CATARACTOGENESIS IN RATS BY Momordica charantia L. FRUITS
A dissertation submitted to
THE TAMIL NADU Dr. M.G.R. MEDICAL UNIVERSITY CHENNAI – 600 032
In partial fulfillment of the requirements for the award of Degree of MASTER OF PHARMACY
IN
BRANCH – IV- PHARMACOLOGY
Submitted by Mr. M. BALA SURYA REGISTRATION No. 261725102
Under the guidance of
Dr. A.T. Sivashanmugam, M.Pharm., Ph.D.
Department of Pharmacology
COLLEGE OF PHARMACY
SRI RAMAKRISHNA INSTITUTE OF PARAMEDICAL SCIENCES COIMBATORE - 641 044.
May 2019
This is to certify that the M. Pharm., dissertation work entitled “IN SILICO AND IN VITRO ALDOSE REDUCTASE INHIBITION AND IN VIVO ACTIVITY AGAINST GALACTOSE-INDUCED CATARACTOGENESIS IN RATS BY Momordica charantia L.
FRUITS” being submitted to The Tamil Nadu Dr. M.G.R. Medical University, Chennai, in partial fulfillment of Master of Pharmacy programme in Pharmacology was carried out by Mr. M. BALA SURYA (Registration No.261725102) in the Department of Pharmacology, College of Pharmacy, Sri Ramakrishna Institute of Paramedical Sciences, Coimbatore, under my direct supervision and guidance and to my full satisfaction.
Dr. A.T. Sivashanmugam, M.Pharm., Ph.D.
Asst.Professor, Department of Pharmacology, College of Pharmacy, SRIPMS, Coimbatore-44.
Place: Coimbatore Date:
This is to certify that the M. Pharm., dissertation work entitled “IN SILICO AND IN VITRO ALDOSE REDUCTASE INHIBITION AND IN VIVO ACTIVITY AGAINST GALACTOSE-INDUCED CATARACTOGENESIS IN RATS BY Momordica charantia L. FRUITS”
being submitted to The Tamil Nadu Dr. M.G.R. Medical University, Chennai, in partial fulfillment of Master of Pharmacy programme in Pharmacology was carried out by Mr. M. BALA SURYA (Registration No. 261725102) in the Department of Pharmacology, College of Pharmacy, Sri Ramakrishna Institute of Paramedical Sciences, Coimbatore, under the direct supervision and guidance of Dr. A.T.
Sivashanmugam, M.Pharm., Ph.D., Asst.Professor, Department of Pharmacology, College of Pharmacy, Sri Ramakrishna Institute of Paramedical Sciences, Coimbatore.
Dr. K. Asok Kumar, M. Pharm., Ph.D.
Professor & Head, Department of Pharmacology, College of Pharmacy, SRIPMS, Coimbatore-44.
Place: Coimbatore Date:
This is to certify that the M. Pharm., dissertation work entitled “IN SILICO AND IN VITRO ALDOSE REDUCTASE INHIBITION AND IN VIVO ACTIVITY AGAINST GALACTOSE-INDUCED CATARACTOGENESIS IN RATS BY Momordica charantia L. FRUITS”
being submitted to The Tamil Nadu Dr. M.G.R. Medical University, Chennai, in partial fulfillment of Master of Pharmacy programme in Pharmacology was carried out by Mr. M. BALA SURYA (Register No.
261725102) in the Department of Pharmacology, College of Pharmacy, Sri Ramakrishna Institute of Paramedical Sciences, Coimbatore, under the direct supervision and guidance of Dr. A.T.Sivashanmugam M.Pharm., PhD., Asst.Professor, Department of Pharmacology, College of Pharmacy, Sri Ramakrishna Institute of Paramedical Sciences, Coimbatore.
Dr. T. K. Ravi, M. Pharm., Ph.D. FAGE.
Principal, College of Pharmacy, SRIPMS, Coimbatore-44.
Place: Coimbatore Date:
With the blessing of omnipresent God, let me write that the source of honor for the completion of the work embodied in the present dissertation is due to numerous persons by whom I have been inspired, helped and supported during my work done for M. Pharm degree.
My dissertation would not have been possible without the grace of The Almighty GOD who gave me strength and wisdom to complete this project.
First and foremost, I want to pay all my homage and emotions to my beloved parents Mr. Murugan Ramasamy and Mrs. Arulmozhi Thillainagarajan, without whose blessings this task would not have been accomplished. I bow my head with utter respect to them for their continuous source of inspiration, motivation and devotion to me.
I would like to devote my sincere gratitude to my guide Dr. A.T. Sivashanmugam, M.Pharm., Ph.D. Assistant Professor, Department of Pharmacology, College of Pharmacy, SRIPMS, Coimbatore for his kind encouragement, remarkable guidance and valuable suggestion during the tenure of my work.
I would like to my sincere thanks to Dr.K.Asok Kumar, M.Pharm., Ph.D.
Professor& Head of the Department, Department of Pharmacology, College of Pharmacy, SRIPMS, Coimbatore for his guidance and valuable suggestion during my work.
It is my pleasure to express my sedulous gratitude to our Principal Dr.
T.K.Ravi, M.Pharm., Ph.D. FAGE. College of Pharmacy, SRIPMS, Coimbatore for giving us an opportunity to do this project work and for providing all necessary facilities for it.
I extend my profound gratitude and respectful regards to our Managing Trustee, Thiru. R. Vijayakumhar, Managing Trustee, M/s. SNR Sons Charitable Trust, Coimbatore for providing the adequate facilities in this institution to carry out this work.
My solemn thanks to my dear teachers to Dr. M. Uma Maheswari, M.Pharm., Ph.D. Professor, Dr. V. Subhadra Devi, M.Pharm.,Ph.D. Dr. A
the course of the work.
It is my privilege to express my sincere thanks to Dr. M. Gandhimathi, M.Pharm., Ph.D. Department of Pharmaceutical Analysis, Dr. R. Jayaprakasam, M.Pharm., Ph.D. Professor and Dr. R. Venkatasamy M.Sc., Ph.D. Senior Lab Technician Department of Pharmacognosy, for providing me all the facilities to carry out the analytical work and phytochemical screening studies.
My Special thanks to my friends and Batch mates Padmanaban Pugalenthiren, Nivetha Panneerselvam, Shiny Mariadhas, Nayanika Dwarkanath, Bhargav Iyer Mohan, Nivetha Ravi, Arya P Anil, Karthika Hemanth, Lakshmi Menon, Vijay Durai, Suthakaran Veeran for their kind support and cooperation.
My Special thanks to my juniors Naveena, Narmatha, Kishore, Ajin, Dhanya, Muthukumaran, Saradha Preetha, Nandhu, Vishali, Dhivya, Dhilsha, Auxi for their kind support and cooperation.
I place my heartful thanks to my sweet sisters Mrs. Logeshwari Rathakrishnan and Mrs. Archana Kaliraj for their valuable support.
My special thanks to the office staff of our college Mrs. R. Vathsala, Mrs.
Nirmala and Mrs. Rajeswari for all the help and support given by them to me.
My special thanks to the Lab assistant of our college Mr. G. John and Lab Attenders Mrs. S. Karpagam and Mrs. R. Beula Hepsibah for all the help and support given by them to me.
I wish to thank of Star Color Park for framing project work in a beautiful manner.
Balasurya Murugan
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Introduction
Review of Literature
Aim & Objective
Plan of Work
Materials & Methods
Results & Discussion
Summary & Conclusion
References
Annexure
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INTRODUCTION
Cataract has been derived from the Greek word ‘katarraktes’ which means
‘waterfall’ assumed that an ‘abnormal humour’ developed and flowed in front of lens to decrease vision.
Cataract refers to development of any opacity in the lens or its capsule. It may occur due to formation of opaque lens fibres or due to degenerative process leading to opacification of the normally formed transparent lens fibres[1].
Fig. 1: Picture showing difference between Healthy eye & cataract eye
According to a 2014 estimate the current number of people with visual impairment (which includes both low vision and blindness) is put at 285 million worldwide 39 million people are blind while 246 million people live with low vision.
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Ninety percent of the world’s blind population lives in developing countries. In developed countries, blindness is mainly due to disorders of the posterior segment of the eye while in the developing countries of Asia, Africa, Middle East Africa, Asia, and parts of South America, blindness is predominately due to disorders of the anterior segment of the eye (cataract and corneal scaring).
Several studies have shown a rise in the prevalence of certain eye diseases in the elderly. These include refractive error, eyelid disorders, dry eye syndrome, conjunctival diseases, cataract, age related macular degeneration (ARMD), and glaucoma. In India reported prevalence of low vision and blindness is 32% and 12.2%, respectively, among adults aged 50 years and older. About 58.7% of adults aged 60 years and above were visually impaired and 5.9% were blind [2].
Fig. 2: Picture chart showing proportion of cases of blindness due to major cause
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About 4.25 million adults aged 40 years and above have moderate to severe visual impairment or blindness. The prevalence of blindness and severe visual impairment in 13,599 adults aged 40 years and older was 4.2% and 1.5% respectively [2].
Cataract was the leading cause of blindness (57.6%), followed by glaucoma (14.5%), uncorrected refractive error (11.9%), diabetic retinopathy (8.3%), corneal opacity (4.2%), and ARMD (3.5%) [2].
Symptoms
• Faded colours
• Blurry vision
• Halos around light
• Trouble with bright lights
• Trouble In seeing at night
Risk Factors
• Ageing
• Diabetes
• Excessive intake of alcohol
• Excessive sunlight exposure
• Heredity
• Hypertension
• Overweight
Complications of Cataract
• Blindness
• Falling
• Depression
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[1]• Etiological classification
• Morphological classification
Etiological classification
I. Congenital and development cataract II. Acquired cataract
➢ Senile cataract
➢ Traumatic cataract
➢ Complicated cataract
➢ Metabolic cataract
➢ Electric cataract
➢ Radiational cataract
➢ Toxic cataract
i. Corticosteroid-induced cataract ii. Miotics-induced cataract
iii. Copper (in chalcosis) and iron (in siderosis) induced cataract
➢ Cataract associated with skin diseases
➢ Cataract associated with osseous diseases
➢ Cataract with miscellaneous syndromes
Morphological classification
➢ Capsular cataract
➢ Subcapsular cataract
➢ Cortical cataract
➢ Supranuclear cataract
➢ Nuclear cataract
➢ Polar cataract
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Metabolic cataracts
These cataracts occur due to endocrine disorders and biochemical abnormalities.
A few common varieties of metabolic cataracts are [1].
• Diabetic cataract
• Galactosaemic cataract
• Hypocalcaemic cataract
• Cataract due to error of copper metabolism
Molecular Docking
Molecular docking is a computational technique for exploration of the possible binding modes of a substrate or inhibitor to a given enzyme or receptor to give the optimal interactions. To perform a docking the first requirement is to have the 3D structure of receptor or protein of interest which can be determined by X-ray crystallography or NMR spectroscopy. This protein structure and a 3D database of potential ligands serve as input to a docking programme. The success of a docking programme depends on two components (Target Enzyme & Ligand) [3]. Molecular modeling is a tool for doing chemistry. Molecular docking may be defined as an optimization problem, which would describe the “best-fit” orientation of a ligand that binds to a particular protein of interest. The aim of molecular docking is to achieve an optimized conformation for both the protein and ligand and relative orientation between protein and ligand such that the free energy of the overall system is minimized. In the field of molecular modeling, docking is a method which predicts the preferred orientation of one molecule to a second when bound to each other to form a stable complex.
Knowledge of the preferred orientation may be used to predict the binding affinity between two molecules or strength of association (scoring functions). During the docking process, the ligand and the protein adjust their conformation to achieve an overall “best- fit” and this kind of conformational adjustments resulting in the overall binding is referred to as “induced-fit” [4].
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Drug targets
Target is a naturally existing cellular or molecular structure involved in the process of drug development and meant to act on. Already established targets help in understanding of both how it is involved in human pathology and how the target functions in normal physiology. The new targets are not established targets. New targets include newly discovered protein molecules, and those proteins functions have been clear under scientific research process.
Identification of right target and active site
Target is a protein molecule and it closely related to disease. It plays an important role in signal transduction pathway that often disrupted in the diseased condition.
Enzymes are one of the targets, they have binding pockets for inhibition as well as substrates.
Lipinski’s rule of Five
This rule was postulated by Christopher A. Lipinski in 1997, based on the observation that most of the drugs are relatively small and lipophilic in nature. Lipinski's rule of five is a rule of thumb to evaluate drug-likeness. This rule states that, an orally active "drug-like" molecule has:
• Partition coefficient (log P) less than 5
• Molecular weight under 500 daltons
• Not more than 10 hydrogen bond acceptors (O and N group)
• Not more than 5 hydrogen bond donors (OH and NH group)
• Number of violations less than 5
• All the numbers should be multiples of 5, which is the basis for the rules name.
The rule describes about pharmacokinetic properties of a drug in the human body, including their absorption, distribution, metabolism, and excretion (ADME). But this rule does not predict if a compound is pharmacologically active or not. This set of rules
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suggests that the necessary properties for good oral bioavailability and reflects the notion that pharmacokinetics, toxicity and other adverse effects are directly linked to the chemical structure of a drug [5].
Types of docking
Rigid dockingThe rigid docking is suitable position for the ligand in receptor environment obtained while maintaining its rigidity.
Flexible docking
In this process, receptor-ligand interaction was obtained by changing internal torsions of ligand into the active site while receptor remains fixed.
Docking approaches
Two approaches mainly popular in molecular docking.
Shape complementarity
This technique is used to describe the matching of ligand and protein as complementarity surfaces.
Simulation
It is the actual docking process additionally calculating the interaction energies between ligand and protein molecule.
Mechanics of docking
[6]To perform a docking screen, the first requirement is a structure of a protein.
Protein structure has been determined by using X-ray crystallography or NMR spectroscopy. The protein structure and database of potential ligands serve as inputs to a docking programme. The success of docking program depends on: search algorithm and
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scoring function.
a) Search algorithm
A strict search algorithm would completely elucidate all possible binding modes between ligand and receptor. Various searching algorithms have been developed and widely used in molecular docking software. But it would be too expensive to computationally generate all the possible conformations. Some commonly used searching algorithms are: Monte Carlo (MC) methods, fragment based method, distance geometry, matching method, ligand fit method, point complementarity method, blind docking, inverse docking, genetic algorithms and molecular dynamics.
Monte Carlo (MC) method
Methods are among the most established and widely used stochastic optimization techniques. These methods use sampling technique and are able to generate states of low energy conformations. The system makes random moves and accepts or rejects each conformation based on Boltzmann probability. Simulated annealing is a generalization of a Monte Carlo method for examining the equations of state and frozen states of n-body systems. The initial state of the system has random thermal motion within a specified potential force field. The effective temperature of the system (the degree of random motion) is decreased overtime, until a final stable docked position is obtained. The random motion of the ligand allows for exploration of the local search space, and the decreasing temperature of the system acts to drive it to a minimum energy. One of the most widely used simulated annealing procedures is the Metropolis Monte Carlo simulated annealing algorithm [7].
Fragment based method
Fragment based methods can be described as dividing the ligand into separate protons or fragments, docking the fragments and finally linking these fragments together with target protein. Some mainly used fragment based methods are FlexX.
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Distance geometry
Many types of structural information can be expressed as intra or intermolecular distances. The distance geometry formalism allows these distance to be assembled and 3 dimensional structures consistent with them to be calculated. The fast sampling of the conformational space do not always results in reliable results. An example of a program using distance geometry in docking problem is DockIt.
Matching method
This method focuses on complementarity. Ligand atom is placed at the ‘best’
position in the site generating a ligand receptor configuration that may require optimization.
Ligand fit method
Ligand fit term provide a rapid accurate protocol for docking small molecules ligand into protein active sites for considering shape complimentarity between ligand and protein active sites.
Point complementarity method
These methods are based on evaluating a shape and/or chemical complementarity between interacting molecules [8].
Blind docking
It is introduced for detection of possible binding sites and modes of peptide ligand by scanning the entire surface of protein targets.
Inverse docking
This method uses computer for finding toxicity and side effects of protein targets on a small molecule. Knowledge of these targets combined with that of proteomics pharmacokinetic profile can facilitates the assessment of potential toxicities side effect of drug candidate. One of these protocols is selected for docking studies of particular ligand.
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Genetic algorithm (GA)
It is adaptive heuristic search technique premised on the evolutionary ideas of natural selection and genetics. The basic concept of GA is designed to simulate processes in natural system necessary for evolution, which is akin to the principles first laid down by Darwin. As such they represent an intelligent exploitation of a random search within a defined search space to solve a problem. In a genetic algorithm, there is a population of solutions that undergo mutation and crossover transformations. The newly generated solutions undergo selection, biased towards the fit among them. The algorithm maintains a selective pressure towards an optimal solution, with a randomized information exchange permitting exploration of the search space. A range of programs implements GA for docking [9].
Molecular dynamics (MD)
Molecular dynamics (MD) is widely used as a powerful simulation method in many fields of molecular modeling. In the context of docking, by moving each atom separately in the field of the rest atoms, MD simulation represents the flexibility of both the ligand and protein more effectively than other algorithms. The disadvantage of MD simulations is that they progress in very small steps and thus have difficulties in stepping over high energy conformational barriers, which may lead to inadequate sampling. MD simulations are often efficient at local optimization. Thus a current strategy is to use random search in order to identify the conformation of the ligand, followed by the further subtle MD simulations [10].
b) Scoring functions
The purpose of the scoring function is to delineate the correct poses from incorrect poses, or binders from inactive compounds in a reasonable computation time.
Scoring functions involve estimating, rather than calculating the binding affinity between the protein and ligand and through these functions, adopting various assumptions and
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simplifications. Scoring functions can be divided into:
i) Force-field-based scoring functions ii) Empirical based scoring functions iii) Knowledge-based scoring functions.
Force-field-based scoring functions
Classical Force-field-based scoring functions assess the binding energy by calculating the sum of the non-bonded (electrostatics and van der Waals) interactions.
The electrostatic terms are calculated by a Columbic formulation. Force-field-based scoring functions also have the problem of slow computational speed. Thus cut-off distance is used to handle the non-bonded interactions. This also results in decreasing the accuracy of long-range effects involved in binding.
Extensions of force-field-based scoring functions consider the hydrogen bonds, solvation’s and entropy contributions. Software programs, such as DOCK, GOLD and AutoDock, offer users such functions. They have some differences in the treatment of hydrogen bonds, the form of the energy function, etc. The results of docking with force- field-based functions can be further refined with other techniques, such as linear interaction energy and free-energy perturbation methods (FEP) to improve the accuracy in predicting binding energies.
Empirical scoring functions
In empirical scoring functions, binding energy decomposes into several energy components, such as hydrogen bond, ionic interaction, hydrophobic effect and binding entropy. Each component is multiplied by a coefficient and then summed up to give a final score. Coefficients are obtained from regression analysis fitted to a test set of ligand-protein complexes with known binding affinities. Empirical scoring functions may be treated in a different manner by different software, and the numbers of the terms included are also different. LUDI, PLP, ChemScore are examples derived from empirical scoring functions.
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Knowledge-based scoring functions
Knowledge based scoring functions use statistical analysis of ligand-protein complexes crystal structures to obtain the inter-atomic contact frequencies and distances between the ligand and protein. The scoring is done by statistically observing the intermolecular relation between the ligand and the biological target protein using
“Potential of Mean Force”. The intermolecular interactions are mainly taken into account for the functional group or atoms that occur frequently. The result of this method is evaluated based on the binding interactions. PMF, Drug Score, SMoG and Bleep are examples of knowledge-based functions [11].
Various docking software’s
Over 60 docking software systems and more than 30 scoring functions are reported. Molecular docking is implemented as part of software packages for molecule design and simulation. More than one search method and scoring functions are provided in order to increase the accuracy of the simulations. Only some of the software was made available and a limited number of them are widely used. Commonly used software’s are:
• DOCK
• GOLD (Genetic Optimization for Ligand Docking)
• FlexX (Future Leaders Exchange)
• SLIDE (Screening for Ligands by Induced-fit Docking)
• FRED
• Hammerhead
• Auto Dock
• Auto Dock 4.2 [12]
Applications of Drug Design
❖ Lead identification
❖ Lead optimization
❖ Structural elucidation by X-ray crystallography
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❖ Virtual screening analysis
❖ Structure based drug design
❖ Combinatorial library design
❖ Chemical mechanistic studies [4].
Aldose Reductase (Aldehyde Reductase)
Aldose reductase (AR) is a. cytosolic NADPH-dependent oxido-reductase enzyme that catalyzes the reduction of a variety of aldehydes and carbonyls, including monosaccharides. It is primarily known for catalyzing the reduction of glucose to sorbitol. It is the first step in polyol pathway of glucose metabolism. The polyol pathway was first identified in the seminal vesicle it demonstrated the conversion of blood glucose into fructose, an energy source for sperm cells. The presence of sorbitol in diabetic rat lens was lead to cataract formation [13].
Several studies have suggested that increased reduction of glucose by AR contributes to the development of secondary diabetic complications (neuropathy, nephropathy, retinopathy, cataractogenesis). During hyperglycemic event, the elevated glucose level enhances the activity of AR by increasing glucose flux through polyol pathway. AR messenger ribonucleic acid (mRNA) is highly expressed in the rat lens, retina and sciatic nerve, the major target organs of diabetic complication. The increased activity of AR results in decreased NADPH/NADP+ ratio. It has impact an on other NADPH-dependent enzymes, such as nitric oxide (NO) synthase and glutathione reductase. The retarded activity of the antioxidant enzyme, glutathione reductase causes oxidative stress under diabetic conditions. Increased sorbitol flux through the polyol pathway causes increases in NADH/NAD+ ratio [14].
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Fig. 3: Role of Aldose reductase in cataractogenesis[13]
Structure of Aldose Reductase Enzyme
Aldose reductase was protypical enzyme of the aldo-keto reductase enzyme superfamily. It comprises 315 aminoacids residues and folds into a β and α barrel structural motif composed of 8 parellel β-strands [15].
Adjacent strands are connected by eight peripheral α-helical segments running anti-parallel to the β-sheet. The catalytic active site situated in the barrel core. The NADPH co-factor is situated at the top of the β and α barrel, with the nicotiamide ring projects down in the centre of the barrel and pyrophosphate straddling the barrel lip [16].
Physiological Significance of AR
Aldose reductase contributes to metabolic imbalances associated with diabetes and its complications in the eye and peripheral nerves system. While it is generally accepted that AR-mediated pathogenesis is dependent on chronically elevated ambient
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hexose levels as in diabetes mellitus and galactosaemia. Beneficial roles of AR in the cells when hexose levels are normal are still under investigations. AR gene expression is widespread, as evidenced by the presence of gene transcripts in a large number of human tissues. It is suggested that the enzyme might function physiologically as a general house- keeping enzyme under normal conditions. In addition, new evidence points to a potential role for AR in cytokine-mediating signaling processes [17].
a) Osmoregulatory Role
The kidney is one of the richest tissue sources of AR, with most of the enzyme localized in the medullary portion from which quantities of the enzyme are isolated for biochemical studies. Sorbitol is one of the organic osmolytes that balance the osmotic pressure of extracellular NaCl, fluctuating in accord once with urine osmolality. These findings therefore suggest the osmoregulatory role of AR in the renal homeostasis.
Increased extracellular osmolarity stimulated an increase in intracellular sorbitol.
Ablation of AR gene in mice results in defect in kidney function. The mice become unable to concentrate their urine to normal level. Absence of AR leads to a defect in water resorption, as sorbitol constitutes only 2% of the total osmolality of mouse kidney.
Studies on the factors that interact with these response elements and augment the transcription of AR gene may provide insight into the regulatory mechanisms of the gene expression [17].
b) Detoxification
AR is thought to play a major role in the synthesis of sorbitol as an osmolyte in the kidney medulla, its distribution among tissues unaffected by extracellular osmotic stress suggests an alternate metabolic role. The marked hydrophobic nature of the active site is unusual for an enzyme thought to be involved in the metabolism of aldo-sugars. It has been demonstrated that hydrophobic substrate is the catalytic preference of AR. AR reduced lipid peroxidation-derived aldehydes as well as their glutathione conjugates.
Expression of AR is enhanced under conditions of oxidative stress both in cell culture system and in vivo and that the inhibition of AR increases the accumulation of lipid peroxidation products during inflammation and ischemia. It has been shown that cells
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resistant to oxidative stress express higher levels of AR than the corresponding sensitive cells and that the inhibition of AR increases the sensitivity of these cells to cytotoxic aldehydes. AR is an important component of mechanisms that remove and detoxify these aldehydes when they are generated in oxidized lipids. It could be concluded that AR fulfills a role as an oxidative defense protein. Aldose reductase also catalyzes the reduction of acrolein, a highly reactive and mutagenic molecule generated during lipid peroxidation and as a metabolic by-product of cyclophosphamide. Glucose is one of the endogenous substrates for AR. The enzyme may also act as an extra hepatic detoxification enzyme in various tissues. The significance of AR in the polyol pathway may be quite limited under non-diabetic conditions. It provides an osomolyte sorbitol in the renal medulla and supplies fructose as an energy source of sperm in the seminal vesicle [17].
c) Unique Tissue Distribution Pattern of AR
The unexpected distribution pattern of AR is not only in different species but in tissues other than “target” organs of diabetic complications. In human tissues AR is quite abundant in the epithelial cells lining the collecting tubules in the renal medulla, seminal vesicles, retina, lens and muscle. In mouse, AR mRNA was most abundantly expressed in the testis, and very low level of the transcript was detected in the sciatic nerve and lens.
These results suggest that mouse AR may possess a significant role in the testicular metabolism. The low expression of the enzyme in the nerve and lens was in marked contrast with the findings in rat. It indicated the localization of the enzyme transcript in these “target” organs of diabetic complications. Consistent with these findings is the absence of cataract formation during the course of hyperglycemia in mouse, in contrast with the finding in rat. Rat is the first experimental model of sugar cataract formation.
Immunoblot and immune-histochemical analyses in rat tissues further showed high levels of AR protein in the adrenal gland and various reproductive organs, including the granulosa cells of rat ovary. Cyclic changes in the expression and localization of AR were observed in rat ovary during the estrous cycle. These changes in the enzyme expression were indicated to be under hormonal control and functional role of AR in the female reproductive organ.
Department of Pharamacology Page 17 INVIVO MODELS FOR CATARACTOGENESIS
[18]• Napthalene-induced cataract
• Selenite-induced nuclear cataract
• Glucocorticoid-induced cataract
• Smoke-induced cataract
• UV-induced cataract
• Microwave-induced cataract
• Transforming growth factor β (TGFβ) - induced cataract
• Sugar-induced cataract
➢ Alloxan-induced cataract
➢ Streptozotocin-induced cataract
➢ Galactose -induced cataract
Selenite-induced cataract
Selenite cataract resembles human cataract in many ways such as vesicle formation, increased calcium, insoluble protein, decreased water soluble protein and reduced glutathione (GSH). Selenite cataract shows no high molecular weight protein aggregation or increased disulfide formation and is dominated by rapid calpain-induced proteolytic precipitation while semile cataracts may be produced by prolonged oxidative stress.
Napthalene-induced cataract
Napthalene is oxidized in the liver first to an epoxide and then converted into naphthalene dihydrodiol. This stable component on reaching the eye gets converted
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enzymatically to dihydroxynapthalene. Being unstable at physiological pH 1,2 dihydroxynapthalene spontaneously auto-oxidises to 1,2 napthoquinone and H2O2. It alkylates proteins, glutathione and aminoacids and generates free radicals.
Glucocorticoid-induced cataract
Glucocorticoid cataract results in the formation of steroid-adduct protein induction of transglutaminase and reduction of ATPase activity may lead to cataract.
Steroid cataracts are produced by the activities of glucocorticoids and progressed by way of production of oxidative stress similar to other types of cataract.
Smoke-induced cataract
Cigarette smoke contains trace and heavy metals. The increased metal contents in lens cause lens damage by the mechanism of oxidative stress forming oxygen free radicals by Fenton reaction. Cigarette associated with the accumulation of iron and calcium.
UV-induced cataract
Epidemiological studies have shown a link between exposure to UV radiation in sunlight and development of cataract. Experimental studies confirm that UV radiation induces cataract. There is lack of data on the age dependence in experimental UV radiation cataract.
Microwave- induced cataract
Microwave radiation has been reported to produce posterior subcapsular and cortical cataracts in rabbits and dogs within a short span of time.
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Transforming growth factor β (TGFβ) - induced cataract
TGFβ is induced by injecting approximately 60ng. TGFβ stimulates lens epithelial cells to undergo aberrant morphologic and molecular changes that mimic the changes observed in humans posterior subcapsular and cortical cataract.
Sugar cataract
1) Alloxan- induced cataract
Alloxan is a cyclic urea analog which is highly reactive molecules that is readily reduced to dialuric acid then auto-oxidized back to alloxan resulting in the production H2O2, superoxide and hydroxyl radical. The other mechanism reveals the ability of alloxan to react with protein sulphydryl groups on hexokinase a signal recognition enzyme in the pancreatic β cell that couples changes in the blood glucose concentration to the rate of insulin secretion. Inhibition of glucokinase and other SH- containg membrane proteins on the β-cell would eventually results in cell necrosis with in minutes.
2) Streptozotocin-induced cataract
Diabetic related cataractogenic changes are seen in the animals injected with streptozotocin. The chemical structure of streptozotocin has a glucose molecule with highly reactive nitrosourea side chain which initiates cytotoxic action. The glucose moiety directs this agent to the pancreatic β cells. It binds to the membrane receptor to generate structural damage.
• Process of methylation
• Free radical generation
• Nitric oxide (NO) production
At the intracellular level these major phenomena are responsible for β cells death. The damage caused to β cells alters the sugar metabolism leads to diabetes.
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3) Galactose - induced cataract
It is associated with inborn error of galactose metabolism [19]. Osmotic over hydration of the lens occurs due to accumulation of galactitol when galactose is metabolized by NADPH+ dependent aldose reductase. Aldose reductase is a enzyme involved in secondary diabetic complication including cataractogenesis. It is key enzyme of polyol pathway that catalyse coenzyme NADPH-dependent reduction of glucose to sorbitol and galactose to galactitol [20].Excessive accumulation of intracellular galactitol found in various tissues results in hyper-osmotic effects. In eye this results in cellular swelling which initiates a cascade of biochemical steps that result in lens opacification
[21]. This initiates an unfolded protein response that generates ROS and apoptotic signaling leading to free radical production. Increased free radical generation compromises natural antioxidant defense resulting in oxidative stress lead to cataract formation[22].
Mechanism of galactose-induced cataractogenesis
The changes associated with galactose cataractogenesis include the initial reduction of galactose into galactitol through intervention of aldose reductase with NADPH as a co-factor. Accumulation of galactitol in the lens it was not subsequently metabolized. It creates cellular hypertonicity associated with the following
• Influx of water,
• Swelling of the lens fibres,
• Epithelial cell edema,
• Damage of plasma membrane,
• Compromise of cellular permeability,
• Drop in myinositol level,
• Reduction in Na+, K+, ATPase activity,
• Influx of Na+, Cl-, and efflux K+,
• Loss of glutathione and aminoacids
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These are the morphological, biochemical, enzymatic and molecular alterations in the lens associated with galactose-induced cataracts [23].
Fig. 4: Structure of galactose and galactitol
Fig. 5: Mechanism of galactose-induced cataract
Galactose Galactitol
Increased osmolarity Influx of water
& Osmotic
damage to Lens
Cataract
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Advantages of galactose-induced model
Various animal models have been used for the screening the plants against cataract. Out of that galactose induced cataract is commonly used, it produces the large amount of reduced form, galactitol and finally into glucose. Galactitol is not subsequently metabolised as compared to the sorbitol. In this model it is supposed that factor initiating galactose cataracts in young rats are similar to those involve in the human galactose cataract model. Three mechanism involve in the formation of cataract are oxidation, polyol pathway and non enzymatic glycation[24].
Pharamacological Strategies For Preventing Cataract
[25]Drugs have been developed and aimed to interact at the level of altered lens metabolism and lens pathophysiology. The anti-cataract agents claimed to be effective in vitro, in vivo and in epidemiological studies may be broadly classified in the following categories.
❖ Aldose reductase inhibitors
❖ Non-steroidal anti-inflammatory drugs
❖ Vitamins, minerals and antioxidants
❖ Miscellaneous agents
Potential Target for the Prevention of Cataract formation
Aldose reductase has been implicated in the etiology of diabetic complications. A variety of compounds have been observed to inhibit AR. Orally active inhibitors of the enzyme have been investigated for many years. Several of these compounds have progressed to the clinical level; only Epalrestat is currently on the market. Due to the limited number of a valuable drug for the treatment of diabetic complication, a number of rational approaches for the discovery of AR inhibitors have under been taken since the determination of the 3-dimensional structure of the enzyme. There are a variety of structurally diverse AR inhibitors [13-14].
Department of Pharamacology Page 23 Aldose Reductase Inhibitors (ARI’s)
Aldose reductase enzyme of the polyol metabolic pathway, and especially its inhibition by aldose reductase inhibitors (ARIs), has been gaining attention over the last years from the pharmaceutical community, as it appears to be a promising pharmacotherapeutic target. It was first found to be implicated in the etiology of the long term diabetic complications such as retinopathy, nephropathy and neuropathy. Emerging reports have suggested that, under normal glucose concentration, ALR may be up regulated by factors other than hyperglycemia and therefore be involved also in other pathological processes that have become major threats to human health in the 21st century. A number of cardiac disorders, including myocardial ischemia and ischemia reperfusion injury, congestive heart failure, cardiac hypertrophy, and cardiomyopathy have been linked to increased reactive oxygen species (ROS) generation and lipid peroxidation within myocardium and studies have been contacted in order to determine the role of ALR in myocardial metabolism during ischemia. ALR has been reported to be implicated with inflammation, mood disorders, renal insufficiency, ovarian abnormalities and human cancers such as liver, breast, ovarian, cervical and rectal cancers. Although several ARIs have progressed to the clinical level, only one is currently on the market.
Thus, attention is currently targeted to discover ARIs of distinct chemical structures, being neither hydantoin nor carboxylic acid derivatives [15].
Classes of AR Inhibitors
Cyclicimide groups• Sorbinil
• Fidarestat Acetic acid moiety
• Tolrestat
• Ponalrestat
• Zopolrestat.
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These drugs has been thoroughly analyzed by structural analysis of the AR and NADPH and several clinical studies. It is noted that the cyclicimide or acetic acid moieties bind to an essentially hydrophilic area of the active side of AR, which contains the Tyr-48, His-110 and Trp-111 residues. Inhibitors containing the cyclicimide or carboxylic groups exhibit similar in vitro but different in vivo activities. The carboxylic acid-containing inhibitors have lower in vivo activity, which has been attributed to relatively lower pKa values, thus causing ionization at physiological pH and an inability to traverse cell membranes. Cyclicimides have higher pKa and are only partially ionized at physiological pH, thus being able to pass through cell membranes and have better pharmacokinetic properties. Sorbinil possessed all these attributes, but its development as a therapeutic agent was halted due to hypersensitive reaction. The flavonoids are also good inhibitors of AR but do not contain either the carboxylic acid or cyclicimides moieties. This class of inhibitors, both naturally occurring and synthetic, has higher pKa values than the carboxylic acid and also has antioxidant properties which prevent cataract formation.
Aromatic groups
• Ponalrestat (Phthalazinyl group)
• Tolrestat (Naphthyl group)
• Zopolrestat (Benzothiazole group)
• Epalrestat (2' -thioxo- 1,3-thiazolan-4-one group)
• Ponalrestat (Halogenated benzyl group)
These aromatic groups bind in the hydrophobic pocket of AR, Trp-111, Phe-122 and Leu-300 residues, either through hydrogen bonding or hydrophobic contact. A newer class of AR inhibitors is the phenyl sulfonyl nitromethanes which exhibited potent activity against AR and some of which also showed irreversible inhibition. The departure of the NADP+ from the enzyme is believed to be the rate-determining step and this is when the current AR inhibitors inhibit enzyme action. It was shown that the inhibitors that bind to hydrophobic pocket were better AR inhibitors. The hydrogen-bonding
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interactions between the inhibitors and active site residues (Tyr-48, His- 110, Trp-111) oriented the inhibitor in the active site[16].
Clinical Trials of AR Inhibitors
Cataract was significantly influenced by mean AR levels. The protective effect was less noticeable if intensive control was instituted after some progression occurred.
Similar results were found in the study of galactosemic dogs, which showed that correction of hyperglycemia through removal of dietary galactose did not stop the progressive appearance of lens abnormalities associated with diabetic cataract. These studies emphasize that cataract followed a long term pathogenesis and that once initiated, pharmacological efforts to interfere are far less likely to be successful than prophylactic treatment prior to onset of early and perhaps, irreversible tissue changes.
Novel structures free from the hydantoin nucleus found in inhibitors such as sorbinil, better tissues penetration and activity than the carboxylic acid inhibitors and higher selectivity against AR. A similar rationale applies for AR inhibitors studies to establish efficacy toward diabetic neuropathy. These potential design flaws in prior clinical trials, failure to demonstrate inhibitor efficacy may be related to poor pharmacokinetic profiles of the investigated compounds. For example, inadequate nerve penetration almost certainly contributed to the failure of ponalrestat in clinical trials for diabetic neuropathy. Unexpected toxicity was a factor leading to the termination of clinical trials of sorbinil and tolrestat. Diabetic patients without any symptomatic neuropathy were treated with the aldose reductase inhibitor sorbinil, significant improvement in the conduction velocity was observed in all three nerves tested: the peroneal motor nerve, the median motor nerve, and the median sensory nerve. The major adverse reaction of sorbinil was a hypersensitivity reaction in the early weeks of therapy, which is similar to that seen with other hydantoins. The efficacy of another class of inhibitor, tolrestat, was modest in diabetic patients already symptomatic of neuropathy.
The only adverse reaction reported on tolrestat was an increase in serum levels of alanine aminotransferase or aspartate aminotransferase. Some patients in the placebo group also exhibited similar clinical findings during the study [17].
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Importance of herbal medicines
Medicinal plants have been used in all cultures as a source of medicine. The WHO estimates that around 80% of the world population uses herbal medicine for some aspect of primary health care. In India more than 70% of the population uses herbal formulations for treatment of ailments based on vast experience-based evidence. Use of herbal drugs for treating ailments is followed in Ayurveda, Yoga, Siddha, Unani and Homeopathy forms of alternative medicines. Even Allopathy practitioners tend to prescribe herbal drugs for treating various ailments. Majority of population still have limited access or no access to modern medicines and rely on traditional ways of treatment. Herbal medicines are now in great demand among the population in developing countries because they are inexpensive, better cultural acceptability, better compatibility with the human body and minimal side effects.
WHO has recommended the evaluation of effectiveness of plants in condition where we lack a safer modern drug. A proper scientific evaluation and screening of plants for pharmacological and chemical investigations are necessary for the discovery of potential anticataract agents. Herbalists generally prefer use of unpurified plant extracts containing varied phytoconstituents and claim they work synergistically in treating ailments. The composition of phytoconstituents buffers each other and provides the synergistic effect in healing the diseases [13].
Role of herbal medicines in galalctose-induced cataracatogenesis
Efficient aldose reductase inhibitors with excellent in vitro and in vivo biological activities act against rat galactosemic cataract. Herbal medicines have a major role in the inhibition of aldose reductase enzyme these drugs are comparatively safer and free from major side effects [20]. Major hindrance in using medicinal plants in treatment of any ailment is the lack of scientific and clinical data proving their safety and efficacy [21]. Many medicinal plants used extensively for aldose reductase inhibition and cataractogenesis they include: Garcinia mangostana, Barleria lupulina, Houttuynia Cordata, Lonchocarpus cyanescens, Enicostemma hyssopifolium (EH), Gymnema
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sylvestre, Eclipta alba, and Tinospora cordifolia, Hybanthus enneaspermus, Potentilla fulgens Ceasalpinia digyna, Alangium lamarckii, Phyllanthus niruri, Curcuma longa, Glycerrhiza glabra, Heliotropium indicum, Andrographis paniculata.
The plant which I have selected for my study was unripe fruits of Momordica charantia Linn. belonging to the family Cucurbitaeace. It is widely distributed in tropical and subtropical regions of the world. It has been used in folk medicine for the treatment of diabetes mellitus, and its fruit has been used as a vegetable for thousands of years.
Phytochemicals including proteins, polysaccharides, flavonoids, triterpenes, saponins, ascorbic acid and steroids have been found in this plant. Various biological activities of M. charantia have been reported, such as antihyperglycemic, antibacterial, antiviral, antitumor, immunomodulation, antioxidant, antidiabetic, anthelmintic, antimutagenic, antiulcer, antilipolytic, antifertility, hepatoprotective, anticancer and anti-inflammatory activities [25].
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PLANT PROFILE
Momordica charantia L. (Fruit)
Fig. 6: Picture of M. charantia (fruit) Fig. 7: Picture of M. charantia plant Family : Cucurbitaceae
Synonyms : M. chinensis, M. elegans, M. indica, M. operculata, M. sinensis Description
Taste : Very bitter
Colour : Green and Orange Size : 5-15cm
Shape : Pedulous, Fusiform
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Common Names [26]
Tamil : Pava, Pakar English : Bitter gourd Kannada : Karali Hindi : Karela Gujarati : Karelo Sanskrit : Karavelli Bengali : Baramasiya Malayalam : Kaypa Telugu : Kakara
Parts Used : Fruits, Seeds, Leaves, Roots
Phytoconstituents: Momordica charantia L. (fruit) contains following constituents Glycosides : Momordin, Charantin
Alkaloids : Momordicin
Acids : Fatty acid, Palmitic acid, Stearic acid, Oleic acid, Linoleic acid, Linolenic acid, Elacostearic acid
Amino acids : Glutamic acid, lactamic acid, beta-lactamic acid, phenylalanine, proline, α-aminobutyric acid
Others : 5-hydroxytryptamine, Lectins, vicine [27].
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Traditional & Medicinal Uses
Asthma, burning sensation, colic, constipation, cough, diabetes, fever (malaria), gout, helminthiasis, inflammation, leprosy, skin diseases, opthalmia, ulcer and wound [26]. Ethnomedical Uses
Abortions, birth control, increasing milk flow, menstrual disorders, vaginal discharge, constipation, food, diabetes, hyperglycemia, jaundice, stones, fever (malaria), gout, eczema, fat loss, hemorrhoids, hydrophobia, intestinal parasites, skin, leprosy, pneumonia, psoriasis, rheumatism, scabies, snakebite, vegetables, piles, tonic, anthelmintic, purgative [26].
Reported Activities [28-39]
Analgesic and anti pyretic [28], antiplasmodium [29], anti-inflammatory [30], antidiabetic [31], antioxidant [32], antimicrobial [33], chemoprotective [34], antitumor [35], antidepressant [36], hypoglycemic [37], antiulcerative and immunomodulatory, anti- malarial, antineoplastic [38], antifertility, antiviral, anti-genotoxic, anti-helmintic, activities [39].
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REVIEW OF LITERATURE
Dong et al., (2019) reported oligopeptides from herbal medicine because they are often present in very low concentrations in a complex matrix. Twenty-eight oligopeptides were recently identified by high performance liquid chromatography and quadrupole-time-of-flight-mass spectrometry (HPLC-Q-TOF-MS) from Momordica charantia L. (Cucurbitaceae), and a septapeptide, FHGKGHE (Phe-His-Gly-Lys-Gly- His- Glu), named MCLO-12, showed the best anticancer activity against the non-small cell lung cancer A549 cell line in vitro, with an IC50 value of 21.4 - 2.21 mM. The anti- proliferative activity assay results showed that MCLO-12 induced apoptosis of A549 cells in a concentration-dependent manner. Treatment of the cells with MCLO-12 (10.7- 42.8 mM /mL) caused strong intracellular reactive oxygen species (ROS) upregulating activities and activated caspase expression. MCLO-12 also suppressed the Trx system and subsequently activated a number of Trx-dependent pathways, including the ASK1, MAPK-p38 and JNK pathways. Thus research provides a good reference point for anti- NSCLC research into oligopeptides [40].
Abdul et al., (2018) evaluated the Antidepressant activity of Aqueous extract of Momordica charantia leaves. Depression is a common debilitating illness contributing to increase in morbidity and mortality worldwide. About 20% of all depressed patients are refractory to treatment with available antidepressants at adequate doses. Momordica charantia commonly known as Karela is widely used in Indian cuisine [38].
May et al., (2018) reported the effect on reducing pain in primary knee osteoarthritis is not well studied. Aim to determine the effects of Momordica charantia in reducing pain among primary knee osteoarthritis patients. Thirty-eight and thirty-seven primary knee osteoarthritis patients underwent 3 months of Momordica charantia and placebo supplementation respectively. Pain and symptoms throughout the Momordica charantia supplementation period were assessed using Knee Injury and Osteoarthritis Outcome Score. After 3 months supplementation period, body weight, body mass index, and fasting blood glucose reduced significantly in the Momordica charantia group. There
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were also significant improvements in Knee Injury and Osteoarthritis Outcome Score.
The placebo group had also shown significant improvements in certain Knee Injury and Osteoarthritis Outcome Score, with increased of the analgesic score. Momordica charantia supplementation offers a safe alternative to reducing pain and improving symptoms among the primary knee osteoarthritis patients while reducing the need for analgesia consumption. These beneficial effects can be seen as early as 3 months of supplementation [41].
Hussain et al., (2018) examined the M. charantia extract partitioned in different solvents was assessed for antioxidant (2, 2-diphenyl l-picrylhydrazyl), total phenolic contents (TPC), total flavonoid contents (TFC), antiglycation, alpha amylase and acetylcholinesterase inhibitory activities along with cytotoxic, thrombolytic and antibiofilm potentials. Most effective antioxidant fraction was n-hexane with TPC and TFC, highest in n-butanol and ethanol fractions, respectively. Ethyl acetate fraction showed maximum glycation and alpha amylase inhibitions and optimum acetylcholinesterase inhibition was by ethanol fraction. Fractions exhibited significant hemolytic and thrombolytic efficacies and bacterial growth restraint. The present research reveals some medicinal potency of M. charantia [42].
Fang et al., (2018) reported the progress in the antitumor aspect of bitter melon with a focus on the underlying molecular mechanisms. Bitter melon or bitter gourd (Momordica charantia) is a common vegetable in Asia and it is distinctive for its bitter taste. As an ingredient in folk medicine, research from different laboratories in recent years supports its potential medicinal applications with anti-tumor, anti diabetic, anti-HIV activities in both in vitro and animal studies. Further mechanistic studies as well as clinical trials are necessary to further verify its medicinal applications [43].
Perez et al., (2018) evaluated the cultivation of five bitter melon cultivars grown under field conditions in College Station (TX, USA). Additionally, ascorbic acid, amino acids and phenolic compounds were quantified from various cultivars grown in different years. The yield of the first year of evaluation was comparable to other bitter
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melon growing regions, ranging from 9371.5 kg ha-1 for the Japanese Spindle cultivar to 20 839.1 kg ha-1 for the Hong Kong Green cultivar. Multivariate analysis suggests a strong correlation between yield and growth degree days, water use efficiency and organic matter, as well as an inverse correlation with the amount or precipitation during the growing season. The highest levels of total phenolics were consistently found the Indian White cultivar. Seven phenolics and organic acids were identified and quantified by liquid chromatography-mass spectrometry and high-performance liquid chromatography, respectively. Additionally, the highest levels of total amino acids were found in the Large Top cultivar. The current 3-year field study demonstrates that it is feasible to grow bitter melon commercially in Texas with proper climatic and agronomic conditions. Bitter melon is a rich source for ascorbic acid, amino acids and phenolic compounds, which makes it a valuable food source with respect to improving human health [44].
Bhat et al., (2018) studied the effect of aqueous extract of Momordica charantia (AEMC) on fasting blood glucose (FBG), tissue glycogen, glycosylated haemoglobin, plasma concentrations of insulin and GLP-1 hormone in healthy and diabetic wistar rats. Male Wistar rats (both normal and diabetic) were treated with AEMC by gavaging (300 mg/kg body wt/day for 28 days). AEMC was found to increase tissue glycogen, serum insulin and GLP-1 in diabetic Wistar rats, where as decrease in FBG and Glycosylated haemoglobin non-significantly in normal, significantly in diabetic Wistar rats. The elevation of GLP-1 level in normal and diabetic treated groups may be due to the L-cell regeneration and proliferation by binding with L-cell receptors and makes a conformational change, resulting in the activation of a series of signal transducers. The polar molecules of M. charantia also depolarize the L-cell through elevation of intracellular Ca2+ concentration and which in turn releases GLP-1. GLP-1 in turn elevates beta-cell proliferation and insulin secretion. The findings tend to provide a possible explanation for the hypoglycemic action of M. charantia fruit extracts as alternative nutritional therapy in the management and treatment of diabetes [45].
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Cao et al., (2018) evalutaed the methanol extracts of Momordica charantia L.
fruits are extensively studied for their antiaging activities. A new cucurbitane-type triterpenoid (1) and nine other known compounds (2-10) were isolated, and their structures were determined according to their spectroscopic characteristics and chemical derivatization. Biological evaluation was performed on a K6001 yeast bioassay system.
The results indicated that all the compounds extended the replicative lifespan of K6001 yeast significantly. Compound 9 was used to investigate the mechanism involved in the increasing of the lifespan. The results indicated that this compound significantly increases the survival rate of yeast under oxidative stress and decreases ROS level. Further study on gene expression analysis showed that compound 9 could reduce the levels of UTH1 and SKN7 and increase SOD1 and SOD2 gene expression. In addition, it could not extend the lifespan of the yeast mutants of Uth1, Skn7, Sod1, and SOD2. These results demonstrate that compound 9 exerts antiaging effects via antioxidative stress and regulation of UTH1, SKN7,SOD1, and SOD2 yeast gene expression [46].
Farooqi et al., (2018) reported the biologically and pharmacologically active molecules isolated from M. charantia have shown significant anti-cancer activity in cancer cell lines and xenografted mice. In this review spotlight was set on the bioactive compounds isolated from M. charantia that effectively inhibited cancer development and progression via regulation of protein network in cancer cells. Summarize most recent high-quality research work in cancer cell lines and xenografted mice related to tumor suppressive role-play of M. charantia and its bioactive compounds. Although M.
charantia mediated health promoting, anti-diabetic, hepatoprotective, anti-inflammatory effects have been extensively investigated, there is insufficient information related to regulation of signaling networks by bioactive molecules obtained from M. charantia in different cancers. M. charantia has been shown to modulate AKT/mTOR/p70S6K signaling, p38MAPK-MAPKAPK-2/HSP-27 pathway, cell cycle regulatory proteins and apoptosis associated proteins in different cancers and still there are visible knowledge gaps related to the drug targets in different cancers have not yet developed comprehensive understanding of the M. charantia mediated regulation of signal
