Integrating In-silico and In-vitro Approaches to Screen the Antidiabetic Drug from Trigonella foenum graecum Linn.

One of cardiovascular diseases, i.e. Diabetes is reported either through absence of insulin or resistance against insulin. Treatment for diabetic disease related to Type 1 and 2 which includes lots of expenditure every year in the form of capsules or preparing different types of formulation. Recently, more than 400 medicinal plants have been screened to fulfill the requirement of the potent antidiabetic drug. Isolation and purification of effective herbal medicine from these medicinal plants to cure diabetes disease are still challenging. In the present study, our group worked on different enzymes that played a crucial role in the carbohydrate metabolism. For these studies, number of secondary metabolites (19) and enzymes (5) were screened in silico for antidiabetic potential. The Original result of these studies which showed that alpha amylase formed best interaction with carpaine (an alkaloid) with the lesser binding energy -7.44 kcal/mol as compared with the standard drug Acarbose. Therefore, further in-vitro studies were included, the screening of alpha amylase inhibitory activity using different solvent extract. At the concentration of 1 mg/ml FGCE showed highest inhibitory activity i.e. 37.7%. Thin layer chromatography (TLC) was also performed to confirm the number of phytochemicals present in different extract. Overall, these studies claimed that medicinal plant posses a potential antidiabetic activity, but still investigation is required to find out and purify the bioactive compound which can be served as a potent antidiabetic drug.


INTRODUCTION
Bioinformatics, Biochemistry and pharmacology techniques are more common and showed its significant impact on drug designing and also showed its demand for production of drugs against intracellular and extracellular diseases. These drugs should be designed and tested within a short period of time with low risk. Recently, Kirchmair and co-authors mentioned about in silico methods for the estimation of chemical interactions with drug metabolizing enzymes including prediction of possible metabolites [1]. In addition, drug basically targets specific molecules that are present in the cellular pathway specific for disease condition or specific against pathogenic microorganism, but remains ineffective to any other important metabolic pathway of the human body [2]. As human being constantly suffers from various life threatening diseases like diabetes, HIV, cancer, etc., it is still challenging to fulfill the demand of an efficient method of drug development to produce an ideal drug [3].
Diabetes mellitus, a chronic metabolic disorder characterized through hyperglycemic condition resulting either through absence of insulin or resistance of available insulin in animal and human model [4]. In diabetes, hyperglycemic condition will appear only when blood glucose level is reported and enhanced in a significant amount and is associated with various abnormalities related to carbohydrate metabolism leading to various cardiovascular and neurological complications. Number of cases related to diabetes enhanced every year and roughly estimated more than 151 million people died per year and suggested that until 2030 the number of people with diabetes is likely to exceed 553 million worldwide. Among diabetes types, Type 2 diabetes is more common and approximately more than 95% people suffering from this disease [5,6]. Type 1 diabetes is caused due to failure of insulin secretion by β-pancreatic cells while Type 2 diabetes occurs due to progressive insulin resistance [7]. As per the literature more than 400 traditional plants have been used for the treatment of diabetes disease [6]. The management of type 2 diabetes could be done by delaying the absorption of glucose through the inhibition of any one of the enzymes that are involved in the carbohydrate metabolism specially the one which hydrolyze or digesting it [8]. It could target inhibition of αglucosidase, α-amylase [8], β-glucosidase [9], glycogen synthase kinase [10]. Activation of glucokinase is also a targeted therapy for the type 2 diabetes. In vitro studies play a crucial role to screen out potent inhibitors of these enzymes from various plants sources [11].
Trigonella foenum graecum Linn. or Fenugreek is most popular Indian medicinal plant because of its broad range applications. Fenugreek possesses various pharmacological properties such as, antioxidant activity, chemopreventive activity, anticancer activity, antidiabetic activity, immunomdulatory effect gastroprotective effect etc. [12]. Apart from its medicinal properties fenugreek also used as condiment, incense, as well as used to embalm mummies [13]. Major secondary metabolites present in the fenugreek are alkaloids, flavonoids, Saponins, tannins etc. as mentioned in Table 1 [14,15,16].
In the present study, in-silico as well as in-vitro attempt is made to understand the possible interaction of the target drugs that would enable to design the potent drug for the treatment of type 2 Diabetes mellitus.

As shown in
Energy minimization of these ligands and further docking analysis was performed using Autodock module available in PyRx Version 0.8 software (http://pyrx.sourceforge.net/). Total 10 conformers were analyzed for each compound to predict the most favorable interaction and final docking interaction between ligand and protein were analyzed using LigPlot software (https://www.ebi.ac.uk/thorntonsrv/software/LIGPLOT/).

Plant material and extract preparation
Fenugreek seeds were collected from a local market of India and authenticated by the Department of Botany, Padmashri Vikhe Patil College, Pravaranagar (Loni), Tal.Rahata, District Ahmednagar, (MS), India. Seeds were ground into fine powder. The powder was successively extracted by maceration in petroleum ether, chloroform, ethanol and water (increasing order of their polarity) and solvent was evaporated to obtain dry crude extracts. Percent yield of the extract in each solvent was calculated [17,18].

In-vitro
Alpha amylase inhibitory activity assay A total of 250 µl of test samples and standard drug (100-1000 µg/ml) were added to 250 µl of 0.20 mM phosphate buffer (pH 6.9) containing α-amylase (0.5 mg/ml in 0.02 M phosphate buffer, pH-6.9 with 0.006 M Sodium Chloride) solution. The reaction mixture was then preincubated at 25°C for 10 min. After incubation, 250 µl of a 1% starch solution (in 0.02 M sodium phosphate buffer, pH 6.9) was added to each tube. The solution was further incubated at 25°C for 10 min. Finally, reaction was terminated with 500 µl of DNSA (3, 5 dinitrosalicylic acid, a chromogen). The test tubes were incubated in a boiling water bath for 5 min and allowed to cool at room temperature. The solution was then diluted with 5 ml distilled water. Absorbance of the reaction mixture was measured at 540 nm. Control shows 100% enzyme activity and prepared using the same procedure replacing the extract with distilled water [19].
The α-amylase inhibitory activity was calculated by using the following formula: % Inhibition = [(Abs control -Abs extracts )/Abs control ] x 100 IC 50 value was determined graphically.

Chromatographic separation
TLC was performed to confirm the presence of different bioactive compound. Chromatoplates were prepared by mixing silica gel and distilled water in 1:2 ratios and applied on a microscope slide at a uniform thickness of 0.5 mm. After drying, the plates were activated in an oven at 110°C 1 hr. 10 µl of the extract were spotted on a chromatoplate, dried and allowed to develop a chromatogram using an appropriate solvent as shown in Table 3. Developed chromatogram was observed with exposure of the plates to iodine vapor [20,21]. Rf value was calculated using the following formula: Rf = Distance travelled by solute (cm) /Distance travelled by solvent (cm)

Molecular Docking Analysis
The molecular docking technique is used to estimate the binding affinities and energies of ligand which played a crucial role in the structure based drug design process [22,23]. In our study, total 19 secondary metabolites reported and isolated from fenugreek which was docked with key regulatory enzymes that are important in the diabetes management. The docking result of  2 and 1a). Carpaine forms a hydrogen bond with the Gln63 residue of the A chain of the alpha amylase and the bond distance is 3.28A° ( Fig. 2A).
Alpha glucosidase does not form any hydrogen bond, but it does interact with carpaine by hydrophobic interaction (Fig. 2B). Similarly Glycogen synthase kinase 3β does not form any hydrogen bond with tigogenin but interact with hydrophobic non-covalent interactions (Fig. 2D).
With the Glucokinase carpaine interact by forming hydrogen bond with Asn204 and Asn 231 with bond distance 3.00A° and 2.77A° respectively (Fig. 2C). The hydrogen bond is very much important for the directionality and specificity, which is required for the selective molecular interaction [26]. Trp58, Tr59, Tyr62, Leu162, Thr163, Asp300, His305 are the residue of the A chain of the alpha amylase those interact with carpaine by hydrophobic interactions (Fig. 2A). Hydrophobic interaction of carpaine with glucokinase clears that Asn204, Asp205, Thr206, Gly229, Cys230, Asn231, Glu256, Gln287, Glu290 amino acid residues of glucokinase are involved (Fig. 2C). As both alpha amylase and glucokinase showed best docking interaction the two enzymes were the topic of interest for further in-vitro analysis. In drug designing, alpha amylase inhibition while glucokinase activation is the important aspect.

In-vitro Alpha Amylase Inhibitory Activity Assay Analysis
Various carbohydrates hydrolyzing enzymes are targeted to decrease the hyperglycemia. These drugs are very much effective in the regulation of glucose metabolism without stimulating or activating the insulin / insulin secretion [27]. Acarbose and Vaglibose are the examples which are considered to be inhibited alpha amylase activity [28]. Alpha amylase inhibitors are a kind of anti-nutrients which suppress hydrolysis of starch [29]. In the present study Acarbose was taken as a control to compare our results. Acarbose showed the highest percent inhibition 65% at the concentration of 1 mg/ml (  [30]. It can be thought that the potent antidiabetic activity shown by the different extract may be due to the presence of various phytochemicals like phenols, flavonoids, saponins, steroids, alkaloids, terpenoids etc. as a bioactive compound [31].
To detect the bioactive compounds present in the fenugreek extracts we proceeded further for the separation of these phytochemicals by TLC method.

TLC Fingerprinting
TLC fingerprinting of fenugreek plant extract using different solvent confirmed the presence of diverse phytochemicals while their Rf values reveal us about their polarity, high Rf value indicates the low polarity and vise versa [32,19]. Investigation of phytochemicals that are present in fenugreek, found that petroleum

CONCLUSION
By analyzing the result we have concluded that secondary metabolites isolated from fenugreek possess and showed potent antidiabetic activity.
In-silico studies hypothesized that among the four enzymes studied alpha amylase enzyme in complex with the carpaine alkaloid would prove the best for further regulation of the antidiabetic activity. In vitro assay confirmed that the phytochemicals present in the different fenugreek extract are responsible for antidiabetic activities. These phytochemicals extracted in different plant extracts includes alkaloids, terpenoids, flavonoids, tannins, polyphenols, polyacetylenes, sterols, saponins are responsible for this activity. Further investigation is required to find out and purify the bioactive compound which can be served as a potent antidiabetic drug.