energy: Contribution of Solvation Factor to Protein Binding

   JM Choi, AWR Serohijos, S Murphy, D Lucarelli, LL Lofranco, A Feldman, and EI Shakhnovich^†

   Biophysical Journal 108 (4): 795–798 (2015)

   Abs DOI

   It has long been known that solvation plays an important role in protein-protein interactions. Here, we use a minimalistic solvation-based model for predicting protein binding energy to estimate quantitatively the contribution of the solvation factor in protein binding. The factor is described by a simple linear combination of buried surface areas according to amino-acid types. Even without structural optimization, our minimalistic model demonstrates a predictive power comparable to more complex methods, making the proposed approach the basis for high throughput applications. Application of the model to a proteomic database shows that receptor-substrate complexes involved in signaling have lower affinities than enzyme-inhibitor and antibody-antigen complexes, and they differ by chemical compositions on interfaces. Also, we found that protein complexes with components that come from the same genes generally have lower affinities than complexes formed by proteins from different genes, but in this case the difference originates from different interface areas. The model was implemented in the software PYTHON, and the source code can be found on the Shakhnovich group webpage: http://faculty.chemistry.harvard.edu/shakhnovich/software.

2014

1. 4. Evolution of Specificity in Protein-Protein Interactions

   O Peleg, JM Choi, and EI Shakhnovich^†

   Biophysical Journal 107 (7): 1686–1696 (2014)

   Note Abs DOI

   Biophysical Journal Best of 2014

   Hub proteins are proteins that maintain promiscuous molecular recognition. Because they are reported to play essential roles in cellular control, there has been a special interest in the study of their structural and functional properties, yet the mechanisms by which they evolve to maintain functional interactions are poorly understood. By combining biophysical simulations of coarse-grained proteins and analysis of proteins-complex crystallographic structures, we seek to elucidate those mechanisms. We focus on two types of hub proteins: Multi hubs, which interact with their partners through different interfaces, and Singlish hubs, which do so through a single interface. We show that loss of structural stability is required for the evolution of protein-protein-interaction (PPI) networks, and it is more profound in Singlish hub systems. In addition, different ratios of hydrophobic to electrostatic interfacial amino acids are shown to support distinct network topologies (i.e., Singlish and Multi systems), and therefore underlie a fundamental design principle of PPI in a crowded environment. We argue that the physical nature of hydrophobic and electrostatic interactions, in particular, their favoring of either same-type interactions (hydrophobic-hydrophobic), or opposite-type interactions (negatively-positively charged) plays a key role in maintaining the network topology while allowing the protein amino acid sequence to evolve.

2. 3. Influenza A H1N1 Pandemic Strain Evolution – Divergence and the Potential for Antigenic Drift Variants

   EY Klein^†, AWR Serohijos, JM Choi, EI Shakhnovich, and A Pekosz

   PLOS ONE 9 (4): e93632 (2014)

   Abs DOI

   The emergence of a novel A(H1N1) strain in 2009 was the first influenza pandemic of the genomic age, and unprecedented surveillance of the virus provides the opportunity to better understand the evolution of influenza. We examined changes in the nucleotide coding regions and the amino acid sequences of the hemagglutinin (HA), neuraminidase (NA), and nucleoprotein (NP) segments of the A(H1N1)pdm09 strain using publicly available data. We calculated the nucleotide and amino acid hamming distance from the vaccine strain A/California/07/2009 for each sequence. We also estimated Pepitope–a measure of antigenic diversity based on changes in the epitope regions–for each isolate. Finally, we compared our results to A(H3N2) strains collected over the same period. Our analysis found that the mean hamming distance for the HA protein of the A(H1N1)pdm09 strain increased from 3.6 (standard deviation [SD]: 1.3) in 2009 to 11.7 (SD: 1.0) in 2013, while the mean hamming distance in the coding region increased from 7.4 (SD: 2.2) in 2009 to 28.3 (SD: 2.1) in 2013. These trends are broadly similar to the rate of mutation in H3N2 over the same time period. However, in contrast to H3N2 strains, the rate of mutation accumulation has slowed in recent years. Our results are notable because, over the course of the study, mutation rates in H3N2 similar to that seen with A(H1N1)pdm09 led to the emergence of two antigenic drift variants. However, while there has been an H1N1 epidemic in North America this season, evidence to date indicates the vaccine is still effective, suggesting the epidemic is not due to the emergence of an antigenic drift variant. Our results suggest that more research is needed to understand how viral mutations are related to vaccine effectiveness so that future vaccine choices and development can be more predictive.

2012

1. 2. Universal Correction of Density Functional Theory to Include London Dispersion (up to Lr, Element 103)

   H Kim^*, JM Choi^*, and WA Goddard^†

   The Journal of Physical Chemistry Letters 3 (3): 360–363 (2012)

   Abs DOI

   Conventional density functional theory (DFT) fails to describe accurately the London dispersion essential for describing molecular interactions in soft matter (biological systems, polymers, nucleic acids) and molecular crystals. This has led to several methods in which atom-dependent potentials are added into the Kohn–Sham DFT energy. Some of these corrections were fitted to accurate quantum mechanical results, but it will be tedious to determine the appropriate parameters to describe all of the atoms of the periodic table. We propose an alternative approach in which a single parameter in the low-gradient (lg) functional form is combined with the rule-based UFF (universal force-field) nonbond parameters developed for the entire periodic table (up to Lr, Z = 103), named as a DFT-ulg method. We show that DFT-ulg method leads to a very accurate description of the properties for molecular complexes and molecular crystals, providing the means for predicting more accurate weak interactions across the periodic table.

2008

1. 1. State-Selective Predissociation Dynamics of Methylamines: The Vibronic and H/D Effects on the Conical Intersection Dynamics

   DS Ahn, J Lee, JM Choi, KS Lee, SJ Baek, K Lee, KK Baeck, and SK Kim^†

   The Journal of Chemical Physics 128: 224305 (2008)

   Abs DOI

   The photodissociation dynamics of methylamines (CH₃NH₂ and CD₃ND₂) on the first electronically excited state has been investigated using the velocity map ion imaging technique probing the H or D fragment. Two distinct velocity components are found in the H(D) translational energy distribution, implying the existence of two different reaction pathways for the bond dissociation. The high H(D) velocity component with the small internal energy of the radical fragment is ascribed to the N–H(D) fragmentation via the coupling of S₁ to the upper-lying S₂ repulsive potential energy surface along the N–H(D) bond elongation axis. Dissociation on the ground S₀ state prepared via the nonadiabatic dynamics at the conical intersection should be responsible for the slow H(D) fragment. Several S₁ vibronic states of methylamines including the zero-point level and nν₉ states (n = 1, 2, or 3) are exclusively chosen in order to explore the effect of the initial quantum content on the chemical reaction dynamics. The branching ratio of the fast and slow components is found to be sensitive to the initial vibronic state for the N–H bond dissociation of CH₃NH₂, whereas it is little affected in the N–D dissociation event of CD₃ND₂. The fast component is found to be more dominant in the translational distribution of D from CD₃ND₂ than it is in that of H from CH₃NH₂. The experimental result is discussed with a plausible mechanism of the conical intersection dynamics.