Engineering Bifidobacterium longum Endo-α-N-acetylgalactosaminidase for Neu5Acα2-3Galß1-3GalNAc reactivity on Fetuin.

Endo-α-N-acetylgalactosaminidase from Bifidobacterium longum (EngBF) belongs to the glycoside hydrolase family GH101 and has a strict preference towards the mucin type glycan, Galß1-3GalNAc, which is O-linked to serine or threonine residues on glycopeptides and -proteins. While other enzymes of the GH101 family exhibit a wider substrate spectrum, no GH101 member has until recently been reported to process the α2-3 sialidated mucin glycan, Neu5Acα2-3Galß1-3GalNAc. However, work published by others (ACS Chem Biol 2021, 16, 2004-2015) during the preparation of the present manuscript demonstrated that the enzymes from several bacteria are able to hydrolyze this glycan from the fluorophore, methylumbelliferyl. Based on molecular docking using the EngBF homolog, EngSP from Streptococcus pneumoniae, substitution of active site amino acid residues with the potential to allow for accommodation of Neu5Acα2-3Galß1-3GalNAc were identified. Based on this analysis, the mutant EngBF variants W750A, Q894A, K1199A, E1294A and D1295A were prepared and tested, for activity towards the Neu5Acα2-3Galß1-3GalNAc O-linked glycan present on bovine fetuin. Among the mutant EngBF variants listed above, only E1294A was shown to release Neu5Acα2-3Galß1-3GalNAc from fetuin, which subsequently was also demonstrated for the substitutions: E1294 M, E1294H and E1294K. In addition, the kcat/KM of the EngBF variants for cleavage of the Neu5Acα2-3Galß1-3GalNAc glycan increased between 5 and 70 times from pH 4.5 to pH 6.0.

Identification of a Catalytic Nucleophile-Activating Network in the endo-α-N-Acetylgalactosaminidase of Family GH101.

Bifidobacterium longum endo-α-N-acetylgalactosaminidase (GH101), EngBF, is highly specific toward the mucin Core 1 glycan, Galß1-3GalNAc. Apart from the side chains involved in the retaining mechanism of EngBF, Asp-682 is important for the activity. In the crystal structures of both EngBF and EngSP (from Streptococcus pneumoniae), we identified a conserved water molecule in proximity to Asp-682 and the homologue residue in EngSP. The water molecule also coordinates the catalytic nucleophile and three other residues conserved in GH101 enzymes; in EngBF, these residues are His-685, His-718, and Asn-720. With casein-glycomacropeptide as the substrate, the importance of Asp-682 was confirmed by the lack of a detectable activity for the D682N enzyme. The enzyme variants, H685A, H718A, H685Q, and H718Q, all displayed only a modestly reduction in kcat of up to 15 fold for the H718A variant. However, the double-substituted variants, H685A/H718A and H685Q/H718Q, had a greatly reduced kcat value by about 200 fold compared to that of wild-type EngBF. With the synthetic substrate, Galß(1-3)GalNAcα1-para-nitrophenol, kcat of the double-substituted variants was only up to 30-fold reduced and was found to increase with pH. Compared to the pre-steady-state kinetics of wild-type EngBF, a burst of about the size of the enzyme concentration was absent with the double-substituted EngBF variants, indicating that the nucleophilic attack had become at least as slow as the hydrolysis of the enzyme intermediate. Together, the results indicate that not only Asp-682 but also the entire conserved network of His-685, His-718, and what we suggest is a catalytic water molecule is important in the activation of the catalytic nucleophile.

Carving out a Glycoside Hydrolase Active Site for Incorporation into a New Protein Scaffold Using Deep Network Hallucination.

Enzymes are indispensable biocatalysts for numerous industrial applications, yet stability, selectivity, and restricted substrate recognition present limitations for their use. Despite the importance of enzyme engineering in overcoming these limitations, success is often challenged by the intricate architecture of enzymes derived from natural sources. Recent advances in computational methods have enabled the de novo design of simplified scaffolds with specific functional sites. Such scaffolds may be advantageous as platforms for enzyme engineering. Here, we present a strategy for the de novo design of a simplified scaffold of an endo-α-N-acetylgalactosaminidase active site, a glycoside hydrolase from the GH101 enzyme family. Using a combination of trRosetta hallucination, iterative cycles of deep-learning-based structure prediction, and ProteinMPNN sequence design, we designed proteins with 290 amino acids incorporating the active site while reducing the molecular weight by over 100 kDa compared to the initial endo-α-N-acetylgalactosaminidase. Of 11 tested designs, six were expressed as soluble monomers, displaying similar or increased thermostabilities compared to the natural enzyme. Despite lacking detectable enzymatic activity, the experimentally determined crystal structures of a representative design closely matched the design with a root-mean-square deviation of 1.0 Å, with most catalytically important side chains within 2.0 Å. The results highlight the potential of scaffold hallucination in designing proteins that may serve as a foundation for subsequent enzyme engineering.