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      Insights into the mechanism of substrate specificity in a novel PL15_3 subfamily oligo-alginate lyase VBAly15A

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      1 , 1 , 2 , 1 , , 1
      Applied and Environmental Microbiology
      American Society for Microbiology
      alginate, alginate lyase, catalytic mechanism, substrate specificity

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          ABSTRACT

          Alginate is a major component of brown algae cell walls and can be degraded via β-elimination by alginate lyases. These enzymes are classified into polysaccharide lyases and oligo-alginate lyases (Oals), with Oals mainly represented by the PL15 and PL17 families. Unlike PL17 Oals, which are widely present in alginate-degrading microorganisms, PL15 enzymes are only identified in a limited number of microorganisms, and their biochemical characteristics remain poorly understood. In this research, a novel PL15 alginate lyase, VBAly15A, from the marine bacterium, Vibrio sp. B1Z05, was identified and characterized. It belongs to a new PL15_3 subfamily and exhibits high activity toward polyM substrates. VBAly15A is thermostable in medium temperatures, tolerant to alkaline up to 11.0, and polyM-specific Oal, and it can first degrade alginate polymers into disaccharides and subsequently catalyze disaccharides into monomers via an exolytic mode. Site-directed mutagenesis showed that Arg 114, Tyr 470, and Arg 110 in the active groove are essential for the stable binding of the substrate. In addition, the amino acid His 226 in VBAly15A, previously suggested to act as a catalytic base, is not essential for catalysis, whereas Tyr 280, previously proposed to act as a catalytic acid, is required for enzyme activity. Structural bioinformatic and biochemical analyses revealed that His 226 functions as a catalytic base, specifically abstracting protons from G-type substrates, while Tyr 280 acts as both a catalytic acid and a base. This catalytic mechanism is likely conserved in PL15 family alginate lyases.

          IMPORTANCE

          Alginate, as a renewable resource for sustainability, has great application prospects. In addition to polysaccharide lyases, Oals are critical for the full degradation of alginate, a key prerequisite for biorefinery. So far, most identified and well-characterized Oals belong to the PL17 family. However, the catalytic mechanism of PL15 Oals is limited, and even the catalytic base and acid are not fully elucidated. The significance of this study lies in discovering and characterizing a novel Oal VBAly15A that divides into a new PL15 subfamily, PL15_3. Not only are key amino acid residues involved in enzyme activity identified, but residues acting as the catalytic base and acid are also demonstrated. The distance of the catalytic residues His and Tyr to the C5 proton of the sugar ring determines the substrate specificity. Therefore, this work provides new insights into the mechanism of substrate specificity in alginate lyases.

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          Highly accurate protein structure prediction with AlphaFold

          Proteins are essential to life, and understanding their structure can facilitate a mechanistic understanding of their function. Through an enormous experimental effort 1 – 4 , the structures of around 100,000 unique proteins have been determined 5 , but this represents a small fraction of the billions of known protein sequences 6 , 7 . Structural coverage is bottlenecked by the months to years of painstaking effort required to determine a single protein structure. Accurate computational approaches are needed to address this gap and to enable large-scale structural bioinformatics. Predicting the three-dimensional structure that a protein will adopt based solely on its amino acid sequence—the structure prediction component of the ‘protein folding problem’ 8 —has been an important open research problem for more than 50 years 9 . Despite recent progress 10 – 14 , existing methods fall far short of atomic accuracy, especially when no homologous structure is available. Here we provide the first computational method that can regularly predict protein structures with atomic accuracy even in cases in which no similar structure is known. We validated an entirely redesigned version of our neural network-based model, AlphaFold, in the challenging 14th Critical Assessment of protein Structure Prediction (CASP14) 15 , demonstrating accuracy competitive with experimental structures in a majority of cases and greatly outperforming other methods. Underpinning the latest version of AlphaFold is a novel machine learning approach that incorporates physical and biological knowledge about protein structure, leveraging multi-sequence alignments, into the design of the deep learning algorithm. AlphaFold predicts protein structures with an accuracy competitive with experimental structures in the majority of cases using a novel deep learning architecture.
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            MEGA X: Molecular Evolutionary Genetics Analysis across Computing Platforms.

            The Molecular Evolutionary Genetics Analysis (Mega) software implements many analytical methods and tools for phylogenomics and phylomedicine. Here, we report a transformation of Mega to enable cross-platform use on Microsoft Windows and Linux operating systems. Mega X does not require virtualization or emulation software and provides a uniform user experience across platforms. Mega X has additionally been upgraded to use multiple computing cores for many molecular evolutionary analyses. Mega X is available in two interfaces (graphical and command line) and can be downloaded from www.megasoftware.net free of charge.
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              Clustal W and Clustal X version 2.0.

              The Clustal W and Clustal X multiple sequence alignment programs have been completely rewritten in C++. This will facilitate the further development of the alignment algorithms in the future and has allowed proper porting of the programs to the latest versions of Linux, Macintosh and Windows operating systems. The programs can be run on-line from the EBI web server: http://www.ebi.ac.uk/tools/clustalw2. The source code and executables for Windows, Linux and Macintosh computers are available from the EBI ftp site ftp://ftp.ebi.ac.uk/pub/software/clustalw2/
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                Author and article information

                Contributors
                Role: Editor
                Journal
                Appl Environ Microbiol
                Appl Environ Microbiol
                aem
                Applied and Environmental Microbiology
                American Society for Microbiology (1752 N St., N.W., Washington, DC )
                0099-2240
                1098-5336
                March 2025
                27 February 2025
                27 February 2025
                : 91
                : 3
                : e02351-24
                Affiliations
                [1 ]State Key Laboratory of Microbial Technology, Shandong University, Ringgold 520252; , Qingdao, China
                [2 ]Qingdao Vland Biotech Company Group, Ringgold 641181; , Qingdao, China
                Georgia Institute of Technology; , Atlanta, Georgia, USA
                Author notes
                Address correspondence to Yingjie Li, yingjie.li@ 123456sdu.edu.cn

                The authors declare no conflict of interest.

                Author information
                https://orcid.org/0009-0006-5919-5270
                https://orcid.org/0009-0000-4437-6630
                Article
                aem02351-24 aem.02351-24
                10.1128/aem.02351-24
                11921355
                40013786
                28bad09a-f2ab-4f22-8f6c-aedf937e10fd
                Copyright © 2025 Tang et al.

                This is an open-access article distributed under the terms of the Creative Commons Attribution 4.0 International license.

                History
                : 22 November 2024
                : 04 February 2025
                Page count
                supplementary-material: 1, authors: 5, Figures: 7, Tables: 1, References: 50, Pages: 17, Words: 9280
                Funding
                Funded by: Shandong Provincial Natural Science Foundation;
                Award ID: No. ZR2022MD078
                Award Recipient :
                Funded by: National Natural Science Foundation of China (NSFC);
                Award ID: No. 41706165
                Award Recipient :
                Funded by: Fundamental Research Funds of Shandong University;
                Award ID: N0. 2019HW022
                Award Recipient :
                Categories
                Enzymology and Protein Engineering
                molecular-and-cellular-biology, Molecular and Cellular Biology
                Custom metadata
                March 2025

                Microbiology & Virology
                alginate,alginate lyase,catalytic mechanism,substrate specificity
                Microbiology & Virology
                alginate, alginate lyase, catalytic mechanism, substrate specificity

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