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The mechanisms behind Concanavalin A (ConA) circular permutation have been under investigation since 1985. Although a vast amount of information is available about this lectin and its applications, the exact purpose of its processing remains unclear. To shed light on this, this study employed computer simulations to compare the unprocessed ProConA with the mature ConA. This approach aimed to reveal the importance of the post-translational modifications, especially how they affect the lectin stability and carbohydrate-binding properties. To achieve these goals, we conducted 200 ns molecular dynamics simulations and trajectory analyses on the monomeric forms of ProConA and ConA (both unbound and in complex with D-mannose and the GlcNAc2Man9 N-glycan), as well as on their oligomeric forms. Our findings reveal significant stability differences between ProConA and ConA at both the monomeric and tetrameric levels, with ProConA exhibiting consistently lower stability parameters compared to ConA. In terms of carbohydrate binding properties, however, both lectins showed remarkable similarities in their interaction profiles, contact numbers, and binding free energies with D-mannose and the high-mannose -glycan. Overall, our results suggest that the processing of ProConA significantly enhances the stability of the mature lectin, especially in maintaining the tetrameric oligomer, without substantially affecting its carbohydrate-binding properties.
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http://dx.doi.org/10.1016/j.crstbi.2024.100140 | DOI Listing |
Neural Netw
August 2025
Faculty of Electronics, Photonics, and Microsystems, Wroclaw University of Science and Technology, Wybrzeze Wyspianskiego 27, Wroclaw, 50-370, Poland.
Convolutional neural networks (CNNs) are among the most widely used machine learning models for computer vision tasks, such as image classification. To improve the efficiency of CNNs, many compression approaches have been developed. Low-rank methods approximate the original convolutional kernel with a sequence of smaller convolutional kernels, leading to reduced storage and time complexities.
View Article and Find Full Text PDFbioRxiv
August 2025
Institute for Protein Design, University of Washington, Seattle, WA 98195, USA.
Self-assembling protein nanoparticles are being increasingly utilized in the design of next-generation vaccines due to their ability to induce antibody responses of superior magnitude, breadth, and durability. Computational protein design offers a route to novel nanoparticle scaffolds with structural and biochemical features tailored to specific vaccine applications. Although strategies for designing new self-assembling proteins have been established, the recent development of powerful machine learning-based tools for protein structure prediction and design provides an opportunity to overcome several of their limitations.
View Article and Find Full Text PDFAdv Exp Med Biol
August 2025
Department of Pathology and Laboratory Medicine, Western University, London, ON, Canada.
Circular RNA (circRNA) is becoming an increasingly popular field of study and topic of interest. With that, there is a renewed and heightened interest in generating circular RNA for both research and clinical use. CircRNA generation began in the 1990s using in vitro chemical ligation and has since expanded out to include in vitro enzymatic synthesis along with in vivo vector-based systems.
View Article and Find Full Text PDFJ Mood Anxiety Disord
December 2025
School of Medicine, Deakin University and Barwon Health, Australia.
Background: We evaluated whether a large language model could assist in selecting psychopharmacological treatments for adults with treatment-resistant depression.
Methods: We generated 20 clinical vignettes reflecting treatment-resistant depression among adults based on distributions drawn from electronic health records. Each vignette was evaluated by 2 expert psychopharmacologists to determine and rank the 5 best next-step pharmacologic interventions, as well as contraindicated or poor next-step treatments.
Genome Biol Evol
July 2025
Department of Structural and Molecular Biology, University College London, London, UK.
Protein folds are structural units defined by the number, type, arrangement, and orientation of their core secondary structural elements. The universe of protein folds is highly interconnected. Local sequence similarities, referred to as sequence motifs, link structurally distinct folds.
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