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Sun, H.

Publications and source records attributed to Sun, H..

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Regulation of a Classical Allosteric Molecular Machine by an Intrinsically Disordered Domain: the C-termini of GroEL

The bacterial chaperonin GroEL is a canonical example of an ATP-dependent molecular machine that must couple ligand binding to productive conformational work. GroEL passes through a series of distinct structural shifts, driven by ATP binding and hydrolysis, which power a facilitated protein folding reaction. How the complex allostery of the GroEL oligomer creates a folding cycle that is both efficient and directional remains incompletely understood. Here, we combine variable-temperature native ion mass spectrometry with single-molecule FRET to examine how the intrinsically disordered, highly conserved GroEL C-terminal tails impact the allosteric behavior of a single GroEL ring. Our observations show that the C-terminal tails restrain the conformational dynamics of the GroEL ring, most likely through direct interactions with the upper apical domains of the GroEL subunits, a constraint that is progressively released as ATP binds. These results support a model in which the C-terminal tails act as an entropic regulator of the GroEL reaction cycle: transient interactions between the tails and GroEL apical domains restrain premature ring opening and tune the energetic threshold for productive engagement by the smaller GroES co-chaperonin. By linking disordered tail dynamics to the classically cooperative reorganization of the GroEL ring, this mechanism enforces an ordered allosteric cascade that minimizes wasteful formation of empty GroEL-GroES cavities. These findings reveal how the conformational properties of an intrinsically disordered element can be exploited to optimize the energetic efficiency and functional timing of a large allosteric machine.

biophysics

Automatic bioinformatic software named entity recognition from literature

Bioinformatics software and databases are essential components of modern life science research, yet their mentions in the scientific literature are often inconsistent and difficult to systematically identify at scale. The lack of a comprehensive and up-to-date catalog of bioinformatics resources hinders efforts toward automated biomedical knowledge extraction and streamlined data analysis. Here we present SNAIL, a hybrid named entity recognition framework designed to automatically identify bioinformatics software and database (SW/DB) names from biomedical texts. SNAIL integrates complementary lexical and semantic modeling strategies. The lexical component captures orthographic patterns and contextual cues characteristic of SW/DB names, while the semantic component leverages contextual embeddings generated by transformer-based language models such as SciBERT, combined with an explicit token-masking strategy to enhance entity-focused representations. A large training corpus was constructed automatically through a hybrid pipeline that integrates citation-hinted extraction with large language model-assisted distillation. Evaluation on two independent benchmark datasets and real-world research articles demonstrates that SNAIL substantially outperforms existing approaches, including domain-specific methods such as bioNerDS2 and general-purpose large language models such as ChatGPT, Gemini, Grok and Claude. Applying SNAIL to large-scale literature analysis further reveals distinct journal-level preferences across bioinformatics subfields. These results demonstrate that SNAIL provides an accurate and scalable solution for identifying bioinformatics resources in scientific texts and enables systematic meta-analysis of tool usage and research trends.

bioinformatics

Near-infrared optoacoustic modulation of the blood-brain barrier permeability using size-tuned hyperbranched gold nanoconstructs

The blood-brain barrier (BBB) constitutes a major bottleneck for the systemic delivery of most therapeutic agents to the central nervous system. Here, we report near-infrared reversible optoacoustic modulation of the BBB permeability (NIR-ROAMBBB), leveraging endothelial tight junction targeting hyperbranched gold nanoconstructs (HBGNCs) to amplify localized optoacoustic transduction under femtosecond laser excitation. We first synthesized HBGNCs with tunable particle sizes (62-150 nm) and consistent branch morphologies via a seed-mediated growth approach, and uncovered a non-monotonic relationship between particle dimension and optoacoustic output, where the 62 nm HBGNCs generated nearly twofold stronger optoacoustic signal than gold nanorods and gold nanostars under matched excitations. Conjugation with BV11 antibodies against junctional adhesion molecule A increased HBGNC endothelial association and cerebral accumulation, enabling focal and fluence-dependent transient BBB opening (3-6 h) under 800 nm femtosecond pulsed laser excitation, as validated by in vitro trans-endothelial electrical resistance measurements, ex vivo Evans blue extravasation staining, and in vivo NIR imaging. Featuring deep tissue penetration of NIR light, robust optoacoustic conversion of HBGNCs, and negligible femtosecond laser-induced photothermal damage, this non-invasive strategy enables precise focal modulation of BBB permeability and potential drug delivery.

bioengineering