Priyadarshini J.L. College of Pharmacy, Electronic Zone, MIDC, Hingna Road, Nagpur, Maharashtra, India 440016
Wound healing is a multicellular and complicated process that strives to restore the skin’s barrier function. Different cell types, including keratinocytes, endothelial cells and fibroblasts collaborate for the process to complete. Tridax procumbens is a very important natural plant that is commonly found in the tropical region and has a wide range of pharmacological actions. In the present study the molecular docking was used to identify the activity of four compounds from T. procumbens to the selected receptor. The goal of this work was to anticipate the capacity of T. procumbens compounds to interact with , IL-6. Pyrx was used to run docking simulations for these compounds. Results of this study showed that all the compounds showed interaction with selected target proteins. Among the compounds, Cynaroside, Quercetin, Linoleic, Linolenic, Palmitoleic acid, Campesterol, 9-Heptadecanone showed excellent binding and hydrogen bond interaction with all the selected target proteins. The results showed that T. procumbens compounds are effective anti-inflammatory agents. However, further research is required to validate the action of these molecules.
1.1 Drug Discovery and Development: -
Drug discovery and development is a scientific process through which new medicines are identified, evaluated, and brought to the market for therapeutic use. It is a highly complex and multidisciplinary field involving chemistry, biology, pharmacology, and medical sciences. The aim is to develop drugs that are safe, effective, and of high quality for the treatment and prevention of diseases such as Cancer and infectious disorders.
Drug discovery and development is a systematic and lengthy process used to identify, test, and bring new medicines to market. It begins with the identification of a biological target such as a protein, gene, or receptor that is associated with a disease. Once a target is identified, scientists validate it to confirm that modifying it will have a therapeutic effect. After validation, the process moves to the discovery phase where thousands of chemical compounds are screened to find “hit” molecules that show potential activity against the target.
These hit compounds are then optimized to improve their effectiveness, safety, and drug-like properties, leading to the selection of a promising “lead” compound. The next stage is preclinical testing, where the lead compound is tested in laboratory experiments and animal models to evaluate its toxicity, pharmacokinetics, and overall safety profile. If the results are satisfactory, the drug enters clinical trials, which are conducted in humans.
Clinical trials are carried out in three main phases. Phase I trials involve a small number of healthy volunteers to assess safety and dosage. Phase II trials are conducted on a larger group of patients to evaluate the drug’s effectiveness and side effects. Phase III trials include a much larger population to confirm effectiveness, monitor adverse reactions, and compare the new drug with existing treatments. If the clinical trials are successful, the data is submitted to regulatory authorities for approval.
Regulatory agencies such as the FDA or CDSCO carefully review all preclinical and clinical data to ensure the drug is safe and effective for public use. Once approved, the drug is manufactured on a large scale and marketed for medical use. Even after approval, the drug continues to be monitored in the post-marketing or Phase IV stage to detect any long-term or rare side effects in the general population.
1.2 Drug Development Stages: -
Figure no.1 Drug Development Stages
Drug development is a long and complex process used to discover, test, and bring a new medicine to market. It ensures that drugs are safe, effective, and of good quality before being used by patients.
1. Drug Discovery & Development
This is the initial stage where scientists identify a disease target (such as a protein or gene) and search for potential drug molecules.
2. Preclinical Research
Before testing in humans, the drug is tested in the laboratory and on animals.
3. Clinical Trials (Human Testing)
This stage tests the drug in humans and is divided into 3 phases:
????Phase I
Small group (20–100 healthy volunteers)
Focus: Safety and dosage
???? Phase II
Larger group (100–300 patients)
Focus: Effectiveness and side effects
???? Phase III
Large population (1,000–3,000+ patients)
Focus: Confirmation of effectiveness, monitoring adverse reactions
4. Regulatory Approval
Government agencies review all data to ensure safety and effectiveness.
Agencies: FDA (USA), CDSCO (India), EMA (Europe)
Review of clinical and preclinical data
Approval is granted if standards are met
5. Manufacturing & Marketing
Once approved, the drug is produced on a large scale and made available to the public.
6. Post-Market Surveillance (Phase IV)
Even after approval, the drug is continuously monitored.
1.3 CADD (COMPUTER AIDED DRUG DESING) :-
Computer-Aided Drug Design (CADD) is a computational approach used in modern pharmaceutical research to discover, design, and optimize new drug molecules with the help of computer software and simulation techniques. It plays an important role in reducing the time, cost, and experimental effort required in traditional drug discovery processes. CADD integrates knowledge from chemistry, biology, pharmacology, and computer science to predict how small molecules interact with biological targets such as proteins, enzymes, or receptors.
CADD is broadly classified into two main types: structure-based drug design (SBDD) and ligand-based drug design (LBDD). Structure-based drug design is used when the three-dimensional structure of the target protein is known. In this method, researchers study the active site of the protein and design or screen molecules that can fit into the binding pocket effectively. Techniques such as molecular docking and molecular dynamics simulation are commonly used to analysed the interaction between the drug and the target protein. Ligand-based drug design is used when the structure of the target protein is not available but information about known active compounds exists. In this approach, scientists analysed existing molecules that show biological activity and identify common chemical features responsible for their effectiveness. Methods such as pharmacophore modelling and quantitative structure–activity relationship (QSAR) are used to predict the activity of new compounds based on structural similarity.
The CADD process typically begins with target identification, where a disease-related biological molecule is selected. This is followed by target structure preparation, in which the three-dimensional structure of the protein is obtained from experimental databases or computational modelling. After this, large chemical libraries containing millions of compounds are prepared for virtual screening. Virtual screening is a computational technique used to filter and identify the most promising drug-like molecules from large databases.
The selected compounds are then subjected to molecular docking studies to predict their binding orientation and affinity with the target protein. The best-performing compounds are further optimized to improve their potency, selectivity, and safety. In addition, ADMET prediction is performed to evaluate absorption, distribution, metabolism, excretion, and toxicity properties of the drug candidates before experimental testing.
CADD is widely used in modern drug discovery for diseases such as cancer, viral infections, bacterial infections, and neurological disorders. It has significantly contributed to the development of antiviral drugs, including drugs used in HIV and COVID-19 treatment research. Pharmaceutical industries extensively use CADD tools such as AutoDock, Schrödinger Suite, MOE, and Discovery Studio for drug screening and optimization. One of the major advantages of CADD is that it reduces the need for extensive laboratory experiments by predicting the most promising compounds in advance.
Figure no.2 Computer Aided Drug Desing
1.4 Molecular Docking: -
Molecular docking is a computational technique used in Computer-Aided Drug Design (CADD) to predict the preferred orientation of a small molecule (ligand) when it binds to a target protein or receptor. It helps scientists understand how a drug molecule fits into the active site of a protein and how strong the interaction is. The main goal of molecular docking is to estimate the binding affinity between the ligand and the target, which indicates how effectively a drug can inhibit or activate a biological function.
In molecular docking, both the ligand and the receptor are modelled in three-dimensional form. The ligand is placed into the binding site of the receptor in different orientations, and each position is evaluated using scoring functions. These scoring functions predict the stability and strength of the interaction based on factors such as hydrogen bonding, hydrophobic interactions, electrostatic forces, and van der Waals forces.
Molecular docking is generally divided into two main steps: search algorithm and scoring function. The search algorithm explores possible conformations and orientations of the ligand within the binding site, while the scoring function ranks these conformations based on predicted binding energy. The best docking pose is the one with the lowest binding energy and strongest interaction with the target protein.This technique is widely used in drug discovery to screen large libraries of compounds and identify potential drug candidates quickly and efficiently. It reduces the need for extensive laboratory experiments by narrowing down the most promising molecules for further testing. Molecular docking is especially useful in the development of drugs for cancer, infectious diseases, and neurological disorders.
Molecular docking is classified based on the flexibility of the ligand (drug molecule) and the receptor (target protein). The main types are
1. Rigid Docking
2. Flexible Ligand Docking
3. Flexible Receptor Docking
4. Induced Fit Docking
5. Ensemble Docking
???? 1. Rigid Docking
In rigid docking, both the ligand and the receptor are treated as completely rigid structures. No flexibility is allowed in either molecule during docking. The ligand is simply fitted into the fixed active site of the receptor. This method is fast and computationally simple but less accurate because it does not reflect real biological conditions.
???? 2. Flexible Ligand Docking
In flexible docking, the ligand is allowed to rotate and change its shape while binding to the receptor. The receptor remains rigid in most cases. This method provides more realistic results compared to rigid docking because it considers different conformations of the ligand.
???? 3. Flexible Receptor Docking
In this method, the receptor protein is also allowed some flexibility during docking. This is important because proteins can change shape when a ligand binds to them. However, this method is more complex and requires higher computational power.
???? 4. Induced Fit Docking
Induced fit docking allows flexibility in both the ligand and the receptor. It considers that the protein binding site may adjust its shape to fit the ligand. This method is more accurate and closely represents real biological interactions but is computationally expensive.
???? 5. Ensemble Docking
In ensemble docking, multiple different conformations of the receptor are used for docking. This helps in considering protein flexibility without changing its structure during simulation. It improves prediction accuracy and is widely used in modern drug discovery.
Figure no.3 Molecular Docking
1.5 Wound Healing: -
Wound healing is a natural biological process by which the body repairs damaged tissues after injury. It involves a complex series of events that restore the integrity and function of the skin or other tissues. The process is essential for survival because it prevents infection, reduces blood loss, and restores normal tissue structure. Wound healing occurs in four main phases: hemostasia, inflammation, proliferation, and remodelling.
The first stage, hemostasia, begins immediately after injury, where blood vessels constrict and blood clotting occurs to stop bleeding. Platelets play an important role by forming a fibrin clot that acts as a temporary barrier.
The second stage is the inflammatory phase, where white blood cells such as neutrophils and macrophages migrate to the wound site to remove dead cells, bacteria, and debris. This phase helps prevent infection and prepares the wound for healing.
The third stage is the proliferative phase, where new tissue is formed. Fibroblasts produce collagen, which provides strength to the wound. New blood vessels form through angiogenesis, and the wound begins to close as epithelial cells grow over the damaged area.
The final stage is the remodelling or maturation phase, which can last for months or even years. During this phase, collagen fibres are reorganized and strengthened, and the wound tissue gradually gains maximum strength, although it may never fully regain the original strength of the skin.
Wound healing can be affected by factors such as age, nutrition, blood supply, infection, diabetes, and medications. Poor healing may lead to chronic wounds or complications such as ulcers. Wound healing is an important area of medical research, and various drugs, dressings, and biomaterials are developed to enhance speed up the healing process.
Figure no.4 Mechanism of Action of Wound Healing
Receptors Involved in Wound Healing
Wound healing is regulated by several cell surface receptors that respond to growth factors, cytokines, and extracellular signals. These receptors control inflammation, cell migration, tissue formation, and remodelling during the healing process.
Role of IL-6 Receptor in Wound Healing
Interleukin-6 (IL-6) is a multifunctional cytokine that plays an important role in regulating inflammation and tissue repair during wound healing. The IL-6 receptor (IL-6R) is a cell surface receptor that binds IL-6 and activates intracellular signalling pathways involved in immune response and tissue regeneration. IL-6 signalling occurs through two main mechanisms: classic signalling and trans-signalling.
In classic signalling, IL-6 binds to membrane-bound IL-6R present on certain cells such as hepatocytes and some immune cells. This complex then associates with a signal-transducing protein called gp130, leading to activation of intracellular pathways such as JAK/STAT3, MAPK, and PI3K/AKT. These pathways regulate cell survival, proliferation, and inflammation, which are essential for wound repair. In trans-signalling, IL-6 binds to a soluble form of IL-6R, and this complex can act on a wider range of cells that do not normally express IL-6R. This mechanism is particularly important in chronic inflammation and tissue regeneration during wound healing.
During the early inflammatory phase of wound healing, IL-6 is rapidly produced by immune cells such as macrophages, neutrophils, and fibroblasts. It helps recruit additional immune cells to the wound site and promotes the clearance of pathogens and damaged tissue. IL-6 also stimulates acute phase responses that support the body’s Défense mechanisms.
In the proliferative phase, IL-6 contributes to tissue regeneration by promoting fibroblast activation, collagen production, and angiogenesis (formation of new blood vessels). It also supports keratinocyte migration, which is important for re-epithelialization of the wound surface. However, excessive or prolonged IL-6 signalling can lead to chronic inflammation and delayed wound healing. Elevated IL-6 levels are often associated with non-healing wounds such as diabetic ulcers and inflammatory skin conditions. Overall, the IL-6 receptor plays a dual role in wound healing by promoting both inflammatory Défense and tissue repair. Proper regulation of IL-6 signalling is essential for balanced and effective wound healing.
Figure no.5 IL-6 Mechanism of Wound Healing
1.6 Tridax Procumbens: -
???? Biological Source
Tridax procumbens consists of the whole plant or leaves of Tridax procumbens Linn., belonging to the family Asteraceae.
???? Geographical Source
The plant is widely distributed in tropical and subtropical regions, especially in India, Africa, and South America. It commonly grows as a weed in fields, roadsides, and waste lands.
???? Macroscopic Characters
???? Microscopic Characters
???? Chemical Constituents
???? Pharmacological Actions
?? Mechanism of Action (Wound Healing)
The plant promotes wound healing by:
???? Uses
???? Preparation / Formulation
Figure no.6 Tridax Procumbens Plant
2. AIM AND OBJECTIVE: -
AIM: -
To investigate the pharmacological potential of Tridax procumbens in wound healing by studying its effects on collagen synthesis, fibroblast proliferation, angiogenesis, and epithelialization.
OBJECTIVES : -
3. EXPERIMENT WORK: -
3.1 Downloading Software Program: -
PYRX: - PyRx is an open-source virtual screening software used in Computer-Aided Drug Design to perform molecular docking and analysed ligand–protein interactions. It provides a user-friendly graphical interface that integrates tools such as AutoDock and AutoDock Vina for docking simulations. PyRx allows researchers to import protein and ligand structures, prepare molecules, and perform energy minimization before docking.
The software is widely used for virtual screening of large compound libraries to identify potential drug candidates. It helps in predicting binding affinity and selecting the best ligand based on docking scores. PyRx also supports visualization of molecular interactions, which aids in understanding how a drug binds to its target receptor.
BIOVIA-DISCOVERY STUDIO: - BIOVIA Discovery Studio is widely used in Computer-Aided Drug Design (CADD) to study interactions between ligands (drug molecules) and biological targets such as proteins and enzymes. It allows researchers to visualize molecular structures in three dimensions and analysed binding interactions at the atomic level.
The software includes various modules for molecular docking, pharmacophore modelling, quantitative structure–activity relationship (QSAR) studies, and virtual screening.
AVAGADRO: - is an open-source molecular modelling and visualization tool used in chemistry, pharmacology, and Computer-Aided Drug Design (CADD). It is designed to build, edit, and visualize molecular structures in three-dimensional (3D) form.
CHEMSKETCH: - ACD/ChemSketch is a chemical drawing and molecular modeling software developed by Advanced Chemistry Development (ACD/Labs). It is widely used in chemistry, pharmacology, and Computer-Aided Drug Design (CADD) for drawing chemical structures and predicting basic molecular properties.
3.2 Preparation of Ligand: -
In this study, Triadx Procumbens, was chosen for wound healing properties. Various phytochemical present in triadx procumbens to its therapeutic effects. To understand further select phytoconstituent using Chemsketch software and then structure was cleaned and then structure was saved in the working folder as mol file. This mol file was then accessed in Avogadro software tool in which that the mol file is convert to pdb format and then structure was optimized by using the optimization tool and then saved the optimized structure in the working directory as .pdb file.
Table No.1. Phytoconstituent of Tridax Procumbens
|
Sr.No |
Ligands |
IUPAC Name |
2D Structure |
|
1 |
9-Heptadecanone |
heptadecan-9-one |
|
|
2 |
Beta-amyrone |
4aR,6aR,6bS,8aR,12aR,14aR,14bR)-4,4,6a,6b,8a,11,11,14b-octamethyl-2,4a,5,6,7,8,9,10,12,12a,14, 14a-dodecahydro-1H-picen-3-one |
|
|
3 |
Beta-sitosterol |
(3S,8S,9S,10R,13R,14S,17R)-17-[(2R,5R)-5-ethyl-6-methylheptan-2-yl]-10,13-dimethyl-2,3,4,7,8,9,11,12,14,15,16, 17-dodecahydro-1H-cyclopenta[a] phenanthren-3-ol |
|
|
4 |
Campesterol |
: (3S,8S,9S,10R,13R,14S,17R)-17-[(2R,5R)-5,6-dimethylheptan-2-yl]-10,13-dimethyl-2,3,4,7,8,9,11,12,14,15,16, 17-dodecahydro-1H-cyclopenta[a] phenanthren-3-ol |
|
|
5 |
Cynaroside |
2-(3,4-dihydroxyphenyl)-5-hydroxy-7-[(2S,3R,4S,5S,6R)-3,4,5-trihydroxy-6-(hydroxymethyl) oxan-2-yl] oxychromen-4-one |
|
|
6 |
Framycetin |
(2R,3S,4R,5R,6R)-5-amino-2-(aminomethyl) -6-[(1R,2R,3S,4R,6S)-4,6-diamino-2-[(2S,3R,4S,5R)-4-[(2R,3R,4R,5S,6S) -3-amino-6-(aminomethyl) -4,5-dihydroxyoxan-2-yl] oxy-3-hydroxy-5- (hydroxymethyl)oxolan-2-yl] oxy-3-hydroxycyclohexyl] oxyoxane-3,4-diol |
|
|
7 |
Lupeol |
(1R,3aR,5aR,5bR,7aR,9S,11aR,11bR, 13aR,13bR)-3a,5a,5b,8,8,11a- hexamethyl-1-prop-1-en-2-yl-1,2,3,4,5,6,7,7a,9,10,11,11b,12,13, 13a,13b-hexadecahydrocyclopenta [a]chrysen-9-ol |
|
|
8 |
Olane-12-en-3-one |
(6aR,6bS,8aR,12aS,14aR,14bR)-4,4,6a,6b,8a,11,11,14b-octamethyl-2,4a,5,6,7,8,9,10,12,12a,14,14a-dodecahydro-1H-picen-3-one |
|
|
9 |
Quercetin |
2-(3,4-dihydroxyphenyl)-3,5,7-trihydroxychromen-4-one |
|
|
10 |
Stigmasterol |
(3S,8S,9S,10R,13R,14S,17R)-17- [(E,2R,5S)-5-ethyl-6-methylhept -3-en-2-yl]-10,13-dimethyl-2,3,4,7,8,9,11,12,14,15,16,17 -dodecahydro-1H-cyclopenta [a]phenanthren-3-ol |
|
|
11 |
Linoleic |
octadeca-9,12-dienoic acid |
|
|
12 |
Linolenic |
octadeca-9,12,15-trienoic acid |
|
|
13 |
Palmitoleic acid |
hexadec-9-enoic acid |
|
3.3 Preparation of Receptor: -
Figure no.7 3ED Structure of receptor 6P9E
3.4 Physicochemical Properties: -
Lipinski rule was used to assess the physiochemical properties of all the selected ligands and to predict their drug like properties, and the Swiss ADME as used to computer SMILE structure of each compound.
3.5 ADME Studies:
ADME (Absorption, Distribution, Metabolism and Excretion) studies are indeed crucial in drug development to assess how a drug behaves the body. Swiss ADME software was used to determine these properties of each ligand.
3.6 Druglikeness :-
SwissADME evaluates drug-likeness by applying rules such as Lipinski, Ghose, Veber, Egan, and Muegge, along with physicochemical properties like molecular weight, lipophilicity, and polarity, to predict whether a compound is suitable for oral drug development.
3.7 Toxicity Study: -
It allows users to input a compound (via name, SMILES, or structure) and predicts over 60 toxicity endpoints, including acute toxicity (LD??), organ toxicity (like hepatotoxicity and neurotoxicity), carcinogenicity, mutagenicity, immunotoxicity, and clinical toxicity.
The platform uses multiple predictive models (about 61) based on approaches such as fragment analysis, pharmacophore modelling, and machine learning algorithms (e.g., Random Forest and neural networks) to generate results with confidence scores.
3.8 Molecular Docking: -
To perform molecular docking using PyRx:-
4. RESULTS AND DISCUSSION: -
1. Physicochemical properties: -
The physicochemical properties of the compound were studied to predict the pharmacokinetics of the drugs, using Lipinski’s Rule of Five is a set of guidelines used to evaluate the drug-likeness of a compound, particularly its potential for good oral bioavailability. It states that a molecule is more likely to be orally active if it has a molecular weight of 500 Daltons or less, a lipophilicity value (Log P) not greater than 5, no more than 5 hydrogen bond donors, and no more than 10 hydrogen bond acceptors.
Table No.2. Physicochemical Properties of Ligands
|
Sr. No |
Ligands |
No. of rotatable bonds |
No. of H- bond accept |
No. of H- bond donors |
Molar refractivity |
Molecular Weight (g/mol) |
TPSA |
|
1 |
9-Heptadecanone |
14 |
1 |
0 |
84.03 |
254.45 |
17.07 |
|
2 |
Beta-amyrin |
0 |
1 |
1 |
134.88 |
426.72 |
20.23 |
|
3 |
Beta-sitosterol |
6 |
1 |
1 |
133.23 |
414.71 |
20.23 |
|
4 |
Campesterol |
5 |
1 |
1 |
128.42 |
400.68 |
20.23 |
|
5 |
Cynarocide |
4 |
11 |
7 |
108.13 |
448.38 |
190.28 |
|
6 |
Framycetin |
9 |
19 |
13 |
135.11 |
614.64 |
353.11 |
|
7 |
Lupeol |
1 |
1 |
1 |
135.14 |
426.72 |
20.23 |
|
8 |
Olane-12-en-3-one |
0 |
1 |
10 |
132.92 |
424.70 |
17.07 |
|
9 |
Quercetin |
1 |
7 |
5 |
78.03 |
302.24 |
131.36 |
|
10 |
Stigmasterol |
5 |
1 |
1 |
132.75 |
412.69 |
20.23 |
|
11 |
Linoleic |
14 |
2 |
1 |
89.46 |
280.85 |
37.30 |
|
12 |
Linolenic |
13 |
2 |
1 |
88.99 |
278.43 |
37.30 |
|
13 |
Palmitoleic acid |
13 |
2 |
1 |
80.32 |
254.41 |
37.30 |
2. ADME Properties: -
ADME data predict using the Swiss ADME online web server database of phytocompounds.
Table No.3. Pharmacokinetics Properties of Ligands
|
Sr. No |
Ligands |
GI absorption |
BBB permeant |
P-gp substrate |
CYP1A2 inhibitor |
CYP2C19 inhibitor |
Log Kp (cm/s) |
|
1 |
9-Heptadecanone |
HIGH |
NO |
NO |
YES |
NO |
-2.87 |
|
2 |
Beta-amyrin |
LOW |
NO |
NO |
NO |
NO |
-2.41 |
|
3 |
Beta-sitosterol |
LOW |
NO |
NO |
NO |
NO |
-2.20 |
|
4 |
Campesterol |
LOW |
NO |
NO |
NO |
NO |
-2.50 |
|
5 |
Cynarocide |
LOW |
NO |
YES |
NO |
NO |
-8.00 |
|
6 |
Framycetin |
LOW |
NO |
YES |
NO |
NO |
-16.43 |
|
7 |
Lupeol |
LOW |
NO |
NO |
NO |
NO |
-1.90 |
|
8 |
Olane-12-en-3-one |
LOW |
NO |
NO |
NO |
NO |
-2.61 |
|
9 |
Quercetin |
HIGH |
NO |
NO |
YES |
NO |
-7.05 |
|
10 |
Stigmasterol |
LOW |
NO |
NO |
NO |
NO |
-2.74 |
|
11 |
Linoleic |
HIGH |
YES |
NO |
YES |
NO |
-3.05 |
|
12 |
Linolenic |
HIGH |
YES |
NO |
YES |
NO |
-3.41 |
|
13 |
Palmitoleic acid |
HIGH |
YES |
NO |
YES |
NO |
-3.18 |
3. Drug likeness :-
The drug-likeness capability of phytoconstituents can be predict using Lipinski, Ghose, Veber, Egan, and Muegge rules which are based on certain physicochemical parameters.
Table No.4. Drug likeness Properties of Ligands
|
Sr. No |
Ligands |
Lipinski |
Ghose |
Veber |
Egan |
Muegge |
Bioavailability score |
|
1 |
9-Heptadecanone |
YES |
NO |
NO |
NO |
NO |
0.55 |
|
2 |
Beta-amyrone |
YES |
NO |
YES |
NO |
NO |
0.55 |
|
3 |
Beta-sitosterol |
YES |
NO |
YES |
NO |
NO |
0.55 |
|
4 |
Campesterol |
YES |
NO |
YES |
NO |
NO |
0.55 |
|
5 |
Cynarocide |
NO |
YES |
NO |
NO |
NO |
0.17 |
|
6 |
Framycetin |
NO |
NO |
NO |
NO |
NO |
0.17 |
|
7 |
Lupeol |
YES |
NO |
YES |
NO |
NO |
0.55 |
|
8 |
Olane-12-en-3-one |
YES |
NO |
YES |
NO |
NO |
0.55 |
|
9 |
Quercetin |
YES |
YES |
YES |
YES |
YES |
0.55 |
|
10 |
Stigmasterol |
YES |
NO |
YES |
NO |
NO |
0.55 |
|
11 |
Linoleic |
YES |
NO |
NO |
NO |
NO |
0.85 |
|
12 |
Linolenic |
YES |
NO |
NO |
YES |
NO |
0.85 |
|
13 |
Palmitoleic acid |
YES |
YES |
NO |
YES |
NO |
0.85 |
4. Toxicity Study :-
Toxicity prediction is the important step in drug development and design. High demand for computational predictive model to evaluate the potent toxic effects of drugs. In silico study toxicity of drug is evaluating by Protox 3.0 online database.
Table No.5. Toxicity Study of Ligand
|
Sr. No |
Ligands |
Predicted Toxicity class |
Predicted LD50 (mg/kg) |
Carcinog enicity |
Hepato toxicity |
Immuno toxicity |
Nephro toxicity |
|
1 |
9-Heptadecanone |
5 |
5000 |
INACTIVE |
INACTIVE |
INACTIVE |
INACTIVE |
|
2 |
Beta-amyrone |
5 |
5000 |
INACTIVE |
INACTIVE |
ACTIVE |
INACTIVE |
|
3 |
Beta-sitosterol |
4 |
890 |
INACTIVE |
INACTIVE |
ACTIVE |
INACTIVE |
|
4 |
Campesterol |
4 |
890 |
INACTIVE |
INACTIVE |
ACTIVE |
INACTIVE |
|
5 |
Cynaroside |
5 |
5000 |
INACTIVE |
INACTIVE |
INACTIVE |
ACTIVE |
|
6 |
Framycetin |
5 |
2275 |
INACTIVE |
INACTIVE |
INACTIVE |
ACTIVE |
|
7 |
Lupeol |
4 |
2000 |
INACTIVE |
INACTIVE |
ACTIVE |
INACTIVE |
|
8 |
Olane-12-en-3-one |
5 |
5000 |
INACTIVE |
INACTIVE |
ACTIVE |
INACTIVE |
|
9 |
Quercetin |
3 |
159 |
ACTIVE |
INACTIVE |
INACTIVE |
INACTIVE |
|
10 |
Stigmasterol |
4 |
890 |
INACTIVE |
INACTIVE |
ACTIVE |
INACTIVE |
|
11 |
Linoleic |
4 |
1190 |
INACTIVE |
ACTIVE |
ACTIVE |
INACTIVE |
|
12 |
Linolenic |
6 |
10000 |
INACTIVE |
INACTIVE |
INACTIVE |
INACTIVE |
|
13 |
Palmitoleic acid |
2 |
48 |
INACTIVE |
INACTIVE |
INACTIVE |
INACTIVE |
5. Binding affinity of Ligands :-
Table No.6. Binding affinity of phytoconstituents of Triadx Procumbens with (IL-6) 9P6E receptor
|
Sr. No |
Ligands |
Binding affinity |
|
1 |
9-Heptadecanone |
-5.4 |
|
2 |
Beta-amyrone |
0.5 |
|
3 |
Beta-sitosterol |
- |
|
4 |
Campesterol |
-5.9 |
|
5 |
Cynaroside |
-7.7 |
|
6 |
Framycetin |
-5.3 |
|
7 |
Lupeol |
-3.6 |
|
8 |
Olane-12-en-3-one |
-1.9 |
|
9 |
Quercetin |
-7.3 |
|
10 |
Stigmasterol |
-5.1 |
|
11 |
Linoleic |
-6.1 |
|
12 |
Linolenic |
-6.2 |
|
13 |
Palmitoleic acid |
-6.1 |
6. 3D and 2D Structure of Phytoconstituents of Tridax Procumbens: -
Table no.7. 3D and 2D Structures of Phytoconstituents of Tridax Procumbens
|
Sr.No |
LIGAND |
3D STRUCTURE |
2D STRUCTURE |
|
1. |
BETA-AMYRONE |
|
|
|
2. |
9-HEPTADEC ACONE |
|
|
|
3.
|
CAMPESTE ROL |
|
|
|
4. |
CYNARO SIDE |
|
|
|
5. |
FRAMY CETINE |
|
|
|
6. |
LINOLEIC |
|
|
|
7. |
LINOLENIC |
|
|
|
8. |
LUPIOL |
|
|
|
9. |
OLANE-12- EN-3-ONE |
|
|
|
10. |
PALMITIC |
|
|
|
11. |
PALMITOLIC ACID |
|
|
|
12. |
QUERCITIN |
|
|
|
13. |
STIGME STEROL |
|
|
5. CONCLUSION: -
The Tridax Procumbens contain 13 majors Phytoconstituents. The study of ADME showed all phytoconstituents are absorbed from the GI tract and Toxicity showed they are non-toxic and obey the Lipinski rule. The Molecular Docking of phytoconstituents with 6P9E receptor for Wound Healing showed Cynaroside, Quercetin, Linoleic, Linolenic, Palmitoleic acid, Campesterol, 9-Heptadecanone have good binding affinity as compare as to standard drug
Framycetin, therefore Cynaroside, Quercetin, Linoleic, Linolenic, Palmitoleic acid, Campesterol, 9-Heptadecanone act as lead molecule for further development on acting IL-6 receptor for better Wound Healing activity with minimum sides effects.
REFERENCES
D. P. Kawade, M. R. Chaudhari, S. M. Raut, N. B. Kureshi, N. T. Borkar, O. A. Lalzare, P. S. Mithe, Molecular Docking Analysis of Tridax Procumbens Phytocompounds Targeting Wound Healing Properties, Int. J. of Pharm. Sci., 2026, Vol 4, Issue 5, 3508-3528. https://doi.org/10.5281/zenodo.20184232
10.5281/zenodo.20184232
