Structure-function relationships in NDP-sugar active SDR enzymes: Fingerprints for functional annotation and enzyme engineering

Costa, Matthieu Da; Gevaert, Ophelia; Overtveldt, Stevie Van; Lange, Joanna; Joosten, Han; Desmet, Tom; Beerens, Koen

doi:10.1016/j.biotechadv.2021.107705

Cited by 20 publications

(59 citation statements)

References 63 publications

(83 reference statements)

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“…These CEP1 enzymes all belong to the large short-chain dehydrogenase/reductase (SDR) enzyme superfamily and more specifically the extended SDRs ( Persson et al, 2009 ; Persson and Kallberg, 2013 ; Gräff et al, 2019 ). They share a common structural fold (i.e., extended Rossmann-fold with characteristic Glycine motif and catalytic triad ([ST]x n Yx 3 K) ( Da Costa et al, 2021 )) and mechanistic features (i.e., catalysis starts with an initial oxidation step, see below).…”

Section: Structurementioning

confidence: 99%

GDP-Mannose 3,5-Epimerase: A View on Structure, Mechanism, and Industrial Potential

Beerens

Gevaert

Desmet

2022

Front. Mol. Biosci.

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GDP-mannose 3,5-epimerase (GM35E, GME) belongs to the short-chain dehydrogenase/reductase (SDR) protein superfamily and catalyses the conversion of GDP-d-mannose towards GDP-l-galactose. Although the overall reaction seems relatively simple (a double epimerization), the enzyme needs to orchestrate a complex set of chemical reactions, with no less than 6 catalysis steps (oxidation, 2x deprotonation, 2x protonation and reduction), to perform the double epimerization of GDP-mannose to GDP-l-galactose. The enzyme is involved in the biosynthesis of vitamin C in plants and lipopolysaccharide synthesis in bacteria. In this review, we provide a clear overview of these interesting epimerases, including the latest findings such as the recently characterized bacterial and thermostable GM35E representative and its mechanism revision but also focus on their industrial potential in rare sugar synthesis and glycorandomization.

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Section: Structurementioning

confidence: 99%

GDP-Mannose 3,5-Epimerase: A View on Structure, Mechanism, and Industrial Potential

Beerens

Gevaert

Desmet

2022

Front. Mol. Biosci.

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“…Because the structures of protein sequences often evolve more slowly than sequences themselves [26], structure-based MSA algorithms are usually able to achieve better performance than methods that only consider sequence alignment [12]. By learning the structure-based multiple sequence alignment from public datasets, Matthieu et al can successfully identify clear patterns in correlation of crucial residues [11]. However, these methods rely heavily on the structure information of known protein sequences, which may not always be available especially when an increasing amount of new protein sequences are discovered every day.…”

Section: Related Work 21 Multiple Sequence Alignmentmentioning

confidence: 99%

“…Their basic idea is that the structures of protein sequences usually evolve much more slowly than sequences themselves [26]. Hence, they believe that if a model can consider the structure of sequences, this model has great potential of achieving better results than other models that only rely on sequence alignment [26,12,11]. Armougom et al introduce a server termed EXPRESSO to automatically select templates by running BLAST [2,8] to identify close homologous by considering the structural information of sequences in the PDB database [4].…”

Section: Introductionmentioning

confidence: 99%

fastMSA: Accelerating Multiple Sequence Alignment with Dense Retrieval on Protein Language

Liang

Sun

Zheng

et al. 2021

Preprint

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Evolutionarily related sequences provide information for the protein structure and function. Multiple sequence alignment, which includes homolog searching from large databases and sequence alignment, is efficient to dig out the information and assist protein structure and function prediction, whose efficiency has been proved by AlphaFold. Despite the existing tools for multiple sequence alignment, searching homologs from the entire UniProt is still time-consuming. Considering the success of AlphaFold, foreseeably, large- scale multiple sequence alignments against massive databases will be a trend in the field. It is very desirable to accelerate this step. Here, we propose a novel method, fastMSA, to improve the speed significantly. Our idea is orthogonal to all the previous accelerating methods. Taking advantage of the protein language model based on BERT, we propose a novel dual encoder architecture that can embed the protein sequences into a low-dimension space and filter the unrelated sequences efficiently before running BLAST. Extensive experimental results suggest that we can recall most of the homologs with a 34-fold speed-up. Moreover, our method is compatible with the downstream tasks, such as structure prediction using AlphaFold. Using multiple sequence alignments generated from our method, we have little performance compromise on the protein structure prediction with much less running time. fastMSA will effectively assist protein sequence, structure, and function analysis based on homologs and multiple sequence alignment.

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“…Recently, we described the so-called heptagonal box model for the NDP-sugar active short-chain dehydrogenase/reductase superfamily based on conservation and correlation patterns. The different subfamilies and specificities can be distinguished based on which amino acids occupy the seven “walls” or fingerprint regions of the model [ 40 ].…”

Section: Introductionmentioning

confidence: 99%

Discovery of a Kojibiose Hydrolase by Analysis of Specificity-Determining Correlated Positions in Glycoside Hydrolase Family 65

et al. 2021

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The Glycoside Hydrolase Family 65 (GH65) is an enzyme family of inverting a-glucoside phosphorylases and hydrolases that currently contains 10 characterized enzyme specificities. However, its sequence diversity has never been studied in detail. Here, an in-silico analysis of correlated mutations was performed, revealing specificity-determining positions that facilitate annotation of the family’s phylogenetic tree. By searching these positions for amino acid motifs that do not match those found in previously characterized enzymes from GH65, several clades that may harbor new functions could be identified. Three enzymes from across these regions were expressed in E. coli and their substrate profile was mapped. One of those enzymes, originating from the bacterium Mucilaginibacter mallensis, was found to hydrolyze kojibiose and a-1,2-oligoglucans with high specificity. We propose kojibiose glucohydrolase as the systematic name and kojibiose hydrolase or kojibiase as the short name for this new enzyme. This work illustrates a convenient strategy for mapping the natural diversity of enzyme families and smartly mining the ever-growing number of available sequences in the quest for novel specificities.

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Structure-function relationships in NDP-sugar active SDR enzymes: Fingerprints for functional annotation and enzyme engineering

Cited by 20 publications

References 63 publications

GDP-Mannose 3,5-Epimerase: A View on Structure, Mechanism, and Industrial Potential

GDP-Mannose 3,5-Epimerase: A View on Structure, Mechanism, and Industrial Potential

fastMSA: Accelerating Multiple Sequence Alignment with Dense Retrieval on Protein Language

Discovery of a Kojibiose Hydrolase by Analysis of Specificity-Determining Correlated Positions in Glycoside Hydrolase Family 65

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