Enzymes are key proteins performing the basic functional activities in cells. In humans, enzymes can be also responsible for diseases, and the molecular mechanisms underlying the genotype to phenotype relationship are under investigation for diagnosis and medical care. Here, we focus on highlighting enzymes that are active in different metabolic pathways and become relevant hubs in protein interaction networks. We perform a statistics to derive our present knowledge on human metabolic pathways (the Kyoto Encyclopaedia of Genes and Genomes (KEGG)), and we found that activity aldehyde dehydrogenase (NAD(+)), described by Enzyme Commission number EC 1.2.1.3, and activity acetyl-CoA C-acetyltransferase (EC 2.3.1.9) are the ones most frequently involved. By associating functional activities (EC numbers) to enzyme proteins, we found the proteins most frequently involved in metabolic pathways. With our analysis, we found that these proteins are endowed with the highest numbers of interaction partners when compared to all the enzymes in the pathways and with the highest numbers of predicted interaction sites. As specific enzyme protein test cases, we focus on Alpha-Aminoadipic Semialdehyde Dehydrogenase (ALDH7A1, EC 2.3.1.9) and Acetyl-CoA acetyltransferase, cytosolic and mitochondrial (gene products of ACAT2 and ACAT1, respectively; EC 2.3.1.9). With computational approaches we show that it is possible, by starting from the enzyme structure, to highlight clues of their multiple roles in different pathways and of putative mechanisms promoting the association of genes to disease.

Highlighting human enzymes active in different metabolic pathways and diseases: The case study of EC 1.2.3.1 and EC 2.3.1.9 / Babbi G.; Baldazzi D.; Savojardo C.; Martelli P.L.; Casadio R.. - In: BIOMEDICINES. - ISSN 2227-9059. - ELETTRONICO. - 8:8(2020), pp. 250.250-250.262. [10.3390/BIOMEDICINES8080250]

Highlighting human enzymes active in different metabolic pathways and diseases: The case study of EC 1.2.3.1 and EC 2.3.1.9

Babbi G.
Primo
;
Baldazzi D.;Savojardo C.;Martelli P. L.;Casadio R.
2020

Abstract

Enzymes are key proteins performing the basic functional activities in cells. In humans, enzymes can be also responsible for diseases, and the molecular mechanisms underlying the genotype to phenotype relationship are under investigation for diagnosis and medical care. Here, we focus on highlighting enzymes that are active in different metabolic pathways and become relevant hubs in protein interaction networks. We perform a statistics to derive our present knowledge on human metabolic pathways (the Kyoto Encyclopaedia of Genes and Genomes (KEGG)), and we found that activity aldehyde dehydrogenase (NAD(+)), described by Enzyme Commission number EC 1.2.1.3, and activity acetyl-CoA C-acetyltransferase (EC 2.3.1.9) are the ones most frequently involved. By associating functional activities (EC numbers) to enzyme proteins, we found the proteins most frequently involved in metabolic pathways. With our analysis, we found that these proteins are endowed with the highest numbers of interaction partners when compared to all the enzymes in the pathways and with the highest numbers of predicted interaction sites. As specific enzyme protein test cases, we focus on Alpha-Aminoadipic Semialdehyde Dehydrogenase (ALDH7A1, EC 2.3.1.9) and Acetyl-CoA acetyltransferase, cytosolic and mitochondrial (gene products of ACAT2 and ACAT1, respectively; EC 2.3.1.9). With computational approaches we show that it is possible, by starting from the enzyme structure, to highlight clues of their multiple roles in different pathways and of putative mechanisms promoting the association of genes to disease.
2020
Highlighting human enzymes active in different metabolic pathways and diseases: The case study of EC 1.2.3.1 and EC 2.3.1.9 / Babbi G.; Baldazzi D.; Savojardo C.; Martelli P.L.; Casadio R.. - In: BIOMEDICINES. - ISSN 2227-9059. - ELETTRONICO. - 8:8(2020), pp. 250.250-250.262. [10.3390/BIOMEDICINES8080250]
Babbi G.; Baldazzi D.; Savojardo C.; Martelli P.L.; Casadio R.
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11585/789473
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