Tanwar A; Chawla R; Ansari MM; Thakur P; Chakotiya AS; Dixit B; Arora R; Sharma RK; Khan HA

Research Article

Austin Arthritis. 2016; 1(2): 1008.

Herbal Informatics Approach for Identification and Validation of Natural Compounds Targeting Gouts

Tanwar A^1,2, Chawla R², Ansari MM¹, Thakur P², Chakotiya AS², Dixit B¹, Arora R³, Sharma RK² and Khan HA¹*

¹Heavy Metal and Clinical Toxicology Laboratory, Department of Medical Elementology and Toxicology, Hamdard University, Hamdard Nagar, New Delhi, India

²Division of CBRN Defence, Institute of Nuclear Medicine and Allied Sciences, Delhi, India

³Office of DG (LS), Defence Research and Development Organisation, DRDO Bhawan, Delhi, India

*Corresponding author: Khan HA, Heavy Metal and Clinical Toxicology Laboratory, Department of Medical Elementology and Toxicology, Hamdard University, Hamdard Nagar, New Delhi, India

Received: May 25, 2016; Accepted: July 05, 2016; Published: July 07, 2016

Abstract

Gout is a form of inflammatory arthritis that is caused by deposition of monosodium urate crystals in synovial fluid of joints and other soft tissues. However, the incidence rate of gout is higher in recent decades, it affects 1-2% of the population in western countries. Conventional treatments are not or less effective for patients with such inflammatory condition because of the propensity of these drugs to cause gastrointestinal adverse effects. The present study emphasized the herbal informatics tool for selecting the natural compound to attenuate the symptoms of inflammatory arthritis by inhibiting their disease factors, which includes classical literature surge model followed by the decision matrix and optimization scores to identify the potential leads for discovering its therapeutic potential. Herbals identified by the bioprospection study were validated by molecular docking analysis, which could further help in drug discovery programs to study chemical and biological methods. The purpose of this study is to identify an herbal lead, which could be used to inhibit the inflammatory pathway of gout at in vitro and in vivo animal models.

Keywords: Herbal informatics; Bioprospection; Gout; Arthritis; Ethnopharmacology; Molecular docking

Introduction

Gout is a progressive inflammatory arthritis, affecting 1-2% of the population in western country in which Indian population contributes approximately 0.75%, where it is more common in men than the females had polyarticular gout [1]. It is characterized by a chronic hyperuricemia condition in which the serum urate levels above ≥ 400μmol/L, and also exceeded the level of physiological saturation threshold [2]. Interactions between Monosodium Urate (MSU) Crystals and cell types including mast cells, endothelial cells, neutrophils, macrophages and synovial fibroblasts are established with clinical manifestations of gout [3].

The one of the most painful form of inflammatory arthritis is acute gout that is characterized by the abrupt onset of severe joint pain, swelling, and erythema. Various risk factors are elevated the concentration serum urate persisting crystal deposition in the joints leading to irreversible joint damage. The inflammatory response is characterized by the initiation of the critical attack, leukocyte recruitment, enlargement and subsequent resolution. The balance between the monocytes and differentiated macrophages plays a key role in modulating the inflammatory response to MSU crystals [4].

There are numerous treatment strategies or allopathic medication such as first line drug (celecoxib), second line drug (glucocorticoid) and third line drug (colchine) for alleviation of the inflammatory pathways of gout, but they are poorly tolerated by the patient due to its long term toxicity like hepatic cell (hepatocytes) damage, gastrointestinal toxicity, and it has not been widely used due to a toxic effect on other organs [5]. Nowadays, Natural products are considered as excellent sources in the management of clinical disorders like aging, arthritis, diabetes. The renewed interest in natural therapeutic methods and the use of herbal therapy has led to a gradually growing interest in natural compounds and the classical methods of plant extract preparations [6]. It has been predicted that about 420,000 plant species exist on earth but only 10% i.e. around 35,000 plants have been explored for their medicinal usage [7]. The World Health Organization (WHO) estimated that medicines prepared from plant source endow with primary healthcare for approximately 3.5 to 4 billion people globally [8].

The present study emphasized the rationale to adopt the Insilicobioprospection model, in order to bio prospect, discover, analyze and authenticate the Herbal Medicine (HM) into Modern Herbal Medicine (MHM), which is based on its ethnopharmacological importance, as testified in ancient literature or otherwise in clinical literature of various countries. Utilizing an herbal informatics approach, leads identified by herbal informatics used for further validation by the molecular docking, which could be useful to discover the potential therapeutic moiety to study at in vitro and in vivo level.

Methodology

Selection of bioactivity parameters using classical approach

Bioactivity parameters that are mainly responsible for the virulence/ disease factor of the inflammation were selected by Classical bioprospection approach that involves the understanding of the mechanistic aspects or pathophysiology of disorder as exemplified in (Table 1).

Table 1: Rationale for selection of Bioactivity parameters.

S.No
Biactivity parameter
Rationale for selection

1
IL 1 beta [9].

IL-1 is proinflammatory cytokine play a critical role in the pathogenesis. IL-1 blockade could be used to reduce joint inflammation and prevent progressive joint damage.
Herbal showing IL-1B inhibiting activity Eclipta Prostata, Ficus Racemosa etc.

2
IL-6 [10].

IL-6 plays a pleiotropic role both in terms of activating the inflammatory response and osteoclastogenesis. Significant improvement in signs and symptoms are due to blocking of IL-6 receptor.
Natural compounds showed inhibitoy effect on IL-6 like Nelumbonucifera, Ocimum sanctum(tulsi), Oxalis Corniculata etc.

3
TNF-alpha
[11-13].

TNF-α spontaneously develops osteoclasts differentiation in the joints with a progressive inflammation, cellular proliferation and bone destruction.
Herbal showing anti- TNF –a activity, Tridaxprocumbens, Solanum Nigrum, Stevia Rebaudiana, TagetesMinutaetc etc.

4
Xanthine oxidase [14]

Enzymes involved in purine catabolism syntethizes uric acid and hydrogen peroxide and accumulate of uric acid cause its precipitation in kidneys and joints (in particular in metatarso-phalangeal joints).
Xanthine oxidase used as therapeutic target for gout

5
AMP Deaminase [15].

Congenital hyperuricæmia is caused by the presence of an abnormal A.M.P. deaminase.
Inhibition of AMP deaminase, useful in the management of Gout.

6
COX-2 [16].

Inflammatory gout has increased expression of COX-2.
Inhibition of Cyclooxygenase 2 (COX-2) has emerged as an important for the treatment of gout.
Plants having anti-inflammatory activity Allium sativum, Berberisaristata etc.



Table 1: Rationale for selection of Bioactivity parameters.

Evaluation of relevance factor using keywords hits scoring matrix approach

This step is accomplished by calculating the percentage relevance of the respective parameters using Pub Med as a search engine tool that rely on Academic Search engine Optimization (ASEO) . ASEO is a basic principle that involves grading of those scholarly objects on the top position that are most expected to be examined [15]. This yield ‘N’ total hits, out of them initial n=20 presents the sample, which is the representative fraction of the population that is followed by judgments or purposive sampling. In judgments or purposive sampling the hits are deliberately selected or discrete on the basis of relevance. Percentage weightage will be determined by using the following formula and then weightage will be calculated.

Percentage relevance=(Relevant Hits× 100)/20.

Selection of herbal plants using classical bioprospection approach

The classical bioprospection approach accounts for investigation of the following variables based on literature review to devise a logical conclusion, resulted in selection of plants was shown in (Table 2). It includes a) Ethnopharmacological importance; b) Relevance of Herb in traditional medicine; c) Availability factor or cultural acceptability in localized regions; d) Any vedic literature supporting its use; e) Investigations/ prior experience on potential of the herb; f) Indirect indications, if any etc.

Table 2: Ethnopharmacological properties of herbal compounds for rationale based selection.




  
    S.No. 
    Herbals
    Common name 
    Ethnopharmacological    properties
    Phyto-constituents
    Traditional uses
  
  
    1.
    Curcuma    Longa [17] 
    Turmeric
    Anti- rheumatic, Anti-inflammatory, Anti-oxidant
    Curcumin, Demethoxycurcumin    (DMC) and bisdemethoxycurcumin (BDMC)
    Used    for Sprains, swellings, cough, and wounds. 
  
  
    2.
    Azadirachta    indica [18] 
    Neem
    Anti-helminthic, Anti-fungal, Anti-diabetic, Anti-bacterial, Anti-viral, contraceptive, Anti-inflammatory, Anti-oxidant    and Anti-carcinogenic 
    Saponins, Anthraquinones,    Flavonoids. 
    Used for Skin diseases, Healthy hair, Detoxifyblood,    Balance blood sugar levels, and Sanitizing wounds.
  
  
    3.
    Mangifera indica [19] 
    Mango 
    Anti-oxidant, Anti-diabetic, Antiviral, Anthelmintic, Anti-allergenic,    Antiparasiti
    Polyphenolics,Flavonoids,Triterpenoids    Bark: Protocatechic acid, Catechin, Mangifera 
       
    Tumour, Heat stroke,    Miscarriage, Anthrax, Blisters, Wounds in the mouth, Tympanitis,
  
  
    4.
    Zingiber    Officinale [20] 
    Ginger
    Antioxidant, Anti-inflammatory, Anti-tumour, Anti-microbial,    Anti-diabetic. 
    Gingerol and Zingerone
    Nausea, Indigestion, Cold, Flu,    Poor circulation, Menstrual cramps etc.
  
  
    5.
    Withania somnifera [21] 
    Ashwagandha 
    Anti-stress, Anti-tumor, Anti-inflammatory,    Anti-arthritic and Anti-oxidant.
    Alkaloids: Isopelletierine,    Anaferine, Cuseohygrine, Anahygrine, Withanolides, Withaferins, Saponins
    Eases stress, Lower blood pressure, Inflammation    of joints, Nervous disorders and
      Epilepsy
  
  
    6.
    Camellia sinensis [22] 
    Green tea
    Anti-tumor, Anti diabetic, Anti-inflammatory
    Flavonoids, Catechin, Epigallocatechin    Gallate (EGCG), L-theanine, Caffeine, theophylline,    Theobromine, and Theanine.
    Control bleeding, Heal wounds,    Aid digestion, Improve heart
      Mental health and Regulate body temperature.
  
  
    7.
    Vitisvinifera [23] 
    Grapes 
    Anti-inflammatory and Anti-sclerotic 
    Anthocyanins, hydroxycinnamic acids, and Stilbenoids 
    Cholera,    smallpox, nausea, skin and eye infections.²¹
  
  
    8.
    Allium sativum [24] 
    Garlic
    Anti-Inflammatory,    Antibacterial, Antifungal, Antiviral and Anti- rheumatic. 
    Allicin    (diallyl-dithiosulfinate) Diallyldisulphide, vinyldithiins, S-allylcysteine, Saponins, flavonoids, Maillard reaction, Fatty acid and ethyl linoleate (ELA).
    Used for the treatment of Smallpox.
  
  
    9.
    Syzygium aromaticum [25] 
    Cloves
    Anti- rheumatic,
      Antimicrobial    and Antioxidant 
    Gallotannins, Triterpenes, flavonoids,    and phenolic acids 
    Carminative, to increase hydrochloric acid    in the stomach and to improve peristalsis
  
  
    10.
    Piper nigrum [26] 
       
     
      Black pepper
       
    Anti-inflammatory,
      Anti-flatulent, Anti-oxidant,antimicrobial,    gastro-protective, and antidepressant.
    Pyrrolidines, Piperamide, Piperamine, Pipericide, Sarmentosine, Sarmentine, and Trichosta.
    Constipation, Insomnia, Oral abscesses, Sunburn, toothaches, Flatulence and Indigestion. 
  
  
    11.
    Tinospora cordifolia [27] 
     
      Giloy
    Antineoplastic,    Antioxidant, Hepatoprotective,and Hypolipidemic
    Alkaloids, diterpenoid lactones, glycosides,    sesquiterpenoid, aliphatic compounds, phenolics, polysaccharides, steroids    (tinosporine, tinosporide, tinosporaside, cordifolide, cordifol,    heptacosanol. 
    Used for Diabetes, jaundice, high    cholesterol,    upset stomach, fever, and to boost the immune    system. 
  
  
    12.
    Rubiacordifolia
      [28] 
    Manjishta
    Anti-inflammatory 
    Mollugin, Purpurin, Quinonoid, Anthraquinones, Iridoids,    Hexapeptides, Rubiprasins, Quinones, and Triterpenoid. 
    Blood disorders and reduce    swelling.
  
  
    13.
     
      Garcinia Cambogia 
      [29] 
    Malabar tamarind 
    Anti-inflammatory, Anti-cancer, Antibacterial and    Antioxidant
    Hydroxycitric acid, Garcinol, Succinic acid,    Tartaric acid, Oxy-guttiferone M, Rheediaxanthone A, Isogarcino, Garcinol
    Obesity, appetite control, weight loss diets,    high triglycerides and high cholesterol
  
  
    14.
    Gmelina Arborea
      [30] 
    Gamhar 
    Anti-inflammatory, and Anti-rhuthematic
    tyrosol    [2-(4-hydroxyphenyl)ethanol], (+)-balanophonin, 8-5′ neolignan, balanophonin,    gmelinol, 2,6-dimethoxy-p-benzoquinone and    3,4,5-trimethoxyphenol
    Pains, burning sensations, and    fever.
  
  
    15.
    Lilium Polyphyllum
      [31] 
    White Lily
      (Kalihari)
    Anti-inflammatory, and Anti-rhuthematic
    2,4-D, Glyphosate, fluridone, triclopyr,    and imazamox.
    Inflammation and swelling.
  
  
    16.
    Madhuca Indica
      [32] 
    Mahua 
    Anti-inflammatory, and Anti-rhuthematic
    saponin, alkaloid, glucoside, Sapogenin,    triterpenoids, steroids, madhucic acid, 
    Wound Healing, headaches, Itching, pain, and inflammation. 
  
  
    17.
    Mentha    arvensis
      [33] 
    Mint
      (Pudina)
    Anti-inflammatory, and Anti-rhuthematic
    Menthol, menthone, carvone, limonene, linalool,    menthyl acetate, piperitone, and pulegone 
    Inflammation and swelling.
  
  
    18.
    Terminalia chebula
      [34] 
    Haritaki
    Anti-inflammatory, and Anti-rhuthematic
    Tannin,     chebulinic acid, ellagic acid, Anthraquinones, polyphenols, terpenes,    anthocyanins,flavonoids, alkaloids and glycosides
    Digestive diseases, urinary diseases, diabetes,    skin
      Diseases, heart    diseases, and fever.
  
  
    19.
    Hypericum perforatum
      [35] 
    Saint    John's wort 
    Anti-inflammatory, 
      Antidepressant an    Anti-Rheuthmatic 
    Hypericin, Quercetin, Hyperforin,    naphthodianthrones, phloroglucinols, flavonoids, pseudohypericin,    amentoflavone, Quercetin, chlorogenic acid and essential oils.
    Depression,anxiety,    obsessive-compulsive disorder(OCD),enopausal mood swings, and premenstrual    syndrome.
  
  
    20.
    Peganum harmala [36] 
    Harmal    seeds 
    Anti-Rheuthmatic
    Alkaloid, harmine, papaverine,    Lycoris alkaloids, lycorine and lycoricidinol
    Inflammation and swelling.
  
  
    21.
    Crocus sativus
      [37] 
    Saffron 
    Anti-inflammatory,and Anti-rhuthematic
    Safranal, isophoron, riboflavin,    thiamine, 2-phenyl ethanol, utanic acid, and lenolenic.
    Used for Painful mensuration, coughs, Asthma, cough, intestinal gas, dry and teeth    problem.
  
  
    22.
    Tephrosia purpurea
      [38] 
    Fabaceae 
    Anti-inflammatory,  anti-oxidant and Anti-rhuthematic
    Polyphenols, flavonoids,    Quercetin, gallic acid, and allopurinol.
    Inflammation, ulcer, urinary disorders and    diseases related to liver and heart.



Table 2: Ethnopharmacological properties of herbal compounds for rationale based selection.

Binary coefficient matrix to evaluate the presence/ absence of a parameter in selected plants

This methodology works on the principle of 0-1 binary code of absence/presence of a particular parameter in selected plants from previous step. Based on this, all the plants having more than 04 parameters, reported in PubMed search engine (n= first 20 hits) against ‘Bioactivity Parameter + Selected Plant’ random search model, were selected. It relates to the fact that only these plants which can support holistic approach should be screened for the next level analysis, in line with the rationale of present study [39].

Weightage matrix based analysis

This step includes evaluation of overall weightage of plants (Scores ≥4 in past venture) by multiplying their binary score with weightage obtained in above step. This is a primary step to screen the plants utilizable to subsequent analysis and removes fake positive results attributed towards investigator’s biasness due to ‘experience factor’. This step enhances the ‘uncertainty factor’ required for statistically valuable outcome. This step identifies potential plant leads based on in silico bioprospection approach subjected to fuzzy set membership analysis and optimization to validate the findings [40].

Fuzzy set membership analysis for decision matrix

In this approach, the given mathematical relationship was used to calculate the relevance of the variety/product;

μs=([(S) – min(S)] )/(max(S) – min(S)).

where, μS represents the desirability values of members of the fuzzy set S. Min(S) and max(S) are minimum and maximum values, respectively, in the fuzzy set S. [41].

Optimization of decision matrix score

In this approach the numerical value of scores obtained were converted into a leveled score by using a scaled magnitude represented by a symbol.

Molecular docking

To validate the bioprospection model in silico docking simulations of most relevant bioactivity parameter against pre-selected phytoligands were carried using Hex 8.0 software. Software’s used: Argus Lab (4.0.1), Open Babel (2.4), and Hex (8.0).

Retrieval of 3D structure of COX-2 receptor and preparation of ligand database

The experimental 3D tertiary structure of COX-2 retrieved from RCSB Protein Data Bank as a pdb file (PDB ID- Q05769). Hydrogen atoms were introduced into the enzyme structure using Argus lab (4.0.1) to customize it as the receptor molecule for rigid docking. The predominant phytoconstituent and 2 standard chemotherapeutic inhibitor of COX-2 were retrieved from PUBCHEM. Hydrogen atoms were introduced into the ligand structure using Argus Lab (4.0.1) to customize them for rigid docking. The hydrogenated ligand molecules were then converted into pdb format using Open Babel (2.4) interface as required for rigid docking.

Active site analysis

DoGSiteScorer is a grid-based method which uses a Difference of Gaussian filter to detect potential binding pockets solely based on the 3D structure of the COX 2 -and splits them into sub pockets. Global properties, describing the size, shape and chemical features of the predicted (sub) pockets are calculated. The druggability score is provided for each (sub) pocket, based on a linear combination of the three descriptors describing volume, hydrophobicity and enclosure. Furthermore, a subset of meaningful descriptors is incorporated to predict the (sub) pocket druggability score (values are between zero and one). The higher the score the more druggable the pocket is estimated to be [42].

Ligand receptor docking (Hex 8.0)

Receptor and Ligand files were imported in the Hex 8.0 software. Graphic settings and Docking parameters were customized as follows and rigid docking was performed. E values of the docking predicted the free energy of docking, which served as the basis for ranking phyto ligands in increasing order of their docking abilities.

The parameters used in the docking process were:

a) Correlation type: Shape and electro

b) FFT mode: 3D fast lite

c) Grid Dimension: 0.6

d) Receptor range: 1800

e) Ligand range: 1800

f) Twist range: 3600

Results

Selection of bioactivity parameters using classical approach

On the basis of the keyword hits scoring analysis, weightage was given to various parameters identified for screening of herbal plants with respect to factors involved in causing gout. as exemplified in (Table 3). Weightage was decided according to the percentage relevance obtained for each parameter. Highest relative percentage relevance was obtained for COX-2 inhibition (i.e. 6), followed by other parameters like TNF- alpha Inhibition (5.5), IL-1beta Inhibition (4.5), Xanthine oxidase Inhibition (4.5), IL-6 inhibition (3.5) and AMP Deaminase inhibition (2.5).

Table 3: Weightage assigned to the Factors based on Average Percentage Relevance.




  
    S.No.
    Bioactivity parameter    (BAP)
    Total number of Hits
    Hits Relavant
    Percentage (%) Relevance
    Weightage score
  
  
    
       
    
    IL 1 beta
    5242
    9
    45
    4.5
  
  
    
       
    
    IL-6
    13141
    7
    35
    3.5
  
  
    
       
    
    TNF-alpha
    36569
    11
    55
    5.5
  
  
    
       
    
    Xanthine oxidase
    1769
    9
    45
    4.5
  
  
    
       
    
    AMP Deaminase
    168
    5
    25
    2.5
  
  
    
       
    
    COX-2
    8272
    12
    60
    6



Table 3: Weightage assigned to the Factors based on Average Percentage Relevance.

Binary (presence-absence) coefficient matrix

Out of 50 identified herbals, 27 herbals exhibited a binary score of either 4 or more than 4, higher than that of the counterparts, e.g. Ethnopharmacological relevance behind the selection of various herbal plants was also exemplified in (Table 2), Curcuma Longa, Camellia sinensis, Peganum harmala, Ocimum sanctum, Zingiber Officinale, Withania somnifera, Vitis vinifera, Piper nigrum, Punica granatum, Rosmarinus officinalis, Picrorhiza kurroa, Terminalia chebula, Hypericum perforatum, Azadiracha indica, Mangifera indica, Trigonella foenum-graecum, Allium sativum, Syzygium aromaticum, Phyllanthus emblica, Centella asiatica, Harpagophytum procumbens, Tinospora cordifolia, Garcinia Cambogia, Crocus sativus, Swertia chirayita, Malus domestica..

Simple additive weighing matrix

Out of 27 plants selected on the basis of binary coefficient matrix (Binary Matrix score ≥ 4), it was revealed that 13 herbal plants showed immense potential of acting as a therapeutic agent. e.g. Curcuma Longa,Camellia sinensis, Peganum harmala, Ocimum sanctum, Zingiber Officinale, Withania somnifera, Vitis vinifera, Piper nigrum, Punica granatum, Rosmarinus officinalis, Picrorhiza kurroa, Terminalia chebula, and Hypericum perforatum.

Fuzzy set optimization

On the basis of decision matrix analysis, 03 herbals like Curcuma Longa, Camellia sinensis, and Peganum harmala held the top most position with μS score being 1, relative to the lowest μS score exhibited by Malusdomestica (0.70). Optimized scores were also obtained for the selected plants based on fuzzy set membership analysis as shown in (Table 4).

Table 4: Binary matrix and fuzzy set optimization of herbals targeting arthritis.




  
    S.No. 
    Herbal 
    Herbal code 
    Binary score 
    Weightage score 
    Fuzzy score 
  
  
    1. 
    Curcuma    Longa
    Cl
    6
    26.5
    1
  
  
    2. 
    Camellia sinensis 
    Cs
    6
    26.5
    1
  
  
    3. 
    Peganum    harmala
    Ph
    6
    26.5
    1
  
  
    4. 
    Ocimum    sanctum
    Os
    5
    24
    0.7
  
  
    5. 
    ZingiberOfficinale
    Zo
    5
    24
    0.7
  
  
    6. 
    Withania somnifera
    Ws
    5
    24
    0.7
  
  
    7. 
    Vitus    vinifera 
    Vv
    5
    24
    0.7
  
  
    8. 
    Piper    nigrum 
    Pn
    5
    24
    0.7
  
  
    9. 
    Punica    granatum 
    Pg
    5
    24
    0.7
  
  
    10. 
    Rosmarinus    officinalis 
    Ro
    5
    24
    0.7
  
  
    11. 
    Picrorhiza    kurroa 
    Pk
    5
    24
    0.7
  
  
    12. 
    Terminalia    chebula 
    Tc
    5
    24
    0.7
  
  
    13. 
    Hypericum    perforatum 
    Hp
    5
    24
    0.7



Table 4: Binary matrix and fuzzy set optimization of herbals targeting arthritis.

Molecular docking

Active site analysis: Active site analysis using Dog Site Scorer revealed that one pockets P1 of the COX-2 were found to be energetically favorable for performing molecular docking studies. Out of the pockets present, P1 (0.67) was found to be more druggable based on its linear combination of volume, hydrophobicity and enclosure attributed to its descriptors than the other pockets [P0 (0.41), P3(0.07)] as shown in (Figure 1).

S.No	Biactivity parameter	Rationale for selection
1	IL 1 beta [9].	IL-1 is proinflammatory cytokine play a critical role in the pathogenesis. IL-1 blockade could be used to reduce joint inflammation and prevent progressive joint damage. Herbal showing IL-1B inhibiting activity Eclipta Prostata, Ficus Racemosa etc.
2	IL-6 [10].	IL-6 plays a pleiotropic role both in terms of activating the inflammatory response and osteoclastogenesis. Significant improvement in signs and symptoms are due to blocking of IL-6 receptor. Natural compounds showed inhibitoy effect on IL-6 like Nelumbonucifera, Ocimum sanctum(tulsi), Oxalis Corniculata etc.
3	TNF-alpha [11-13].	TNF-α spontaneously develops osteoclasts differentiation in the joints with a progressive inflammation, cellular proliferation and bone destruction. Herbal showing anti- TNF –a activity, Tridaxprocumbens, Solanum Nigrum, Stevia Rebaudiana, TagetesMinutaetc etc.
4	Xanthine oxidase [14]	Enzymes involved in purine catabolism syntethizes uric acid and hydrogen peroxide and accumulate of uric acid cause its precipitation in kidneys and joints (in particular in metatarso-phalangeal joints). Xanthine oxidase used as therapeutic target for gout
5	AMP Deaminase [15].	Congenital hyperuricæmia is caused by the presence of an abnormal A.M.P. deaminase. Inhibition of AMP deaminase, useful in the management of Gout.
6	COX-2 [16].	Inflammatory gout has increased expression of COX-2. Inhibition of Cyclooxygenase 2 (COX-2) has emerged as an important for the treatment of gout. Plants having anti-inflammatory activity Allium sativum, Berberisaristata etc.

S.No.	Herbal	Herbal code	Phytoconstituents	E -value (Kcal/mol)
	Curcuma Longa	Cl	Curcumin	-46.05
	Camellia sinensis	Cs	Epigallocatechin Gallate	-59.12
	Peganum harmala	Ph	Harmalol	-28.19
	Ocimum sanctum	Os	Anthocyanins	-23.52
	Zingiber officinale	Zo	Gingerol	-26.32
	Withania somnifera	Ws	Withaferins	-55.47
	Vitus vinifera	Vv	Quercetin	-420.32
	Piper nigrum	Pn	Piperidines	-46.88
	Punica granatum	Pg	Ellagic acid	-25.80
	Rosmarinus officinalis	Ro	Rosmarinic acid	-43.47
	Picrorhiza kurroa	Pk	Picroside I	-29.62
	Terminalia chebula	Tc	Arjunolic acid	0.7
	Hypericum perforatum	Hp	Hydroxycinnamic acid	-30.55
	Meloxicam	Standard inhibitor		-18.98
	Colchicine	Standard inhibitor		-18.23

Herbal Informatics Approach for Identification and Validation of Natural Compounds Targeting Gouts

Abstract

Introduction

Methodology

Selection of bioactivity parameters using classical approach

Evaluation of relevance factor using keywords hits scoring matrix approach

Selection of herbal plants using classical bioprospection approach

Curcuma Longa [17]

Turmeric

Mango

Anti-oxidant, Anti-diabetic, Antiviral, Anthelmintic, Anti-allergenic, Antiparasiti

Zingiber Officinale [20]

Antioxidant, Anti-inflammatory, Anti-tumour, Anti-microbial, Anti-diabetic.

Grapes

Anti-inflammatory and Anti-sclerotic

Anti-Inflammatory, Antibacterial, Antifungal, Antiviral and Anti- rheumatic.

Binary coefficient matrix to evaluate the presence/ absence of a parameter in selected plants

Weightage matrix based analysis

Fuzzy set membership analysis for decision matrix

Optimization of decision matrix score

Molecular docking

Retrieval of 3D structure of COX-2 receptor and preparation of ligand database

Active site analysis

Ligand receptor docking (Hex 8.0)

Results

Selection of bioactivity parameters using classical approach

Binary (presence-absence) coefficient matrix

Simple additive weighing matrix

Fuzzy set optimization

Molecular docking

Discussion

Conclusion

Acknowledgement

References