Proteomics comparison of aspartic protease enzyme in...

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69 http://journals.tubitak.gov.tr/biology/ Turkish Journal of Biology Turk J Biol (2016) 40: 69-83 © TÜBİTAK doi:10.3906/biy-1412-88 Proteomics comparison of aspartic protease enzyme in insects Samin SEDDIGH 1, *, Maryam DARABI 2 1 Department of Plant Protection, Varamin-Pishva Branch, Islamic Azad University, Varamin, Iran 2 Department of Agronomy and Plant Breeding Sciences, College of Aboureihan, University of Tehran, Tehran, Iran * Correspondence: [email protected] 1. Introduction Proteases (peptidases or proteinases) are a large category of enzymes that catalyze the hydrolysis of peptide bonds. Proteases that cleave peptide bonds within the polypeptide chain are classified as endopeptidases, and those that cleave peptide bonds at the N or C termini of polypeptide chains are known as exopeptidases (López-Otín and Bond, 2008). us, the term “protease” includes both “endopeptidases” and “exopeptidases”, while the term “proteinase” is used to describe only “endopeptidases” (Ryan, 1990). Proteases are present in all organisms and are involved in various physiological processes, including the production of nutrients for cell growth and proliferation (Lin et al., 2011), for protein degradation (Ciechanover, 2005), and as regulatory components for diverse physiological functions (Ehrmann and Clausen, 2004; Oikonomopoulou et al., 2006). Proteases include aspartic, cysteine, glutamic, serine, and threonine proteases, depending on the amino acids present in the active site, or the metalloproteases, if a metal ion is required for catalytic activity (Alagarsamy et al., 2006). Microbial-sourced proteases are invaluable commercial enzymes and account for approximately 60% of the total worldwide sales of industrial enzymes (Rao et al., 1998). ey are used in food, detergents, and pharmaceutical and biotechnology industries (Najafi et al., 2005; López-Otín and Bond, 2008; Yegin et al., 2011; Sabotič and Kos, 2012; Zhao et al., 2013). Aspartic proteases (APs; EC: 3.4.23), commonly known as acidic proteases, are one of the major catalytic classes of proteases, which are widely distributed not only in plants but also among vertebrates, yeasts, nematode parasites, fungi, and viruses (Davies, 1990; Rawlings and Barrett, 1995). ey are also found in insects; for instance, in larval Cyclorrhapha several digestive aspartic peptidases were reported, such as in Musca domestica (Greenberg and Paretsky, 1955), Stomoxys calcitrans (Lambremont et al., 1959), Calliphora vomitoria (Fraser et al., 1961), M. domestica and Sarcophaga ruficornis (Sinha, 1975), and C. vicina (Pendola and Greenberg, 1975). In M. domestica, it was proposed that the midgut aspartic peptidase is a cathepsin D-like enzyme (Lemos and Terra, 1991). Other insects have digestive aspartic peptidases in their guts, including some species of Hemiptera (Houseman and Downe, 1983; Knop Wright et al., 2006) and Coleoptera (ie and Houseman, 1990; Wolfson and Murdock, 1990; Silva and Xavier-Filho, 1991). In the species of six families Abstract: Aspartic proteases (APs; EC: 3.4.23) are a catalytic type of protease enzymes that use an activated water molecule, bound to one or more aspartate residues, for catalysis of their peptide substrates. In this study, bioinformatic analyses of APs enzymes were performed on insect protein sequences, including nineteen species of eleven different families. According to the conserved motifs obtained with MEME and MAST tools, three motifs were common to all insects. e structural and functional analyses of five selected insects from different orders were performed with ProtParam, SOPMA, SignalP 4.1, TMHMM 2.0, and ProDom tools in the ExPASy database. e tertiary structure of Apis mellifera as a sample of insects was predicted by the Phyre2 server using the “1qdm” model (PDB accession code: 1qdm) and was compared with Swiss-Model. e 3D structure quality was verified by the PROCHECK server. MegAlign was used for protein sequence alignment, and a phylogenetic tree was constructed with MEGA 6.06 soſtware using the neighbor-joining method. In protein–protein interaction analysis with STRING 9.1, zero and twenty-seven significant protein interaction groups were identified in A. mellifera and other species, respectively. e obtained data provide a background for bioinformatic studies of the function and evolution of other insects and organisms. Key words: Aspartic protease, bioinformatics, insects, phylogenetic analysis, protein–protein interaction, structural analysis, tertiary structure Received: 25.12.2014 Accepted/Published Online: 27.04.2015 Final Version: 05.01.2016 Research Article

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http://journals.tubitak.gov.tr/biology/

Turkish Journal of Biology Turk J Biol(2016) 40: 69-83© TÜBİTAKdoi:10.3906/biy-1412-88

Proteomics comparison of aspartic protease enzyme in insects

Samin SEDDIGH1,*, Maryam DARABI2

1Department of Plant Protection, Varamin-Pishva Branch, Islamic Azad University, Varamin, Iran2Department of Agronomy and Plant Breeding Sciences, College of Aboureihan, University of Tehran, Tehran, Iran

* Correspondence: [email protected]

1. IntroductionProteases (peptidases or proteinases) are a large category of enzymes that catalyze the hydrolysis of peptide bonds. Proteases that cleave peptide bonds within the polypeptide chain are classified as endopeptidases, and those that cleave peptide bonds at the N or C termini of polypeptide chains are known as exopeptidases (López-Otín and Bond, 2008). Thus, the term “protease” includes both “endopeptidases” and “exopeptidases”, while the term “proteinase” is used to describe only “endopeptidases” (Ryan, 1990). Proteases are present in all organisms and are involved in various physiological processes, including the production of nutrients for cell growth and proliferation (Lin et al., 2011), for protein degradation (Ciechanover, 2005), and as regulatory components for diverse physiological functions (Ehrmann and Clausen, 2004; Oikonomopoulou et al., 2006). Proteases include aspartic, cysteine, glutamic, serine, and threonine proteases, depending on the amino acids present in the active site, or the metalloproteases, if a metal ion is required for catalytic activity (Alagarsamy et al., 2006). Microbial-sourced proteases are invaluable commercial enzymes and account for approximately 60% of the total worldwide sales of industrial enzymes

(Rao et al., 1998). They are used in food, detergents, and pharmaceutical and biotechnology industries (Najafi et al., 2005; López-Otín and Bond, 2008; Yegin et al., 2011; Sabotič and Kos, 2012; Zhao et al., 2013).

Aspartic proteases (APs; EC: 3.4.23), commonly known as acidic proteases, are one of the major catalytic classes of proteases, which are widely distributed not only in plants but also among vertebrates, yeasts, nematode parasites, fungi, and viruses (Davies, 1990; Rawlings and Barrett, 1995). They are also found in insects; for instance, in larval Cyclorrhapha several digestive aspartic peptidases were reported, such as in Musca domestica (Greenberg and Paretsky, 1955), Stomoxys calcitrans (Lambremont et al., 1959), Calliphora vomitoria (Fraser et al., 1961), M. domestica and Sarcophaga ruficornis (Sinha, 1975), and C. vicina (Pendola and Greenberg, 1975). In M. domestica, it was proposed that the midgut aspartic peptidase is a cathepsin D-like enzyme (Lemos and Terra, 1991). Other insects have digestive aspartic peptidases in their guts, including some species of Hemiptera (Houseman and Downe, 1983; Knop Wright et al., 2006) and Coleoptera (Thie and Houseman, 1990; Wolfson and Murdock, 1990; Silva and Xavier-Filho, 1991). In the species of six families

Abstract: Aspartic proteases (APs; EC: 3.4.23) are a catalytic type of protease enzymes that use an activated water molecule, bound to one or more aspartate residues, for catalysis of their peptide substrates. In this study, bioinformatic analyses of APs enzymes were performed on insect protein sequences, including nineteen species of eleven different families. According to the conserved motifs obtained with MEME and MAST tools, three motifs were common to all insects. The structural and functional analyses of five selected insects from different orders were performed with ProtParam, SOPMA, SignalP 4.1, TMHMM 2.0, and ProDom tools in the ExPASy database. The tertiary structure of Apis mellifera as a sample of insects was predicted by the Phyre2 server using the “1qdm” model (PDB accession code: 1qdm) and was compared with Swiss-Model. The 3D structure quality was verified by the PROCHECK server. MegAlign was used for protein sequence alignment, and a phylogenetic tree was constructed with MEGA 6.06 software using the neighbor-joining method. In protein–protein interaction analysis with STRING 9.1, zero and twenty-seven significant protein interaction groups were identified in A. mellifera and other species, respectively. The obtained data provide a background for bioinformatic studies of the function and evolution of other insects and organisms.

Key words: Aspartic protease, bioinformatics, insects, phylogenetic analysis, protein–protein interaction, structural analysis, tertiary structure

Received: 25.12.2014 Accepted/Published Online: 27.04.2015 Final Version: 05.01.2016

Research Article

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of the order Hemiptera, APs (cathepsin D-like proteinases) were found along with cysteine proteinases (Houseman and Downe, 1983). It has been found that the temporal activity profile of an AP is associated with fat body histolysis during the early metamorphosis of Ceratitis capitata (Rabossi et al., 2004). A lysosomal AP from Aedes aegypti has been purified and characterized (Cho et al., 1991). Two AP-encoding complementary deoxyribonucleic acids were characterized from the small intestine (posterior midgut) of Triatoma infestans (Balczun et al., 2012). AP was also cloned from Chilo suppressalis (Walker) with the PCR method, and its sequence characteristics and variations in the Chinese populations were analyzed (Li et al., 2014). Two aspartic proteases were found in the fecal fluid of the leaf-cutting ant Acromyrmex echinatior (Kooij et al., 2014).

AP activity has also been detected in recombinant proteins of bacterial origin (Hill and Phylip, 1997). They are known to play a crucial role in a wide range of biological functions (Zhao et al., 2013); however, they have received considerable attention because of their significant role in human diseases (Umezawa et al., 1970). APs are a catalytic type of protease enzymes on which comprehensive reviews have been published (Fruton, 1971; Tang, 1979). They are endopeptidases that depend on aspartic acid residues for their catalytic activity. The active site of AP residue is located within the motif Asp-Xaa-Gly, in which Xaa can be Ser or Thr (Blundell et al., 1991; Sielecki et al., 1991).

APs use an activated water molecule, bound to one or more aspartate residues, for catalysis of their peptide substrates (Baldwin et al., 1993) (Figure 1). APs contain certain important enzymes such as pepsin, chymosin, renin, cathepsin D, and proteases isolated from different fungi. These enzymes are homologous entirely in terms of amino acid sequences, particularly around the active site residues (Fruton, 1971; Tang, 1979; Fruton, 1987). According to the MEROPS (http://merops.sanger.ac.uk/) database, created by Rawlings and Barrett (1999), APs are grouped into 16 different families on the basis of their amino acid sequence homology, which in turn are assembled into six different clans based on their evolutionary relationship and tertiary structure (Rawlings and Barrett, 1995). MEROPS contains a full listing of all sequences related to the AP family.

Most APs show maximal activity at a low pH (pH 3–4) and have isoelectric points in the range of pH 3–4.5. Their molecular masses are in the range of 30–45 kDa (Blundell

et al., 1991; Sielecki et al., 1991). The low pH of midguts of many members of Coleoptera and Hemiptera provides more favorable environments for APs (pH optimum ~3–5) than the high pH of most insect guts (pH optimum ~8–11) (Houseman et al., 1987), where the aspartic and cysteine proteinases would not be active. Several insect species have comparable pH optima for AP: for example, 3.5 in Rhodnius prolixus (Terra et al., 1988), 4.5 in Leptinotarsa decemlineata (Thie and Houseman, 1990), 3.3 in Callosobruchus maculates (Silva and Xavier-Filho, 1991), 3.0 in A. aegypti (Cho et al., 1991), 3.0–3.5 in larval M. domestica (Lemos and Terra, 1991), 4.0 in Parasarcophaga surcoufi (Dorrah et al., 2000), and 4.0 in Crenotiades dilutes and Parasarcophaga hertipes (Colebatch et al., 2001; Elmelegi et al., 2006).

The effect of some peptidase inhibitors on the activity of APs is important in plant protection. Inhibition of aspartic peptidases by thiol compounds has been reported previously in other insects such as R. prolixus (Houseman and Downe, 1982), P. hertipes (Barrett, 1977), and L. decemlineata (Thie and Houseman, 1990). Inhibition assays indicated that cysteine, aspartyl (cathepsin D), serine (trypsin, chymotrypsin-like) proteases, and metalloproteases act in cereal leaf beetle digestion (Wielkopolan et al., 2015). The trypsin inhibitors present in soybean were subsequently shown to be toxic to the larvae of the flour beetle Tribolium confusum (Lipke et al., 1954).

Bioinformatics plays a fundamental role in the analysis and interpretation of genomic and proteomic data. It uses methods and technologies from mathematics, statistics, computer sciences, physics, biology, and medicine (Romano et al., 2011). In this study, we applied bioinformatics analysis to this gene for elucidation of structural, functional, and phylogenetic relationships in insects. Analyses of multiple alignment, molecular mass, isoelectric point, signal peptide, motifs, transmembrane domain, secondary and spatial structure, and evolution were performed to provide an understanding of the evolutionary mechanisms of the AP protein family.

2. Materials and methods2.1. Aspartic proteases sequence retrievalThe AP protein reference sequences (RefSeq) belonging to different insect species were downloaded from the National Center for Biotechnology Information (NCBI) (http://www.ncbi.nlm.nih.gov; date received: October 2014) in FASTA format. Due to the large number of sequences available for AP, it was not feasible to analyze all the sequences. Thus, total data consisted of 19 insect species, which are listed in Table 1 with their accession numbers. One species from each order of insects (Coleoptera, Diptera, Hymenoptera, Lepidoptera, and Phthiraptera) was selected as the representative of that order for structural analysis.Figure 1. Aspartic protease mechanism.

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2.2. Multiple alignment and conserved motif analysisThere are many tools for defining the existence or absence of noticeable domains; however, they are unable to recognize smaller individual motifs and more divergent patterns. Accordingly, the motifs of protein sequences were created using the Multiple Em for Motif Elicitation program (MEME; version 4.9.1) and Motif Alignment and Search Tool (MAST; version 4.9.1), available at http://meme.nbcr.net/meme (Bailey et al., 2009), to study the variation of AP protein in insects. The program was set to report the 10 most robust motifs of 7–30 amino acids, occurring zero times or once per sequence, among the proteins belonging to the APs of nineteen insect species. MegAlign from the DNASTAR package (version 12.1) was used for multiple alignment analysis of APs. Sequences were aligned using ClustalW method with default parameters.2.3. Structural and functional analysisSeveral online web services and software programs were used for the analysis of AP in insects. Comparative and bioinformatics analyses were carried out online on the EXPASY website (http://expasy.org/tools). Molecular

weight, isoelectric points, and secondary structures of AP proteins were estimated using Compute pI/Mw (http://web.expasy.org/compute_pi/) (Bjellqvist et al., 1993, 1994; Gasteiger et al., 2005) and SOPMA (http://npsa-pbil.ibcp.fr/cgi-bin/npsa_automat.pl?page=npsa_sopma.html) (Geourjon and Deleage, 1995) in each representative species. The presence and location of signal peptide cleavage sites in AP sequences were predicted by the SignalP 4.1 server (Petersen et al., 2011). TMHMM (http://www.cbs.dtu.dk/services/TMHMM-2.0/) (Moller et al., 2001) and ProDom (http://prodom.prabi.fr/prodom/current/html/form.php) (Servant et al., 2002) were used to identify transmembrane helices and functional domains in AP protein, respectively.2.4. Tertiary structure prediction and evaluation of the modelThe tertiary structure prediction and visualization of AP were performed with the Protein Homology/analogY Recognition Engine V2.0 (PHYRE2) server (http://www.sbg.bio.ic.ac.uk/phyre2/html/page.cgi?id=index) (Kelley and Sternberg, 2009) and compared with Swiss-Model predictions (Biasini et al., 2014).

Table 1. The nineteen insect species analyzed in the current study.

Index Scientific name Abbreviation Family Accession number

1 Apis dorsata Ad-AP Apidae XP_006607509

2 Apis florea Af-AP Apidae XP_003693293

3 Apis mellifera Am-AP Apidae XP_392857

4 Bombus impatiens Bi-AP Apidae XP_003489428

5 Bombyx mori Bm-AP Bombycidae NP_001037351

6 Bombus terrestris Bt-AP Apidae XP_003403066

7 Ceratitis capitata Cc-AP Tephritidae XP_004531541

8 Culex quinquefasciatus Cq-AP Culicidae XP_001867326

9 Drosophila ananassae Da-AP Drosophilidae XP_001955129

10 Drosophila persimilis Dpe-AP Drosophilidae XP_002013092

11 Drosophila pseudoobscura pseudoobscura Dp-AP Drosophilidae XP_001358331

12 Drosophila willistoni Dw-AP Drosophilidae XP_002064935

13 Drosophila yakuba Dy-AP Drosophilidae XP_002098017

14 Megachile rotundata Mr-AP Megachilidae XP_003705085

15 Musca domestica Md-AP Muscidae NP_001273807

16 Microplitis demolitor Mde-AP Braconidae XP_008560602

17 Nasonia vitripennis Nv-AP Pteromalidae XP_001600858

18 Pediculus humanus corporis Ph-AP Pediculidae XP_002427417

19 Tribolium castaneum Tc-AP Tenebrionidae XP_966517

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In order to evaluate the stereochemical qualities and accuracy of the 3D model, PROCHECK 3.5 analysis (http://www.ebi.ac.uk/thornton-srv/software/PROCHECK) was used and a Ramachandran plot was drawn (Laskowski et al., 1993, 1996).2.5. Protein–protein interactionsThe Search Tool for the Retrieval of Interacting Genes/Proteins (STRING 9.1) database (http://string-db.org/) was used to predict the interacting proteins (Franceschini et al., 2013). The database contains information from various sources, including experimental repositories, computational prediction methods, and public text groups.2.6. Phylogenetic analysisPhylogenetic analyses of APs based on amino acid sequences were carried out using Molecular Evolutionary Genetic Analysis (MEGA; version 6) (Tamura et al., 2013). Sequences were aligned with the ClustalW method, and a phylogenetic tree was obtained by neighbor-joining (NJ) with complete gap deletion using the Poisson substitution model, rates among sites, uniform rates, same patterns among lineages (homogeneous), and 1000 bootstrap replications.

3. ResultsIn the current study, a total of nineteen APs protein sequences of eleven different insect families were analyzed with bioinformatics tools. Five insects were chosen as representatives of each insect order for structural analysis, including Apis mellifera (Hymenoptera), Bombyx mori

(Lepidoptera), Musca domestica (Diptera), Pediculus humanus corporis (Phthiraptera), and Tribolium castaneum (Coleoptera). 3.1. Multiple alignment and conserved motif analysisA conserved motif is a sequence pattern that occurs repeatedly in a group of related protein sequences. Motif analyses of AP proteins were performed in order to find patterns of conserved motifs, and the MEME program was run to detect sequence motifs in insect samples. MEME represents motifs as position-dependent letter-probability matrices, which designate the probability of each possible letter at each position in the pattern, whereas motifs in MAST are represented as position-dependent scoring matrices, which describe the score of each possible letter at each position in the pattern. Ten conserved motifs of APs were identified by MEME (Figure 2) and are listed in Table 2. These results also revealed that only three motifs (1, 8, and 10) were shared by all insects. The alignment of protein sequences by MegAlign showed high homology among various insects. Three similar conserved motifs were shown in the alignment report (Figure 3).3.2. Structural and functional analysisMolecular weight and the isoelectric point of each representative sample were predicted. AP protein in all insects ranged from 383 to 390 amino acids in length. The theoretical isoelectric points and molecular weight were calculated at a range of 5.64–8.70 and 41,622.63–42,509.98 kDa, respectively (Table 3).

Figure 2. Motifs for AP proteins. The MAST motifs are shown as different-colored boxes. The E-value of a sequence is the expected number of sequences in a random database of the same size that would match the motifs as well as the sequence.

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The Self-Optimized Prediction Method with Alignment (SOPMA) server calculates the percentage of alpha helix, extended strand, beta sheet, and random coil in the secondary structure of protein sequences. The prediction of the secondary structure of APs based on hierarchical neural network analysis (Combet et al., 2000) showed that the most plentiful structural elements of the secondary structure were extended strand and random coils, whereas beta turns and alpha helixes were occasionally distributed in the proteins (Table 3).

Secretory proteins are synthesized in the endoplasmic reticulum and are identified with their signal peptides. A signal peptide is a short peptide (5–30 amino acids long) that exists at the N-terminal of most of the newly synthesized proteins, which are destined towards the secretory pathways (Blobel and Dobberstein, 1975). Signal peptides are extremely heterogeneous, and many prokaryotic and eukaryotic signal peptides are functionally interchangeable even between different species; however, the efficiency of protein secretion is strongly determined by the signal peptide (Von Heijne, 1985; Kober et al., 2013). The SignalP 4.1 server predicts the existence and location of signal peptide cleavage sites in protein sequences. The method includes a prediction of cleavage sites and a signal/nonsignal peptide prediction based on a combination of several artificial neural networks. The results of SignalP indicated that all the members of AP possess a signal peptide, which is synthesized in the cytoplasm. The length of all signal peptides in insect AP is 17–20 amino acid residues (Table 3). The maximum length of signal peptide belonged to Md-AP (about 20 amino acid residues), while Am-AP and Ph-AP had a maximum of about 17 amino acid residues as the shortest signal peptide length in N-terminal extension among representative insects (Table

3). Signal peptide cleavage site predictions for AP are shown in Figure 4.

Proteins can end up as integral membrane components. These proteins are said to be transmembrane. Transmembrane domain cleavage site predictions for APs are shown in Table 3. The number of transmembrane helices in representative insects was variable between zero and one.

Pattern and profile search was performed by the Protein Domain Database (ProDom) server. ProDom is constructed automatically by clustering homologous segments. This database consists of domain family entries. Each entry provides a multiple sequence alignment of homologous domains and a family consensus sequence. The analysis of functional domains of the AP samples showed different domains (Figure 5). A comparison of ProDom domains showed that there were nineteen similar domains among samples, which are listed in Table 4 with their positions and E-values. 3.3. Tertiary structure prediction and assessment of the modelThree-dimensional modeling of Am-AP was estimated by the Protein Homology/analogY Recognition Engine 2.0 (PHYRE2) (Figure 6a). PHYRE2 uses profile–profile matching and secondary structure for the prediction of tertiary structure. This server also uses the alignment of hidden Markov models via HHsearch (Söding, 2005) to significantly improve accuracy of alignment and detection rate. The model of Am-AP by PHYRE2 was predicted using the “d1qdma2” model (PDB accession code: 1qdm), with 100% confidence and 56% identity. The PHYRE2 result was compared with predicted models of Swiss-Model (Figures 6b–6d). Swiss-Model (http://swissmodel.expasy.org/) is an automated system for modeling the 3D structure of

Table 2. Motif sequences identified with MEME.

Motif Width E-value Sites Sequence

1 23 1.2e-272 19 P[PK]Q[DK]F[KR]V[IV]FDTGSSNLWVP[SG]KKC

2 24 6.1e-251 18 ILGDVFIG[RK][YF]YT[EV]FDMGNNRVGFA

3 30 5.5e-286 18 QTFAEALSEPGL[AV]FVAAKFDGILG[ML][AG]YS[KS]I

4 30 1.1e-284 18 NIAC[KL]LH[NR]KY[DN][SN][ST]KSSTY[KV]KNGTDFAI[RQ]YG

5 30 2.8e-241 12 Y[VI]L[KR]V[TA]Q[FM]GKT[VI]CLSGFMG[MI]DIPPPNGPLW

6 30 1.4e-225 18 HY[ES]G[SD]FTY[VL]PV[DT][RK]K[GA]YWQFKMDS[IV]S[VI]GSDK

7 22 5.4e-177 15 P[QT]PEPLSNYLDAQY[YF]G[VP]I[ST]IGT

8 16 1.2e-149 19 GC[EQ]AIAD[TS]GTSLIAGP

9 22 2.2e-180 18 P[VP]FYNM[VYC]KQ[GN]L[VI]P[QS][PC][VI]FSFYLN

10 22 8.4e-144 19 SGS[LV]SGYLSTDTV[TDN][IV][AG]G[LM][KT][IV][KS][DN]

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Figure 3. Multiple alignment of APs amino acid sequences of insects by MegAlign in DNASTAR package using ClustalW method. Shade with blue residues match the consensus; shade with yellow residues differ from the consensus. The conserved motifs (1, 8, and 10) are shown in the shape.

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a protein from its amino acid sequence using homology modeling techniques (Biasini et al., 2014). The 3D models of both servers indicated that they all adopt very similar tertiary structures; therefore, these results suggested that the designated PDB code is the best model of AP.

Verification of the stereochemical quality of Am-AP structure was performed by the Programs to Check the Stereochemical Quality of Protein Structures (PROCHECK) server, and the Ramachandran plot was designated. The Ramachandran plot shows the phi–psi torsion angles for all residues in the structure, except those at the chain termini. The coloring/shading on the plot represents the different regions (Morris et al., 1992). The plot revealed that the tertiary structure of Am-AP has good chain stereochemistry (Figure 7).3.4. Phylogenetic analysisThe multiple sequence alignment of full-length protein sequences was used to construct an unrooted phylogenetic tree, and the NJ method was used for its design. The NJ algorithm is commonly applied with distance tree-building regardless of the optimization criterion. This method is comparatively rapid. The results of the phylogenetic tree showed that all AP proteins were separated into 3 different groups, designated as Groups I–III (Figure 8). Most of the designated groups were supported by more than 50 bootstrap values, shown in branches. Based on the tree, Cc-AP was excluded from the groups because of low bootstrap support. Each group contained six members of different families; consequently, all Apoidea insects were designated to Group II. All the members of the Drosophilidae family were classified in Group I with a Hymenopteran species, Nv-AP. Group III contained different insects from several families. Although similarities are clear within a family, there is not enough knowledge about different families’ relationships and similarities. However, these results suggested that, in insects, APs are very similar to each other and are probably inherited from a common ancestor.

3.5. Functional interaction network analysis of aspartic proteasesIn order to predict the interacting proteins, Am-AP was applied to the STRING 9.1 tool as a representative of insects. STRING is a database of known and predicted protein interactions. The interactions include direct (physical) and indirect (functional) associations. According to the results, no datasets were predicted in A. mellifera, although twenty-seven of these existed in other organisms. Ten functional partners were identified in the network analyses, listed in Table 5. According to the protein–protein interaction analysis, seven enriched pathways of KEGG were obtained, including mTOR signaling pathway, pyrimidine metabolism, DNA replication, lysosome, regulation of autophagy, drug metabolism, and metabolic pathways. The K-means algorithm was used for protein clustering in twelve different colors (Figure 9).

4. DiscussionIn this study, bioinformatics methods were used to identify the characteristics of AP in nineteen species from eleven different insect families.

Before finding APs in some insects like Coleoptera, it was proven that pepstatin, a powerful and specific inhibitor of APs, strongly inhibited proteolysis of the midgut enzymes of Colorado potato beetle, L. decemlineata, demonstrating that an AP was present in the midgut extracts (Wolfson and Murdock, 1987). In corn, cysteine protease has been shown to confer resistance to fall armyworm (Spodoptera frugiperda) via degradation of the peritrophic membrane of this chewing insect, which interferes with nutrient acquisition, ultimately killing the insect (Jiang et al., 1995; Pechan et al., 2002; Mohan et al., 2006). Therefore, knowing the characterization of this enzyme can be helpful in insect pest control and integrated pest management.

Table 3. Predictions of primary and secondary structures, transmembrane domains, and signal peptides of 5 different aspartic protease proteins using Compute PI/Mw, SOPMA, TMHMM, and SignalP 4.1.

SignalP 4.1 prediction resultsTMHMM prediction resultSOPMA prediction resultsCompute pI/Mw prediction results

LengthName

Signal peptide positionNumber of predicted TMHs

Predicted TM helix

Alpha helix

Betaturn

Extended strand

Random coil

MWPI

1–170__21.305.7132.7340.2642,222.215.90385Am-AP

1–181A5-A2419.536.2534.1140.1041,622.636.25384Bm-AP

1–200__19.747.6931.7940.7742,425.895.64390Md-AP

1–170__17.996.1732.1343.7042,509.988.70383Ph-AP

1–181A5-A2421.095.4732.0341.4141,635.697.53384Tc-AP

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Figure 4. Prediction of signal peptide cleavage sites in five selected species of insects by SignalP 4.1 server. C-score (raw cleavage site score), S-score (signal peptide score), and Y-score (combined cleavage site score) are shown.

Figure 5. Graphical results of functional domains of five different insect species detected by ProDom.

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Figure 6. Comparing tertiary structure prediction of AP protein in Am-AP (accession number: XP_392857; PDB accession code: 1qdm): (a) intensive model by Phyre2 server; (b), (c), and (d) three models of Swiss-Model predictions.

Table 4. Functional domains of five different insect orders of AP protein by ProDom.

IndexProDom domain

Am-AP Bm-AP Md-AP Ph-AP Tc-AP

Position Score E-value Position Score E-value Position Score E-value Position Score E-value Position Score E-value

1 PD198173 18–60 112 0.0003 5–61 297 8e-26 3–66 277 2e-23 19–59 148 2e-08 9–59 174 1e-11

2 PD522343 61–103 223 3e-17 62–104 235 1e-18 67–109 235 1e-18 60–106 220 6e-17 60–102 229 7e-18

3 PDB2A9G7 67–290 124 1e-05 69–289 118 4e-05 75–239 142 7e-08 68–284 122 1e-05 74–296 161 5e-10

4 PDA7L942 69–174 108 0.0008 52–175 137 3e-07 56–183 106 0.001 49–176 119 3e-05 40–173 131 1e-06

5 PD000182 105–161 148 2e-08 108–158 262 9e-22 113–163 195 5e-14 106–156 154 3e-09 106–156 212 6e-16

6 PDC0Q4U8 107–382 223 3e-17 109–384 149 1e-08 114–387 177 6e-12 146–380 152 5e-09 107–381 199 2e-14

7 PDA923K1 140–385 188 4e-13 124–383 152 5e-09 146–390 175 9e-12 122–382 208 2e-15 125–379 187 4e-13

8 PD933308 168–192 119 4e-05 169–193 128 4e-06 174–197 120 3e-05 167–191 118 5e-05 167–191 122 1e-05

9 PDB8S246 169–333 175 1e-11 170–333 167 1e-10 175–338 161 4e-10 168–331 139 2e-07 168–332 190 2e-13

10 PDA5R6K7 185–298 160 7e-10 190–297 99 0.008 202–303 141 8e-08 202–296 139 2e-07 184–297 150 8e-09

11 PD890699 193–252 250 2e-20 194–255 286 2e-24 198–262 318 3e-28 194–258 256 5e-21 192–254 278 1e-23

12 PDB3O874 226–299 142 8e-08 226–294 123 1e-05 232–294 115 0.0001 225–285 124 8e-06 225–298 167 1e-10

13 PDA1D2U8 261–293 144 4e-08 259–292 169 5e-11 263–299 159 8e-10 256–293 136 4e-07 259–294 144 4e-08

14 PDB0S9U8 265–354 145 3e-08 264–349 134 7e-07 270–359 107 0.0007 263–347 131 2e-06 264–353 136 4e-07

15 PD876079 267–347 147 2e-08 256–333 144 4e-08 273–354 134 6e-07 265–345 137 3e-07 258–333 150 1e-08

16 PD777487 267–372 110 0.0004 266–371 106 0.001 272–390 124 9e-06 265–370 113 0.0002 266–371 111 0.0003

17 PDA9Z9E1 298–327 123 1e-05 297–323 145 4e-08 303–331 149 9e-09 296–324 101 0.005 297–325 114 0.0001

18 PD058906 301–347 154 3e-09 302–346 140 1e-07 315–352 158 9e-10 308–345 153 5e-09 309–346 167 9e-11

19 PDA1D277 348–384 187 5e-13 347–383 205 4e-15 353–389 190 2e-13 346–383 183 1e-12 347–384 199 2e-14

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Figure 7. Ramachandran plot of Am-AP (PDB accession code: 1qdm). The Ramachandran plot shows the phi–psi torsion angles for all residues in the structure (except those at the chain termini). Glycine residues are separately identified by triangles, as these are not restricted to the regions of the plot appropriate to the other side chain types. The coloring/shading on the plot represents the different regions as follows: the darkest areas (shown in red) correspond to the ‘core’ regions representing the most favorable combinations of phi–psi values. Ideally, one would hope to have over 90% of the residues in these ‘core’ regions. The percentage of residues in the ‘core’ regions is one of the better guides to stereochemical quality. The regions are labeled as follows: A-Core alpha, L-Core left-handed alpha, a-Allowed alpha, l-Allowed left-handed alpha, ~a-Generous alpha, ~l-Generous left-handed alpha, B-Core beta, p-Allowed epsilon, b-Allowed beta, ~p-Generous epsilon, and ~b-Generous beta.

Figure 8. The phylogenetic tree of AP protein from insects using the CLUSTALW (MEGA 6) program. The NJ method was used to construct the tree. Numbers associated with branches show bootstrap support values for NJ analyses higher than 50. Three major groups, designated from I to III, are marked with different colors.

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Table 5. Characteristics of input protein Am-AP (cathepsin D XP_392857) and functional partners predicted with STRING 9.1.

Index Name Functions Score

1 Atg1 Autophagy-specific gene 1 0.812

2 GB17311 Similar to CG8444-PA 0.755

3 GB14710 Venom serine carboxypeptidase 0.643

4 GB11983 Similar to angiotensin-converting enzyme CG8827-PA, isoform A 0.623

5 GB16675 Similar to angiotensin-converting enzyme, testis-specific isoform precursor (ACE-T) (Dipeptidyl carboxypeptidase I) (Kininase II) 0.623

6 GB20065 Similar to angiotensin I-converting enzyme (peptidyl-dipeptidase A) 1 isoform 1 0.623

7 GB19369 Similar to rudimentary-like CG3593-PA (468 aa) 0.627

8 GB11271 Similar to proprotein convertase subtilisin/kexin type 1 preproprotein 0.609

9 Fur1 Furin-like protease 1 0.609

10 Mcm5 Minichromosome maintenance 5 0.624

Figure 9. The interactive network view of predicted proteins of protein–protein interactions using STRING 9.1 tool. Network nodes are proteins, and the edges represent the predicted functional associations. Intercluster edges are represented by dashed lines.

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Bioinformatics is an interdisciplinary field that develops methods and software tools for understanding biological data. It is a powerful tool for predicting the structure and function of a protein from its amino acid sequence by means of its similarity to a sequence of known structure or function. This method plays a key role in guiding the experimental characterization of a genome (Martin et al., 2004). Because of its effectiveness and low cost, bioinformatics has been widely used to predict antigenic epitopes on proteins (Bai et al., 2012). Thus, it seems that these tools have revolutionized the study of genetics (Darabi et al., 2012; Darabi and Farhadi-Nejad, 2013; Kesici et al., 2013; Seddigh and Darabi, 2014). In conclusion, our study employed bioinformatics methods to explain the structure, function, and molecular mechanism of AP protein in insects. We used several different software packages and online services to predict protein function, such as 3D structure, protein–protein interaction network, and evolution relationships of AP in insects. Bioinformatics analysis has allowed us to predict primary and secondary structures of representative insect samples. The 3D prediction revealed that the tertiary structure of insect APs is common to that of other enzymes belonging to the AP family, whose crystallographic structure has been determined (Kervinen et al., 1999). Topology predictions were analyzed and motifs were obtained.

The obtained data of the bioinformatics analysis indicated that AP is a secretory protein, and the positions of

the secretory proteins of each sample from representative insects were predicted by SignalP analysis. The function of AP can be the same among insects, which resulted from nineteen similar domains by ProDom.

All aspartate proteases have a highly conserved sequence of Asp-Thr-Gly. In general, these enzymes are monomeric enzymes consisting of two domains, and it is thought that these domains may have arisen through ancestral gene duplication. Since phylogenetic analyses can be the basis of molecular and biochemical analyses of protein families, the protein research was performed on the AP protein family in insects. Based on their phylogenetic relationships, AP proteins were divided into 3 groups. Phylogenetic analysis showed that evolutionary relationships among different groups of AP proteins were inevitable. Moreover, within each group, similar amino acid sequences suggested strong evolutionary relationships among different families.

In this research, bioinformatics analyses of insect APs showed similarities between this protein in different families, and the obtained data provide a background for bioinformatics studies on the function and evolution of APs in other insects and organisms.

AcknowledgmentThis research was supported by the Varamin-Pishva Branch of the Islamic Azad University. We express our sincere appreciation.

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