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. 2018 Apr 27;8(5):227. doi: 10.1007/s13205-018-1260-9

Purification, developmental expression, and in silico characterization of α-amylase inhibitor from Echinochloa frumentacea

Priyankar Panwar 1, A K Verma 1,✉, Ashutosh Dubey 1
PMCID: PMC5924430  PMID: 29719769

Abstract

Barnyard (Echinochloa frumentacea) and finger (Eleusine coracana) millet growing at northwestern Himalaya were explored for the α-amylase inhibitor (α-AI). The mature seeds of barnyard millet variety PRJ1 had maximum α-AI activity which increases in different developmental stage. α-AI was purified up to 22.25-fold from barnyard millet variety PRJ1. Semi-quantitative PCR of different developmental stages of barnyard millet seeds showed increased levels of the transcript from 7 to 28 days. Sequence analysis revealed that it contained 315 bp nucleotide which encodes 104 amino acid sequence with molecular weight 10.72 kDa. The predicted 3D structure of α-AI was 86.73% similar to a bifunctional inhibitor of ragi. In silico analysis of 71 α-AI protein sequences were carried out for biochemical features, homology search, multiple sequence alignment, phylogenetic tree construction, motif, and superfamily distribution of protein sequences. Analysis of multiple sequence alignment revealed the existence of conserved regions NPLP[S/G]CRWYVV[S/Q][Q/R]TCG[V/I] throughout sequences. Superfam analysis revealed that α-AI protein sequences were distributed among seven different superfamilies.

Keywords: α-Amylase inhibitor, Barnyard millet, Bifunctional inhibitor, In silico analysis, Expression analysis

Introduction

α-AI is extensively found in many plant seeds and tubers, being particularly abundant in cereals and legumes (Franco et al. 2002; Mehrabadi et al. 2010). These molecules play a key role in plant defense toward pests and pathogens (Franco et al. 2000), which cause severe damages to field crops and stored grains (Koiwa et al. 1997; Pereira et al. 1999; Franco et al. 2002). As these inhibitors could show different specificities against α-amylases from different sources and inhibitors with a wide specificity spectrum are strongly favoured for insect control (Franco et al. 2000). Several kinds of α-amylase and proteinase inhibitors in seeds and vegetative organs act to regulate the numbers of phytophagous insects (Konarev 1996; Chrispeels et al. 1998; Gatehouse and Gatehouse 1998). α-AI are attractive candidates for the control of seed weevils as these insects are highly dependent on starch as an energy source (Franco et al. 2000). In cereal seeds, α-AI are proteins with 120–130 amino acids based on their primary and tertiary structures, disulphide bonds positions and reactive site localization α-AI may be classified into six families (lectin-like, knotting-like, Kunitz-like, γ-purothionin-like, thaumatin-like and cereal-type) (Richardson 1981; Strobl et al. 1995). Many insects have several α-amylases that differ in specificity, and successful utilization of a food source is dependent on the expression of α-amylase for which there is no specific inhibitor (Silva et al. 2000). The α-AI have long been proposed as possible important weapons against pests whose diets make them highly dependent on α-amylase activity. In vitro and in vivo trials using α-AI, including those made under field conditions, have now fully confirmed their potential for increasing yields by controlling insect populations (Franco et al. 2000). α-AIs have been isolated and characterized in white bean, kidney bean, sorghum, green gram, black gram, wheat, little millet and finger millet (Mulimani and Supriya 1993; Veronique et al. 1997; Kokiladevi et al. 2005; Heidari et al. 2005; Sivakumar et al. 2006; Barrett and Udani 2011) However, there is no report on presence of α-AI in barnyard millet.

Barnyard millet (Echinochloa frumentacea) is important millet grown in the arid and semiarid region of the world. Barnyard millet is a good source of protein, fat, carbohydrates, and crude fiber (Kumar and Parameshwaran 1998; Veena et al. 2005; Devi et al. 2014) apart from mineral (Panwar et al. 2016) and vitamins (Veena et al. 2005). It also contains phytochemicals, such as phenolic acids, flavonoids and tannins (Kulkarni et al. 1992; Panwar et al. 2016) which serve as good source of natural antioxidants.

The present study, α-AI, was investigated in the barnyard (E. frumentacea) and finger (Eleusine coracana) millet. The α-AI genes and protein from barnyard millet were purified. We isolated the α-AI and performed a comparative in silico analysis of the reference nucleotide and protein sequences of α-AI from different organisms available in NCBI and ExPASy databases. The sequences were utilized for study of variation in their biochemical features, multiple sequence alignment, and sequence homology, phylogenetic tree construction, distribution of motifs, and superfamily using various bioinformatics tools and software.

Materials and methods

Plant materials

Seeds of different varieties of barnyard millet (VL21, VL29, VL172, VL207, and PRJ1) were procured from Vivekananda Parvatiya Krishi Anushandhan Sansthan, Almora, (ICAR) and Uttrakhand University of Horticulture and Forestry, Bharsar, Uttrakhand, India.

α-AI activity

Seeds (1 g) were finely ground in pestle mortar and mixed with 10 ml 1% NaCl (w/v) by shaking for 1 h and kept overnight at 4 °C. The mixture was centrifuged and final volume of supernatant was made with 25 ml with 1% NaCl solution. α-AI activity was measured in the supernatant. The enzyme was assayed using the procedure of Bernfeld (1955). One unit of amylase was defined as the amount of enzyme which yields 1 mol of glucose at 37 °C for 1 min at pH 6.7. One unit of inhibitory activity is that which reduce the activity of amylase by one unit under the assay conditions. Seeds of different developmental stages of Barnyard millet variety PRJ1 (viz. 7, 14, 21, and 28 days and matured) was harvested and α-AI was isolated and assayed.

Purification of α-AI

Purification of α-AI was done as described by McEwan et al. (2010) with slight modification. Barnyard millet variety PRJ1 seeds (50 g) were ground with 200 ml of 0.02M phosphate buffer (6.9 pH) containing 1% (w/v) polyvinylpolypyrrolidone. The mixture was stirred at room temperature (25 °C) for 4 h and then filtered through muslin cloth. The residue was re-extracted and combined filtrate was centrifuged at 12,000g for 20 min and collected the supernatant. The obtained supernatant was treated with ammonium sulfate salt to 80% saturation for overnight at 4 °C. The precipitated protein was collected by centrifugation at 10,000 rpm for 20 min. The supernatant was decanted and the pellet was dissolved in a minimum amount of phosphate buffer (20 mM, pH 6.9). The ammonium sulfate fractions were dialyzed against 10 mM phosphate buffer (pH 6.9) at 4 °C for 48 h with repeated changes of buffer. The protein was concentrated in PEG-6000 at 4 °C until. α-AI activity and protein content was measured in concentrated fraction using starch as substrate (Bernfeld 1955) and Bradford method (Bradford 1976), respectively. Concentrated sample obtained after dialysis was loaded into a DEAE-cellulose column (28 × 1.25 cm), equilibrated with 0.02M phosphate buffer (pH 6.9). Stepwise elution was carried out with a linear gradient of 0.1–0.5 M NaCl in 0.02 M phosphate buffer. Fractions (2 ml) were collected at 0.42 ml/min elution rate. Total protein was monitored by the absorbance at λ280nm on a spectrophotometer. All fractions were analyzed for α-AI activity, active fractions were pooled, and protein content was measured in each fraction by the Bradford method (1976). Active fractions were concentrated and were used for carrying out size-exclusion chromatography using Sephadex G 75 columns. The standard molecular weight marker protein catalases (240 kDa), Bovine serum albumin (66 kDa), ovalbumin (43 kDa), and lysozyme (13.5 kDa) were used for the determination of molecular weight. The SDS-PAGE of purified protein samples was analyzed using the method described by Laemmli (1970).

Semi-quantitative PCR-based expression profiling of α-AI

Different stages of seeds (100 mg) of barnyard millet variety PRJ1 were ground in with liquid nitrogen. The ground seeds were immediately mixed with 1 ml of RNA-XPress Reagent and transferred to a 2.0 ml collection tube and RNA isolation was performed as per the protocol given in the RNA—press kit procured from Himedia Pvt. Ltd. Complementary DNA (cDNA) was synthesized using reverse transcriptase (RT) by ProtoScript® First Strand cDNA Synthesis kit (New England Biolabs).

Eleusine coracana alpha-amylase–trypsin bifunctional inhibitor gene, partial cds (DQ494211.1) sequence was retrieved from NCBI (http://www.ncbi.nlm.nih.gov/) for primer designing (forward ACAATCCGCTGGACAGCTGC and reverse CCGAGTAAGGAGAGGCAGAA). For semi-quantitative analysis, tubulin gene was selected as endogenous internal standard. The tubulin primer (forward CTCCAAGCTTTCTCCCTCCT and reverse GCATCATCACCTCCTCCAAT) used as internal control was designed from Genbank database (Acc. no. CX265249). The primers were custom synthesized by SBS Gentech Co. Ltd., Biochem Lifesciences, New Delhi.

Semi-quantitative PCR analysis of α-AI in different developmental stages of seeds of barnyard millet was carried by made the reaction mixture contain 200 ng of genomic DNA, 200 µM of each dNTPs, 1 µM each primer, 1U Taq polymerase, 1.5 mM Mg2+ and 1X PCR buffer. Amplification was carried in temperatures: 95 °C for 5 min, followed by 30 cycles of 94 °C for 45 s, 60 °C for 45 s, 72 °C for 2 min and final extension for 10 min at 72 °C. The PCR amplification was resolved on 1% (w/v) agarose gel.

In silico analysis of α-AI sequence

Amplified PCR products were sequenced by automated DNA sequencer at the DNA Sequencing Facility, SciGenome Labs private LTD, Cochin, Kerala, India. The sequence analysis was done using NCBI database by employing BLASTN algorithm (http://www.ncbi.nlm.nih.gov/GenBank/htmL) (Altschul et al. 1990). Nucleotide sequence was translated into protein sequence using ExPASy translate tool (http://web.Expasy.Org/translate/) and used for in silico characterization. The tertiary structure of α-AI was predicted using the homology modelling approach at SWISS-MODEL workspace (http://swissmodel.expasy.org/) (Guex and Peitsch 1997; Arnold et al. 2006).

In silico analysis of different classes of α-AI

Seven classes of α-AI were analyzed separately using reference protein sequence entries for these α-AI classes from online databases. Representative protein sequences were used as probes to the BLAST database from NCBI (http://www.ncbi.nlm.nih.gov/). The protein sequences in FASTA format from refseq entries, which were shown to exhibit α-AI activities, were selected for further in silico study. The evolutionary history was inferred using the neighbor-joining method (Saitou and Nei 1987). The tree was drawn to scale, with branch lengths in the same units as those of the evolutionary distances used to infer the phylogenetic tree. The evolutionary distances were computed using the Poisson correction method and were in the units of the number of amino acid substitutions per site (Zuckerkandl and Pauling 1965). All positions containing gaps and missing data were eliminated. Evolutionary analyses were conducted in MEGA5 (Tamura et al. 2011). For domain search, the Pfam site (http://www.sanger.ac.uk/software/pfam/ search. html) was used. Superfam server (http://supfam.cs.bris.ac.uk/SUPERFAMILY/hmm.html) was used for the analysis of superfamily present of the protein sequences. Domain analysis was used MEME (http://meme.sdsc.edu/meme/meme.html) (Bailey and Elkan 1994). The conserved protein motifs deduced by MEME were characterized for biological function analysis using BlastP (http://www.ncbi.nlm.nih.gov/) and domains were studied with Interproscan providing the best possible match based on highest similarity score.

Physiochemical data were produced from various tools in the EXPASY Proteomic server (Clustal W, ProtParam, Protein calculator, Compute pI/Mw, ProtScale) (Kyte and Doolittle 1982). The molecular weights (kDa) of the various α-AIs were calculated by the addition of average isotopic masses of amino acid in the protein and deducting the average isotopic mass of one water molecule. The pI of the enzyme was calculated using pKa values of amino acid according to Bjellqvist et al. (1993).

Results and discussion

α-AI quantity

α-AI in seeds of barnyard millet varieties varied from 36.27 ± 0.33 to 24.82 ± 0.63 U/g, while in seeds of finger millet varieties, it ranged from 24.81 ± 0.30 to 20.04 ± 0.19 U/g. It indicates that barnyard millet contains higher α-AI activity compared to finger millet. In barnyard millet varieties, α-AI was distinctly higher in variety PRJ1 (36.27 ± 0.33 U/g) followed by other VL172 (27.68 ± 0.23 U/g), VL29 (26.73 ± 0.58 U/g), VL207 (26.72 ± 0.69 U/g) and VL21 (24.82 ± 0.63 U/g), respectively. α-AI in seeds of finger millet varieties was markedly higher in variety VL315 (24.81 ± 0.30 U/g) followed by four other varieties VL146 (22.90 ± 0.45 U/g), VL324 (21.95 ± 0.54 U/g), VL149 (21.00 ± 0.38 U/g) and VL204 (20.04 ± 0.19 U/g), respectively. Results revealed that α-AI content in seeds of barnyard millet varieties showed inhibitory activity from 60.32 ± 0.46 to 41.26 ± 0.84%, while α-AI content in seeds of finger millet varieties exhibited inhibitory activity from 41.27 ± 0.27 to 33.34 ± 0.18% (Fig. 1). Duncan post hoc analysis of α-AI in seeds of barnyard millet and finger millet showed nine groups. No significant difference was observed between varieties falling within a single group depicted with the same superscript at P ≤ 0.05, i.e., group a (PRJ1), group b (VL172), group c (VL29 and VL207), group d (VL21 and VL315), group f (VL146), group g (VL324), group h (VL149), and group i (VL204). Kokiladevi et al. (2005) studied the effect of α-AI activity crude protein extracts from the seeds of Vigna sublobata on larval α-amylase of insect (Callosobruchus analis) and exhibited that inhibitory activity 110.01% for Vigna umbellata, 80.50% for V. sublobata, and 70.03 for V. Glabracens. Barnyard millet variety PRJ1 contained the highest α-AI; hence, it was chosen for the purification and characterization of α-AI.

Fig. 1.

Fig. 1

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α-AI in seeds of different varieties of barnyard millet (VL21, VL29, VL172, VL207, and PRJ1) and finger millet (VL146, VL149, VL204, VL315, and VL324). Values are expressed as mean ± standard deviation (n = 3). Means with different letters (a, b, c, d, e and f) were significantly different at the level of P < 0.05

Screening of α-AI at different developmental stages of seed

Barnyard millet variety PRJ1, which showed the highest α-AI activity, was subjected to the screening of α-AI activity at different developmental stages of their seed. α-AI activity of seeds increased from 7 days after seed set to maturation stage (Table 1). α-AI 35.98 ± 0.07 U/g was found highest in matured seed with specific inhibitory activity 8.99 U/mg followed by other, 28 days (32.55 ± 0.12 U/g), 21 days (31.40 ± 0.05 U/g), 14 days (25.67 ± 0.39 U/g), and 7 days (18.61 ± 0.13 U/g), respectively. In matured seeds, α-AI activity was found 59.09 ± 0.09%.

Table 1.

Screening of α-AI at different developmental stages of maturation of barnyard millet seed

Seed stage Inhibition (U/g) % inhibition Specific inhibitory activity (U/mg)
7 days 18.61 ± 0.13 30.37 ± 0.04 4.65
14 days 25.67 ± 0.39 41.38 ± 0.09 6.42
21 days 31.40 ± 0.05 48.16 ± 0.14 7.85
28 days 32.55 ± 0.12 52.78 ± 0.28 8.14
Matured seed 35.98 ± 0.07 59.09 ± 0.09 8.99
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Screening of α-AI in different developmental stages of seed of barnyard millet (PRJ1), i.e., 7, 14, 21, and 28 days and matured seed. Values are mean values ± standard deviation of three determinations (n = 3)

Richardson (1991) reported inhibitors as a storage protein because of presence in a large amount in dry/matured seed. α-AI represents about 6% of the protein in soybean (Rackis and Anderson 1964), up to 10% of the total protein of barley seeds (Mikola and Kirsi 1972), over 10% of the soluble proteins in potato tubers (Weder 1981) and about 20% of the soluble proteins of seeds of the Brazilian Carolina tree Adenanthera pavonina (Richardson et al. 1986). Hence, matured seeds of barnyard millet variety PRJ1 contained high α-AI protein and showed highest α-AI activity. Kokiladevi et al. (2005) reported, during the development of Vigna sublobata seed the α-AI activity was detected after 10 days of seed development and gradually increased until maturation of seeds, i.e., 15 days (45.23 IU/g), 20 days (93.27 IU/g), 25 days (126.25 IU/g), 30 days (151.39 IU/g), and dry seed (155.20 IU/g), respectively; similar pattern was observed in seeds of barnyard millet in our investigation.

Purification of α-AI

α-AI from matured seeds of barnyard millet variety PRJ1 was extracted with the specific activity 27.87 U/mg in 0.02 M phosphate buffer (pH 6.9) containing 1% polyvinylpolypyrrolidone. Specific activity of α-AI after 80% ammonium sulfate precipitation was 50.77 U/mg with 1.82 purification fold. After ion-exchange chromatography, specific activity of α-AI was found 271.03 U/mg with 9.73-fold purification (Table 2). After gel-filtration chromatography specific activity of α-AI was found 620.14 U/mg with 22.25-fold purification which was approximately 8% in yield (Fig. 2). Shivaraj and Pattabiraman (1981) also characterized two α-AI from finger millet (Elusine coracana Geartn) after subjecting to 55% ammonium sulfate precipitation, dialysis against 2 mM sodium acetate buffer, pH 5.0, CM-cellulose and Sephadex G-50 and found 14.3 and 16.5 kDa protein. SDS-PAGE electrophoresis analysis of the purified α-AI showed the presence of a single band in Coomassie Blue R-250 dye (Fig. 3). Its apparent molecular mass was approximately 14.3 kDa. The molecular mass was also confirmed by gel-filtration chromatography (Fig. 2). In the gel filtration, applied sample resolved the protein in a single peak (fraction number 37–50) which contained α-AI activity. The calculated elution volume (Ve) was 78.25 ml. The molecular weight of α-AI was determined from the standard calibration curve, which was approximately 14 kDa (Fig. 4). α-AIs have been purified from various sources and found the molecular weight between the range of 14.0 and 77.0 kDa (Table 3). The molecular weight of the α-AI of barnyard millet was found relatively low compared to Phaseolus vulgaris (Veronique et al. 1997), Palo fierro (Guzman-Partida et al. 2007), and Phaseolus acutifolius (Yamada et al. 2001), but was found identical with Elusine coracana (Shivaraj and Pattabiraman 1981), Panicum miliaceum (Nagaraj and Pattabiraman 1985), and Vigna sublobata (Kokiladevi et al. 2005).

Table 2.

Purification table of α-AI protein from Barnyard millet seed (variety PRJ1)

Purification steps Volume (ml) Total inhibitory activity (U/ml) Protein (mg/ml) Specific activity (U/mg) Fold purification Yield (%)
Crude extract 121 25.69 0.92 27.87 1 100
Ammonium sulfate precipitation 6.5 363.64 7.16 50.77 1.82 76
Ion-exchange 2 397.60 1.47 271.03 9.73 26
Size exclusion 5 267.90 0.43 620.14 22.25 8
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Fig. 2.

Fig. 2

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Purification profile of α-AI with Sephadex G-75 (gel-filtration chromatography). Marker protein mixture contained catalase (240 kDa), Bovine serum albumin (66 kDa), ovalbumin (43 kDa), and lysozyme (14.3 kDa)

Fig. 3.

Fig. 3

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SDS-PAGE of purified α-AI from barnyard millet seed (PRJ1) lane 1, crude protein; lane 2, ammonium sulfate precipitate at 80%; lane 3, ion-exchange chromatography; lane 4, gel-filtration chromatography; lane 5 molecular weight marker

Fig. 4.

Fig. 4

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Molecular weight determination of α-AI (AAI) from the standard curve drawn between log10 molecular weight v/s elution volume (Ve)

Table 3.

α-AI purified from different organisms

Source organism Purification techniques Size of α-amylase inhibitor Subunits References
Elusine coracana CM-Cellulose and Sephadex-G75 14.3 and 16.5 kDa Monomer Shivaraj and Pattabiraman (1981)
Panicum miliaceum CM-Cellulose, DEAE-Cellulose and Sephadex-G75 14 kDa Monomer Nagaraj and Pattabiraman (1985)
Colocasia esculenta DEAE-Sephacel and Sephadex G-100 17 and 19 kDa Monomer McEwan et al. (2010)
Phaseolus vulgaris Chromatofocusing and Gel filtration 43 kDa Dimer Veronique et al. (1997)
Palo fierro Affinity Chromatography 77 kDa Dimer Guzman-Partida et al. (2007)
Vigna sublobata Sephadex-G75 and RP-HPLC 14 kDa Monomer Kokiladevi et al. (2005)
Triticum aestivum FPLC – Dimer Heidari et al. (2005)
Phaseolus acutifolius DEAE-Sephacel and ConA-Sepharose 35 kDa Dimer Yamada et al. (2001)
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Semi-quantitative PCR for expression analysis of α-AI

Semi-quantitative PCR of different developmental stages of barnyard millet seeds showed increased levels of the transcript from 7 to 28 days, while in matured seeds of barnyard millet, α-AI gene expression was not found (Fig. 5). Variation in the band intensity would, therefore, represent differences in cDNA concentration. Intensity of bands was revealed by relative densitometry values in gel on densitometry analysis (Alpha EaseFC software, Alpha Innotech Corporation, USA) found increasing order of intensity, i.e., in 7 days (3.3%), 14 days (7.8%), 21 days (18.3%), 28 days (31.0%), matured seed (0.0%) and in tubulin gene (39.5%).

Fig. 5.

Fig. 5

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α-AI gene expression profiling in different developmental stages (7, 14, 21, and 28 days and matured seed) of seeds of barnyard millet (PRJ1). Sterile distilled water was used as a control. Tubulin was used as an internal control

Sequencing and characterization of α-AI gene sequence

The amplified PCR product was sequenced to found 315 bp. NCBI nucleotide BLAST (http://www.ncbi.nlm.nih.gov/) revealed 99% homology with E. coracana alpha-amylase–trypsin bifunctional inhibitor gene, partial cds (gb|DQ494211.1). The translated product of DNA sequence contained 104 amino acids, which was retrieved from ExPASy translate tool (http://web.expasy.org/translate/) (Fig. 6).

Fig. 6.

Fig. 6

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Translated protein sequence (104 amino acids) form α-AI nucleotide sequence (315) bp. Conserved sequences are highlighted. Two conserved motifs ‘N-P-L-P-[S/G]-C-R-W-Y-V-V-[S/Q]-[Q/R]-T-C-G-[V/I]’ (amino acids, 1–17) and ‘L-E-D-L-P-G-C-P-R-Q-V-Q-R-E-F-A-[A/P/R]-K-L-V-T-[E/P]-[G/A]-E-C-N-L-S-T-[I/V]-H-[G/N]’ (amino acids 65–96), were found in α-AI of barnyard millet

The 3D structure model of α-AI was constructed in SWISS-MODEL workspace using already existing α-AI structure (Tenebrio molitor Larval Alpha-Amylase complex with the bi- functional inhibitor of ragi) as a template. 1–98 amino acids were used for the construction of the 3D structure and 86.73% similarity was found with the template sequence (1tmqB). Predicted 3D structure of α-AI of barnyard millet is shown in (Fig. 7). Very less E value (1.64068e−42) in sequence identity indicates that the 1tmqB and α-AI of barnyard millet has a very similar structure.

Fig. 7.

Fig. 7

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Three-dimensional structural model of α-AI from barnyard millet. The 3D structure model of α-AI was constructed in SWISS-MODEL workspace using α-AI structure of ragi as a template. 1–98 amino acids were used for the construction of the 3D structure and 86.73% similarity was found with the template sequence

Bioinformatics analysis for characterization of α-AI

Amino acid composition of the translated product of α-AI gene from barnyard millet was analyzed by ProtParam to find the molecular weight (10.72 kDa), theoretical pI (6.77), and negatively charged as it contained 12 negatively charged amino acids and 11 positively charged amino acids (Table 4). Aliphatic index of α-AI was 83.93. Aliphatic index of protein measures the relative volume occupied by aliphatic side chains of the amino acids: alanine, valine, leucine, and isoleucine. Globular proteins with high aliphatic index have high thermostability and an increase in aliphatic index protein thermostability increases (Ikai 1980; Rawlings et al. 2006). The amino acid composition of α-AI protein sequence was in (Table 5). Ala, Arg, Gly, Glu, Gly, Leu, Pro, and Ser were major amino acids constituting about 57.68% α-AI. Six cysteine residues present in the sequence revealed that α-AI bear disulfide bonds, which were believed to be essential for conformational stability and catalytic activity (Hung et al. 2003) (Fig. 6).

Table 4.

Characterization of α-AI from barnyard millet

Source organism No. of Amino acids Molecular weight Theoretical pI No. of negatively charged amino acids No. of positively charged amino acids Instability index Aliphatic index GRAVY
Echinochloa  frumentacea 104 10,720.5 6.77 12 11 43.55 83.93 0.007
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Table 5.

Amino acid composition of α-AI from Barnyard millet

S. no. Amino acid Number Composition (%)
1 Ala (A) 8 7.69
2 Arg (R) 8 7.69
3 Asn (N) 2 1.92
4 Asp (D) 4 3.84
5 Cys (C) 6 5.77
6 Gln (Q) 5 4.8
7 Glu (E) 8 7.69
8 Gly (G) 9 8.65
9 His (H) 3 2.88
10 Ile (I) 3 2.88
11 Leu (L) 10 9.62
12 Lys (K) 3 2.88
13 Met (M) 2 1.92
14 Phe (F) 1 0.96
15 Pro (P) 8 7.69
16 Ser (S) 9 8.65
17 Thr (T) 4 3.84
18 Trp (W) 1 0.96
19 Tyr (Y) 3 2.88
20 Val (V) 7 6.73
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Alignment of homologous sequences was performed with Mega 5.0 (Tamura et al. 2011) showed two conserved motifs, namely, ‘N-P-L-P-[S/G]-C-R-W-Y-V-V-[S/Q]-[Q/R]-T-C-G-[V/I]’ (amino acids, 1–17) and ‘L-E-D-L-P-G-C-P-R-Q-V-Q-R-E-F-A-[A/P/R]-K-L-V-T-[E/P]-[G/A]-E-C-N-L-S-T-[I/V]-H-[G/N]’ (amino acids, 65–96), were found in α-AI of barnyard millet and these sequences are homologous to α-AI of E. coracana, Sorghum bicolor and Zea mays. (Fig. 8). Superfam analysis of protein sequence of α-AI of barnyard millet revealed their similarity to proteinase/ α-AI family (Bifunctional inhibitor/lipid-transfer protein/seed storage 2S albumin super family) with Amaranthus hypochondriacus, Hordeum vulgare, Triticum aestivum, S. bicolor, and Secale cereal.

Fig. 8.

Fig. 8

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Phylogenetic tree constructed by NJ method based on α-AI protein sequences similarity

In silico analysis of protein sequences of α-AI

Seventy-one protein sequences of α-AI were retrieved from NCBI protein database. The accession numbers of retrieved sequences along with species names are listed in Table 6. Analysis of multiple sequence alignment revealed the presence of conserved regions throughout sequences. In sequences, a conserved site ‘MASKSS[I/C][T/D] LLLAAVL[A/V]S[V/I]’ was observed toward their N-terminus, followed by one more sequence ‘LV[T/A][S/P]G[H/Q]CN[V/L][M/A]T[V/I]HN[A/T/V][P/R]Y’. Evolutionary relationships between different sequences were studied using phylogenetic tree constructed by Neighbor-joining method (Fig. 9). Overall, seven major clusters were observed in the phylogenetic tree. Cluster ‘1’ represents 12 sequences of A. hypochondriacus, E. frumentacea, H. vulgare, T. aestivum, S. bicolor, and S. cereale. The biochemical features of this cluster are listed in Table 6. The amino acid residues in sequences of this cluster ranged from 25 to 171 with a molecular weight range 2.71–18.52 kDa. Isoelectric point (pI) for this group was placed between 3.92 and 7.50. The instability index is used to measure in vivo half-life of a protein (Guruprasad et al. 1990). The proteins which have been reported as in vivo half-life of less than 5 h showed an instability index greater than 40, whereas those having more than 16 h half-life (Rogers et al. 1986) have an instability index of less than 40. Instability index of this cluster placed between 25.76 and 57.42. Aliphatic index of protein measures the relative volume occupied by aliphatic side chains of the amino acids: alanine, valine, leucine, and isoleucine. Globular proteins with high aliphatic index have high thermostability and an increase in aliphatic index increases protein thermostability (Ikai 1980; Rawlings et al. 2006). Aliphatic index of cluster one ranged from 21.25 to 93.47. The variation among α-AI in this group in terms of physiological parameters like a number of negatively charged and positively charged amino acids and hydropathicity (GRAVY). Cluster ‘2’ represents seven α-AI sequences of H. vulgare, Ricinus communis, and T. aestivum. The amino acids of this group ranged between 44 and 690 with molecular weight 4.80–75.75 kDa. The theoretical pI of this group was found from 5.23 to 7.56. Instability index of this cluster ranged between 25.65 and 57.61. Aliphatic index of cluster two ranged from 66.10 to 92.42 represents high thermostability of this group. Cluster ‘3’ represents S. bicolor, H. vulgare, Zea mays, Oryza sativa, and E. coracana. This cluster was further divided into two subclusters. Subcluster 1 includes 6 sequences of S. bicolor. Subcluster 2 includes sequences of S. bicolor, H. vulgare, Zea mays, Oryza sativa, and E. coracana. The amino acid residues of this cluster ranged 105–185 and molecular weight 11.47–19.62 kDa with pI values placed between 6.45 and 8.96. Instability index of cluster 3 ranged between 41.62 and 73.58, indicated that in vivo half-life of proteins of this cluster are less than 5 h and aliphatic index of this group ranged from 66.95 to 99.01. Cluster 4 consists α-AI sequences of Delonix regia and T. aestivum. The amino acid residues of this cluster ranged 19–121 and molecular weight ranged 2.07–13.89 kDa and pI values placed between 9.08 and 9.99. Instability index of this cluster ranged between 50.14 and 55.23 and Aliphatic index ranged from 41.05 to 95.12. Cluster 5 represents the bacterial α-AI sequences of Streptomyces (S. ghanaensis, S. avermitilis, S. roseosporus, S. griseosporeus, S. olivaceoviridis, S. tendae, S. rochei, and S. aureofaciens) and one sequence of R. communis. These α-AI contained amino acids ranged 36–120 and their molecular weight ranged from 3.93 to 12.62 kDa. The pI of this group was ranged from 4.11 to 7.73. Instability index of these bacterial sequences ranged 15.97–38.69, indicated that in vivo half-life of these proteins are more than 16 h. Aliphatic index of cluster 5 ranged from 56.67 to 90.19. Cluster 6 represents the α-AI sequences of Arabidopsis thaliana, Corynebacterium matruchotii, Coix lacryma-jobi, E. coracana, and Zea mays. The sequences of cluster 6 contained amino acids in the range of 95–205 with molecular weight ranged from 9.33 to 20.62 kDa and their pI value ranged in 5.21–9.89. Instability index of this cluster ranged between 9.45 and 56.43 and Aliphatic index ranged from 26.82 to 113.67 represents high thermostability variation in this group. Cluster 7 represents 13 α-AI sequences of Delonix regia, H. vulgare, T. aestivum, Oryza sativa, R. communis, P. vulgaris, and Medicago truncatula. The amino acids residues in this group ranged from 22 to 769 with molecular weight ranged 2.31–78.59 kDa and theoretical pI values ranged from 3.84 to 9.42.

Table 6.

List of source organism of retrieved α-AI protein sequences (with accession number)

S. no. Source organism Accession no. Total sequences
1 Oryza sativa NP_001059199.1, P29421 2
2 Zea mays NP_001232812.1, NP_001106233.1, NP_001105061.1, NP_001148385.1, NP_001147967.1, NP_001148116.1 6
3 Sorghum bicolor XP_002461684.1, XP_002461685.1, XP_002459322.1, P81367, XP_002459323.1, XP_002461687.1, XP_002459556.1, P81368 8
4 Corynebacterium matruchotii ZP_07404539.1 1
5 Streptomyces ghanaensis ZP_06575095.1 1
6 Streptomyces avermitilis NP_822072.1 1
7 Streptomyces roseosporus ZP_04713226.1, ZP_06588930.1 2
8 Arabidopsis thaliana NP_973763.1, NP_001117596.1, NP_177496.3 3
9 Medicago truncatula XP_003628867.1, XP_003628864.1 4
10 Ricinus communis XP_002531545.1, XP_002530403.1, XP_002528537.1 3
11 Hordeum vulgare P16968, P13691, P32936, P34951, P01086, P07596, P16969, P28041, P11643 9
12 Triticum aestivum P10846, Q43691, P16852, P16347, P17314, P16850, P01083, P01085, Q43723, P16159, P16851, P01084 12
13 Eleusine coracana P01087, 1B1U, 1003192A, 1BIP 4
14 Secale cereale P83048 1
15 Phaseolus vulgaris Q41114, P81870 2
16 Coix lachryma-jobi P15326 1
17 Delonix regia P86366, P86367 2
18 Streptomyces tendae P01092 1
19 Streptomyces aureofaciens P04082 1
20 Amaranthus hypochondriacus P80403 1
21 Streptomyces griseosporeus P20078, P01093 2
22 Streptomyces olivaceoviridis P20596, P09921 2
23 Streptomyces rochei P07512 1
24 Echinochloa  frumentacea AAI-BM 1
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Fig. 9.

Fig. 9

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Phylogenetic tree of α-AI protein sequences from different source organisms

Superfam tools for super family analysis of sequences of α-AI revealed seven different super families (Table 7). All bacterial α-AI sequences of Streptomyces ghanaensis (ZP_06575095.1), S. avermitilis (NP_822072.1), S. roseosporus (ZP_04713226.1 and ZP_06588930.1), S. griseosporeus (P20078 and P01093), S. olivaceoviridis (P20596 and P09921), S. tendae (P01092), S. rochei (P07512), S. aureofaciens (P04082), and C. matruchotii (ZP_07404539.1) were belong to α-AI tendamistat super family. α-AI sequences of A. hypochondriacus (P80403), A. thaliana (NP_973763.1, NP_001117596.1 and NP_177496.3), D. regia (P86366 and P86367), E. coracana (P01087, 1B1U, 1003192A, and 1BIP), E. frumentacea (AAI-BM), H. vulgare (P16968, P13691, P32936, P34951, P01086, P16969, P28041, and P11643), Oryza sativa (NP_001059199.1), S. cereal (P83048), S. bicolor (XP_002461684.1, XP_002461685.1, XP_002459322.1, XP_002459323.1, XP_002461687.1, XP_002459556.1, P81367, and P81368), T. aestivum (P10846, Q43691, P16852, P17314, P16850, P01083, P01085, Q43723, P16159, P16851, and P01084), and Zea mays (NP_001232812.1, NP_001106233.1, NP_001105061.1, and NP_001148385.1) were belong to Bifunctional inhibitor/lipid-transfer protein/seed storage 2S albumin super families. α-AI of M. truncatula (XP_003628867.1 and XP_003628864.1), P. vulgaris (Q41114 and P02873), R. communis (XP_002531545.1, XP_002530403.1 and XP_002528537.1) and Zea mays (NP_001147967.1 and NP_001148116.1) were found in Concanavalin A-like lectins/glucanases super family. In protein kinase-like (PK-like) superfamily, α-AI of R. communis (XP_002531545.1, XP_002530403.1 and XP_002528537.1) and Zea mays (NP_001147967.1 and NP_001148116.1) was found. α-AI sequences of H. vulgare (P07596), Oryza sativa (P29421), and T. aestivum (P16347) were found in STI-like superfamily. MEME analysis with given parameters results in frequently observed 20 motifs (Table 8). A set of 29 amino acids sequences ‘WWWCYPGMAIPHNPLPSCRWYVKQQTCGI’ representing motif 1 was conserved and uniformly observed in 32 α-AI protein sequences, revealing their identity with domain AAI_LTSS super family (Table 9).

Table 7.

ProtParam results of α-AI sequences from different source organisms

Serial no. Accession no. Source organism No. of amino acids Molecular weight Theoretical PI Total no. of negatively charged residues (Asp + Glu) Total no. of positively charged residues (Arg + Lys) Instability index Aliphatic index GRAVY
1 NP_001059199.1 Oryza sativa Japonica Group 148 15767.3 7.48 14 15 42.11 87.97 0.099
2 NP_001232812.1 Zea mays 155 16342.1 8.07 12 14 60.78 88.26 0.132
3 NP_001106233.1 Zea mays 155 16301.9 8.07 12 14 60.91 88.90 0.144
4 NP_001105061.1 Zea mays 185 19626.7 8.29 14 17 58.77 85.03 0.077
5 XP_002461684.1 Sorghum bicolor 145 15522.1 7.46 11 12 50.92 92.90 0.334
6 XP_002461685.1 Sorghum bicolor 148 15565.2 8.55 10 14 56.25 87.03 0.253
7 XP_002459322.1 Sorghum bicolor 105 11471.2 7.38 12 13 73.58 66.95 − 0.237
8 XP_002459323.1 Sorghum bicolor 147 15563.2 7.46 11 12 46.56 89.59 0.265
9 XP_002461687.1 Sorghum bicolor 151 15769.3 6.54 12 12 63.29 99.01 0.291
10 XP_002459556.1 Sorghum bicolor 143 14898.5 8.04 9 11 47.84 91.54 0.487
11 ZP_07404539.1 Corynebacterium matruchotii ATCC 14266 170 18288.7 5.21 19 16 35.22 60.29 − 0.405
12 ZP_06575095.1 Streptomyces ghanaensis ATCC 14672 115 12020.6 7.73 9 10 24.87 67.91 − 0.028
13 NP_822072.1 Streptomyces avermitilis MA-4680 119 12552.1 6.54 11 11 38.69 81.18 − 0.004
14 ZP_04713226.1 Streptomyces roseosporus NRRL 11379 101 10220.5 5.60 6 5 33.36 80.40 0.193
15 NP_973763.1 Arabidopsis thaliana 205 20621.4 6.50 8 8 44.78 75.27 0.199
16 ZP_06588930.1 Streptomyces roseosporus NRRL 15998 83 8531.4 5.00 6 4 33.21 67.11 0.00
17 NP_001117596.1 Arabidopsis thaliana 134 14607.2 8.14 8 10 50.12 93.88 0.158
18 NP_177496.3 Arabidopsis thaliana 152 16509.5 8.67 8 12 40.02 96.25 0.384
19 NP_001148385.1 Zea mays 213 21654.2 8.12 9 11 56.43 84.88 0.302
20 XP_003628867.1 Medicago truncatula 265 29260.9 4.91 23 15 25.84 90.11 0.028
21 XP_003628864.1 Medicago truncatula 300 33616.0 5.36 30 22 33.63 92.83 − 0.070
22 NP_001147967.1 Zea mays 749 77272.2 6.69 67 65 49.34 87.33 0.050
23 NP_001148116.1 Zea mays 769 78596.8 6.55 67 64 49.76 87.36 0.092
24 XP_002531545.1 Ricinus communis 681 76273.8 5.96 77 66 29.98 90.18 − 0.109
25 XP_002530403.1 Ricinus communis 346 38765.4 9.42 27 36 38.51 85.06 − 0.149
26 XP_002528537.1 Ricinus communis 690 75756.3 6.05 73 65 36.17 92.42 − 0.082
27 P16968 Hordeum vulgare 146 15816.0 5.36 13 12 27.72 66.10 − 0.127
28 P01093 Streptomyces griseosporeus 78 8121.9 4.22 9 4 15.97 68.85 − 0.012
29 P09921 Streptomyces olivaceoviridis 73 7424.1 4.42 7 1 28.95 64.25 − 0.036
30 P13691 Hordeum vulgare 152 16429.3 5.36 15 13 40.03 83.95 0.186
31 P20596 Streptomyces olivaceoviridis 75 7626.3 4.27 8 1 28.45 62.53 − 0.092
32 P81367 Sorghum bicolor 118 12499.5 8.96 8 14 57.42 71.19 − 0.070
33 P01084 Triticum aestivum 124 13185.1 5.23 12 10 32.71 78.71 0.038
34 P32936 Hordeum vulgare 149 16526.1 5.77 13 12 52.11 73.36 − 0.057
35 P16851 Triticum aestivum 145 15459.7 6.86 12 12 25.76 77.31 − 0.049
36 P34951 Hordeum vulgare 143 15178.7 6.68 9 9 57.59 86.71 0.318
37 P01086 Hordeum vulgare 148 16135.6 7.50 11 12 48.51 84.46 0.075
38 P07596 Hordeum vulgare 203 22163.8 7.77 21 22 60.41 64.43 − 0.469
39 P29421 Oryza sativa subsp. japonica 200 21417.4 8.66 19 22 57.03 81.90 − 0.156
40 P01087 Eleusine coracana 122 13138.3 8.07 10 12 43.55 83.93 0.007
41 P16969 Hordeum vulgare 147 15964.5 8.12 18 20 41.62 95.51 0.019
42 P83048 Secale cereale 25 2712.9 3.92 4 1 32.18 62.40 − 0.260
43 P07512 Streptomyces rochei 76 8129.8 4.49 8 2 32.63 51.32 − 0.250
44 P16159 Triticum aestivum 143 15782.3 5.31 12 10 56.21 81.19 0.015
45 Q43723 Triticum aestivum 121 13831.2 9.23 14 21 53.23 95.12 − 0.130
46 P15326 Coix lachryma-jobi 133 14305.2 6.07 11 10 9.45 58.80 − 0.456
47 Q41114 Phaseolus vulgaris 240 26596.5 5.17 25 18 31.91 82.00 − 0.223
48 P81870 Phaseolus vulgaris 30 3195.6 3.84 4 1 21.78 113.67 0.283
49 1B1U Eleusine coracana 122 13138.3 8.07 10 12 43.55 83.93 0.007
50 1003192A Eleusine coracana 95 9331.5 9.89 2 11 48.72 77.37 0.099
51 1BIP Eleusine coracana 122 13128.2 8.07 10 12 43.55 83.93 0.013
52 P01085 Triticum aestivum 124 13337.3 6.66 11 11 39.41 77.98 0.015
53 P20078 Streptomyces griseosporeus 120 12624.2 4.91 13 9 22.29 80.50 0.225
54 P01083 Triticum aestivum 153 16799.5 7.45 14 15 25.65 78.30 0.022
55 P81368 Sorghum bicolor 116 12776.1 8.55 8 12 47.47 83.19 0.157
56 P28041 Hordeum vulgare 145 15499.7 5.86 14 12 38.64 78.07 − 0.090
57 P16850 Triticum aestivum 145 15516.7 7.50 12 13 35.86 79.38 − 0.031
58 P17314 Triticum aestivum 167 18108.1 7.43 11 12 48.69 93.47 0.213
59 P11643 Hordeum vulgare 171 18525.5 6.07 12 11 50.48 86.78 0.177
60 P80403 Amaranthus hypochondriacus 32 3592.1 6.08 3 3 37.70 21.25 − 0.613
61 P16347 Triticum aestivum 180 19633.0 6.77 22 21 56.01 70.44 − 0.476
62 P13867 Zea mays 206 22074.7 8.16 16 19 30.19 53.54 − 0.257
63 P04082 Streptomyces aureofaciens 36 3938.2 4.11 5 2 31.89 56.67 − 0.317
64 P01092 Streptomyces tendae 104 10759.1 6.01 8 7 27.87 90.19 0.179
65 P16852 Triticum aestivum 27 3070.3 4.37 2 1 47.59 57.78 − 0.233
66 Q43691 Triticum aestivum 121 13889.2 9.08 15 21 55.52 95.12 − 0.155
67 P02873 Phaseolus vulgaris 246 27207.2 5.03 25 18 32.97 84.76 − 0.192
68 P86366 Delonix regia 19 2071.3 9.99 1 3 50.14 41.05 − 1.274
69 P86367 Delonix regia 22 2312.4 5.51 4 3 31.83 26.82 − 1.268
70 P10846 Triticum aestivum 44 4796.6 7.56 2 3 57.61 77.50 0.107
71 AAI-BM Echinochloa  frumentacea 104 10720.5 6.77 12 11 43.55 83.93 0.007
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Table 8.

Distribution of Super families among α-AI from different source organisms using superfam server

Serial no. Family Super family Sequences accession no. (range of amino acids)
1 Alpha-amylase inhibitor tendamistat Alpha-amylase inhibitor tendamistat ZP_04713226.1 (28–96), ZP_07404539.1 (11–65), ZP_06575095.1 (41–109), NP_822072.1 (33–103), ZP_06588930.1 (10–78), P01093 (2–72), P09921 (2–71), P20596 (2–73), P07512 (2–71), P20078 (34–104), P04082 (2–36), P01092 (31–103)
2 Proteinase/alpha-amylase inhibitors Bifunctional inhibitor/lipid-transfer protein/seed storage 2S albumin NP_001059199.1 (32–138), NP_001232812.1 (33–146), NP_001106233.1 (33–146), NP_001105061.1 (63–176), XP_002461684.1 (30–135), XP_002461685.1 (29–131), XP_002459322.1 (3–102), XP_002459323.1 (33–138), XP_002461687.1 (30–142), XP_002459556.1 (18–137), NP_973763.1 (36–104), NP_001117596.1 (32–113), NP_177496.3 (32–113), NP_001148385.1 (43–117), P16968 (19–136), P13691 (36–147), P81367 (7–110), P01084(6–117), P32936 (30–137), P16851 (13–140), P34951 (30–142), P01086 (24–138), P01087 (2–116), P16969 (29–138), P83048 (1–25), P16159 (30–137), Q43723 (25–114), 1B1U(2–116), 1003192A (1–93), 1BIP (2–116), P01085 (6–117), P01083 (36–140), P81368 (3–108), P28041 (29–142), P16850 (29–142), P17314 (25–160), P11643 (32–164), P80403 (1–32), P16852 (2–27), Q43691 (25–114), P10846 (6–44), AAI-BM
3 Legume lectins Concanavalin A-like lectins/glucanases XP_003628867.1 (25–258), XP_003628864.1 (25–259), NP_001147967.1 (28–256), NP_001148116.1 (34–266), XP_002531545.1 (49–277), XP_002530403.1 (42–251), XP_002528537.1 (34–274), Q41114 (23–223), P02873 (24–228)
4 Protein kinases, catalytic subunit Protein kinase-like (PK-like) NP_001147967.1 (375–688), NP_001148116.1 (393–704), XP_002531545.1 (339–631), XP_002528537.1 (333–622)
5 Kunitz (STI) inhibitors STI-like P07596 (24–201), P29421 (23–195), P16347 (1–178)
6 Family 19 glycosidase Lysozyme-like P15326 (10–133)
7 Osmotin, thaumatin-like protein Osmotin, thaumatin-like protein P13867 (2–206)
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Table 9.

MEME analysis of α-AI sequences

Motifs Motifs presents in no. of sequences Motifs width Meme.xmL (peptide) best possible match Domain
1 32 29 WWWCYPGMAIPHNPLPSCRWYVKQQTCGI AAI_LTSS super family
2 22 32 LEDLPGCPREMQRDFAKTLVTEGECNLMTIHG Local conserved domains
3 32 15 MKRRCCQELAKIPQY Local conserved domains
4 32 15 CRCEALRIMMDGMYT Local conserved domains
5 10 50 PAPECVHYYQDWRYTFVTNDCAITYSVTVEYQDGQEVPCRILNPGDITTF Local conserved domains
6 20 21 HHQLILSAAVLLSVFAAAAAT Local conserved domains
7 4 50 WRHRYEIIAGVASALHYLHHEWEQRVIHRDIKSSNVMLDENYNARLGDFG PKc_like super family
8 4 50 RSEFLAELSIIAGLRHRNLVRLQGWCYKKGEILLVYDYMPNGSLDRHLFD PKc_like super family
9 8 26 KNHIVAVEFDTFMDEQFHDVNHNHIK Lectin_L-type superfamily
10 2 50 QQAMRCVAKLMPCQPYIHLSIPPPPLCCNPMKQIAEKDVSCLCTAFKHPD AAI_LTSS super family
11 3 50 DVRISFRAYTTCVQSTEWHIDSELVSGRRHVITGPVKDPSPSGRENAFRI STI super family
12 6 38 HEFSYKELSFATKGFDEKNLIGQGDFGVVYKGILPKHN PKc_like super family
13 6 21 GFSGATQGSYETHDILWWSFS Lectin_L-type super family
14 2 49 EKYSGAEVHEYKLMACGDWCQDLGVFRDLKGGAWFLGATEPYHVVVFKK STI super family
15 4 15 AECPWILGGGTMPSK Local conserved domains
16 7 16 PGYGTNGNYVLGLVLC Local conserved domains
17 5 25 PGCRKEVMKLTAASIPAVCKLPIPN AAI_LTSS super family
18 4 42 EGRILEAVDPRLGNEYEEGEARRVLLLGLACSHPEPALRPGM Local conserved domains
19 4 35 FYKAPFQIRDSTTGNVMSFDTNFTMNITTHRQANS Lectin_L-type super family
20 2 50 MLHRNWDLSFKFPNFFGPYRNDIINYQGDAVESNGTIQLTKIENDINMPY Lectin_L-type super family
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Conclusions

The mature seeds of barnyard millet variety PRJ1 contain higher α-AI activity compared to finger millet and the α-AI activity is increased during the developmental stages of seed up to 7 days. α-AI gene from barnyard millet variety PRJ1 contains 315 bp nucleotides and translated product contains 104 amino acids with MW 10.72 kDa. Bioinformatic analysis reveals that it has more similar to the bifunctional inhibitor of ragi. Similarity analysis of various α-AI showed a conserved region in all the sequences and is distributed in seven superfamilies. Hence, phylogenetic clustering and variation among biochemical features of different α-AI might contribute in further classification and selection of suitable α-AI for biotechnological application. Conserved sequences in motifs may be utilized for designing of specific degenerate primers for identification and isolation of type and class of α-AI. Apart from this sequence information, structural information is also required to identify new α-AI. Thus, in silico analysis might be used for future genetic engineering of α-AI.

Acknowledgements

This work is highly acknowledged to the Department of Science and Technology (DST) for provided facilities under DST-FIST programme. We sincerely thank Director Research, Dean CBSH, G. B. P. U. A. and T., Pantnagar for providing necessary requirements for the research work.

Author contributions

PP contributed in all the experiment under the guidance of AKV and AD. All authors’ proof reads the manuscript.

Compliance with ethical standards

Conflict of interest

The authors declare that they have no conflict of interest.

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