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BY 4.0 license Open Access Published by De Gruyter March 7, 2023

Study of NAD-interacting proteins highlights the extent of NAD regulatory roles in the cell and its potential as a therapeutic target

  • Sara Duarte-Pereira ORCID logo EMAIL logo , Sérgio Matos ORCID logo , José Luís Oliveira ORCID logo and Raquel M. Silva ORCID logo


Nicotinamide adenine dinucleotide (NAD) levels are essential for the normal physiology of the cell and are strictly regulated to prevent pathological conditions. NAD functions as a coenzyme in redox reactions, as a substrate of regulatory proteins, and as a mediator of protein-protein interactions. The main objectives of this study were to identify the NAD-binding and NAD-interacting proteins, and to uncover novel proteins and functions that could be regulated by this metabolite. It was considered if cancer-associated proteins were potential therapeutic targets. Using multiple experimental databases, we defined datasets of proteins that directly interact with NAD – the NAD-binding proteins (NADBPs) dataset – and of proteins that interact with NADBPs – the NAD-protein–protein interactions (NAD-PPIs) dataset. Pathway enrichment analysis revealed that NADBPs participate in several metabolic pathways, while NAD-PPIs are mostly involved in signalling pathways. These include disease-related pathways, namely, three major neurodegenerative disorders: Alzheimer’s disease, Huntington’s disease, and Parkinson’s disease. Then, the complete human proteome was further analysed to select potential NADBPs. TRPC3 and isoforms of diacylglycerol (DAG) kinases, which are involved in calcium signalling, were identified as new NADBPs. Potential therapeutic targets that interact with NAD were identified, that have regulatory and signalling functions in cancer and neurodegenerative diseases.

1 Introduction

Nicotinamide adenine dinucleotide (NAD) is a crucial metabolite in the cell, generally known for its function as cofactor in oxidation-reduction reactions responsible for energy production in the form of ATP, where it alternates between the oxidized (NAD+) and the reduced (NADH) forms. By transferring electrons between reactions, NAD participates in a multitude of metabolic processes that are key to the normal physiology of the cell including glycolysis, the citric acid cycle, fatty acids beta-oxidation and mitochondrial electron transport. Additionally, NAD is a substrate for proteins involved in cell survival, DNA damage repair, calcium signalling, or transcription regulation. NAD-dependent enzymes include sirtuins (SIRTs) [1], poly- and mono-(ADP-ribose) polymerases (PARPs and MARTs) [2, 3], and cyclic ADP-ribose hydrolases, such as CD38 [4]. Maintenance of NAD cellular levels depends on a balance between its production and its depletion, for which the interconversion between NAD+/NADH and NADP/NADPH is not accounted.

Another role for NAD was acknowledged more recently, where NAD would function as a direct modulator of protein–protein interactions (PPIs), through its binding to the NUDIX domain [5]. The NUDIX domain is a 23 amino acid long general structure of a Nucleoside Diphosphate linked to a variable moiety X, with catalytic activity on nucleotides. Through their activity, many NUDIX proteins contribute to cellular homeostasis by cleaning the cell from deleterious compounds. Others regulate the concentrations of several metabolites, such as NAD, NADP and ADP-ribose. Others remove 5′-cap from RNA and control the stability of mRNA, as well as gene expression. Nevertheless, several NUDIX enzymes remain uncharacterized [68].

NAD binding to the NUDIX homology domain (NHD) of the Deleted in Breast Cancer 1 (DBC1) protein prevented its interaction with PARP1 [5], and the DBC1-PARP1 interaction inhibits PARP1 normal function in the DNA damage repair process. Conversely, DBC1 regulates the activity of several proteins such as the transcription factor p53; the androgen and estrogen receptors (AR and ER), that are involved in hormone signalling; the BRCA1, which is also a DNA damage repair protein; and other NAD-dependent proteins that are epigenetic regulators, such as SIRT1 and HDAC3 [9].

The PARP catalytic domain is an example of a conserved protein domain that is common to all proteins within the PARP family, in which resides their main function of transferring the ADP-ribose moiety from its substrate (NAD) to carboxylate groups of aspartic and glutamic residues [10].

In this study, we aimed to characterize the NAD interactome, due to multitude of NAD cellular functions and relevance of NAD metabolism in normal and pathological conditions. Considering the NAD role in regulating PPIs, we focused on NAD-binding proteins and their interactions. Multiple experimental databases were surveyed to define an NAD-binding dataset, that was characterized through pathway enrichment analysis and protein structural domains analysis. The full human proteome was then screened, and a selection of potential NAD-binding proteins were further analysed. As previously reported in [11], we identified new proteins that potentially interact with NAD. Here, we described in detail the NADBPs dataset, we predicted NAD interacting residues of known NADBPs to serve as a reference and we further analysed the NUDIX containing proteins. We also uncovered NADBPs that are cancer-associated and potential drug targets. In addition, we performed molecular docking to predict the NAD-binding to potential NADBPs.

2 Workflow

2.1 Data collection

2.1.1 NAD-binding proteins (NADBPs) dataset

The first dataset was composed by proteins that directly interact with NAD, obtained from several databases of experimentally validated data. Namely, the following databases were searched: Human Metabolome Database (, STITCH (, Protein Data Bank (, ChEMBL (, PubChem ( and DrugBank ( The NADBPs dataset was composed by the sum of the proteins identified in the interactions from the six chemical databases used, as described in [11].

2.1.2 NAD-related proteins dataset

To study the proteins potentially related to NAD, an NAD-related dataset was defined. This was made using “NAD” as a keyword search, which considered all proteins that have “NAD” in protein name or in any field of description, such as protein family names, gene description, function or ontology classification. All human reviewed proteins obtained through UniProt ( [12] and from IMEX Consortium database ( [13] were considered.

2.1.3 NAD-protein–protein interactions (NAD-PPIs) dataset

A dataset composed by the proteins that interact with the NADBPs was built using three sources: BIOGRID ( [14], STRING ( v.10 [15] and IMEX Consortium, as previously described [11].

2.2 Gene ontology (GO) analysis of the protein datasets

GO analysis was performed on PANTHER ( [16], through an overrepresentation test (Fisher’s exact, False Discovery Rate correction), using the Pathways annotation dataset (version 13.0). The NAD-binding, the NAD-related and the NAD-PPIs datasets were analysed.

2.3 Identification of putative NAD-binding proteins

The most frequent protein domains and protein families within the NADBPs dataset were identified [11]. The total of 20,303 human reviewed proteins from the Uniprot database were considered as a reference dataset, and the 50,588 unreviewed proteins as a test dataset. Proteins that presented at least one of the most frequent NADBPs domains were retrieved from both reference and test datasets. The genes/proteins that were found exclusively within the test dataset of unreviewed proteins were identified and further analysed using the NADbinder ( [17] to predict the number of NAD interacting residues, and the STRING database ( v. 11 [15], to obtain the interactions of each of those proteins.

2.4 Molecular docking

To evaluate the potential binding of NAD to the top target, an automated in silico molecular docking analysis was performed using SwissDock web server (, as described by Grosdidier and collaborators [18]. NAD ligand was used as provided by ZINC database (, with the ID ZINC8214766, and the protein 3D structures of the top target were retrieved from AlphaFold database ( [19].

2.5 Cancer associated proteins and potential drug targets

Proteins from the NADBPs dataset were compared with catalogues of protein-coding genes from the subproteomes of the Human Protein Atlas ( [20]. Namely, the cancer proteome, that contains a list of 569 mutated proteins strongly implicated in cancer, as defined through the catalogue of somatic mutations in cancer (COSMIC), and the druggable proteome, that contains a list of 754 proteins targeted directly by an FDA approved drug, were considered. Currently, approximately four thousand protein-coding genes in the UniProt database have experimental evidence of involvement in several disease conditions, including cancer, neurologic, systemic and cardiovascular disease. From those, a list of 1326 proteins annotated in The Human Protein Atlas as potential drug targets, was also considered, as they belong to known drug target protein classes, such as enzymes, transporters, receptors and ion-channels, and are not yet targets for FDA approved or experimental drugs in the Drugbank database.

3 Results

3.1 NAD-binding and NAD-related proteins differ in their predominant cellular roles

After collecting data from six different databases, we obtained a NADBPs dataset composed by a total of 439 proteins (Figure 1 and Appendix A). The NAD metabolite was found under different forms and names, and both oxidized and reduced forms were included. The highest numbers of interactions with NAD were found on the databases STITCH, DrugBank and the Human Metabolome Database.

Figure 1: 
Venn-diagram showing the number of NAD-binding proteins obtained from each source.
Figure 1:

Venn-diagram showing the number of NAD-binding proteins obtained from each source.

The analysis of the 439 NADBPs showed that around 80% of these proteins were enzymes, most with catalytic activity, involved in metabolite interconversion. The major protein classes were dehydrogenases (92 proteins), from which over 30 were NADH dehydrogenase, and oxidoreductases (55 proteins), but several others were identified, as shown in Figure 2. More than one hundred proteins were mitochondrial isoforms of enzymes, which participate in the chain of reactions responsible for ATP production. Adding to enzymes that use NAD as cofactor in redox reactions, we also found all PARPs and all SIRTs, which are enzymes that use NAD as a substrate. Regarding their molecular function, a small number of proteins involved in regulation or transporter activities was also found.

Figure 2: 
Classification of the NAD-binding proteins according to the protein class from PANTHER ( The graphics represent the classes with more than 10 proteins. The remaining 43 classes comprising a total of 105 proteins are under the label “other” and 71 proteins remained non-classified.
Figure 2:

Classification of the NAD-binding proteins according to the protein class from PANTHER ( The graphics represent the classes with more than 10 proteins. The remaining 43 classes comprising a total of 105 proteins are under the label “other” and 71 proteins remained non-classified.

The NAD-related datasets included all proteins potentially related to NAD, either by protein names or by any field of description. For the “NAD-related” dataset, we obtained 456 proteins from UniProt and 1907 from IMEX. In a total of 2125 proteins, only 238 were common to both sources. We then identified 279 proteins that were also present in the NADBP dataset, leaving a total of 1846 NAD-related proteins that do not bind NAD directly.

We performed a GO analysis on the 439 proteins of the NADBPs dataset (Table 1) and on the 1846 proteins of the NAD-related dataset, to compare the results of the enriched pathways obtained in each one. Only two pathways were common to the two datasets, Glycolysis and the FAS signalling pathway. We found 31 pathways specific of the NADBPs dataset, that were not enriched on the NAD-related dataset. Those included pathways related to biosynthesis or metabolism of nucleic acids, carbohydrates, and amino acids.

Table 1:

NADBPs dataset pathway enrichment.

Pathway Fold enrichment
(min. 3.04–max. 47.93)
Biosynthesis Adrenaline and noradrenaline biosynthesis 6.18
Alanine biosynthesis 47.93
Androgen/estrogene/progesterone biosynthesis 23.97
Asparagine and aspartate biosynthesis 35.95
De novo purine biosynthesis 6.39
Formyltetrahydroformate biosynthesis 29.96
Gamma-aminobutyric acid synthesis 23.97
Histidine biosynthesis 47.93
Isoleucine biosynthesis 23.97
Leucine biosynthesis 47.93
Methionine biosynthesis 47.93
O-antigen biosynthesis 19.17
Proline biosynthesis 28.76
Serine glycine biosynthesis 38.35
Tetrahydrofolate biosynthesis 19.17
Valine biosynthesis 31.95
Basic metabolism 5-Hydroxytryptamine degradation 38.35
Acetate utilization 31.95
Aminobutyrate degradation 47.93
Fructose galactose metabolism 19.97
Glutamine glutamate conversion 23.97
Glycolysis 14.38
Methylmalonyl pathway 19.17
Phenylethylamine degradation 35.95
Purine metabolism 20.54
Pyruvate metabolism 30.5
TCA cycle 38.35
Xanthine and guanine salvage pathway 23.97
Signaling Dopamine receptor mediated signaling pathway 4.79
Endothelin signaling pathway 5.46
FAS signaling pathway 7.05
GABA-B receptor II signaling 11.28
Heterotrimeric G-protein signaling pathway-Gi alpha and Gs alpha mediated pathway 3.04

In the NAD-related dataset, we found 36 pathways that did not appeared in the NADBPs dataset, that were mostly related to signalling. The highest fold enrichment values were found in the pentose phosphate pathway (the highest fold = 10.1), the JAK/STAT signalling, and four pathways related to p53 signalling. Of note, disease related pathways arose in the NAD related dataset, such as Alzheimer, Huntington, and Parkinson diseases. Also, signalling pathways related to angiogenesis, inflammation, and apoptosis, which are disease related mechanisms, were identified within the results.

3.2 Proteins that interact with NADBPs comprise about half of the human proteome

Then, the NAD-protein–protein interactions (NAD-PPIs), i.e., the proteins that interacted with the NADBPs were studied. Using the 439 proteins from the NADBPs dataset, 9823 pairs of proteins from STRING database were obtained, that corresponded to a total of 7815 unique gene name identifiers, 19,682 pairs from BIOGRID database, that corresponded to a total of 6479 unique gene IDs, and 5594 pairs from IMEX, that corresponded to a total of 3301 unique IDs. After mapping each type of ID retrieved from each database to the UniProtKB ID, with reviewed annotation (either using automatic tools or manually, in the case of automatically unmapped IDs), the duplicated entries we removed that were mainly due to gene or protein alternative names, or disease names associated to those genes. From STRING, a total of 7533 proteins were successfully mapped and 75 elements remained unmapped. From BIOGRID, a total of 5752 proteins were mapped and 54 remained unmapped. Most of these unmapped IDs were pseudogenes. From IMEX, 2500 proteins were mapped, and 90 elements remained unmapped. We found 40 CHEBI IDs, that were retrieved from CHEBI database for identification, but were not included for further analysis, since they corresponded to chemical compounds that interact with NADBPs and not protein-protein interactions, as it was intended. The proteins common to the three sources of PPIs were identified, and a final list of 10,020 proteins involved in PPIs with NADBPs remained.

As this represents about half of the human proteins annotated so far, according to the most recent version of UniProt Knowledge Database (UniProtKB 2020_06, [21]), with 20,379 reviewed proteins on the human proteome, the 1368 proteins common to all databases (Figure 3) were further analysed. With this, the selection of the most validated interactions was assured.

Figure 3: 
Venn-diagram representing the protein-protein interactions from STRING, BIOGRID and IMEX databases, where the 439 NADBPs were used as query.
Figure 3:

Venn-diagram representing the protein-protein interactions from STRING, BIOGRID and IMEX databases, where the 439 NADBPs were used as query.

A GO analysis was performed on the 1368 proteins from the NAD-PPIs dataset and compared with the results from the NADBPs dataset described previously (Table 1). Similarly to the NAD-related dataset, the NAD-PPIs dataset presented an enrichment in several signalling pathways, as compared to the NADBPs dataset. The pathways with the highest number of genes (over 50) were related to hormone receptors signalling, namely for gonadotropin and for the gastrointestinal peptide hormones cholecystokinin and gastrin, followed by the Wnt signalling and angiogenesis pathways. Several other pathways were related to hormone or growth factor signalling, and disease pathways also emerged, namely three major neurodegenerative diseases, Alzheimer’s, Huntington’s, and Parkinson’s.

3.3 Overview of NADBPs protein structural domains

Protein domains analysis was performed on the 439 NADBPs through PFAM database and all matches that achieved an expectation value (E-value) below 1 (max. 0.88) were selected. The results show the top hit domain for each protein and how many hits were found. Within the 439 proteins, 1101 identifications were made, which corresponded to a total of 412 different domains. Two proteins didn’t have an identified domain (NDUFA11 and GPAT2) and, in the remaining 437 proteins, 222 different domains were identified as top hit. More than half of the proteins (56% – 247 proteins) belonged to the FAD/NAD(P)-binding Rossmann fold superfamily, and 27% belonged to the Ankyrin repeat superfamily. In our approach, the top 15 more common domains, which appeared in more than 10 proteins (Table 2), were selected. Five different ankyrin repeats were among these top domains found. Others were the short chain dehydrogenase, the aldehyde dehydrogenase family, the cytochrome P450 and the poly(ADP-ribose) polymerase (PARP) catalytic domain.

Table 2:

The top 15 domains identified in the NADBPs dataset.

Domain hmm ID Domain name Number of proteins Description
PF00023.29 Ank 30 Ankyrin repeat
PF13637.5 Ank_4 25 Ankyrin repeat
PF13857.5 Ank_5 24 Ankyrin repeat
PF00106.24 adh_short 23 Short chain dehydrogenase
PF13561.5 adh_short_C2 22 Enoyl-(Acyl carrier protein) reductase
PF13606.5 Ank_3 21 Ankyrin repeat
PF08659.9 KR 20 KR domain
PF12796.6 Ank_2 20 Ankyrin repeat
PF00211.19 Guanylate_cyc 18 Adenylate and Guanylate cyclase catalytic domain
PF00171.21 Aldedh 16 Aldehyde dehydrogenase family
PF00644.19 PARP 15 Poly(ADP-ribose) polymerase catalytic domain
PF01370.20 Epimerase 14 NAD dependent epimerase/dehydratase family
PF00153.26 Mito_carr 12 Mitochondrial carrier protein
PF00107.25 ADH_zinc_N 10 Zinc-binding dehydrogenase
PF00067.21 p450 10 Cytochrome P450

We also identified 65 proteins that had one of the 43 domains containing the term “NAD” in their names or descriptions. Eighteen proteins contain specifically one of the six different “NAD binding domain”, namely the D-isomer specific 2-hydroxyacid dehydrogenase, the 3-hydroxyacyl-CoA dehydrogenase, the lactate/malate dehydrogenase, the malic enzyme, the UDP-glucose/GDP-mannose dehydrogenase family, and the 6-phosphogluconate dehydrogenase NAD binding domains. The NUDIX domain was found only in two proteins from the NAD-binding dataset, namely NUDT12 and NUDT7.

3.4 Identification of 13 new NAD-binding proteins based on protein domains

We searched for the 15 domains that were identified in ten or more proteins from the NADBPs dataset (Table 2) within the dataset of the full human proteome unreviewed proteins (test dataset) and obtained 901 protein sequences. After removing all protein fragments and duplicates, 255 proteins were identified, which corresponded to 204 single genes. A similar approach was performed in the reference dataset yielding 474 genes. Given our aim to identify uncharacterized proteins, from the 204 genes, 195 that were also identified in the reference dataset were excluded and 8 genes remained, corresponding to 13 protein sequences, found uniquely in the test dataset (Table 3).

Table 3:

Proteins identified from the test dataset.

UniProt ID Status Gene name Protein name Length Number of NAD
A0A087WV00 Unreviewed DGKI Diacylglycerol kinase (DAG kinase) 932 21
E7EM72 Unreviewed DGKI Diacylglycerol kinase (DAG kinase) 1047 29
E7EWQ4 Unreviewed DGKI Diacylglycerol kinase (DAG kinase) 1078 31
E9PFX6 Unreviewed DGKI Diacylglycerol kinase (DAG kinase) 734 23
E9PNL8 Unreviewed DGKZ Diacylglycerol kinase (DAG kinase) 707 26
E9PK39 Unreviewed LRRK1 Leucine-rich repeat serine/threonine-protein kinase 1 650 12
E9PMK9 Unreviewed LRRK1 Leucine-rich repeat serine/threonine-protein kinase 1 689 7
Q495V5 Unreviewed POTEB POTE ankyrin domain family member B (POTEB protein) 301 16
D6R9P2 Unreviewed SLC9B2 Sodium/hydrogen exchanger 9B2 112 11
D6RC49 Unreviewed TRPC3 Short transient receptor potential channel 3 276 5
J3QTB0 Unreviewed TRPC3 Short transient receptor potential channel 3 793 33
A0A087WV96 Unreviewed CYP3A7-CYP3A51P CYP3A7-CYP3A51P readthrough 506 27
V9GXZ4 Unreviewed FPGT-TNNI3K FPGT-TNNI3K readthrough 949 24

Among the 13 proteins, there were five isoforms of the Diacylglycerol (DAG) kinase, four encoded by the DGKI gene, and one encoded by DGKZ gene. There were two other kinase isoforms, from the Leucine-rich repeat serine/threonine-protein kinase 1, encoded by the LRRK1 gene. There were also two proteins related to membrane transport, the Sodium/hydrogen exchanger 9B2 (SLC9B2) and two isoforms of a short transient receptor potential channel encoded by the TRPC3 gene. A smaller isoform of the POTEB member of the ankyrin family was also found. Of note, POTEB was the only protein that presented simultaneously two of the 15 domains (Ank_2 e Ank_5). Additionally, there were two proteins resultant from the readthrough of two genes, CYP3A7-CYP3A51P, which belong to a subfamily of the Cytochrome P450, and FPGT-TNNI3K, from the neighbouring fucose-1-phosphate guanylyltransferase (FPGT) and TNNI3 interacting kinase (TNNI3K) genes.

To evaluate the possibility that NAD has an impact on the interactions between these proteins, we further searched for the interactions of each of the proteins. DGKI and SLC9B2 had no reported interactions, as well as the proteins resultant from the two readthrough events. LRRK1 had the highest number of interactions, followed by TRPC3.

3.5 Number of NAD interacting residues in new and known NADBPs

The 13 identified proteins were further analysed using the NADbinder software (Table 3). Here, instead of the protein structure, the protein sequence is considered. The highest number of NAD-interacting residues was 33 and was identified in the longest isoform of TRPC3, with 793 amino acids, followed by the longest isoform of DGKI with 1078 amino acids, where 31 residues were identified. The five DAG kinase isoforms retrieved more than 20 NAD-interacting residues, as well as the two readthrough proteins. A positive correlation was observed between the amino acid length and the number of NAD-interacting residues identified.

To serve as a reference, six proteins known to be involved in NAD metabolism were additionally scanned for the number of NAD interacting residues. Namely, two enzymes that consume NAD intracellularly (PARP1 and SIRT1), two enzymes that consume NAD extracellularly (CD38 and CD73), and two enzymes that participate in NAD biosynthesis (NAMPT and NAPRT) were analysed. Among these sequences, there was no significant correlation between the number of NAD-binding residues and protein length. According to the NADbinder analysis results, CD73 had the highest number of NAD interacting residues (51), and the remaining NAD-consuming enzymes had between 37 and 43 residues, which were higher than the ones identified in the 13 previously studied proteins. NAMPT and NAPRT don’t interact directly with the NAD molecule, and presented 39 and 18 NAD interacting residues, respectively. However, they bind nicotinamide and nicotinic acid, similar molecules that are NAD precursors, and are responsible for the first steps of their conversion into NAD.

3.6 NUDIX containing proteins in NADBPs dataset

As it was previously described that NUDIX domain directly interacts with NAD, the proteins within NADBPs dataset that are NUDIX hydrolases, NUDT7 and NUDT12, were also studied. In NUDT7, 21 NAD interacting residues were identified and, in NUDT12, only six residues were detected. We also searched for their interactors, considering only experimentally validated physical interactions, and found three proteins that interact with NUDT7 and three proteins that interact with NUDT12 (Figure 4).

Figure 4: 
Protein–protein interactions of NUDIX proteins from the NAD-binding proteins dataset. (a) NUDT7 and (b) NUDT12. Queried proteins are represented by red nodes and the line thickness indicates the confidence level of the interaction. Only physical interactions are represented. The network was obtained through STRING (
Figure 4:

Protein–protein interactions of NUDIX proteins from the NAD-binding proteins dataset. (a) NUDT7 and (b) NUDT12. Queried proteins are represented by red nodes and the line thickness indicates the confidence level of the interaction. Only physical interactions are represented. The network was obtained through STRING (

3.7 Identification of NADBPS as potential new drug targets mutated in cancer

We found 122 proteins that are NAD-binding and potential drug targets. Two of them also belong to the set of cancer mutated genes, fumarate hydratase (FH) and 5′-nucleotidase, cytosolic II (NT5C2). Additionally, three other NADBPs, which mutations are implicated in cancer, were found in the catalogue of FDA approved targets, namely, 5-aminoimidazole-4-carboxamide ribonucleotide formyltransferase/IMP cyclohydrolase (ATIC), androgen receptor (AR) and isocitrate dehydrogenase 2 (IDH2).

4 Discussion

NAD binds to a large number of different proteins in order to perform a diversity of functions within the cell. In those reactions, NAD can: (1) act as an enzymatic cofactor in redox reactions, (2) be degraded by NAD-dependent enzymes, and (3) mediate protein-protein interactions, therefore regulating several cellular processes. Our approach in this study to identify potential NAD-binding proteins, drove us to a global analysis of the NAD interactome. We integrated data from various sources to include a large dataset of proteins that were already known to interact with the NAD molecule, or that were in some way related to NAD functions. We functionally characterized the protein datasets through gene ontology and protein structural domains analysis.

Through the analyses of enriched pathways, based on gene ontology annotations, we found that NADBPs are involved in a diversity of cellular pathways. The comparison with the NAD-related or the NAD-PPIs datasets emphasised that NADBPs are central in basic metabolism and biosynthetic processes. Nonetheless, essential metabolic pathways, such as glycolysis and TCA cycle, and signalling pathways mediated by GABA or dopamine receptors, were found in all datasets. Conversely, the proteins that participate in NAD-PPIs are involved in signalling pathways, from development and apoptosis to general immune and hormone responses, and including many disease pathways, showing the extension of the action of this small molecule.

Analysis of the protein structural domains showed that the ankyrin repeats were the most frequent, with some proteins presenting more than one ankyrin repeat in their structures. The ankyrin domain is very frequent in all human proteome as it mediates protein-protein interactions [22] and regulates the function of other proteins [23]. Confirming their high frequency, in the unreviewed dataset here obtained from the full human proteome, based on the UniProt database, 448 proteins have at least one of the five ankyrin repeats.

Adding to protein structural domains, the number of NAD interacting residues was considered, given that the direct binding of NAD at specific sites of a protein ultimately determines its action [17]. NAD binding to the NUDIX homology domain of DBC1 regulates its action on PARP1, by preventing the interaction between the two proteins [5]. In this study, no more than 10 residues were identified within the NUDIX domain that are conserved across several species. Considering the presence of a specific domain with a folding favourable to an interaction with a small molecule, only a small number of residues might be responsible for the actual interaction. The identification of NAD interacting residues within the sequence of known NADBPs, revealed that, while some NAD consuming enzymes had around 40 residues, the two NUDIX-containing domain proteins had lower numbers (21 and 6).

The role of the NAD-capped RNA hydrolase NUDT12 is directly associated with NAD, also known as deNADding enzyme, and it interacts with Bleomycin Hydrolase (BLMH) through the ankyrin repeats of NUDT12 [24]. The known role of the peptidase BLMH is to cleave the anti-cancer peptide Bleomycin, reducing the intracellular levels of the drug, but its primary biological function remains unknown.

Among the new proteins that might potentially bind NAD identified in our study, TRPC3 (UniProt ID J3QTB0) had the ankyrin repeat domain and had the highest number of NAD-interacting residues. The molecular docking performed revealed a potential NAD-binding location on TRPC3. From a total of 31 clusters of docking positions obtained, 26 were placed within a same location, including the ones with the best scoring and lowest estimated energy (Figure 5).

Figure 5: 
Docking results for NAD ligand on TRPC3 as a target (D6RC49 and J3QTB0). Protein 3D structures were obtained from AlphaFold ( and visualized using Pymol software.
Figure 5:

Docking results for NAD ligand on TRPC3 as a target (D6RC49 and J3QTB0). Protein 3D structures were obtained from AlphaFold ( and visualized using Pymol software.

The corresponding reviewed protein (UniProt ID: Q13507) of TRPC3 is longer than the two isoforms detected here, with 836 amino acids. Its known interactions were found to be mostly involved in signal transduction, response to stress, anatomical structure development, and transport processes, many of them related to calcium transport and signalling, such as the inositol trisphosphate (IP3) receptors ITPR1 and ITPR3, and the Sodium/calcium exchanger SLC8A1.

TRPC3 is a member of the transient receptor potential (TRP) channels family, which regulates intracellular calcium concentration [25] and is directly activated by lipids, specifically diacylglycerol (DAG). Together with IP3, DAG is a product of the hydrolysis of a phospholipid catalysed by the phospholipase C (PLC) enzymes. PLC gamma enzymes are key components of intracellular signalling, and some PLCG1 functions have been associated to a specific protein domain that directly interacts with TRPC3 and PLCG1, regulating calcium entry [26]. Very recently, the role of PLC gamma enzymes in disease development has been explored [27]. Of note, PLCG1 was also found in our dataset of NAD-PPIs, showing that it already binds other NADBPs, and several unreviewed isoforms of DAG kinases were identified in this study as potential NADBPs.

Both NAD-dependent signalling and calcium-dependent signalling are essential in the cell and therefore their dysregulation is often associated with disease. In particular, the role of NAD as a regulator of calcium channels has been recently reviewed, due to its impact on cancer treatment research [28], where calcium channels emerge as potential targets for anticancer therapy. In addition to cancer, the TRP channels, namely the TRPC3 group, regulate functions in neurons and are involved in various neurological and psychiatric disorders [29].

Interestingly, only one ion channel was identified in the primary NADBPs dataset in our study, named Transient receptor potential cation channel subfamily M member 2 (TRPM2). Although it was not identified in the domain analysis through Pfam, the presence of NUDIX domains in the structure of TRPM2 has been described in the literature and associated to its conformational changes and gating functions [30]. The activation of TRPM2 by NAD has been documented for over two decades and is one example of the relation between NAD and calcium metabolism [31].

In a final step of this research, we decided to investigate whether some of the NADBPs were potential therapeutic drug targets. We found FH and NT5C2, which are directly involved in NAD related reactions: the former participates in the TCA cycle and the latter in the NAD synthesis, specifically by catalysing the hydrolysis of NMN into NR or NAMN into NAR. Both enzymes are altered in cancer and are also associated with neurological diseases [3234]. In addition, from the NADBPs dataset ATIC, AR and IDH2 are already being used as therapeutic targets. ATIC participates in purine biosynthesis, where it catalyses the last two steps of the pathway [35]. IDH2 is the mitochondrial isoform of the isocitrate dehydrogenases family of enzymes, that depends on NADP and calcium binding to perform the oxidative decarboxylation of isocitrate, one of the steps of the TCA cycle. Therefore, alterations in these enzymes will have an important impact in metabolism. IDH1 and IDH2 mutations have been described in different types of cancer, including glioblastoma, and are being targeted for acute myeloid leukaemia [36, 37]. The androgen receptor act as a transcription factor and, when activated by the hormone androgen, binds to target genes, and directly regulates gene transcription of a high number of genes. SIRT1, an NAD-dependent deacetylase, regulates AR activity, linking NAD metabolism to ligand-induced hormone signalling [38]. Aberrant expression of AR contributes to the progression of prostate cancer, making this protein a recognized therapeutic target in this context [39]. Alterations in AR have also been associated to neurological diseases, from developmental deficiencies to neurodegenerative disorders [40].

5 Conclusions

Concluding, this global study of the NAD interactome resulted in the identification of new potentially NAD-binding proteins, including TRPC3 and a few isoforms of DGA kinases, which are involved in calcium signalling. NADBPs participate in several metabolic pathways and signalling processes in the cell, while proteins interacting with NADPBs (NAD-PPIs) are mostly involved in signalling pathways. Furthermore, we identified NADBPs that are known (ATIC, AR and IDH2),as well as potential new drug targets in cancer (FH and NT5C2).

Corresponding author: Sara Duarte-Pereira, IEETA/DETI, University of Aveiro, Aveiro, Portugal; and Department of Medical Sciences, iBiMED – Institute of Biomedicine, University of Aveiro, Aveiro, Portugal, E-mail:

Award Identifier / Grant number: CEECINST/00137/2018/CP1520/CT0012

Award Identifier / Grant number: SFRH-BD-108890-2015

Award Identifier / Grant number: UIDB/00127/2020

Award Identifier / Grant number: UIDB/04279/2020

Award Identifier / Grant number: UIDB/04501/2020 (PO-CI-01-0145-FEDER-007628)

  1. Author contribution: All authors have accepted responsibility for the entire content of this manuscript and approved its submission.

  2. Research funding: This work was supported by FEDER (Programa Operacional Factores de Competi-tividade – COMPETE) and by FCT (Fundação para a Ciência e Tecnologia), within the grant SFRH-BD-108890-2015 to SDP, and the projects UIDB/04501/2020 (PO-CI-01-0145-FEDER-007628) to iBiMED, UIDB/00127/2020 to IEETA and UIDB/04279/2020 to CIIS. FCT/MCTES and UCP support CEEC institutional funding of RMS (CEECINST/00137/2018/CP1520/CT0012).

  3. Conflict of interest statement: Authors state no conflict of interest.

Appendix A: List of the proteins that compose the NAD-binding proteins (NADBPs) dataset

UniProt ID Gene name Length UniProt ID Gene name Length
Q8NSZO AADAT 425 P30838 ALDH3A1 453
Q4L235 AASDH 1098 P51648 ALDH3A2 485
Q9NRN7 AASDHPPT 309 P43353 ALDH3B1 468
Q9UDR5 AASS 926 P48448 ALDH3B2 385
P80404 ABAT 500 P30038 ALDH4A1 563
P33897 ABCD1 745 P51649 ALDHSA1 535
P09110 ACAA1 424 Q02252 ALDH6A1 535
P42765 ACAA2 397 P49419 ALDH7A1 539
Q9UKU7 ACAD8 415 Q9H2A2 ALDH8A1 487
P28330 ACADL 430 P49189 ALDH9A1 494
P11310 ACADM 421 P04075 ALDOA 364
P16219 ACADS 412 P05062 ALDOB 364
P45954 ACADSB 432 P09972 ALDOC 364
P24752 ACAT1 427 Q96NU7 AMDHD1 426
Q9BWD1 ACAT2 397 P48728 AMT 403
Q8TDX5 ACMSD 336 P19801 AOC1 751
P21399 ACO1 889 O75106 AOC2 756
Q99798 ACO2 780 Q16853 AOC3 763
O14734 ACOT8 319 Q06278 AOX1 1338
P33121 ACSL1 698 P10275 AR 920
Q9NUB1 ACSS1 689 P62330 ARF6 175
Q9NR19 ACSS2 701 P15848 ARSB 533
Q08828 ADCY1 1119 P51689 ARSD 593
Q08462 ADCY2 1091 P54793 ARSF 590
O60266 ADCY3 1144 QSFYA8 ARSH 562
O95622 ADCY5 1261 QSFYBO ARS3 599
O43306 ADCY6 1168 Q6UVVY0 ARSK 536
P51828 ADCY7 1080 P51690 ARSL 589
P40145 ADCY8 1251 P52961 ART1 327
O60503 ADCY9 1353 Q13508 ARTS 389
P07327 ADH1A 375 Q93070 ART4 314
P00325 ADH1B 375 Q96L15 ARTS 291
P00326 ADH1C 375 A6ND91 ASPDH 283
P08319 ADH4 380 P31939 ATIC 592
P11766 ADHS 374 O75936 BBOX1 387
P28332 ADH6 368 P54687 BCAT1 386
P40394 ADH7 386 O15382 BCAT2 392
Q63HM1 AFMID 303 P12694 BCKDHA 445
P23526 AHCY 432 P21953 BCKDHB 392
O43865 AHCYL1 530 Q02338 BDH1 343
Q96HN2 AHCYL2 611 Q9BUT1 BDH2 245
O95831 AIFM1 613 Q93088 BHMT 406
P14550 AKR1A1 325 P53004 BLVRA 296
P15121 AKR1B1 316 P30043 BLVRB 206
O60218 AKR1B10 316 Q10588 BST1 318
Q04828 AKR1C1 323 Q13137 CALC00O2 446
P52895 AKR1C2 323 P04040 CAT 527
P42330 AKR1C3 323 Q8N4T8 CBR4 237
P17516 AKR1C4 323 P28907 CD38 300
P51857 AKR1D1 326 Q16878 CD01 200
P00352 ALDH1A1 501 P28329 CHAT 748
O94788 ALDH1A2 518 Q8NE62 CHDH 594
P47895 ALDH1A3 512 P21964 COMT 271
P30837 ALDH1B1 517 P43155 CRAT 626
Q3SY69 ALDH1L2 923 Q9UKG9 CROT 612
P05091 ALDH2 517 Q9Y2S2 CRYL1 319
O75390 CS 466 PO4406 GAPDH 335
Q9Y600 CSAD 493 O14556 GAPDHS 408
Q13363 CTBP1 440 O75600 GCAT 419
P56545 CTBP2 445 Q92947 GCDH 438
P32929 CTH 405 P23434 GCSH 173
P00167 CYBSA 134 Q9Y2T3 GDA 454
Q9UHQ9 CYBSR1 305 Q13630 GFUS 321
Q6BCY4 CYBSR2 276 P23378 GLDC 1020
P00387 CYB5R3 301 P00367 GLUD1 558
Q7L1T6 CYBSR4 521 P49448 GLUD2 558
Q6IPT4 CYBSRL 315 O60547 GMDS 372
Q53TN4 CYBRD1 286 P49915 GMPS 693
P08574 CYC1 325 P17174 GOT1 413
P99999 CYCS 105 Q8NHS2 GOT1L1 421
P05093 CYP17A1 508 P00505 GOT2 430
Q02318 CYP27A1 531 Q9HCL2 GPAM 828
P05181 CYP2E1 493 Q6NUI2 GPAT2 795
Q6VVX0 CYP2R1 501 Q86UL3 GPAT4 456
Q9NYLS CYP39A1 469 P21695 GPD1 349
Q02928 CYP4A11 519 Q8N335 GPD1L 351
QSTCH4 CYP4A22 519 P43304 GPD2 727
P22680 CYP7A1 504 Q9UBQ7 GRHPR 328
O75881 CYP7B1 506 P00390 GSR 522
Q9UNU6 CYP8B1 501 H3C1
P11182 DBT 482 H3C2
Q16698 DECR1 335 H3C3
O15121 DEGS1 323 H3C4
Q9UBM7 DHCR7 475 H3C6
P00374 DHFR 187 P68431 H3C7 136
Q86XFO DHFR2 187 H3C8
P49366 DHPS 369 H3C10
Q96HY7 DHTKD1 919 H3C11
P10515 DLAT 647 H3C12
P09622 DLD 509 O95479 H6PD 791
P36957 DLST 453 Q9U383 HACL1 578
Q9NRD9 DUOX1 1551 Q16836 HADH 314
Q9NRD8 DUOX2 1548 P40939 HADHA 763
P30084 ECHS1 290 P55084 HADHB 474
P42126 ECI1 302 P42357 HAL 657
Q08426 EHHADH 723 P31937 HIBADH 336
Q9NXB9 ELOVL2 296 P35914 HMGCL 325
Q9NYP7 ELOVLS 299 PO4035 HMGCR 888
Q8TC92 ENOX1 643 P09601 HMOX1 288
Q16206 ENOX2 610 P30519 HMOX2 316
P22413 ENPP1 925 P15428 HPGD 266
O14638 ENPP3 875 P28845 HSD11B1 292
O95864 FADS2 444 P80365 HSD11B2 405
Q8WVX9 FAR1 515 P14061 HSD17B1 328
Q96K12 FAR2 515 Q99714 HSD17B10 261
Q96IV6 FAXDC2 333 Q8NBQS HSD17B11 300
P37268 FDFT1 417 Q53GQ0 HSD17B12 312
P07954 FH 510 Q9BPX1 HSD17B14 270
P98177 FOX04 505 P37059 HSD17B2 387
Q6ZNAS FRRS1 592 P37058 HSD17B3 310
Q14376 GALE 348 P51659 HSD17B4 736
P07902 GALT 379 O14756 HSD17B6 317
P56937 HSD17B7 341 O15239 NDUFA1 70
Q92506 HSD17B8 261 O95299 NDUFA10 355
P14060 HSD3B1 373 Q86Y39 NDUFA11 141
P26439 HSD3B2 372 Q9UI09 NDUFAl2 145
Q9H2F3 HSD3B7 369 Q9P0J0 NDUFA13 144
P48735 IDH2 452 O43678 NDUFA2 99
P50213 IDH3A 366 O95167 NDUFA3 84
O43837 IDH3B 385 O00483 NDUFA4 81
P51553 IDH3G 393 Q9NRX3 NDUFA4L2 87
P20839 IMPDH1 514 Q16718 NDUFAS 116
P12268 IMPDH2 514 P56556 NDUFA6 128
Q9NPH2 ISYNA1 558 O95182 NDUFA7 113
O15229 KMO 486 P51970 NDUFA8 172
Q16719 KYNU 465 Q16795 NDUFA9 377
Q9H9P8 L2HGDH 463 O14561 NDUFAB1 156
P00338 LDHA 332 O75438 NDUFB1 58
Q6ZMR3 LDHAL6A 332 O96000 NDUFB10 172
Q9BYZ2 LDHAL6B 381 Q9NX14 NDUFB11 153
P07195 LDHB 334 O95178 NDUFB2 105
P07864 LDHC 332 O43676 NDUFB3 98
Q86WU2 LDHD 507 O95168 NDUFB4 129
O00214 LGALS8 317 O43674 NDUFB5 189
P01229 LHB 141 O95139 NDUFB6 128
P18858 LIG1 919 P17568 NDUFB7 137
P49916 LIG3 1009 O95169 NDUFB8 186
P49917 LIG4 911 Q9Y6M9 NDUFB9 179
P21397 MAOA 527 O43677 NDUFC1 76
P27338 MAOB 520 O95298 NDUFC2 119
P40925 MDH1 334 P28331 NDUFS1 727
P40926 MDH2 338 O75306 NDUFS2 463
P48163 ME1 572 O75489 NDUFS3 264
P23368 ME2 584 O43181 NDUFS4 175
Q16798 ME3 604 O43920 NDUFSS 106
Q15800 MSMO1 293 O75380 NDUFS6 124
P00156 MT- CYB 380 O75251 NDUFS7 213
P11586 MTHFD1 935 O00217 NDUFS8 210
P13995 MTHFD2 350 P49821 NDUFV1 464
Q9H903 MTHFD2L 347 P19404 NDUFV2 249
P42898 MTHFR 656 P56181 NDUFV3 108
P49914 MTHFS 203 Q9HAN9 NMNAT1 279
Q13613 MTMR1 665 Q9BZQ4 NMNAT2 307
Q13614 MTMR2 643 Q96T66 NMNAT3 252
Q9Y217 MTMR6 621 Q9NWW6 NMRK1 199
Q9Y216 MTMR7 660 Q9NPI5 NMRK2 230
P03886 MT-ND1 318 P40261 NNMT 264
P03891 MT-ND2 347 Q13423 NNT 1086
P03897 MT-ND3 115 P15559 NQO1 274
P03905 MT-ND4 459 P16083 NQO2 231
P03901 MT-ND4L 98 Q15738 NSDHL 373
P03915 MT-NDS 603 P49902 NTSC2 561
P03923 MT-ND6 174 Q9BQG2 NUDT12 462
Q99707 MTR 1265 P00O24 NUDT7 238
O95544 NADK 446 Q6D104 NXN 435
Q4GON4 NADK2 442 Q04671 OCA2 838
Q6IA69 NADSYN1 706 Q02218 OGDH 1023
P43490 NAMPT 491 Q9ULDO OGDHL 1010
Q6XQN6 NAPRT 538 P55809 OXCT1 520
Q53GL7 PARP10 1025 Q9NRC8 SIRT7 400
Q9NR21 PARP11 338 P53007 SLC25A1 311
Q9HOJ9 PARP12 701 Q9UBX3 SLC25A10 287
Q460N5 PARP14 1801 Q02978 SLC25A11 314
Q460N3 PARP15 678 Q9BQT8 SLC25A21 299
Q8N5Y8 PARP16 322 O14975 SLC27A2 620
Q9UGNS PARP2 583 Q9Y2P5 SLC27A5 690
Q9Y6F1 PARP3 533 Q9NTN3 SLC35D1 355
Q9U10C3 PARP4 1724 Q8N808 SLC35G3 338
Q2NL67 PARP6 630 Q9Y6L6 SLCO1B1 691
Q8N3A8 PARP8 854 Q9NPDS SLCO1B3 702
Q8IXQ6 PARP9 854 P84022 SMAD3 425
P11498 PC 1178 Q13485 SMAD4 552
P61457 PCBD1 104 Q00796 SORD 357
P05165 PCCA 728 Q8NFT2 STEAP2 490
P05166 PCCB 539 Q658P3 STEAP3 488
P35558 Pau 622 Q687X5 STEAP4 459
P08559 PDHA1 390 P08842 STS 583
P29803 PDHA2 388 Q9P2R7 SUCLA2 463
P11177 PDHB 359 P53597 SUCLG1 346
O00330 PDHX 501 Q96I99 SUCLG2 432
P00558 PGK1 417 Q8NBK3 SUMF1 374
P07205 PGK2 417 P17735 TAT 454
O43175 PHGDH 533 O15178 TBXT 435
Q9NRX4 PHPT1 125 O95455 TGDS 350
P00491 PNP 289 O95271 TNKS 1327
P01189 POMC 267 Q9H2K2 TNKS2 1166
O43272 PRODH 600 P60174 TPI1 249
Q9Y617 PSAT1 370 P51580 TPMT 245
Q14914 PTGR1 329 O94759 TRPM2 1503
Q8N8N7 PTGR2 351 Q86TN4 TRPT1 253
Q8TE99 PXYLP1 480 P14679 TYR 529
P32322 PYCR1 319 P17643 TYRP1 537
Q96C36 PYCR2 320 O60701 UGDH 494
Q53H96 PYCR3 274 Q16851 UGP2 508
P09417 QDPR 244 Q9UDW1 UQCR10 63
Q15274 QPRT 297 P14927 UQCRB 111
P11233 RALA 206 P31930 UQCRC1 480
Q8IZVS RDH10 341 P22695 UQCRC2 453
O75452 RDH16 317 P47985 UQCRFS1 274
Q92781 RDHS 318 P07919 UQCRFI 91
Q6NUM9 RETSAT 610 O14949 UQCRQ 82
P12271 RLBP1 317 Q96N76 UROC1 676
Q16518 RPE65 533 Q8NBZ7 UXS1 420
O75845 SCSD 299 P47989 XDH 1333
P22307 SCP2 547
Q8N3Y7 SDR16C5 309
P34896 SHMT1 483
P34897 SHMT2 504
Q96EB6 SIRT1 747
Q81)06 SIRT2 389
Q9NTG7 SIRT3 399
Q9Y6E7 SIRT4 314


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Received: 2022-10-23
Revised: 2023-01-28
Accepted: 2023-02-08
Published Online: 2023-03-07

© 2023 the author(s), published by De Gruyter, Berlin/Boston

This work is licensed under the Creative Commons Attribution 4.0 International License.

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