Biochemistry Sample Research Synopsis for Master & PhD Research

                         MOLECULAR DOCKING OF ALPHA-AMYLASE BY REPURPOSING                                                                                 FDA APPROVED DRUGS

1 Dr. Iqra Ahmad (Biochemistry) 2 Dr. Muhammad Naeem (Business Administration)

Laureate Folks International

https://laureatefolks.blogspot.com

laureatefolks@gmail.com, WhatsApp: +923334446261

 

1           INTRODUCTION

Diabetes mellitus type 2 (T2DM) is non-insulin-dependent diabetes mellitus characterized by increased blood glucose concentration and it is one of the most prevalent metabolic disorders. Almost 1 in 10 people are suffering from T2DM and it is a cause of obesity as well. There are several studies for the treatment of T2DM and some of them have drawbacks. This study aims to find a potential inhibitor for alpha-amylase as it directly participates in the formation of glucose from food. FDA-approved drugs will be screened in this study against alpha-amylase for repurposing their potential. Furthermore, there will be no need to check their drug-likeness and ADMET properties as they have already been approved by following all required properties.

Key Words: Type 2 Diabetes Mellitus, Non-insulin-dependent diabetes, FDA approved drugs, Alpha-Amylase, Auto Dock Vina, Molecular Docking, In-silico Drug Designing.

1.1 Research Questions

1.      Is there a potential for FDA-approved drugs to be used as inhibitors for pancreatic amylase?

2.      Is it possible to reduce obesity and heart diseases in the world by treating Diabetes Mellitus Type 2?

3.      Can Diabetes Mellitus Type 2 be treated by inhibiting alpha-amylase without disturbing bacterial flora of the human body?

1.2 Objectives

1.      To virtually screen, a library of about 200 FDA-approved drugs against alpha-amylase.

2.      To utilize the potential of alpha-amylase for the discovery of potent drugs against diabetes mellitus type 2

3.      To indirectly treat obesity and heart diseases by treating diabetes mellitus type 2.

4.      To repurpose already existing drugs for the wellbeing of diabetes mellitus type 2 patients.

 

1.3 Motivation of Research

According to World Health Organization, T2DM was the 9th leading cause of death in 2019 (Diabetes, n.d.). Globally 462 million individuals are suffering from T2DM and it counts for 6.28% of the world's population. There is currently no cure for T2DM and its prevalence is increasing rapidly throughout the world causing a high rate of mortality and morbidity.

South Asians are more prone to T2DM than other ethnic groups even at low BMI. They include almost 2 billion people on the Earth according to a report published by Narayan and colleagues in 2020 (Narayan & Kanaya, 2020). Insulin is used as a therapy for Type 1 diabetes mellitus but administration of insulin is not enough to treat T2DM as cells do not respond to insulin. There is an urgent need to unravel the cure for T2DM to improve the lifestyle of T2DM patients. Robust measurements and advanced modeling methods are required to be utilized

1.4 Research Contribution

There are several kinds of research to find alpha-amylase inhibitors, this research will contribute to finding some more potent inhibitors that can be confidently used for humans. Academia will get an advantage by discovering the potential of FDA-approved drugs in repurposing their role in pancreatic enzymes. There will be opened a new area of research if the potency of the used drugs in this study exceeds previously utilized drugs in T2DM. There is a high chance that industries will need to manufacture concluded drugs as a treatment of T2DM.

2           LITERATURE REVIEW

Diabetes mellitus can be treated by using FDA-approved drugs as inhibitors of carbohydrate hydrolyzing enzyme alpha-amylase. According to McIntyre et al (2019) Diabetes mellitus is a common non-infective disease characterized by increased blood glucose levels. Diabetes mellitus has two types Type 1 diabetes mellitus occurs due to decreased capacity of the pancreas to secrete insulin. Whereas type 2 Diabetes mellitus occurs due to resistance to insulin by cells and several other metabolic factors. Almost 90 to 95% of diabetics have type 2 diabetes (McIntyre et al., 2019).

 

2.1         Type 2 Diabetes Mellitus:

Type 2 Diabetes mellitus (T2DM) is one of the most prevalent metabolic disorders closely relevant to the pandemic of obesity. There is an impaired secretion of insulin in diabetics which contributes to hyperglycemia. Not only insulin secretion is below the required level, but also T2DM is characterized by resistance to insulin. This insulin resistance is commonly called Insulin resistance metabolic syndrome. Both impaired insulin secretion and insulin resistance are core defects in T2DM but according to Bashary et al (2019), there are other defects as well which contribute to non-regulation in glucose metabolism (Oguntibeju, 2019) (Bashary et al., 2019). Moreover, Narayan and colleagues (2020) reported that poor beta-cell function and lean muscle mass contribute to impaired insulin secretion. Also, it was added that fat deposition in the liver and muscle lead to impaired insulin functioning (Narayan & Kanaya, 2020).

According to Oguntibeju (2019), T2DM can cause microvascular and macrovascular complications. Microvascular complications include those complications which affect small blood vessels. These examples include nephropathy, neuropathy, and retinopathy. Macrovascular complications include the complications of arteries. These examples include cardiovascular diseases and cerebrovascular diseases. Cardiovascular diseases are the most common cause of death in patients with T2DM. Moreover, peripheral artery diseases are also included in macrovascular complications of T2DM. Both micro and macrovascular complications can occur in non-diabetic patients as well. But hyperglycemia makes diabetics more prone to these complications. Mostly heart attack is related to diabetes as diabetics have more chance of having complications in their cardiovascular system (Oguntibeju, 2019).

2.2         Alpha-amylase:

Alpha-amylase is present in the pancreas, hydrolyses alpha 1,4 glycosidic bonds, and participates in the conversion of starch (amyloses and amylopectins), glycogen, and maltodextrins to glucose. Considering the results reported by Oguntibeju et all, it can be said that, all complications in T2DM occur due to an increase in blood glucose concentration (Oguntibeju, 2019). Normalizing blood glucose will treat the disease. Bashary in 2019 highlighted that a way to normalize blood glucose concentration is to stop the formation of glucose from the food. Thus inhibiting alpha-amylase will stop the formation of excess glucose and lead to the normal blood glucose level (Bashary et al., 2019).

Inhibition of alpha-amylase is one of the prime therapeutic strategies for the treatment of T2DM. In 2018 it was published by the journal of drug delivery and therapeutics in a study conducted by Pramod Mourya that plant extracts of alternanthera pungens Kunth showed inhibition of alpha-amylase and alpha-glucosidase (In-Vitro Studies on Inhibition of Alpha-Amylase and Alpha Glucosidase by Plant Extracts of Alternanthera pungens Kunth | Journal of Drug Delivery and Therapeutics, n.d.). Rocha et al (2019) used a panel of chalcones with variable substitution patterns. At the conclusion of that study, it was reported that the panel of chalcones with methoxy, hydroxyl, fluoro, and Bromo substitutions show greater affinity towards alpha-amylase and alpha-glucosidase (Rocha et al., 2019).

In another study conducted in 2019 by Raghu et al fucoidan extracted from Turbinaria conoides showed favorable inhibitory properties for alpha-amylase both in vitro and in silico. Inhibition of alpha-amylase was reported as dose-dependent according to that study (Raghu et al., n.d.). In the same year (2019) by Bashary and Khatik, 1, 3 diaryl-3-(arylamino) propane-1-one derivatives were designed, synthesized, and reported as the antioxidants and the potential alpha-amylase inhibitors. That method was in-silico and Auto Dock Vina was applied as the tool for molecular modeling (Bashary & Khatik, 2019)

 Moreover, Khadayat et al (2020) used the Microtiter plate approach for the evaluation of extracts of thirty-two Nepalese medicinal plants against alpha-amylase. Their study concluded Nepalese medicinal plants might contain certain ingredients that show inhibitory activity against alpha-amylase. They suggested that the potential of medicinal plants should further be explored for the treatment of T2DM (Khadayat et al., n.d.).

2.3         FDA approved Drugs:

Food and Drug Administration (FDA) approved drugs are those which have been tested on their possible benefits and risks and their benefits are more than the risk. These drugs are considered to be safe to use within the prescribed amount and have passed through all stages of clinical trials. According to Kandeel et al, FDA-approved drug repurposing means that the drugs will be tested against some compounds and will be tested if they can be useful in some other impaired physiological condition. Many a time the approved drugs are used for another purpose thus reducing the need to pass through clinical trials and directly reaching the market for the new treatment (Kandeel et al., n.d.).

Guan et al reported in 2019 in his paper “ADMET score is a comprehensive scoring function of evaluation of chemical drug-likeliness” that one of the properties that should be qualified by a good drug is ADMET properties which include Absorption, Distribution, Metabolism, Excretion, and, Toxicity (Guan et al., 2019). Checking these properties is termed as a computer-aided prediction of pharmacokinetics. A drug must qualify all of the screenings otherwise it could cause more harm than good. Absorption means how much drug will be absorbed by the small intestine and Distribution means how much an amount of the drug can reach the targeted sites. In this study the targeted site is the pancreas hence the drug is not needed to be absorbed thus a small quantity can be proved to be very beneficial. Metabolism means its conversion into different metabolites. The excretion of a drug is studied to check for how much time a drug can stay in the body and according to this, it is prescribed either once or twice a day. Toxicity is the amount of dose that can be harmful (Chandrasekaran et al., 2018) (Guan et al., 2019).

2.4         In-silico Drug Designing:

In-silico drug repurposing is regarded as an innovative and modern method to achieve reliable drug design. According to Surabhi and Singh (2018), conventional methods of drug designs take years to synthesize and react to different chemicals in the laboratory. Moreover, a great number of resources are utilized and a huge amount of money is wasted in extracting, storing, transporting, synthesizing, and analyzing chemicals in vivo or in vitro. In silico drug, designing is the need of the era and it takes less time, less money and it is efficient. According to different needs of the experiments and distinguishing nature of compounds, in-silico drug designing or computational drug designing is divided into structural-based drug design and ligand-based drug design (Surabhi & Singh, 2018).

This will be the ligand-based drug designing and molecular docking approach will be utilized as a tool in it. Furthermore, this will be the quantitative research analysis.

2.5         Molecular Docking:

According to Pinzi and Rastelli (2019), molecular docking is a key tool used in in-silico or computational data analysis where various ligands and proteins interact as if they have been mixed in a test tube. It involves the identification of therapeutic drug targets and their inhibitors. Virtual screening by molecular docking predicts favorable protein interactions. (Pinzi & Rastelli, 2019) It is a comparatively easy and less time-consuming method if one has the expertise. Nowadays, it is a trend to use molecular docking techniques for finding the compounds which have good binding affinities for the targeted enzyme or any targeted protein (Morris & Lim-Wilby, 2008).

In most cases, some additional steps are performed like checking drug-likeness on Drulito and ADMET properties on Swissadme. FDA-approved drugs are not needed to be tested on ADMET properties.

 

2.6          Auto Dock Vina:

The auto dock is a graphic tool to assist molecular docking. It is different from the auto dock in that later docking with multiple ligands can not be performed. Although auto dock itself uses Perl software to perform multiplicand molecular docking. Auto dock vina is the advanced version of the auto dock. It is used for drug discovery by interacting with proteins and showing their binding energies. Auto dock vina will be utilized in this research.

Auto dock alone cannot perform molecular docking. Proteins and ligands are needed to be prepared before being opened in the vina interface. Auto dock vina uses additional software for the preparation and conversion of virtual library compounds. Also, it uses different software for the visualization of ligand-protein interactions. All of this software will be discussed in this proposal.

Through all these studies it is confirmed that there is a dominant role of alpha-amylase in the treatment of diabetes mellitus type 2 and scientists have been utilizing the hydrolyzing potential of alpha-amylase to reduce exogenous glucose reaching in the bloodstreams. Different plants have been utilized for the inhibition of alpha-amylase and in silico invitro and in vivo studies have been conducted recently to find a potential inhibitor for alpha-amylase. FDA-approved drugs have not been screened for alpha-amylase till now.

3           The Research Model

Figure 1.1


 In this research model, some simple steps will be needed with the expertise in some docking software that will be discussed later in the proposal. This will be the ligand-based drug designing and molecular docking approach will be utilized as a tool in it. Furthermore, this will be the quantitative research analysis. The methodology will be divided into three stages as depicted in figure 1.1

1.      Selection

2.      Preparation

3.      Docking

In selection ligands and the targeted enzyme will be selected. In this study, the ligands are FDA-approved drugs and the target enzyme is alpha-amylase or pancreatic amylase. Then both of them will be prepared to be used for docking. All the ligands will be converted to pdbqt files as this file is required to be prepared to input data in Auto Dock Vina for molecular docking. The targeted enzyme will be prepared by removing extra side chains and all bounded ligands. Also, the grid will be selected to allow the dimensions for interactions. In the end, the enzyme will also be converted to pdbqt file and preceded to docking. Docking results will be visualized in the form of scores.

4           The hypothesis of the Research Study

·         FDA-approved drugs will be proved to be the potential inhibitors for alpha-amylase hereby providing treatment for Type 2 Diabetes Mellitus.

5           THE RESEARCH GAP

Inhibition of Alpha-amylase is directly involved in treating diabetes mellitus type 2 (Bashary et al., 2019). Alpha-amylase should be studied at a higher level to estimate and utilize its potential for the treatment of one of the most prevalent metabolic disorders of the world; diabetes mellitus type 2. Recently many researchers have confirmed the importance of alpha-amylase as a target enzyme and many classes of compounds have been docked and virtually screened against it. The most common anti-diabetic drugs that work by inhibiting alpha-amylase and slowing carbohydrate digestion include acarbose (Pathak S and Narula N. Optimization of PH for the... - Google Scholar, n.d.).

            Many medicinal plant extracts have been studied for inhibiting alpha-amylase and they have shown better results than acarbose but they interfere with gut flora and produce anti-nutritional effects. Also, Carbonaro et al reported that giving more than the required dose will cause a reduced glycemic response which can cause various health complications (Carbonaro et al., 2001; Heo et al., n.d.).

On satisfactory results selected compounds to pass through different phases of clinical trials before reaching the market. Previously approved drugs should be screened against alpha-amylase to discover if any of them can be repurposed as a potential inhibitor of alpha-amylase.

 

6           METHODOLOGY

6.1         Research Design

The research will be performed following the steps in figure 1.1. Previously discussed steps; target and ligand selection, target and ligand preparation, and the interaction of target and ligand by docking.

6.2         Sampling Procedure and Sample Size

As it is a computational study, in-silico sampling will be performed and the libraries of the ligands will be made. 200 FDA-approved drugs will be selected as ligands and collected in the form of a virtual library.

6.3         Sampling Technique

The drug repurposing technique is utilized in this study. In this sampling technique, FDA    approved drugs are screened against a targeted enzyme to repurpose their role in diabetes mellitus type 2 (T2DM).

6.4         Tools of Data Collection

Following databases will be used as the tools of data collection.

·         Drug Bank

·         Protein Data Bank

6.5         Data Collection Procedure and Methods

Protein Databases will be used for the collection of ligands. FDA-approved drugs will be collected from Drug Bank; a database that has all the FDA-approved drugs available in one place. The 3D structure of each drug will be downloaded in the form of a PDB file. Moreover, the 3D structure of the enzyme will be downloaded from Protein Data Bank in PDB format.

6.6         Data Analysis Methods and Software

All the collected data will be analyzed by using the following two software.

·         Open Babble

·         Auto Dock Vina

Open Babble will be used to convert the PDB file into a pdbqt file and auto dock vina will be used to perform rapid screening of protein-ligand interactions. After the conversion of enzyme in pdbqt formate by open babble software, the domains of the enzyme will be highlighted in the form of a grid in Auto Dock vina. It is necessary to select the grid box otherwise the docking will not be performed. Ligands will be provided the grid area to confirm their position of attachment.

The grid area will be prepared by selecting the active domains of the enzyme. Active domains will be found by finding the sites where the ligands were previously bounded when the enzyme will be downloaded in pdb format. If there will be more than one domain and the grid will be covering most of the area of the enzyme then more than one grid will be selected and docking will be performed more than one time in Auto Dock Vina.

 The lowest binding energies will be shortlisted and the topmost effective ligands will be selected.

6.7          Expected Results

Docking scores or scoring function will expectedly be lower than the standard that will indicate the usefulness of the molecular docking analysis. Lower the docking score more will be the affinity of the ligand to bind to the target. All the drugs may not show good potential for inhibiting the targeted enzyme but some of them will expectedly be the potential inhibitors of the targeted enzyme.

6.8         Time Frame to complete the Research Study

1.      Data collection will require about 5 days

2.      Data preparation will require 5 days as well

3.      Docking will take 2 days

4.      Manuscript writing will take about one month

7           Required Time:

Computerized drug design has become a choice due to the least amount of time utilized in this procedure. With the expertise in library designing and in-silico docking methods this will take about 2 weeks in doing experiments and one month in finalizing the manuscript.

8           Proposed budget:

No budget will be required as there is no need to buy any samples, particularly for this study.

9           Required apparatus:

This study will require a laptop with a good working processer. Docking software like Auto Dock vina will be required Moreover Open Babble will be required for forming pdbqt files and Pymol will be required to view the interaction between ligands. Also, Chemdraw software will be required to draw compounds that cannot be downloaded from the Drug Bank.

10       DISCUSSION

Diabetes mellitus Type 2 disease is a chronic illness that is untreatable till now and can cause mortality. In this disease, there is an increased concentration of glucose in the blood that is unable to reach the cells. It is called hyperglycemia. Hyperglycemia can cause various other illnesses including obesity and heart diseases. Complex carbohydrate-containing food items are hydrolyzed by alpha-amylase in the pancreas and converted to glucose. This glucose is dangerous for T2DM patients. Inhibiting alpha-amylase reduces the formation of glucose by hydrolysis thus exogenous glucose becomes no longer to be damaging for the body. For inhibition of alpha-amylase FDA approved drugs will be virtually screened in this study using the auto dock vina.

The inhibition of carbohydrate hydrolyzing enzyme, alpha-amylase by FDA-approved drugs will be the main purpose of this research. By strong binding affinities of FDA-approved drugs against the targeted enzyme (alpha-amylase) one or more potent drugs may be identified through this research. Reducing blood glucose by inhibiting alpha-amylase will treat hyperglycemia and thereby it will be proved to be a cure for Diabetes Mellitus type 2.

11       REFERENCES:

Bashary, R., & Khatik, G. L. (2019). Design, and facile synthesis of 1,3 diaryl-3-(arylamino)propan-1-one derivatives as the potential alpha-amylase inhibitors and antioxidants. Bioorganic Chemistry, 82, 156–162. https://doi.org/10.1016/J.BIOORG.2018.10.010

Bashary, R., Vyas, M., Nayak, S. K., Suttee, A., Verma, S., Narang, R., & Khatik, G. L. (2019). An Insight of Alpha-amylase Inhibitors as a Valuable Tool in the Management of Type 2 Diabetes Mellitus. Current Diabetes Reviews, 16(2), 117–136. https://doi.org/10.2174/1573399815666190618093315

Carbonaro, M., Grant, G., & Pusztai, A. (2001). Evaluation of polyphenol bioavailability in rat small intestine. European Journal of Nutrition, 40(2), 84–90. https://doi.org/10.1007/S003940170020

Chandrasekaran, B., Abed, S. N., Al-Attraqchi, O., Kuche, K., & Tekade, R. K. (2018). Computer-Aided Prediction of Pharmacokinetic (ADMET) Properties. Dosage Form Design Parameters, 2, 731–755. https://doi.org/10.1016/B978-0-12-814421-3.00021-X

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McIntyre, H. D., Catalano, P., Zhang, C., Desoye, G., Mathiesen, E. R., & Damm, P. (2019). Gestational diabetes mellitus. Nature Reviews Disease Primers 2019 5:1, 5(1), 1–19. https://doi.org/10.1038/s41572-019-0098-8

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Rocha, S., Sousa, A., Ribeiro, D., Correia, C. M., Silva, V. L. M., Santos, C. M. M., Silva, A. M. S., Araújo, A. N., Fernandes, E., & Freitas, M. (2019). A study towards drug discovery for the management of type 2 diabetes mellitus through inhibition of the carbohydrate-hydrolyzing enzymes α-amylase and α-glucosidase by chalcone derivatives. Food & Function, 10(9), 5510–5520. https://doi.org/10.1039/C9FO01298B

Surabhi, S., & Singh, B. (2018). COMPUTER AIDED DRUG DESIGN: AN OVERVIEW. Journal of Drug Delivery and Therapeutics, 8(5), 504–509. https://doi.org/10.22270/JDDT.V8I5.1894

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