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Biology subjects

You, T.

Publications and source records attributed to You, T..

5 recordsLinked to original sources

Molecular Insights into Cell Wall Architecture and Xylan-Bound Cellulose Fibrils in the Wheat Straw

The plant cell wall, a highly abundant renewable resource, remains insufficiently understood in terms of its structure, particularly the architecture of cellulose microfibrils and their interactions with hemicellulose and lignin, which impede the development of efficient downstream conversion. Here we present an alternative model of xylan-bound cellulose microfibril architecture in the cell wall of intact wheat straw, using solid-state nuclear magnetic resonance (ssNMR) coupled with X-ray scattering techniques. We show that the spectroscopic and scattering data can be fit to a simple elementary microfibril consisting of 18 glucan chains, with additional contributions from 0 to 4 tightly bound flat-ribbon xylan chains across the cellulose fibril axis. These xylan-bound cellulose microfibrils are found to serve as the secondary interaction site with lignin, following the non-flat xylan domains. The loose packing of these xylan-bound cellulose fibrils results in a heterogenous hydration landscape within the cell wall, allowing water penetration while maintaining structural integrity through numerous physical contacts between the polymers. This study provides a potential framework to reconcile the mounting biochemical evidence supporting the 18-chain elementary cellulose microfibril model and cellulose synthase complex with the oversized observations from characterization techniques, which report averaged structures influenced by microfibril coalescence and hemicellulose binding. The structural insights also offer valuable information regarding recalcitrance and the potential applications of biomass in biorefinery operations.

biochemistry↗

Accurate Prediction of Antibody Function and Structure Using Bio-Inspired Antibody Language Model

In recent decades, antibodies have emerged as indispensable therapeutics for combating diseases, particularly viral infections. However, their development has been hindered by limited structural information and labor-intensive engineering processes. Fortunately, significant advancements in deep learning methods have facilitated the precise prediction of protein structure and function by leveraging co-evolution information from homologous proteins. Despite these advances, predicting the conformation of antibodies remains challenging due to their unique evolution and the high flexibility of their antigen-binding regions. Here, to address this challenge, we present the Bio-inspired Anti-body Language Model (BALM). This model is trained on a vast dataset comprising 336 million 40% non-redundant unlabeled antibody sequences, capturing both unique and conserved properties specific to antibodies. Notably, BALM showcases exceptional performance across four antigen-binding prediction tasks. Moreover, we introduce BALMFold, an end-to-end method derived from BALM, capable of swiftly predicting full atomic antibody structures from individual sequences. Remarkably, BALMFold outperforms those well-established methods like AlphaFold2, IgFold, ESMFold, and OmegaFold in the antibody benchmark, demonstrating significant potential to advance innovative engineering and streamline therapeutic antibody development by reducing the need for unnecessary trials.

bioinformatics↗

High-Intensity Interval Training Attenuates Impairment in Regulatory Protein Machinery of Mitochondrial Quality Control in Skeletal Muscle of Diet-Induced Obese Mice

Mitochondrial quality control processes are essential in governing mitochondrial integrity and function. The purpose of the study was to examine the effects of 10 weeks of HIIT on the regulatory protein machinery of skeletal muscle mitochondrial quality control and whole-body glucose homeostasis in diet-induced obese mice. Male C57BL/6 mice were randomly assigned to a low-fat diet (LFD) or high-fat diet (HFD) group. After 10 weeks, HFD-fed mice were divided into sedentary and HIIT (HFD+HIIT) groups and remained on HFD for another 10 weeks (n=9/group). Graded exercise test, glucose and insulin tolerance tests, mitochondrial respiration and regulatory protein markers of mitochondrial quality control processes were determined by immunoblots. Ten weeks of HIIT enhanced ADP-stimulated mitochondrial respiration in diet-induced obese mice (P < 0.05) but did not improve whole-body insulin sensitivity. Importantly, the ratio of Drp1(Ser616) over Drp1(Ser637) phosphorylation, an indicator of mitochondrial fission, was attenuated in HFD-HIIT compared to HFD (-35.7%, P < 0.05). Regarding autophagy, skeletal muscle p62 content was lower in HFD group than LFD group (-35.1%, P < 0.05), however, such reduction was disappeared in HFD+HIIT group. In addition, LC3B II/I ratio was higher in HFD than LFD group (15.5%, P < 0.05) but was ameliorated in HFD+HIIT group (-29.9%, P < 0.05). Overall, our study demonstrated that 10 weeks of HIIT was effective in improving skeletal muscle mitochondrial respiration and the regulatory protein machinery of mitochondrial quality control in diet-induced obese mice through the alterations of mitochondrial fission protein Drp1 activity and p62/LC3B-mediated regulatory machinery of autophagy.

physiology↗

Phospholipase A2 inhibitor-loaded micellar nanoparticles attenuate inflammation and mitigate osteoarthritis progression

Treating osteoarthritis (OA) remains a major clinical challenge. Despite recent advances in drug discovery and development, no disease-modifying drug for knee OA has emerged with any significant clinical success, in part due to the lack of valid and responsive therapeutic targets and poor drug delivery within knee joints. In this work, we show that the amount of secretory phospholipase A2 (sPLA2) enzyme increases in articular cartilage in human and mouse OA cartilage tissues. We hypothesize that inhibition of sPLA2 activity may be an effective treatment strategy for OA. To develop a sPLA2-responsive and nanoparticle (NP)-based interventional platform for OA management, we incorporated a sPLA2 inhibitor (sPLA2i) into the phospholipid membrane of micelles. The engineered sPLA2i-loaded micellar nanoparticles (sPLA2i-NPs) were able to penetrate deep into the cartilage matrix, prolong retention in the joint space, and mitigate OA progression. These findings suggest that sPLA2i-NPs can be promising therapeutic agents for OA treatment.

bioengineering↗

Structure-based drug design, virtual screening and high-throughput screening rapidly identify antiviral leads targeting COVID-19

A new coronavirus (CoV) identified as COVID-19 virus is the etiological agent responsible for the 2019-2020 viral pneumonia outbreak that commenced in Wuhan1-4. Currently there is no targeted therapeutics and effective treatment options remain very limited. In order to rapidly discover lead compounds for clinical use, we initiated a program of combined structure-assisted drug design, virtual drug screening and high-throughput screening to identify new drug leads that target the COVID-19 virus main protease (Mpro). Mpro is a key CoV enzyme, which plays a pivotal role in mediating viral replication and transcription, making it an attractive drug target for this virus5,6. Here, we identified a mechanism-based inhibitor, N3, by computer-aided drug design and subsequently determined the crystal structure of COVID-19 virus Mpro in complex with this compound. Next, through a combination of structure-based virtual and high-throughput screening, we assayed over 10,000 compounds including approved drugs, drug candidates in clinical trials, and other pharmacologically active compounds as inhibitors of Mpro. Six of these inhibit Mpro with IC50 values ranging from 0.67 to 21.4 M. Ebselen also exhibited promising antiviral activity in cell-based assays. Our results demonstrate the efficacy of this screening strategy, which can lead to the rapid discovery of drug leads with clinical potential in response to new infectious diseases where no specific drugs or vaccines are available.

biochemistry↗