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Journal of Genetic Engineering and Biotechnology
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In silico structural and functional characterization of Antheraea mylitta cocoonase

Journal of Genetic Engineering and Biotechnology volume 20, Article number: 102 (2022) Cite this article

Abstract

Background

Cocoonase is a serine protease present in sericigenous insects and majorly involved in dissolving of sericin protein allowing moth to escape. Cocoon structure is made up of sericin protein which holds fibroin filaments together. Cocoonase enzyme hydrolyzes sericin protein without harming the fibroin. However, until date, no detailed characterization of cocoonase enzyme and its presence in wild silk moth Antheraea mylitta has been carried out. Therefore, current study aimed for detailed characterization of amplified cocoonase enzyme, secondary and tertiary structure prediction, sequence and structural alignment, phylogenetic analysis, and computational validation. Several computational tools such as ProtParam, Iterative Threading Assembly Refinement (I-TASSER), PROCHECK, SAVES v6.0, TM-align, Molecular Evolutionary Genetics Analysis (MEGA) X, and Figtree were employed for characterization of cocoonase protein.

Results

The present study elucidates about the isolation of RNA, cDNA preparation, PCR amplification, and in silico characterization of cocoonase from Antheraea mylitta. Here, total RNA was isolated from head region of A. mylitta, and gene-specific primers were designed using Primer3 followed by PCR-based amplification and sequencing. The newly constructed 377-bp length sequence of cocoonase was subjected to in silico characterization. In silico study of A. mylitta cocoonase showed 26% similarity to A. pernyi strain Qing-6 cocoonase using Blastp and belongs to member of chymotrypsin-like serine protease superfamily. From phylogenetic study, it was found that A. mylitta cocoonase sequence is closely related to A. pernyi cocoonase sequence.

Conclusions

The present study revealed about the detailed in silico characterization of cocoonase gene and encoded protein obtained from A. mylitta head region. The results obtained infer the presence of cocoonase enzyme in the wild silkworm A. mylitta and can be used for cocoon degumming which will be a valuable and cost-effective strategy in silk industry.

Background

Among animal groups on the planet, insects are the most prosperous and are present in every corner of the world [1]. The advantage of insect’s adaptabilities is associated with their long-term evolution process into the environment, such as reproduction ability, short life cycle, and favorable small size to hide them. Additionally, insects enclose incisive life-cycle strategies, such as diapause [2], mimicry [3] and aposematic signals [4], and long-distance migration [5, 6], which are favorable for survival and population growth. Few holometabolous insects have adapted to cocoon formation as one of the effectual evolutionary strategies that helps to protect immobile pupa from mechanical damage, natural predators, parasites, and other adverse factors.

Significant population of insects from Lepidoptera, Coleoptera, Hymenoptera, and Neuroptera [7,8,9] are capable of spinning. Mature insect larvae spun raw protein material (sericin and fibroin) secreted by its silk gland [10] to build cocoon, for instance, cocoon of domestic silk moth Bombyx mori, Antheraea pernyi, and Antheraea mylitta [11,12,13]. The report from previous study highlights the presence of a protease that hydrolyzes sericin, making the cocoon soft, and helps the moth to escape out [14, 15]. The metabolic pathway of peptide digestion is an important phenomenon of trypsin protease (gene name PRSS; https://www.genome.jp/entry/hsa:5644+hsa:5645+hsa:5646) and hydrolase enzyme (EC no. 3.4.21.4, www.brenda-enzymes.org) which are responsible for breakdown of peptides and related compounds (KEGG database at (http://www.genome.jp/kegg, Fig. 1). Cocoonase (synonym to trypsin, https://www.brenda-enzymes.org/enzyme.php?ecno=3.4.21.4#SYNONYM) is a naturally occurring enzyme that is functionally similar to trypsin. Cocoonase was first described in moths and is present as a single-copy gene [16]. However, recent work has identified multiple cocoonase duplication events in the Heliconius melpomene genome, resulting in at least five duplicates of recent origin [16].

Fig. 1
figure 1

Metabolic pathway of trypsin (EC 3.4.21.4) (synonym of cocoonase) in protein digestion and absorption (KEGG database at http://www.genome.jp/kegg updated 28th Aug 2020)

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Cocoonase enzyme is also well known as serine-trypsin protease or trypsin-like protease enzyme. Both enzymes are grouped in protease category and catalyze the breaking of peptide bonds and functionally defined with EC no. 3.4.21.4. The cocoonase gene coding sequence was unraveled gradually [17, 18], and its application in degumming has been also reported [19,20,21,22,23,24,25]. The boiling of cocoon in water dissolves sericin protein [26], and continuous raw silk filament is reeled and the whole process is known as silk degumming. Also, usage of chemical methods in Industrial Avenue for silk degumming of cocoons is commonly rampant. However, the usage of chemicals like soda, soap, detergents, alkaline, and alkali solution affects both sericin and fibroin, thus hampering the properties of tasar silk-like natural color, texture, and softness [27,28,29].

Therefore, it is expected that enzymatic cocoon degumming will be beneficial and may help to retain natural color, texture, and softness of tasar silk. Additionally, enzymatic methods have other advantages also as it is economical, eco-friendly, and biodegradable [30]. Hydrolyzing activity of cocoonase [31, 32] on sericin is similar as of trypsin. A study elucidating present and future perspective of cocoonase enzyme and its possible role in textile industry has been published [28]. Gene editing technique like CRISPR/Cas9-based Bombyx mori cocoonase gene editing has been the first experimental and phenotypic evidence showing that cocoonase is a cocoon breaking determining factor [33]. Using transcriptomic and genomic data heliconiine cocoonase gene expression across additional tissues, reconstructing their phylogenetic relationships, and examining the rates of gene duplication and deletion have already been described [34].

However, there is no detailed information available about cocoonase gene from A. mylitta silkworm. Furthermore, utilizing cocoonase-based degumming of cocoon strategy requires other information like ample production of cocoonase and its concentration-based degumming activity. Therefore, in present study, an effort has been made to find cocoonase gene and its characterization. Here, RNA was isolated from A. mylitta head region and gene amplification, and molecular study on the cocoonase gene from A. mylitta has been described. Furthermore, characterization of the coding nucleotide sequences predicting the tertiary and quaternary structure [35, 36] along with interaction of potential ligands focused on the active site residues of putative cocoonase protein of A. mylitta (AmCoc) has been done. The obtained findings infer the presence of cocoonase enzyme in the wild silkworm, A. mylitta. Gained information from present study can be utilized for the production of recombinant cocoonase and cocoon degumming.

Methods

Natural habitat of Antheraea mylitta and sample collection

Antheraea mylitta Drury, tasar silkworm, is a wild sericigenous, polyphagous insect spread in different geographical zones in India [37]. Tasar silkworm late pupa (Fig. 2 a–b) and cocoon samples (Fig. 2 c–d) of A. mylitta Drury, feed on Terminalia tomentosa and Shorea robusta [38], were collected from natural habitat of Central Tasar Research and Training Institute, Ranchi, India. Fifth larval stage is the perfect stage to produce cocoonase in maximum. The A. mylita Drury cocoon research samples were kindly provided by Dr. J. P. Pandey (scientist D, CTR &TI, Ranchi, India). CTR&TI is the flagship research institute catering to the R&D need of tropical and temperate (oak) tasar sectors. Late pupal stage samples of 125 days old were selected for RNA isolation from brain tissues (Fig. 2 e–f) via TRIzol® extraction protocol [39]. The Antheraea mylitta pupa samples were disinfected using 70% ethanol and dissected under sterilized condition. Dissected pupa head (anterior portion) was subjected for RNA isolation.

Fig. 2
figure 2

Antheraea mylitta. a 2nd instar larva stage feeding on T. tomentosa, b 4th larvae stage in natural habitat, c and d Antheraea mylitta cocoons on the Terminalia tomentosa in natural environment, e 5th instar pupa sample, and f dissection of 5.th instar pupa sample for RNA isolation

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Retrieval of cocoonase gene sequence and primer designing

The hydrolysis of sericin protein is catalyzed by cocoonase enzyme; therefore, in NCBI database, cocoonase entry was searched, and its sequence from Antheraea pernyi strain was retrieved (NCBI accession no. gi|295,682,679|). The above sequence was submitted to tblastn for getting its coding sequence (GenBank: ADG26770.1). Four sets of primers (including forward and reverse) were obtained using online primer designing tool (Primer3) with optimized parameters such as GC%, length of primer, and amplicon size. List of primer sets used in PCR amplification has been shown in Table 1, as A. mylita and A. pernyi wild silk moth belongs to the same genus. Therefore, cocoonase protein sequence (ADG26770.1) was selected as template for primer designing.

Table 1 Primer sets procured from Xcelris, India
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PCR amplification and sequencing

Four sets of gene-specific primers were used for PCR amplification following the PCR preparations of TaKaRa™. PCR amplification was performed in a final volume of 12.5 μL containing cDNA (150 ng), 10 pmol of the each primers, mixture of dNTPs (Sigma) having concentration of 250 μM, 10 × Taq Polymerase Buffer, and 0.625 U of Taq DNA polymerase (TaKaRa™). The reaction conditions for PCR set up were as follows: an initial denaturation step at 95 °C for 1 min, 35 amplification cycles of denaturation at 95 °C for 30 s, annealing at 49 °C for 30 s, and primer extension at 72 °C for 90 s, followed by a final extension at 72 °C for 10 min with TaKaRa PCR thermal cycler Dice (Thermo Fisher Scientific, USA). The primer set which gave single band amplification with cDNA was selected, and amplified PCR product was submitted for sequencing to Chromous Biotech, Bangalore, India.

Physicochemical characterization

Primary sequence analysis was performed by calculating the physicochemical properties of retrieved protein sequences which include isoelectric point (pI), molecular weight (MW), instability index (II), aliphatic index (AI), and GRAVY or grand average of hydropathicities by using ExPASY-ProtParam tool (http://web.expasy.org/protparam/) [40]. The secondary structural features (like helix, turn, sheet, coil, etc.) were predicted by SOPMA (http://npsa-pbil.ibcp.fr/cgi-bin/npsa_automat.pl?page=/NPSA/npsa_sopma.html) [41] and CFSSP: Chou and Fasman Secondary Structure Prediction server (http://cho-fas.sourceforge.net/), [42, 43]. The PredSL (http://aias.biol.uoa.gr/PredSL/) [44] and PredictProtein (https://predictprotein.org/) [45] were used to predict subcellular location of the derived target protein. Protein dynamics information is also important for understanding protein function. DynaMine web server quickly produces profile describing statistical potential for fast backbone protein movements directly from amino acid sequence available at http://dynamine.ibsquare.be/ [46].

Modeling and structural and functional analysis

3D protein structure of AmCoc was determined by QUARK and I-TASSER server, https://zhanglab.dcmb.med.umich.edu/I-TASSER/ [47, 48]. The stereo-chemical quality assessment of predicted protein structure was performed by PROCHEK [49,50,51,52], RAMPAGE [47, 53, 54], and UCLA-DOE LAB SAVES server (http://services.mbi.ucla.edu/SAVES/). Potential deviations and structural alignment were calculated with TM-align web server [55] (https://zhanggroup.org/TM-align/) for root-mean-square deviation (RMSD). The potential errors were checked in predicted tertiary protein model, while z-score value was calculated and compared with target template by ProSA-web tool [56] (https://prosa.services.came.sbg.ac.at/prosa.php). This displays overall quality and if the input structure lies within the score range for the native proteins of similar size [24, 57].

Sequence annotation and NCBI submission

PCR amplified and obtained cocoonase sequence was analyzed by various computational and web-based online tools. DNA TIS Miner tool [58] (available at http://dnafsminer.bic.nus.edu.sg/) was used for finding start codons and ORF finder tool (http://www.bioinformatics.org/sms2/orf_find.html) for determining ORFs in the cocoonase sequence. The number of exons, exon position, and exon was predicted by GeneWise tool. Conserved domain tool available at https://www.ncbi.nlm.nih.gov/Structure/cdd/cdd.shtml [59,60,61] reports the functional motifs [62] location and was used to predict the presence of conserve domain in predicted protein model of cocoonase (KM388539.1). Moreover, protein domain and domain architecture were analyzed with SMART tool [63] (http://smart.embl-heidelberg.de/), and the presence of motif was performed using MEME tool (https://meme-suite.org/meme/tools/meme). Structural Classification of Proteins (SCOP) available at http://scop.mrc-lmb.cam.ac.uk/scop/ provides comprehensive structural and evolutionary relationships between all proteins whose structure is known [64, 65].

BLAST against Antheraea mylitta genome

Obtained cocoonase sequence (KM388539.1) was subjected to NCBI blast (https://www.ncbi.nlm.nih.gov/) against A. mylitta GenBank assembly GCA_014332785.1 (AM_v1.0).

Results

Details of silkworm late pupa (Fig. 2 a–b), cocoon samples (Fig. 2 c–d), fifth instar larva of A. mylitta (Fig. 2e) moth, and sampling of brain tissues for RNA isolation (Fig. 2f) have been depicted. PCR amplification with gene-specific primer and optimization in respect to annealing temperature, number of cycles, and concentration of the template DNA was performed. The PCR thermal profile cycle was maintained as follows: 95 °C, 1 min; 95 °C, 30 s; 49 °C, 30 s; 72 °C, 90 s; and 72 °C, 10 min for 35 cycles with ApCoc4 primer set. Amplified PCR product (amplicon size ~ 500 bp) of A. mylitta with primer ApCoc4 was submitted for sequencing (Fig. 3). Obtained nucleotide sequences of A. mylitta were subsequently analyzed, assembled, and annotated. Following sequence assembly, a new sequence of AmCoc (377 bp) was constructed. Newly constructed AmCoc nucleotide sequence was checked for the similarity using BLAST with A. pernyi cocoonase gene reported in NCBI database (ADG267710.1) and was found to be identical (query coverage — 11%; maximum identity 97%). The predicted gene constitutes 1 exon with 48% GC content having 122 amino acids in translated protein sequence as explained by GeneWise algorithm (Table 2). DNA TIS Miner tool-based analysis for finding translation initiation sites (TIS) total 4 positions was found. But as per ORF finding tool, at nucleotide position 253, it can be confirmed that gene may start with an open reading frame, and ORF is shown in red-colored font (Table 3). Phylogenetic tree was constructed with new sequence with GenBank ID > gi|731,516,038|gb|KM388539.1| UNVERIFIED: Antheraea mylitta genomic KM388539.1 (Table 4), showed that it is closely related to A. pernyi strain qing_6 cocoonase-like protein mRNA sequence (GenBank ID HM011050.1, Fig. 4). Cooconase gene NCBI blast result shows that sequences are matched with A. mylitta isolate AMDABA2020 scaffold18_size7685921 and whole genome shotgun sequence (Supplementary Fig. S1) showing only 2 matches with A. mylitta isolate AMDABA2020 scaffold18_size7685921 (Supplementary Fig. S2). Smith et al. [16] has reported that cocoonase gene is a single-copy gene in several butterfly and moth genomes (the silk moth Bombyx mori, diamond backed moth Plutella xylostella and monarch butterfly Danaus plexippus, and the Glanville fritillary (Melitaea cinxia). It needs to mention that cocoonase protease activity might be comparable with trypsin protease enzyme activity, because both the abovementioned proteases are enrolled with identical Enzyme Commission number (EC 3.4.21.4), and also, trypsin is synonym to cocoonase.

Fig. 3
figure 3

M, marker, DNA samples amplified with ApCoc4 primer in replicates (amplicon size ~ 500 bp) in L1 and L2

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Table 2 Prediction of exon, exon position, exon range, exon length, and GC content by GeneWise tool
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Table 3 Prediction of start codon, score, position, and Kozak consensus sequence by DNA TIS miner
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Table 4 Antheraea mylitta cocoonase (AmCoc) nucleotide sequence deposited in NCBI
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Fig. 4
figure 4

Phylogenetic tree constructed with AmCoc (accession no.KM388539.1) and enlisted nucleotide cocoonase sequences from homologues

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AmCoc physicochemical parameters were derived using ProtParam tool (Table 5) that corresponds with 124 amino acid residues, molecular weight of 14.681 kDa, and computed pI of 10.97. The deduced amino acid sequence contains 7 negatively charged (− R, Asp + Glu) and 25 positively charged (+ R, Arg + Lys) amino acid residues. The value of instability index, aliphatic index, and grand average of hydropathicity (GRAVY) was 53.44, 59.59, and − 0.733, respectively. The highest frequency of amino acids in the sequence is arginine (12.3%), alanine (10.3%), followed by proline (9.5%). The secondary structure prediction of AmCoc sequence is shown in Fig. 5 and Supplementary Fig. S3. Helix, sheet, and turn (59%, 54.9%, and 19.7%, respectively) as secondary structures were predicted by Chou–Fasman web server. Subcellular location of the derived protein was determined by the PredictProtein (Fig. 6), while using PredSL tools, it was observed that it is a mitochondrial protein. The stability of the derived amino acid sequence was determined by DynaMine web server exhibiting that maximum amino acid residues lay in the rigid area (Fig. 7).

Table 5 Physicochemical parameter of cocoonase computed by ProtParam tool
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Fig. 5
figure 5

Secondary structure of AmCoc

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Fig. 6
figure 6

Subcellular localization of AmCoc mitochondrial protein predicted by PredictProtein tool

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Fig. 7
figure 7

Prediction of dynamic nature of AmCoc protein using DynaMine server: our results showed that the most of regions of AmCoc are rigid, and there are only nine flexible regions with the lowest predicted S2 value which are Phe115 (0.57), Arg116 (0.58, Pro117 (0.56), Pro118 (0.53), Pro119 (0.51), Gly121 (0.46), Trp122 (0.41), and Thr123 (0.43)

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The 3D model of A. mylitta cocoonase protein (KM388539.1) was predicted by QUARK and I-TASSER servers and viewed by PyMol (Fig. 8a). Helices and loops were colored in cyan and magenta, respectively. The best predicted protein structure was selected based on TM score (0.3461). Furthermore, structural validation and quality assessment of the model were carried out using various tools such as PROCHEK, RMSD, RAMPAGE, and z-score. Ramachandran plot-based analysis showed that 70.3% of residues were in the most favored region, 19.7% in the allowed region, while 2% in the disallowed region (Fig. 8b). Also, SAVES ERRAT (78%) and z-score for the AmCoc-predicted protein structure was found to be − 4.92 (Fig. 9). The structural alignment was performed with TM-align tool between AmCoc-predicted protein structure and ApCoc-predicted structure showing the RMSD = 5.68A and viewed in PyMol (Fig. 10). Moreover, protein domain and domain architecture were analyzed with SMART tool (http://smart.embl-heidelberg.de/, 41), and translated AmCoc protein belonged to a distinct SCOP superfamily d1kypa. The deduced amino acid of A. mylitta cocoonase sequence comprised of two motifs which are determined by MEME tool suite (Supplementary Fig. S4). Obtained results indicated that conserved domains of deduced amino acid sequence of cocoonase (Fig. 11) were a trypsin-like serine protease having active site from 75 to 200 query sequence and substrate binding site from 210 to 225 query sequences in NCBI. Both the motifs belong to trypsin-like serine protease, and cocoonase-like protein has been inferred as a conserved domain (cd00190) at the positions of 56–76 and 84–104 and each of 20 amino acid in length. Detailed comparative modeling and protein structure analysis have been performed to infer functional (and perhaps adaptive) differences of heliconiine cocoonase compared with the single-copy moth cocoonase [34].

Fig. 8
figure 8

Predicted 3D model (I-TASSER) of a AmCoc encoded protein where α-helices are shown in cyan color and coils are in magenta. b Ramachandran plot (between φ-ψ torsion angles) of the predicted protein is shown where the cream areas correspond to sterically disallowed regions except glycine, red and brown areas correspond to sterically allowed regions for alpha-helical and beta-sheet conformations, and yellow areas correspond to allowed regions for the left-handed alpha-helix (A right-handed alpha-helix, B beta-sheet, and L left-handed alpha helix)

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Fig. 9
figure 9

(a) ProSA-web z-scores of all protein chains in PDB determined by X-ray crystallography (light blue) or NMR spectroscopy (dark blue) with respect to amino acid chain length. The z-scores of AmCoc is highlighted as large dots Z-score for template protein structure–AmCoc -4.92; (b) SAVES ERRAT graph of AmCoc; (c) Energy plot of AmCoc

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Fig. 10
figure 10

a Superimposed three-dimensional structure model of template ApCoc (red) and target AmCoc (blue). b Pairwise alignment for ApCoc protein sequence and ApCoc protein sequence with ClustalW

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Fig. 11
figure 11

The conserve domain identification of cocoonase by NCBI Conserved Domain Database

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Discussion

Cocoonase is a very important protease enzyme responsible for hydrolyzing sericin of silk cocoon. A study using bioinformatics tools has been published showing that cocoonase is specific to Lepidoptera, and also, it existed before the occurrence of lepidopteran insects spinning cocoons [33]. The primary structure of cocoonase revealed about amino acid sequence arrangement, while secondary and tertiary structure of the protein illustrates the enzymatic function in-depth. The first attempt of the present study was to characterize a novel cocoonase gene amplified from cDNA of A. mylitta brain tissues using computational approaches. PCR amplification was obtained with primer set ApCoc4 (Table 1), and obtained amplified product was subsequently sequenced (Fig. 3). Sequence alignment [66, 67], phylogenetic analysis, motif identification, functional annotation, and structure analysis by homology modeling [68], elucidated that AmCoc shows similarity to proteases from other sericigenous insects such as A. pernyi and B. mori. The annotation of the newly constructed sequence AmCoc (377 bp) was used to search the presence of the serine protease domain, cd00190, using SMART tool. Also, modeling-based data of 30 individual cocoonases indicated that all the cocoonase enzymes have trypsin-like specificity, and also, significant differences were noticed among the surface residues of different cocoonase types which suggest that cocoonase enzyme shows varying adaptation to different chemical environments [34].

Finding ORF and translation initiation sites is important for understanding their key role and predicting the coding region in newly constructed sequence. Gene prediction was performed with GeneWise tool which shows exon positions, exon range, and length to a genomic DNA sequence [69] and listed in Table 2. Relatedness and distinction among linked genetic sequences have been explained by sequence alignment and represented pictorially in phylogenetic tree, defining an evolutionary descent of distinct species, organisms, or genus from a common ancestor [70, 71]. In the current study, phylogenetic analysis revealed that the obtained cocoonase sequence from A. mylitta (accession no. KM388539.1) belongs to the same clade of A. pernyi (ADG267710.1) and evolutionary related as shown in Fig. 4. PredictProtein and PredSL analysis showed that the target protein, A. mylitta cocoonase enzyme from head portion, is mitochondrial protein and possesses signal peptide [72, 73] (Fig. 6).

I-TASSER hierarchical protocol was used for automated protein structure prediction and structure-based function annotation that predicts and infers the secondary and tertiary structures, structural and functional annotations, ligand-binding sites, active sites, enzyme commission, and gene ontology terms [65]. The scale of accuracy for the predictions is based on confidence score (C-score) of the protein model, TM score (scale for measuring the structural similarity between two protein structures), and RMSD value (average distance of all residue pairs) [47, 74] as shown in Fig. 8. The structural alignment was performed between A. mylitta cocoonase predicted structure and A. pernyi cocoonase protein structure showing RMSD value = 5.68A and viewed in PyMol (Fig. 10). The RMSD superimposition value indicated that there is similarity among the target (AmCoc) and the template structure (ApCoc). A. mylitta cocoonase close structural similarity with the template cocoonase from A. pernyi (Fig. 10) suggests that there is a functional similarity with cocoonase from A. mylitta (RMSD = 5.68A, viewed in PyMol) 

Cocoonase gene isolated from head region, characterization and its analysis in silk degumming have not been reported in Antheraea sp.; however, there are previous reports about the presence of cocoonase enzyme in B. mori silk moth (domestic) and A. pernyi (wild) and its role in silk degumming. Through in silico predictions, AmCoc-derived cocoonase gene sequence showed similarity with template sequence, and the presence of conserved domain and motif has been observed which belongs to trypsin-specific family (Fig. 11). Prediction of protein functions using 3D structure information, enzyme commission number, and ligand binding sites has been described using COFACTOR [75]. COFACTOR tool-based analysis of cocoonase protein predicted a template of PDB ID: 3cskA with EC number 3.4.14.4 (dipeptidyl-peptidase III belonging to hydrolase) and active site residues [6, 15, 43, 53, 54, 76]. Similar type prediction has also been described using B. mori cocoonase sequence [65]. The functional difference of enzyme isoforms was calculated using DEEPre tool based on enzyme EC number prediction by deep learning method (Supplementary Fig. S5). Domain and motif identification in protein is a vital step for better understanding of structural and functional inference of predicted protein [18, 77].

A detailed study on the genetic analysis of Indian tasar silk moth (A. mylitta) populations has been published [78]. However, no detailed information is available for A. mylitta cocoonase gene. Furthermore, the study about the cocoonase gene structure, copy number, chromosome location and its expression patterns, etc. in A. mylitta is of great significance. Here, cocoonase gene sequence was subjected to NCBI blast against GenBank assembly Antheraea mylitta—GCA_014332785.1 (AM_v1.0) indicated the matching of sequences with A. mylitta isolate AMDABA2020 scaffold18_size7685921 whole genome shotgun sequence (Supplementary Fig. S1) having 2 matches only (Supplementary Fig. S2), although six copies of cocoonase has been reported in Heliconius melpomene and copy number varies across H. melpomene subpopulation [16]. Also, a detailed list about the copy number variation in cocoonase genes across 18 individuals of four Heliconius melpomene (Hm) subspecies has been elaborated [34]. Nowadays, the gene editing technologies are also being used to unravel the functionality of various genes. Recently, gene editing technique like CRISPR/Cas9 has been used to knock out cocoonase in the silkworm B. mori [33]. Detailed cocoonase gene expression analysis has not been performed in the present study, although PCR-based cocoonase gene amplification was seen in brain tissue only (Fig. 3). Detailed study about mRNA expression levels of cocoonases across multiple H. melpomene tissues (like mouth parts, antennae, head, and legs) has been described where high expression levels were indicative of an important function for cocoonase 3 and cocoonase 4 in the mouth part tissues [34].

Conclusion

In summary, the present study describes about the isolation of RNA, cDNA preparation, PCR-based amplification, sequencing, and identification of cocoonase gene from head region of A. mylitta. Annotation resulted to the newly constructed cocoonase (AmCoc) sequence of 377 bp only. Phylogenetic analysis of ApCoc and AmCoc revealed their evolutionary relationship between different species. NCBI blast against GenBank assembly Antheraea mylitta—GCA_014332785.1 (AM_v1.0) indicated the matching of sequences with A. mylitta isolate AMDABA2020 scaffold18_size7685921 whole genome shotgun sequence. Secondary structure as well as 3D structure prediction of AmCoc cocoonase disclosed the detailed atomic structure, while I-TASSER predicted the most stable structure. AmCoc proteins were searched in PDB for predicting their structural closeness to the target in the PDB (3cskA) and active sites [6, 15, 43, 53, 54, 76]. EC predictions revealed that AmCoc cocoonase (dipeptidyl-peptidase III belonging to hydrolase) has EC number 3.4.14.4. Furthermore, AmCoc enzyme is a mitochondrial protein, which possesses signal peptide and serine protease domain. The present study broadens our knowledge about A. mylitta cocoonase (AmCoc) characteristics which may be helpful in further elucidating its full gene sequences and encoding protein. Obtained findings may further be utilized to add economical value of silk by altering the degumming process of cocoon and thereby retaining the texture and color of silk.

Availability of data and materials

Not applicable.

Abbreviations

EC no:

Enzyme Commission number

AmCoc:

Antheraea mylitta Cocoonase

CTR&TI:

Central Tasar Research and Training Institute

NCBI:

National Center for Biotechnology Information search database

JTT model:

Jones-Taylor-Thornton model

PCR:

Polymerase chain reaction

ApCoc:

Antheraea pernyi Cocoonase

SMART:

Simple Modular Architecture Research Tool

SOPMA:

Secondary structure prediction method

RMSD:

Root-mean-square deviation

CDD:

Conserved Domain Database

DNA TIS:

DNA translation initiation site

GO:

Gene ontology

ORF:

Open reading frame

References

  1. Stork NE (2018) How many species of insects and other terrestrial arthropods are there on Earth? Annu Rev Entomol 63:31–45

    Article  Google Scholar 

  2. Koštál V (2006) Eco-physiological phases of insect diapause. J Insect Physiol 52(2):113–127

    Article  MathSciNet  Google Scholar 

  3. Rudall KM, Kenchington W (1971) Arthropod silks: the problem of fibrous proteins in animal tissues. Annu Rev Entomol 16:73–96

    Article  Google Scholar 

  4. Ruxton GD, Sherratt TN, Speed MP (2004) Avoiding attack: the evolutionary ecology of crypsis, warning signals and mimicry. Oxford University Press, Oxford, pp. 249.

  5. Chapman JW, Reynolds DR, Wilson K (2015) Long-range seasonal migration in insects: mechanisms, evolutionary drivers and ecological consequences. Ecol Lett 18(3):287–302

    Article  Google Scholar 

  6. Dingle H (1972) Migration strategies of insects. Science 175(4028):1327–1335

    Article  Google Scholar 

  7. Donald LJ, Shaw MR, Takahashi M, Yanechin B (2010) Cocoon silk chemistry of non-cyclostome Braconidae, with remarks on phylogenetic relationships within the Microgastrinae (Hymenoptera: Braconidae). J Nat Hist 38:2167–2181

    Google Scholar 

  8. Jenkins MF (1958) Cocoon building and the production of silk by the mature larva of Dianous coerulescens Gyllenhal (Coleoptera: Staphylinidae). Trans R entomol Soc London 110:287–301

    Article  Google Scholar 

  9. Sutherland TD, Young JH, Weisman S, Hayashi CY, Merritt DJ (2010) Insect silk: one name, many materials. Annu Rev Entomol 55:171–188

    Article  Google Scholar 

  10. Gatesy J, Hayashi C, Motriuk D, Woods J, Lewis R (2001) Extreme diversity, conservation, and convergence of spider silk fibroin sequences. Science 291(5513):2603–2605

  11. Duspiva F (1950) The enzymatic processes when the silk spinner (Bombyx mori L.) breaks through the cocoon shell. J Nat Sci B 5b:273–81

    Google Scholar 

  12. Trouvelot L (1867) The American silk worm. Am Nat 1:30–38

    Article  Google Scholar 

  13. Unajak S, Aroonluke S, Promboon A (2014) An active recombinant cocoonase from the silkworm Bombyx mori: bleaching, degumming and sericin degrading activities. J Sci Food Agr 95(6):1179–1189

    Article  Google Scholar 

  14. Latter OHXVIII (2009) The secretion of potassium hydroxide by Dicranura vinula (imago), and the emergence of the imago from the cocoon. Transact Royal Entomol Soc London 40(4):287–292

    Article  Google Scholar 

  15. Latter OHXIV (2009) Further notes on the secretion of potassium hydroxide by Dicranura vinula (imago), and similar phenomena in other Lepidoptera. Transact Royal Entomol Soc London 43(3):399–409

    Article  Google Scholar 

  16. Smith G, Macias-Muñoz A, Briscoe AD (2016) Gene duplication and gene expression changes play a role in the evolution of candidate pollen feeding genes in Heliconius butterflies. Genome Biol Evol 8:2581–2596. https://doi.org/10.1093/gbe/evw180

    Article  Google Scholar 

  17. Wu Y, Wang W, Wang BLD, Shen W (2008) Cloning and expression of the cocoonase gene from Bombyx mori. Sci Agric Sin 41:3277–3285

    Google Scholar 

  18. Ye Y, Godzik A (2014) Comparative analysis of protein domain organization. Genome Res 14:343–353

    Article  Google Scholar 

  19. Geng P, Lin L, Li Y, Fan Q, Wang N, Song L, Li Y (2014) A novel fibrin(ogen)olytic trypsin-like protease from Chinese oak silkworm (Antheraea pernyi): purification and characterization. Biochem Biophys Res Commun 445:64–67

    Article  Google Scholar 

  20. Pandey JP, Sinha AK, Jena K, Gupta VP, Kundu P, Pandey DM (2018) Prospective utilization of Antheraea mylitta cocoonase and its molecular harmony with nature. Int J Adv Res 6:1014–1019

    Article  Google Scholar 

  21. Prasad BC, Pandey JP, Sinha AK (2012) Study of Antheraea mylitta cocoonase and its use in cocoon cooking. Am J Food Technol 7:320–325

    Article  Google Scholar 

  22. Rodbumrer P, Arthan D, Uyen U, Yuvaniyama J, Svasti J, Wongsaengchantra PY (2012) Functional expression of a Bombyx mori cocoonase: potential application for silk degumming. Acta Biochim Biophys Sin 44:974–983

    Article  Google Scholar 

  23. Tingting G, Xiaoling T, Minjin H et al (2021) Cocoonase is indispensable for Lepidoptera insects breaking the sealed cocoon. PLoS Genet 16(9):e1009004

    Google Scholar 

  24. Yang J, Yan R, Roy A, Xu D, Poisson J, Zhang Y (2015) The I-TASSER suite: protein structure and function prediction. Nat Methods 12:7–8

    Article  Google Scholar 

  25. Yang J, Wang W, Li B, Wu Y, Wu H, Shen W (2009) Expression of cocoonase in silkworm (Bombyx mori) cells by using a recombinant baculovirus and its bioactivity assay. Int J Biol 1:107–112

    Article  Google Scholar 

  26. Padamwar MN, Pawar AP (2004) Silk sericin and its applications: a review. J Sci Ind Res 6:323–329

  27. Johnny RV, Karpagam S (2012) Degumming of silk using protease enzyme from Bacillus species. Intern J Sci Nat 3:51–59

    Google Scholar 

  28. Pandey DM, Pandey JP (2014) Cocoonase enzyme: current and future perspectives. Austin J Biotechnol Bioeng 1:2

    Google Scholar 

  29. Pandey JP, Mishra PK, Kumar D, Sinha AK, Prasad BC, Singh BMK, Paul TK (2011) Possible- efficacy of 26 kDa Antheraea mylitta cocoonase in cocoon cooking. Intern J Biol Chem 5:215–226

    Article  Google Scholar 

  30. Devi YR, Singh LR, Devi SK (2012) Comparative evaluation of commonly adopted methods of oak tasar silk cocoon cooking. Intern J Curr Res Review 4(1):106–110

    Google Scholar 

  31. Kafatos FC, Williams CM (1964) Enzymatic mechanism for the escape of certain moths from their cocoons. Science 146:538–540

    Article  Google Scholar 

  32. Kafatos FC, Tartakoff AM, Law JH (1967) Cocoonase. I. Preliminary characterization of a proteolytic enzyme from silk moths. J Biol Chem 242:1477–1487

    Article  Google Scholar 

  33. Gai T, Tong X, Han M, Li C, Fang C, Zou Y, Hu H, Xiang H, Xiang Z, Lu C, Dai F (2020) Cocoonase is indispensable for Lepidoptera insects breaking the sealed cocoon. PLoS Genet 16(9):e1009004

    Article  Google Scholar 

  34. Smith G, Kelly JE, Macias-Muñoz A, Butts CT, Martin RW and Briscoe AD. Evolutionary and structural analyses uncover a role for solvent interactions in the diversification of cocoonases in butterflies. Proc R Soc B. 2018;2852017203720172037.https://doi.org/10.1098/rspb.2017.2037

  35. Dutta A, Katarkar A, Chaudhuri K (2013) In-silico structural and functional characterization of a V. cholerae O395 hypothetical protein containing a PDZ1 and an uncommon protease domain. PLos One 8(2):e56725

    Article  Google Scholar 

  36. Pakdel JD, Zakeri S, Raz A, Djadid ND (2020) Identification, molecular characterization and expression of aminopeptidase N-1 (APN-1) from Anopheles stephensi in SF9 cell line as a candidate molecule for developing a vaccine that interrupt malaria transmission. Malar J 19:79

    Article  Google Scholar 

  37. Arunkumar KP, Sahu AK, Mohanty AR, Awasthi AK, Pradeep AR, Urs SR, Nagaraju J (2012) Genetic diversity and population structure of Indian golden silkmoth. PLoS ONE 7(8):e43716

    Article  Google Scholar 

  38. Jolly MS, Chaturvedi SN, Prasad S (1968) A survey of tasar crops in India. Ind J Sericult 7:56–57

    Google Scholar 

  39. Hummon AB, Lim SR, Difilippantonio MJ, Ried T (2007) Isolation and solubilization of proteins after TRIzol® extraction of RNA and DNA from patient material following prolonged storage. Biotechniques 42:467–472

    Article  Google Scholar 

  40. Gasteiger E, Hoogland C, Gattiker A, Duvaud S, Wilkins MR, Appel RD, Bairoch A (2005) Protein identification and analysis tools on the ExPASy server. In John M. Walker (ed). Totowa: The Proteomics Protocols Handbook, Humana Press; 571–607.

  41. Geoujon C, Deleage G (1995) SOPMA: significant improvements in secondary structure prediction from multiple alignments. Comput Appl Biosci 11:681–684

    Google Scholar 

  42. Chou PY, Fasman GD (1974) Conformational parameters for amino acids in helical, β-sheet, and random coil regions calculated from proteins. Biochemistry 13(2):211–222

    Article  Google Scholar 

  43. Chou PY, Fasman GD (1974) Prediction of protein conformation. Biochemistry 13(2):211–222

    Article  Google Scholar 

  44. Petsalaki EI, Bagos PG, Litou ZI, Hamodrakas SJ (2006) PredSL: a tool for the N-terminal sequence-based prediction of protein subcellular localization. Genom Proteom Bioinform 4(1):48–55. https://doi.org/10.1016/S1672-0229(06)60016-8

    Article  Google Scholar 

  45. Roy A, Kucukural A, Zhang Y (2010) I-TASSER: a unified platform for automated protein structure and function prediction. Nat Protoc 5:725–738

    Article  Google Scholar 

  46. Cilia E, Pancsa R, Tompa P, Lenaerts T, Vranken W (2014) The DynaMine webserver: predicting protein dynamics from sequence. Nucleic Acid Res 42:W264–W270

    Article  Google Scholar 

  47. Rose GD (2019) Ramachandran maps for side chains in globular proteins. Proteins 87(5):357–364

    Article  Google Scholar 

  48. Zhang Y (2008) I-TASSER server for protein 3D structure prediction. BMC Bioinfo 9:40

    Article  Google Scholar 

  49. Laskowski RA, MacArthur MW, Moss DS, Thornton JM (1993) PROCHECK: a program to check the stereochemical quality of protein structures. J Appl Cryst 26:283–291

    Article  Google Scholar 

  50. Laskowski RA, Rullmannn JA, MacArthur MW, Kaptein R, Thornton JM (1996) AQUA and PROCHECK-NMR: programs for checking the quality of protein structures solved by NMR. J Biomol NMR 8:477–486

    Article  Google Scholar 

  51. Lata S, Pandey DM, Pandey JP (2013) Unraveling the sequence similarities, conserve domain and 3D structure of cocoonase to gain insights into their functional integrity. Int J Comput Bioinfo In Silico Model 2:141–146

    Google Scholar 

  52. Morris AL, MacArthur MW, Hutchinson EG, Thornton JM (1992) Stereochemical quality of protein structure coordinates. Proteins 12:345–364

    Article  Google Scholar 

  53. Ho BK, Brasseur R (2005) The Ramachandran plots of glycine and preproline. BMC Struct Biol 5:14

    Article  Google Scholar 

  54. Mahmoodi NM, Moghimi F, Arami M, Mazaheri M (2010) Silk degumming using microwave irradiation as an environmentally friendly surface modification method. Fibers Polymers 11:234–240

    Article  Google Scholar 

  55. Zhang Y, Skolnick J (2005) TM-align: a protein structure alignment algorithm based on TM-score. Nucleic Acids Res 33:2302–2323

    Article  Google Scholar 

  56. Wiederstein M, Sippl MJ (2007) ProSA-web: interactive web service for the recognition of errors in three-dimensional structures of proteins. Nucleic Acids Res 35:407–410

    Article  Google Scholar 

  57. Lovell SC, Davis IW, Arendall WB III, de Bakker PIW, Word JM, Prisant MG, Richardson JS, Richardson DC (2003) Structure validation by Calpha geometry: phi, psi and Cbeta deviation. Proteins 50(3):437–450. https://doi.org/10.1002/prot.10286

    Article  Google Scholar 

  58. Liu H, Han H, Li J, Wong L (2005) DNATISMiner: a web-based software toolbox to recognize two types of functional sites in DNA sequences. Bioinformatics 21:671–673

    Article  Google Scholar 

  59. Marchler BA, Lu S, Anderson JB, Chitsaz F, Derbyshire M, DeWeese-Scott C, Fong JH, Geer LY, Geer RC, Gonzales NR, Gwadz M, Hurwitz DI, Jackson JD, Ke Z, Lanczycki CJ, Lu F, Marchler GH, Mullokandov M, Omelchenko MV, Robertson CL, Bryant SH (2011) CDD: a Conserved Domain Database for the functional annotation of proteins. Nucleic Acids Res 39:D225–D229

    Article  Google Scholar 

  60. Marchler A, Derbyshire MK, Gonzales NR, Lu S, Chitsaz F, Geer LY, Geer RC, He J, Gwadz M, Hurwitz DI, Lanczycki CJ, Lu F, Marchler GH, Song JS, Thanki N, Wang Z, Yamashita RA, Zhang D, Zheng C, Bryant SH (2015) CDD: NCBI’s conserved domain database. Nucleic Acids Res 43(D1):D222–D226

    Article  Google Scholar 

  61. Ochoa A, Llinás M, Singh M (2011) Using context to improve protein domain identification. BMC Bioinformatics 12:90

    Article  Google Scholar 

  62. Bailey TL, Elkan C (1994) Fitting a mixture model by expectation maximization to discover motifs in biopolymers. Proceedings of the second international conference on intelligent systems for molecular biology. AAAI Press, Menlo Park, pp 28–36

    Google Scholar 

  63. Letunic I, Khedkar S, Bork P (2021) SMART: recent updates, new developments and status in 2020. Nucleic Acids Res 49:D458–D460. https://doi.org/10.1093/nar/gkaa937

    Article  Google Scholar 

  64. Andreeva A, Howorth D, Chothia C, Kulesha E, Murzin A (2014) SCOP2 prototype: a new approach to protein structure mining. Nucl Acid Res 42(D1):D310–D314

    Article  Google Scholar 

  65. Andreeva A, Kulesha E, Gough J, Murzin A (2020) The SCOP database in 2020: expanded classification of representative family and superfamily domains of known protein structures. Nucl Acid Res 48(D1):D376–D382

    Article  Google Scholar 

  66. Mortazavi M, Torkzadeh-Mahani M, Kargar F, Nezafat N, Ghasemi Y (2019) In silico analysis of codon usage and rare codon clusters in the halophilic bacteria L-asparaginase. Biologia 75:151–160

    Article  Google Scholar 

  67. Yang J, Roy A, Zhang Y (2013) Protein-ligand binding site recognition using complementary binding-specific substructure comparison and sequence profile alignment. Bioinformatics 29:2588–2595

    Article  Google Scholar 

  68. Mothay D, Ramesh KV (2020) Molecular dynamics simulation of homology modeled glomalin related soil protein (Rhizophagus irregularis) complexed with soil organic matter model. Biologia 76:699–709

    Article  Google Scholar 

  69. Birney E, Clamp M, Durbin R (2004) Genewise and genomewise. Genome Res 14:988–995

    Article  Google Scholar 

  70. Baum D (2008) Reading a phylogenetic tree: the meaning of monophyletic groups. Nat Educ 1(1):190

    Google Scholar 

  71. Kumar S, Stecher G, Li M, Knyaz C, Tamura K (2018) MEGA X: molecular evolutionary genetics analysis across computing platforms. Mol Biol Evol 35(6):154–1549

    Google Scholar 

  72. Garg A, Bhasin M, Raghava GP (2005) Support vector machine-based method for subcellular localization of human proteins using amino acid compositions, their order, and similarity search. J Biol Chem 280:14427–14432

    Article  Google Scholar 

  73. Petersen TN, Brunak S, von Heijne G, Nielsen H (2011) SignalP 4.0: discriminating signal peptides from transmembrane regions. Nat Methods 8:785–786

    Article  Google Scholar 

  74. Anand P, Pandey JP, Pandey DM (2021) Study on cocoonase, sericin, and degumming of silk cocoon: computational and experimental. J Genet Eng Biotechnol 19(1):32. https://doi.org/10.1186/s43141-021-00125-2

    Article  Google Scholar 

  75. Zhang C, Freddolino PL, Zhang Y (2017) COFACTOR: improved protein function prediction by combining structure, sequence and protein-protein interaction information. Nucleic Acids Res 45:W291–W299

    Article  Google Scholar 

  76. Yang J, Zhang Y (2015) Protein structure and function prediction using I-TASSER. Curr Protoc Bioinform 52:5.8.1-5.8.15. https://doi.org/10.1002/0471250953.bi0508s52

    Article  Google Scholar 

  77. Li Y, Wang S, Umarov R, Xie B, Fan M, Li L, Gao X (2018) DEEPre: sequence based enzyme EC number prediction by deep learning. Bioinformatics 34(5):760–769

    Article  Google Scholar 

  78. Chakraborty S, Muthulakshmi M, Vardhini D, Jayaprakash P, Nagaraju J, Arunkumar KP (2015) Genetic analysis of Indian tasar silk moth (Antheraea mylitta) populations. Sci Rep 5:15728

    Article  Google Scholar 

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Acknowledgements

DBT, New Delhi, India, is greatly acknowledged for providing Bioinformatics Facility at BITSnet SubDIC to Department of Bioengineering & Biotechnology, Birla Institute of Technology, Mesra, Ranchi, India. Kind help regarding TASAR cocoon and analysis and discussion of the present study provided by Dr. J. P. Pandey, Scientist, CTR&TI, Ranchi, Jharkhand, India, is also acknowledged. DBT, Government of India, New Delhi, is gratefully acknowledged for providing research grant (BT/PR5375/PBD/19/233/2012 dated 10-06-2013) support to DMP. DBT GOI and TEQIP Phase III is also acknowledged for providing fellowship to Ms. Sneha.

Funding

DBT, Government of India, New Delhi is gratefully acknowledged for providing research grant (BT/PR5375/PBD/19/233/2012 dated 10–06-2013) support to DMP. DBT GOI and TEQIP Phase III is also acknowledged for providing fellowship to Ms. Sneha.

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  1. Department of Bioengineering and Biotechnology, Birla Institute of Technology, Mesra, Ranchi, 835215, Jharkhand, India

    Sneha Sneha & Dev Mani Pandey

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S and DMP designed the study and analyzed the data. S performed the experiments, analyzed the data, and wrote the manuscript. All authors contributed to the final revision of the manuscript. The authors read and approved the final manuscript.

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Supplementary Information

Additional file 1:

Figure S1. NCBI blast result of cocoonase sequence against Antheraea mylitta—GCA_014332785.1 (AM_v1.0). The blast result show that sequences are matched with A. mylitta isolate AMDABA2020 scaffold18_size7685921, whole genome shotgun sequence. Figure S2. NCBI blast result of cocoonase sequence against Antheraea mylitta—GCA_014332785.1 (AM_v1.0). The blast result indicated the 2 matches only with A. mylitta isolate AMDABA2020 scaffold18_size7685921, whole genome shotgun sequence. Figure S3. Secondary structure prediction of Antheraea mylitta cocoonase (AmCoc) from PSPIRED server: (a) Predicted helix, strand and coil of the protein (b) Secondary structure map of cocoonase. Figure S4. MEME tool based result of Antheraea mylitta cocoonase (AmCoc) of KM388539.1 showing two strong motifs in the sequence highlighted in red (MFCAGPPEGGKDSCQGDSGGP) at position 84–104 and in lime green (INKVPYQAYLLLQKBNEYFQC) at position 56- 76. Figure S5. Enzyme Commission numbers and active sites for Antheraea mylitta predicted cocoonase based on the template of PDB ID: 3cskA having C-score of 0.065. The predicted active-site residues are 9, 12, 25, 38, 42 and 77 is highlighted with magenta color code.

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Sneha, S., Pandey, D.M. In silico structural and functional characterization of Antheraea mylitta cocoonase. J Genet Eng Biotechnol 20, 102 (2022). https://doi.org/10.1186/s43141-022-00367-8

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