The increasing availability of experimental and computational protein structures entices their use for function prediction. Here we develop an automated procedure to identify enzymes involved in metabolic reactions by assessing substrate conformations docked to a library of protein structures. By screening AlphaFold-modeled vitamin B6-dependent enzymes, we find that a metric based on catalytically favorable conformations at the enzyme active site performs best (AUROC Score=0.84) in identifying genes associated with known reactions. Applying this procedure, we identify the mammalian gene encoding hydroxytrimethyllysine aldolase (HTMLA), the second enzyme of carnitine biosynthesis. Upon experimental validation, we find that the top-ranked candidates, serine hydroxymethyl transferase (SHMT) 1 and 2, catalyze the HTMLA reaction. However, a mouse protein absent in humans (threonine aldolase; Tha1) catalyzes the reaction more efficiently. Tha1 did not rank highest based on the AlphaFold model, but its rank improved to second place using the experimental crystal structure we determined at 2.26 angstrom resolution. Our findings suggest that humans have lost a gene involved in carnitine biosynthesis, with HTMLA activity of SHMT partially compensating for its function.With structural models now available on a proteome scale, Malatesta et al. show that structure-based screening can help identify proteins catalyzing orphan reactions in metabolic pathways, offering functional insights beyond sequence-based approaches.

One substrate many enzymes virtual screening uncovers missing genes of carnitine biosynthesis in human and mouse / Malatesta, Marco; Fornasier, Emanuele; Di Salvo, Martino Luigi; Tramonti, Angela; Zangelmi, Erika; Peracchi, Alessio; Secchi, Andrea; Polverini, Eugenia; Giachin, Gabriele; Battistutta, Roberto; Contestabile, Roberto; Percudani, Riccardo. - In: NATURE COMMUNICATIONS. - ISSN 2041-1723. - 15:1(2024). [10.1038/s41467-024-47466-3]

One substrate many enzymes virtual screening uncovers missing genes of carnitine biosynthesis in human and mouse

Di Salvo, Martino Luigi;Tramonti, Angela;Contestabile, Roberto
;
2024

Abstract

The increasing availability of experimental and computational protein structures entices their use for function prediction. Here we develop an automated procedure to identify enzymes involved in metabolic reactions by assessing substrate conformations docked to a library of protein structures. By screening AlphaFold-modeled vitamin B6-dependent enzymes, we find that a metric based on catalytically favorable conformations at the enzyme active site performs best (AUROC Score=0.84) in identifying genes associated with known reactions. Applying this procedure, we identify the mammalian gene encoding hydroxytrimethyllysine aldolase (HTMLA), the second enzyme of carnitine biosynthesis. Upon experimental validation, we find that the top-ranked candidates, serine hydroxymethyl transferase (SHMT) 1 and 2, catalyze the HTMLA reaction. However, a mouse protein absent in humans (threonine aldolase; Tha1) catalyzes the reaction more efficiently. Tha1 did not rank highest based on the AlphaFold model, but its rank improved to second place using the experimental crystal structure we determined at 2.26 angstrom resolution. Our findings suggest that humans have lost a gene involved in carnitine biosynthesis, with HTMLA activity of SHMT partially compensating for its function.With structural models now available on a proteome scale, Malatesta et al. show that structure-based screening can help identify proteins catalyzing orphan reactions in metabolic pathways, offering functional insights beyond sequence-based approaches.
2024
metabolic pathways; protein function predictions; structural biology
01 Pubblicazione su rivista::01a Articolo in rivista
One substrate many enzymes virtual screening uncovers missing genes of carnitine biosynthesis in human and mouse / Malatesta, Marco; Fornasier, Emanuele; Di Salvo, Martino Luigi; Tramonti, Angela; Zangelmi, Erika; Peracchi, Alessio; Secchi, Andrea; Polverini, Eugenia; Giachin, Gabriele; Battistutta, Roberto; Contestabile, Roberto; Percudani, Riccardo. - In: NATURE COMMUNICATIONS. - ISSN 2041-1723. - 15:1(2024). [10.1038/s41467-024-47466-3]
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11573/1714840
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