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. 2024 Mar 26;12(1):19. doi: 10.1007/s40203-024-00194-4

In-silico screening of phytomolecules against multiple targets for wound management

Asha Thomas 1,✉, Sheetal Shinde 1, Ravindra Wavhale 1, Pranali Jadhav 1, Sham Tambe 1, Kiran Lokhande 2,3, Sohan Chitlange 1
PMCID: PMC10965871  PMID: 38550524

Abstract

Chronic wound healing, especially in burns, is a major medical challenge with limited treatments. This study employs computational tools to identify phytomolecules that target multiple pathways involved in wound healing. By utilizing shape analysis, molecular docking, and binding energy calculations, potential compounds are pinpointed,to address the growing problem of chronic wounds. Initially, a set of phytomolecules from the ZINC database of natural molecules was screened to find compounds with shapes similar to well-known wound healing phytomolecules like curcumin, chromogenic acid, gallic acid, and quercetin. The most promising phytomolecules identified through shape similarity were further studied through molecular docking studies on several key targets involved in wound healing, including TNF-α, FGF, and TGF-β. Among the tested phytomolecules, a ligand known as Fluorophenyl(5-(5-chloro-1-(2-fluorophenyl)-2-oxopentyl)-4,5,6,7-tetrahydrothieno[3,2c]pyridine-2-yl acetate) exhibited a strong affinity with favourable binding interactions for TNF-α ( – 7.1 kcal/mole), FGF (-6.9 kcal/mole), and TGF-β (-5.1 kcal/mole). Another compound, 2,4 methoxybenzylidene-(-3)-oxo-2,3-dihydro-1-benzofuran-6-yl-4-methoxybenzoate, demonstrated a strong affinity with low binding energy for TNF-α ( – 6.8 kcal/mole) and FGF ( – 7.0 kcal/mole) targets. Isosakuranetin and Ermanin displayed moderate affinity for both TNF-α and FGF, with the highest affinity observed for the TGF-β target. These findings suggest that these identified phytomolecules hold promise as potential lead compounds for further structural modifications, with the goal of designing new molecules that can target multiple pathways involved in the wound healing process.

Keywords: Docking; Wound healing; In-silico studies,Phytomolecules; Shape similarity

Introduction

Wounds, resulting from various factors such as trauma, injuries, and diabetes, have garnered increased attention in the context of acute and chronic wound care (Lo et al. 2012; Gurtner et al. 2008; Monsuur et al. 2016). Wound healing is a complex process involving stages like inflammation, proliferation, and remodelling, which occur concurrently. During inflammation, immune cells like neutrophils and monocytes combat infection (Akbik et al. 2014; Smith et al. 2000). The proliferation phase sees the action of factors like fibroblasts, keratinocytes, and endothelial cells promoting tissue repair and angiogenesis (Singer and Clark 1999; Charteris 1995; Pastar et al. 2014). Remodelling involves the formation of the extracellular matrix for mechanical strength (Young and McNaught 2011; Enochet al. 2006). Globally, wounds and infections affect approximately 8.2 million people, with chronic wound patients facing a higher mortality rate than cancer patients (Sen 2019). This highlights the growing demand for herbal products in prolonged wound treatment (Eming et al. 2007). However, many herbal products lack scientific validation of their mechanisms in wound management (Topmanet al. 2013). To address this, understanding the molecular mechanisms of herbal remedies and their target-specific effects in wound management is essential. Molecular docking studies can aid in identifying molecular targets of phytoconstituents, facilitating the development of target-oriented wound healing drugs (Sharma and Virmani 2020).

In-silico studies are a crucial preliminary step preceding in-vivo investigations. They play a pivotal role in designing site-specific, target-oriented products, thereby enhancing therapeutic efficacy while minimizing potential and sometimes detrimental side effects. In this study, we have incorporated phytomolecules such as quercetin, curcumin, chlorogenic acid, and gallic acid, all known for their notable wound healing properties. Curcumin (1,7-Bis(4-hydroxy-3-methoxyphenyl)-1,6-heptadiene-3,5-dione), a phenolic compound derived from the rhizome of Curcuma longa L. (Zingiberaceae family), possesses a versatile range of properties (Mahmood et al. 2015; Naksuriya et al. 2014). These include antimutagenic, wound healing (Maheshwari et al. 2006), anti-inflammatory (Chattopadhyay et al. 2003), anti-coagulant, anti-infective (Zielinska et al. 2020), antioxidant (Agrawal and Mishra 2010) and anticarcinogenic (Jardim et al. 2015) effects. Curcumin’s multifaceted attributes make it a valuable candidate for therapeutic applications.

The anti-inflammatory, anti-oxidant, and anti-infective properties of curcumin are connected to its wound-healing characteristics, as well as the suppression of STAT (Signal Transducers and Transcription Activators), TNF-α (Tumour Necrosis Factor-Alpha), CCND1 (Cyclin D1), COX-2 (Cyclooxygenase-2), NFkB (Nuclear Factor Kappa-Light-Chain-Enhancer of Activated B Cells), IL (Interleukins) expressions, and down-regulation of MMP-8 (Matrix Metallopeptidases) expression (Mohanty et al. 2012; Akbik et al. 2014; Ghosh et al. 2015). Curcumin has been found to exhibit antimicrobial properties, effectively inhibiting the growth of various infections, including methicillin-resistant Staphylococcus aureus (MRSA) (Mun et al. 2013), as well as P. intermedia, F. nucleatum, and P. gingivitis (Izui et al. 2016).

Chlorogenic acid, [3-(3, 4-dihydroxyphenyl) prop-2-enoyl] oxy-1, 4, 5-trihydroxycyclohexane-1-carboxylic acid, is a polyphenolic compound abundantly present in human diet (Clifford 2000; Wang and Ho 2009). Herbs such as Malus domestica (Apple), Cynara cardunculus (artichoke), Piper betel (betel), Arctium (burdock), Daucuscarota (carrots), Coffea arabica (coffee beans), Lonicera (honeysuckle), Actinidia deliciosa (kiwi fruit), and Artemisia absinthium (wormwood) contain chlorogenic acid (Santana-Galvez et al. 2017). When compared to other polyphenols, chlorogenic acid shows excellent anti-carcinogenic (Bagdas et al. 2012) and antioxidant properties (Xuet al. 2012; Cinkilic et al. 2013). Due to its prevalent occurrence in diverse plant sources, chlorogenic acid presents a potentially economical alternative for treating wounds (Bagdas et al. 2014; Chen et al. 2013). The documented mechanisms underlying chlorogenic acid's wound healing properties encompass the stimulation of collagen production, augmentation of antioxidant activity, increased capillary density, scavenging of free radicals affecting oxidative parameters, and mitigation of inflammation by targeting MMPs expressed in wound tissues (Moghadamet al. 2017; Bagdas et al. 2014).

Literature studies also indicate that quercetin, a flavonoid compound [3, 3′, 4′, 5, 7-pentahydroxy flvanone, is reported to show antioxidant, anti-inflammatory (Xu et al. 2019), and anticancer activities (Raufet al. 2018). Quercetin is found in several herbs including Allium cepa, Vitis vinifera, Prunus avium, Brassica oleracea, Citrus limonn, Ginkgo biloba, Hypericum perforatum (Rauf et al. 2018; Li et al. 2016). Quercetin has been shown to hasten wound healing by increasing the production of collagen and fibronectin at the wound site. It also assists in nerve tissue regeneration at the wound site. Doersch et al. incorporated quercetin into a collagen matrix to generate a novel dressing material for cutaneous wound healing (Doersch and Newell-Rogers 2017). The wound healing duration in quercetin-treated animals was about 14 days, with less fibrosis at the wound site, suggesting that quercetin alters the cell association with the extracellular matrix via altering integrin expression, resulting in reduced fibrosis (Gomathi et al. 2003). Kantand co-workers found that topical use of quercetin improves wound healing by effectively controlling the cytokines and cells involved in different stages of wound healing. The expressions of vascular endothelial growth factor (VEGF) and transforming growth factor-beta 1 (TGF-β1) were greatly up-regulated, but TNF levels were significantly reduced, as wound closure progressed drastically over time (Kant et al. 2020).

Gallic acid, chemically [3, 4, 5-trihydroxybenzoic acid], is a polyphenolic compound with anti-inflammatory (Ben Saad et al. 2017), wound healing (Yang et al. 2016), anti-microbial, anti-oxidant (Badhani et al. 2015), and anti-cancer properties (Bachrach and Wang 2002). Gallic acid is found in the leaves of bearberry, root and bark of pomegranate, gallnuts, oak barks, Cyan coccus (Blueberry), Rubus, Fragaria, Vitis vinifera, Mangifera indica, Juglans (Goldberg and Stefan 2019; Daglia et al. 2014). Gallic acid has been shown to be a promising tissue repair agent and a potential therapy for wounds caused by metabolic problems in various investigations.

Based on the existing evidence of the wound healing potential of these phytomolecules, they were selected as standards to help in identification of other potent phytochemicals through various in-silico approaches.

Materials and methods

The in-silico screening of phytomolecules was done by carrying out shape similarity studies followed by molecular docking studies. The shape similarity study and virtual screening of ligand database were performed using the vROCS version3.3 (Open Eye Scientific Software)(https://www.eyesopen.com/rocs) and ZINC Natural Database (https://zinc.docking.org/substances/subsets/natural-products/). ChemDraw V. 15.0 was used for the preparation of ligands while Open Babel (http://openbabel.org/Main_Page) was used for extraction of PDBQT files. Auto dock (Vina) (http://autodock.scripps.edu/resources/adt) and Discovery studio (https://www.3ds.com/biovia/products/molecular-modeling-simulation/biovia-discovery studio/visualization/) was used for docking and visualization of docked poses.

Shape similarity screening

vROCS 3.3, a shape-based virtual screening tool, was employed to screen phytochemicals from the ZINC database for shape similarity (Sastryet al. 2011). ROCS, another algorithm, ranks molecules based on their similarity to a reference, aiding in the discovery of compounds with similar biological properties. It aligns molecules by shape, colour, or chemical characteristics, using 3D conformations of query and database molecules (Ballester and Richards 2007; Shin et al. 2015). ROCS is efficient, surpassing structure-based screening, and valuable for finding compounds with similar properties based on structural features (Kearnes and Pande 2016; Abdul et al. 2012; Hawkins et al. 2007).

In this study, lower energy conformation of quercetin, curcumin, gallic acid, and chlorogenic acid were submitted individually as query structures and screened to search 3D shape similarity with the ZINC phytochemical database. Results were obtained as Tanimoto shape similarity, Tanimoto colour similarity, and Tanimoto combo similarity that indicates 3D shape similarity, atom similarity, and combine similarity of query molecule with database molecules, respectively. Tanimoto scores are represented on a scale of 0–1 indicating a percentage similarity of 0% to 100% (Bajusz et al. 2015; Anighoro and Bajorath 2016). 3D structures of molecules were annotated with molecular weight, computed log P, and the number of rotatable bonds in the ZINC collection of commercially accessible compounds for virtual screening (Irwin et al. 2020). Any molecule in the library can be subjected to virtual screening, including docking (Imran et al. 2020).

Structure based drug likeness property and ADME/T property

The molecular structures of all ligands were subjected to analysis using the SWISSADME server to verify adherence to Lipinski's rule of five, assessing physicochemical properties such as refractive index, H-bond donor/acceptor, molecular weight, etc. To estimate each ligand's pharmacokinetic and pharmacodynamic features, such as human abdominal absorption, carcinogenicity, cytochrome P inhibitory promiscuity, etc., the ADME/T profile of each ligand has been examined using the ADME/T SAR server.

Molecular docking studies

Molecular docking with AutoDock 4.0(Vina) assessed phytoconstituent interactions with wound management enzymes. Binding energies determine affinity, validating by re-docking the natural ligand. Lower free energy suggests stronger binding to receptors, a crucial aspect of in-silico drug design (Allouche 2011; Selinger and Groot 2010).

Ligand preparation

The standard phytoconstituents and test molecules selected from the shape similarity study were taken for docking studies. Test ligands are downloaded from the PubChem chemical database in sdf format and the 2D molecular structures were drawn using ChemDraw. OPEN BABEL GUI Software was used for the conversion of the 2D structures to 3D.pdb format. Then the energy minimizationwas performed using Avogadro (https://avogadro.cc/) and further docked using Auto dock tools (ADT) 1.5.6 software. The optimized ligands were then used for Docking.

Protein preparation/selection

The study selected protein targets associated with different stages of wound healing. TNF-α is linked to the inflammatory phase and can hinder wound healing by affecting fibroblast function and collagen deposition. Fibroblast Growth Factor (FGF) facilitates wound closure and plays a crucial role in processes like cell proliferation, differentiation, migration, morphogenesis, and angiogenesis, interacting with tyrosine kinase receptors and Heparin sulphate receptor (HS) (Demidova-Rice et al. 2012; Koike et al. 2020). TGF (Transforming Growth Factor) regulates the wound healing remodelling phase, encompassing inflammation, angiogenesis, fibroblast activity, collagen synthesis, and extracellular matrix formation. These targets are vital in orchestrating the various stages of wound healing.

The 3-dimensional structures of the selected targets were downloaded from the Protein data bank (https://www.rcsb.org/) forthe in-silico studies. TNF-α (PDB ID: 2AZ5) with resolution (R = 2.1 A0) having co-crystallized ligand {6,7-Dimethyl-3-[(Methyl{2-[Methyl({1-[3-(Trifluoromethyl)phenyl]-1 h-Indol-3-Yl}methyl) amino]ethyl}amino)methyl]-4 h-Chromen-4-One; FGF (PDB ID: 40EE) with resolution (R = 1.5A0) having co-crystallized ligand 2-Deoxy-3-O-Sulfo-2-(Sulfonating)-Alpha-D-Glucopyranose and TGF-β (PDB ID: 1TGJ) with resolution (R = 2.0A0) having co-crystallized ligand 1, 4-Diethylene dioxide were selected in this study (Fig. 1). All the proteins were prepared by removing water molecules, adding polar hydrogen atoms, Kolman charges, and saved in pdbqt format using Auto dock tools (ADT) 1.5.6.

Fig. 1.

Fig. 1

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3D images of the selected targets and their Lig plots A TNF-α, B Lig plot of TNF-α with co-crystallized ligand, C FGF, D Lig plot of FGF with co-crystallized ligand, E TGF-β, F Lig plot of TGF-β with co-crystallized ligand

Receptor grid generation

The study explored the interaction between the chosen ligands and receptor proteins by creating a receptor grid. The already bound ligand (i.e., co-crystallized ligand) was extracted from the PDBsum website, and the grid was generated using the position of the loaded ligand (confined to the enclosing shell), the centroid of the docked pose and identical in size to the workspace ligand. To carry out in-silico studies, a grid box was defined enclosing the binding pocket with dimensions of centre x: – 18.513, y: – 44.504, and z: – 36.686 with a grid spacing of 0.375A0 for the target TNF-α with (PDB ID: 2AZ5). For the target FGF with (PDBID: 40EE) the dimensions of centre was x: – 13.591, y: – 8.329, z: – 3.464 with a grid spacing of 0.375 A0 and for the target TGF-β with (PDBID: 1TGJ) x: 19.332, y: 20.065, z: 23.982 with a grid spacing of 0.375A0.

Results & discussion

Shape similarity study

In the shape similarity, top molecules were selected based on similarity with the phytochemicals from 500 molecules available in ZINC phytochemical database (Fig. 2). Phytochemicals were categorized according to the Tanimoto combination index, which was computed based on the similarity in both shape and color. Various structural attributes are depicted by distinct colors, with lighter shades indicating a reduced overlap between the query and hit color atoms in three-dimensional space. Shape similarity assesses the quality of the three-dimensional shape alignment between the query and the hit structure (Hawkins et al. 2007). Top two molecules similar to selected compounds with their similarity score in given in Table 1.

Fig. 2.

Fig. 2

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Ligands obtained which are similar to standard lignds and their overlay

Table 1.

Comparison of standard and test ligands on the basis of their shape and colour similarity

Standard Ligand Shape Similarity Ligand Tanimoto combo of Both Shape Tanimoto (%) Colour Tanimoto (%)
Chlorogenic Acid Isochlorogenic Acid 1.95 70–72 19–25
Fluorophenyl (5-(5-Chloro-1-(2-fluorophenyl)-2-oxopentyl)-4,5,6,7-tetrahydrothieno[3,2-c]pyridine-2-yl acetate) 0.90 70–73 12–18
Gallic Acid 5-methoxy resorcinol 1.413 90–91 5–10
Germicidin 1.27 88–20 5–8
Curcumin 2,4 methoxybenzylidene-(-3)-oxo-2,3-dihydro-1-benzofuran-6-yl-4-methoxybenzoate 1.921 70–75 20–25
Methyl rosmarinate 0.91 60–65 20–28
Quercetin Ermanin (5,7 dihydroxy- 3,4 dimethoxy flavone) 1.601 80–87 68–75
Lsosakuranetin 1.55 85–90 60–65
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Structure based drug likeness property and ADME/T property

Lipinski's rule and Veber rule are the two main factors that determine structure-based drug likeness properties. Veber’s rule looks at a potential drug candidate's oral bioavailability. Molecular weight less than 500, log P greater than 5, H-bond acceptor less than 10 and H-bond donor less than 5 as well as molar refractivity in the range of 40 to 130 are acceptable Lipinski’s rule criteria. Veber's rule requires topical polar surface area (TPSA) to be less than 140 and rotatable bonds to be less than 12.

Isochlorogenic acid have shown higher similarity to chlorogenic acid but it has shown three violations in Lipinski’s rule (Mol. Weight: 516.45, H-bond acceptor: 12, H-bond donor: 7) and one violation in Veber’s rule in context of topical polar surface area (211.28), hence it was not selected for further studies. All other selected ligands followed both the rules and summary of the drug-likeness property analysis is presented in Table 2. Ermanin demonstrated impermeability to the BBB, while other ligands showed permeability to BBB. All of them showed high intestinal absorption in humans and non-substrate enzyme activity to p-glycoprotein substrate. All of them showed, non- carcinogenicity and no biodegradability except 5-methoxy resorcinol, which is biodegradable. All the ligands exhibited type III acute oral toxicity.

Table 2.

Structure Based Drug Likeness and ADME/T Properties of Selected Ligands

Sr. No Drug Likeness Properties Fluorophenyl (5-(5-Chloro-1-(2-fluorophenyl)-2-oxopentyl)-4,5,6,7-tetrahydrothieno[3,2-c] pyridine-2-yl acetate) 2,4 methoxybenzylidene-(-3)-oxo-2,3-dihydro-1-benzofuran-6-yl-4-methoxybenzoate Ermanin (5,7 dihydroxy- 3,4 dimethoxy flavone) 5-methoxy resorcinol
1 Molecular weight 409.9 g/mol 252.26 g/mol 314.29 g/mol 140.14 g/mol
2 Heavy atoms 27 19 23 10
3 H-bond acceptor 5 3 6 3
4 H- bond donor 0 0 2 2
5 Molar refractivity 108.73 72.31 84.95 36.98
6 TPSA 74.85 Å2 35.53 Å2 89.13 Å2 49.69 Å2
7 Rotatable bonds 8 2 3 1
8 Lipinski rule Yes, 0 violations Yes, 0 violations Yes, 0 violations Yes, 0 violations
9 Veber rule Yes, 0 violations Yes, 0 violations Yes, 0 violations Yes, 0 violations
10 Blood- brain barrier Yes Yes No Yes
11 Human intestinal absorption High High High High
12 P- glycoprotein substrate Non- substrate Non- substrate Non- substrate Non- substrate
13 CYP450 1A2 Inhibitor No Yes Yes No
14 CYP4502C19 Inhibitor Yes Yes No No
15 CYP450 2C9 Inhibitor Yes Yes Yes No
16 CYP450 2D6 Inhibitor Yes No Yes No
17 CYP450 3A4 Inhibitor Yes Yes Yes Yes
18 Carcinogens Non- carcinogens Non- carcinogens Non- carcinogens Non- carcinogens
19 Biodegradation Not readily biodegradable Not readily biodegradable Not readily biodegradable Readily biodegradable
20 Acute oral toxicity III III III III
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Docking studies

For target TNF-α, among the selected standard ligands, quercetin demonstrated highest binding affinity with – 6.6 kcal/mole through hydrogen bond interactions with Phe144, Pro139 and Gly24 amino acid residues in the binding pocket (Fig. 3). Chlorogenic acid also showed significant binding affinity with -6.2 kcal/mole and exhibited hydrogen bonds with Pro139, Phe144 in the binding pocket. Among the screened ligands, Fluorophenyl (5-(5-chloro-1-(2-fluorophenyl)-2-oxopentyl)-4,5,6,7-tetrahydrothieno[3,2-c]pyridine-2-yl acetate) showed the highest binding affinity with target with – 7.2 kcal/mole and exhibited binding interactions with Leu120,Tyr59, Tyr119, Gln61 and His15 when compared to the standard ligands (Fig. 4).

Fig. 3.

Fig. 3

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Docking pose and 2D interaction of Quercetin with TNF-α

Fig. 4.

Fig. 4

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Docking pose and 2D interaction of Fluorophenyl (5-(5-chloro-1-(2-fluorophenyl)-2-oxopentyl)-4,5,6,7-tetrahydrothieno[3,2-c]pyridine-2-yl acetate) with TNF-α

For target FGF, among the standard selected ligands, chlorogenic acid showed the highest binding affinity target with – 6.8 kcal/mole and exhibited interactions with amino acid residues Arg81, Arg72, Arg39, Leu83 and Val40 in the binding pocket. (Fig. 5)The test ligand Flurophenyl(5-(5-Chloro-1-(2-fluorophenyl)-2-oxopentyl)-4,5,6,tetrahydrothieno[3,2-c]pyridine-2-yl acetate) and 2, 4 methoxy benzylidene-(-3)-oxo-2, 3-dihydro-1-benzofuran-6-yl-4-methoxybenzoate exhibited higher binding affinity ( – 6.9 kcal/mole and – 7.0 kcal/mole respectively) when compared to the standards (Fig. 6)0.2, 4 methoxy benzylidene-(-3)-oxo-2, 3-dihydro-1-benzofuran-6-yl-4-methoxybenzoate exhibited interactions with amino acid residues Gln123, Lys119, Leu126, Tyr124, Arg39 and Asp37 (Table 3).

Fig. 5.

Fig. 5

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Docking pose and 2D interaction of chlorogenic acid with FGF

Fig. 6.

Fig. 6

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Docking pose and 2D interaction of 2, 4 methoxy benzylidene-(-3)-oxo-2, 3-dihydro-1-benzofuran-6-yl-4-methoxybenzoate with FGF

Table 3.

Docking score and interacting residues on selected three targets for wound healing with standards and test ligands

Target PDB Code Name of Ligand Binding Energy Interacting Amino Acid
TNF-α 2AZ5 Quercetin – 6.6 PHE144, Pro139, Gly24
Chlorogenic Acid – 6.2 PRO120, PHE144, LEU120, PRO139
Curcumin – 5.7 TYR151, TYR59, LEU36, HIS15
Gallic Acid – 5.0 PHE144, PRO139, GLY24
Test Ligands
 Fluorophenyl (5-(5-Chloro-1-(2-fluorophenyl)-2-oxopentyl)-4,5,6,7-tetrahydrothieno[3,2-c] pyridine-2-yl acetate) – 7.1 LEU120, TYR59, TYR119, PRO139
 2,4 methoxybenzylidene-(-3)-oxo-2,3-dihydro-1-benzofuran-6-yl-4-methoxybenzoate – 6.8 TYR59, LEU120, HIS15
 Ermanin (5,7 dihydroxy- 3,4 dimethoxy flavone) – 6.3 PHE144, PRO139, GLY24
FGF 40EE  Chlorogenic Acid – 6.8 ALA84, TYR124, LEU82, LEU83
 Quercetin – 6.6 ARG81, LEU83, VAL40, ARG39
 Curcumin – 6.2 LYS21, PHE12, ASN104, ASN102, PRO13
 Gallic Acid – 4.2 TYR120, ARG81, LEU81
Test Ligands
 2,4 methoxybenzylidene-(-3)-oxo-2,3-dihydro-1-benzofuran-6-yl-4-methoxybenzoate – 7.0 ARG39, TYR124, GLN123, LEU126
 Fluorophenyl (5-(5-Chloro-1-(2-fluorophenyl)-2-oxopentyl)-4,5,6,7-tetrahydrothieno[3,2-c] pyridine-2-yl acetate) – 6.9 LEU83, PHE12, PRO141TYR124
 Ermanin (5,7 dihydroxy- 3,4 dimethoxy flavone) – 5.9 ARG81, LEU83, ARG39
TGF-β 1TGJ  Quercetin – 5.6 LYS21, PHE12, PRO13, ASN102
 Chlorogenic Acid – 5.3 ASN84, TYR124, LEU82
 Curcumin – 5.3 ARG18, PHE8, PRO19, ASN102
 Gallic Acid – 4.1 ARG18, ASN10, PHE8
Test Ligands
 Ermanin (5,7 dihydroxy- 3,4 dimethoxy flavone) – 5.4 PRO19, ARG18
 Fluorophenyl (5-(5-Chloro-1-(2-fluorophenyl)-2-oxopentyl)-4,5,6,7-tetrahydrothieno[3,2-c] pyridine-2-yl acetate) – 5.1 LEU11, PRO19, PHE8, TYR124
 2,4 methoxybenzylidene-(-3)-oxo-2,3-dihydro-1-benzofuran-6-yl-4-methoxybenzoate – 5.0 PHE144, GLY24PRO139
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For target TGF-β, quercetin showed the best binding interaction(-5.6 kcal/mole) with formation of hydrogen bonds with Lys21 in the active pocket (Fig. 7). Test ligands, Ermanin, Fluorophenyl (5-(5-Chloro-1-(2-fluorophenyl)-2-oxopentyl)-4,5,6,7-tetrahydrothieno[3,2-c]pyridine-2-yl acetate) and 2, 4 methoxy benzylidene-(-3)-oxo-2, 3-dihydro-1-benzofuran-6-yl-4-methoxybenzoate demonstrated comparable affinities ( – 5.4 kcal/mole, – 5.1 kcal/mole and -5.0 kcal/mole respectively) but lower when compared to quercetin (Fig. 8). Ermanin showed the interactions with amino acid residues Arg18 and Pro19.

Fig. 7.

Fig. 7

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Docking pose and 2D interaction of Quercetin with TGF-β

Fig. 8.

Fig. 8

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Docking pose and 2D interaction of Ermanin with TGF-β

Among the studied standards, quercetin and chlorogenic acid exhibited favourable interactions with good affinity to all the three targets TGF-β, TNF-α, & FGF selected in the study. These ligands will play a crucial role in the wound healing process because they act on critical targets in the wound healing cascade. Among the test ligands, it was observed that Fluorophenyl (5-(5-chloro-1-(2-fluorophenyl)-2-oxopentyl)-4,5,6,7-tetrahydrothieno[3,2-c]pyridine-2-yl acetate) and 2, 4 methoxy benzylidene-(-3)-oxo-2, 3-dihydro-1-benzofuran-6-yl-4-methoxybenzoate had favourable binding interactions with both the TNF-α and FGF targets although with slightly lower affinity to the TGF-β target. Also, ermanin displayed moderate affinity to both the TNF-αand FGF with maximal affinity to the TGF-β target.

Conclusion

Based on the in-silico investigations conducted in this study, it is evident that certain ligands, specifically, Fluorophenyl (5-(5-Chloro-1-(2-fluorophenyl)-2-oxopentyl)-4,5,6,7-tetrahydrothieno[3,2-c] pyridine-2-yl acetate), 2,5 methoxy benzylidene, and Ermanin exhibit promising potential as an initial candidate for further screening and structural modification. These compounds have shown the capacity to interact with multiple targets involved in the complex wound healing process. This multifaceted approach to identifying and selecting ligands with the ability to interact with multiple targets holds significant potential for the treatment of chronic and challenging-to-heal wounds. Further screening and structural modifications of these ligands may lead to the development of novel therapeutics that can address various aspects of wound healing effectively.

Acknowledgements

The authors would like to thank Principal, Dr. D.Y. Patil Institute of Pharmaceutical Sciences and Research, Pimpri, Pune, India, for providing the necessary infrastructural facilities to carry out the work.

Author contributions

Concept – Asha Thomas; Design – Asha Thomas, Ravindra Wavhale; Supervision – Asha Thomas, Ravindra Wavhale; Resources – Kiran Lokhande, Pranali Jadhav; Data Collection and/or Processing – Sheetal Shinde, Sham Tambe, Pranali Jadhav, Kiran Lokhande,; Analysis and/or Interpretation – Asha Thomas, Ravindra Wavhale; Literature Search – Sheetal Shinde, Sham Tambe; Writing – Asha Thomas, Sheetal Shinde, Pranali Jadhav; Critical Reviews – Asha Thomas, Ravindra Wavhale

Data availability

The authors confirm that the data supporting the findings of this study are available within the article [and/or] its supplementary materials.

Declarations

Conflict of interest

The study undertaken does not have conflict of interest with anyone or any institute. The authors declare no competing interests.

Consent for publication

None.

Footnotes

Publisher's Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

References

  1. Abdul Hameed MDM, Chaudhury S, Singh N, Sun H, Wallqvist A, Tawa GJ. Exploring polypharmacology using a ROCS-based target fishing approach. J Chem Inf Model. 2012;52(2):492–505. doi: 10.1021/ci2003544. [DOI] [PubMed] [Google Scholar]
  2. Agrawal DK, Mishra PK. Curcumin and its analogues: potential anticancer agents. Med Res Rev. 2010;30:818–860. doi: 10.1002/med.20188. [DOI] [PubMed] [Google Scholar]
  3. Akbik D, Ghadiri M, Chrzanowski W, Rohanizadeh R. Curcumin as a wound healing agent. Life Sci. 2014;116:1–7. doi: 10.1016/j.lfs.2014.08.016. [DOI] [PubMed] [Google Scholar]
  4. Allouche AR. Gabedit-A graphical user interface for computational chemistry software’s. J Computat Chem. 2011;32:174–182. doi: 10.1002/jcc.21600. [DOI] [PubMed] [Google Scholar]
  5. Anighoro A, Bajorath J. Three-dimensional similarity in molecular docking: prioritizing ligand poses on the basis of experimental binding modes. J Chem Inf Model. 2016;56(3):580–587. doi: 10.1021/acs.jcim.5b00745. [DOI] [PubMed] [Google Scholar]
  6. Bachrach U, Wang YC. Cancer therapy and prevention by green tea: role of ornithine decarboxylase. Amino Acids. 2002;22:1–13. doi: 10.1007/s726-002-8197-9. [DOI] [PubMed] [Google Scholar]
  7. Badhani B, Sharma N, Kakkar R. Gallic acid: a versatile antioxidant with promising therapeutic and industrial applications. RSC Adv. 2015;5:2754057. doi: 10.1039/C5RA01911G. [DOI] [Google Scholar]
  8. Bagdas D, Cinkilic N, Ozboluk HY, Ozyigit MO, Gurun MS. Antihyperalgesic activity of chlorogenic acid in experimental neuropathic pain. J Nat Med. 2012;67:698–704. doi: 10.1007/s11418-012-0726-z. [DOI] [PubMed] [Google Scholar]
  9. Bagdas D, Gul NY, Topal A, Tas S, Ozyigit MO, Cinkilic N, Gul Z, Etoz BC, Ziyanok S, Inan S, Turacozen O, Gurun MS. Pharmacologic overview of systemic chlorogenic acid therapy on experimental wound healing. Naunyn Schmiedebergs Arch Pharmacol. 2014;387:1101–1116. doi: 10.1007/s00210-014-1034-9. [DOI] [PubMed] [Google Scholar]
  10. Bajusz D, Rácz A, Héberger K. Why is Tanimoto index an appropriate choice for fingerprint-based similarity calculations? J Cheminform. 2015;7(1):1–13. doi: 10.1186/s13321-015-0069-3. [DOI] [PMC free article] [PubMed] [Google Scholar]
  11. Ballester PJ, Richards WG. Ultrafast shape recognition to search compound databases for similar molecular shapes. J Comput Chem. 2007;28(10):1711–1723. doi: 10.1002/jcc.20681. [DOI] [PubMed] [Google Scholar]
  12. BenSaad LA, Kim KH, Quah CC, Kim WR, Shahimi M. Anti-inflammatory potential of ellagic acid, gallic acid and punicalagin A&B isolated from Punica granatum. BMC Complement Altern Med. 2017;17:47. doi: 10.1186/s12906-017-1555-0. [DOI] [PMC free article] [PubMed] [Google Scholar]
  13. Charteris DG. Proliferative vitreoretinopathy: pathobiology, surgical management, and adjunctive treatment. Br J Ophthalmol. 1995;79:953–960. doi: 10.1136/bjo.79.10.953. [DOI] [PMC free article] [PubMed] [Google Scholar]
  14. Chattopadhyay I, Biswas K, Bandyopadhyay U, Banerjee R. Turmeric and curcumin: biological actions and medicinal applications. Curr Sci. 2003;87:44–53. [Google Scholar]
  15. Chen WC, Liou SS, Tzeng TF, Lee SL, Liu IM. Effect of topical application of chlorogenic acid on excision wound healing in rats. Planta Med. 2013;79:616–621. doi: 10.1055/s-0032-1328364. [DOI] [PubMed] [Google Scholar]
  16. Cinkilic N, Cetintas SK, Zorlu T, Vatan O, Yilmaz D, Cavas T, Tunc S, Ozkan L, Bilaloglu R. Radioprotection by two phenolic compounds: chlorogenic and quinic acid, on X-ray induced DNA damage in human blood lymphocytes in vitro. Food Chem Toxicol. 2013;53:359–363. doi: 10.1016/j.fct.2012.12.008. [DOI] [PubMed] [Google Scholar]
  17. Clifford M. Chlorogenic acids and other cinnamates–nature, occurrence, dietary burden, absorption and metabolism. J Sci Food Agr. 2000;80:1033–1043. doi: 10.1002/(SICI)1097-0010(20000515)80:73.0.CO;2-T. [DOI] [Google Scholar]
  18. Daglia M, Lorenzo A, Nabavi S, Talas Z, Nabawi S. Polyphenols: well beyond the antioxidant capacity: gallic acid and related compounds as neuroprotective agents: you are what you eat! Curr Pharm Biotechnol. 2014;15:362–372. doi: 10.2174/138920101504140825120737. [DOI] [PubMed] [Google Scholar]
  19. Demidova-Rice TN, Hamblin MR, Herman IM. Acute and impaired wound healing: pathophysiology and current methods for drug delivery, part 2: role of growth factors in normal and pathological wound healing: therapeutic potential and methods of delivery. Adv Skin Wound Care. 2012;25:349–370. doi: 10.1097/01.ASW.0000418541.31366.a3. [DOI] [PMC free article] [PubMed] [Google Scholar]
  20. Doersch KM, Newell-Rogers MK. The impact of quercetin on wound healing relates to changes in αV and β1 integrin expression. Exp Biol Med. 2017;242:1424–1431. doi: 10.1177/1535370217712961. [DOI] [PMC free article] [PubMed] [Google Scholar]
  21. Eming SA, Brach Vogel B, Odorisio T, Koch M. Regulation of angiogenesis: wound healing as a model. Prog HistochemCytochem. 2007;42:115–170. doi: 10.1016/j.proghi.2007.06.001. [DOI] [PubMed] [Google Scholar]
  22. Enoch S, Grey JE, Harding KG. Recent advances and emerging treatments. BMJ. 2006;332:962–965. doi: 10.1136/bmj.332.7547.962. [DOI] [PMC free article] [PubMed] [Google Scholar]
  23. Ghosh S, Banerjee S, Sil PC. The beneficial role of curcumin on inflammation, diabetes and neurodegenerative disease: a recent update. Food Chem Toxicol. 2015;83:111–124. doi: 10.1016/j.fct.2015.05.022. [DOI] [PubMed] [Google Scholar]
  24. Goldberg I, Stefan RJ. Organic and fatty acid production, microbial. Encycl Microbiol. 2019 doi: 10.1016/B978-012373944-5.00156-5. [DOI] [Google Scholar]
  25. Gomathi K, Gopinath D, Ahmed MR, Jayakumar R. Quercetin incorporated collagen matrices for dermal wound healing processes in rat. Biomaterials. 2003;24:2767–2772. doi: 10.1016/s0142-9612(03)00059-0. [DOI] [PubMed] [Google Scholar]
  26. Gurtner GC, Werner S, Brandon Y, Longaker MT. Wound repair and regeneration. Nature. 2008;453:314–321. doi: 10.1038/nature07039. [DOI] [PubMed] [Google Scholar]
  27. Hawkins PCD, Skillman AG, Nicholls A. Comparison of shape-matching and docking as virtual screening tools. J Med Chem. 2007;50:74–82. doi: 10.1021/jm0603365. [DOI] [PubMed] [Google Scholar]
  28. Imran M, Waqar S, Ogata K, Ahmed M, Noreen Z, Javed S, Bibi N, Bokhari H, Amjad A, Muddassar M. Identification of novel bacterial urease inhibitors through molecular shape and structure based virtual screening approaches. RSC Adv. 2020;10:16061–16070. doi: 10.1039/d0ra02363a. [DOI] [PMC free article] [PubMed] [Google Scholar]
  29. Irwin JJ, Tang KG, Young J, Dandarchuluun C, Wong BR, Khurelbaatar M, Moroz YS, Mayfield J, Sayle RA. ZINC20-a free ultralarge-scale chemical database for ligand discovery. J Chem Inf Model. 2020;60:6065–6073. doi: 10.1021/acs.jcim.0c00675. [DOI] [PMC free article] [PubMed] [Google Scholar]
  30. Izui S, Sekine S, Maeda K, Kuboniwa M, Takada A, Amano A, Nagata H. Antibacterial activity of curcumin against periodontopathic bacteria. J Periodontol. 2016;87(1):83–90. doi: 10.1902/jop.2015.150260. [DOI] [PubMed] [Google Scholar]
  31. Jardim KV, Joanitti GA, Azevedo RB, Parize AL. Physico-chemical characterization and cytotoxicity evaluation of curcumin loaded in chitosan/chondroitin sulfate nanoparticles. Mater Sci Eng C Mater Biol Appl. 2015;56:294–304. doi: 10.1016/j.msec.2015.06.036. [DOI] [PubMed] [Google Scholar]
  32. Kant V, Jangir BL, Kumar V, Nigam A, Sharma V. Quercetin accelerated cutaneous wound healing in rats by modulation of different cytokines and growth factors. Growth Factors. 2020;38:105–119. doi: 10.1080/08977194.2020.1822830. [DOI] [PubMed] [Google Scholar]
  33. Kearnes S, Pande V. ROCS-derived features for virtual screening. J Comput Aided Mol Des. 2016;30:609–617. doi: 10.1007/s10822-016-9959-3. [DOI] [PubMed] [Google Scholar]
  34. Koike Y, Yozaki M, Utani A, Murota H. Fibroblast growth factor 2 accelerates the epithelial–mesenchymal transition in keratinocytes during wound healing process. Sci Rep. 2020;10:18545. doi: 10.1038/s41598-020-75584-7. [DOI] [PMC free article] [PubMed] [Google Scholar]
  35. Li Y, Yao J, Han C, Yang J, Chaudhry MT, Wang S, Liu H, Yin Y. Quercetin, inflammation and immunity. Nutrients. 2016;8:167. doi: 10.3390/nu8030167. [DOI] [PMC free article] [PubMed] [Google Scholar]
  36. Lo SF, Hayter M, Hu WY, Tai CY, Hsu MY, Li YF. Symptom burden and quality of life in patients with malignant fungating wounds. J Adv Nurs. 2012;68:131221. doi: 10.1111/j.1365-2648.2011.05839.x. [DOI] [PubMed] [Google Scholar]
  37. Maheshwari RK, Singh AK, Gaddi Pati J, Srimal RC. Multiple biological activities of curcumin: a short review. Life Sci. 2006;78:2081–2087. doi: 10.1016/j.lfs.2005.12.007. [DOI] [PubMed] [Google Scholar]
  38. Mahmood K, Zia KM, Zuber M, Salman M, Anjum MN. Recent developments in curcumin and curcumin based polymeric materials for biomedical applications: a review. Int J BiolMacromol. 2015;81:877–890. doi: 10.1016/j.ijbiomac.2015.09.026. [DOI] [PubMed] [Google Scholar]
  39. Moghadam SE, Ebrahimi SN, Salehi P, Farimani MM, Hamburger M, Jabbar Zadeh E. Wound healing potential of chlorogenic acid and myricetin-3-o-β-rhamnoside isolated from parrotiapersica. Molecules. 2017;22:1501. doi: 10.3390/molecules22091501. [DOI] [PMC free article] [PubMed] [Google Scholar]
  40. Mohanty C, Das M, Sahoo SK. Sustained wound healing activity of curcumin loaded oleic acid based polymeric bandage in a rat model. Mol Pharm. 2012;9:2801–2811. doi: 10.1021/mp300075u. [DOI] [PubMed] [Google Scholar]
  41. Monsuur HN, Boink MA, Weijers EM, Roffel S, Breetveld M, Gefen A, van den Broek LJ, Gibbs S. Methods to study differences in cell mobility during skin wound healing in vitro. J Biomech. 2016;49:1381–1387. doi: 10.1016/j.jbiomech.2016.01.040. [DOI] [PubMed] [Google Scholar]
  42. Mun SH, Joung DK, Kim YS, Kang OH, Kim SB, Seo YS, Kim YC, Lee DS, Shin DW, Kweon KT, Kwon DY. Synergistic antibacterial effect of curcumin against methicillin-resistant Staphylococcus aureus. Phytomedicine. 2013;20:714–718. doi: 10.1016/j.phymed.2013.02.006. [DOI] [PubMed] [Google Scholar]
  43. Naksuriya O, Okonogi S, Schiffler’s RM, Hennink WE. Curcumin nano formulations: a review of pharmaceutical properties and preclinical studies and clinical data related to cancer treatment. Biomaterials. 2014;35:3365–3383. doi: 10.1016/j.biomaterials.2013.12.090. [DOI] [PubMed] [Google Scholar]
  44. Pastar I, Stojadinovic O, Yin NC, Ramirez H, Nusbaum AG, Sawaya A, Patel SB, Khalid L, Isseroff RR, Tomic-Canic M. Epithelialization in wound healing: a comprehensive review. Adv Wound Care. 2014;3:445–464. doi: 10.1089/2Fwound.2013.0473. [DOI] [PMC free article] [PubMed] [Google Scholar]
  45. Rauf A, Imran M, Khan IA, Ur-Rehman M, Gilani SA, Mehmood Z, Mubarak MS. Anticancer potential of quercetin: a comprehensive review. Phytother Res. 2018;32:2109–2130. doi: 10.1002/ptr.6155. [DOI] [PubMed] [Google Scholar]
  46. Santana-Galvez J, Cisneros-Zevallos L, Jacob-Velázquez DA. Chlorogenic acid: recent advances on its dual role as a food additive and a nutraceutical against metabolic syndrome. Molecules. 2017;22:358. doi: 10.3390/molecules22030358. [DOI] [PMC free article] [PubMed] [Google Scholar]
  47. Sastry GM, Dixon SL, Sherman W. Rapid shape-based ligand alignment and virtual screening method based on atom/feature-pair similarities and volume overlap scoring. J Chem Inf Model. 2011;51:2455–2466. doi: 10.1021/ci2002704. [DOI] [PubMed] [Google Scholar]
  48. Selinger D, de Groot BL. Ligand docking and binding site analysis with PyMOL and Auto dock/Vina. J Comput Aided Mol Des. 2010;24:417–422. doi: 10.1007/s10822-010-9352-6. [DOI] [PMC free article] [PubMed] [Google Scholar]
  49. Sen CK. Human wounds and its burden: an updated compendium of estimates. Adv Wound Care. 2019;8:39–48. doi: 10.1089/wound.2019.0946. [DOI] [PMC free article] [PubMed] [Google Scholar]
  50. Sharma P, Virmani T. Synthesis, antimicrobial evaluation and QSAR studies of some newly synthesized imidazole derivatives. Synthesis. 2020;29:6513–6520. [Google Scholar]
  51. Shin WH, Zhu X, Bures MG, Kihara D. Three-dimensional compound comparison methods and their application in drug discovery. Molecules. 2015;20:12841–12862. doi: 10.3390/molecules200712841. [DOI] [PMC free article] [PubMed] [Google Scholar]
  52. Singer AJ, Clark RA. Cutaneous wound healing. N Engl J Med. 1999;341:738–746. doi: 10.1056/nejm199909023411006. [DOI] [PubMed] [Google Scholar]
  53. Smith PD, Kuhn MA, Franz MG, Wachtel TL, Wright TE, Robson MC. Initiating the inflammatory phase of incisional healing prior to tissue injury. J Surg Res. 2000;92:11–17. doi: 10.1006/jsre.2000.5851. [DOI] [PubMed] [Google Scholar]
  54. Topman G, Lin FH, Gefen A. The natural medications for wound healing – curcumin, aloe-vera and ginger – do not induce a significant effect on the migration kinematics of cultured fibroblasts. J Biomech. 2013;46:170–174. doi: 10.1016/j.jbiomech.2012.09.015. [DOI] [PubMed] [Google Scholar]
  55. Wang Y, Ho CT. Polyphenolic chemistry of tea and coffee: a century of progress. J Agri Food Chem. 2009;57:8109–8114. doi: 10.1021/jf804025c. [DOI] [PubMed] [Google Scholar]
  56. Xu JG, Hu QP, Liu Y. Antioxidant and DNA-protective activities of chlorogenic acid isomers. J Agric Food Chem. 2012;60:11625–11630. doi: 10.1021/jf303771s. [DOI] [PubMed] [Google Scholar]
  57. Xu D, Hu MJ, Wang YQ, Cui YL. Antioxidant activities of quercetin and its complexes for medicinal application. Molecules. 2019;24:1123. doi: 10.3390/molecules24061123. [DOI] [PMC free article] [PubMed] [Google Scholar]
  58. Yang DJ, Moh SH, Son DH, You S, Kinyua AW, Ko CM, Song M, Yeo J, Choi YH, Kim KW. Gallic acid promotes wound healing in normal and hyperglucidic conditions. Molecules. 2016;21:899. doi: 10.3390/molecules21070899. [DOI] [PMC free article] [PubMed] [Google Scholar]
  59. Young A, McNaught CE. The physiology of wound healing. Surgery. 2011;29:475–479. doi: 10.1016/j.mpsur.2011.06.011. [DOI] [Google Scholar]
  60. Zielińska A, Alves H, Marques V, Durazzo A, Lucarini M, Alves TF, Morsink M, Willemen N, Eder P, Chaud MV, Severino P, Santini A, Souto EB. Properties, extraction methods, and delivery systems for curcumin as a natural source of beneficial health effects. Medicina. 2020;56:1–19. doi: 10.3390/medicina56070336. [DOI] [PMC free article] [PubMed] [Google Scholar]

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