Evaluating Phytochemicals from Labisia pumila for Potential Healing Properties in Silico compared with the Specified Therapeutic Objectives

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They also have a close relationship to extracellular matrix unbalanced protease activity. A thorough understanding of the underlying mechanism of chronic wounds is crucial for the development of target-specific treatment agents. Numerous research regarding chronic wounds have reported higher expressions of matrix metalloproteinases (MMPs). This in silico study has chosen MMPs as its therapeutic target because they are one of the key molecular players in chronic cutaneous wounds. Utilizing Lipinski's Rule of Five filter, phytochemicals from the native medicinal plant Labisia pumila were extracted from chemical databases and assessed for drug-likeness. Using AutoDock Vina via PyRx, a total of 24 lead compounds that met the predetermined criteria were virtual screened against the therapeutic targets MMP-1, MMP-8, MMP-9, and MMP-12. Eight of the best flavonoid compounds (quercetin, catechin, apigenin, genistein, daidzein, myricetin, epigallocatechin, and kaempferol) with binding affinity scores ranging from − 8.3 to -10.0 kcal/mol were identified as promising candidates for future wound healing drug design and development based on their conformations and binding affinity scores. Labisia pumila phytochemicals wound healing virtual screening matrix metalloproteinases Figures Figure 1 INTRODUCTION In general, wounds that are left open for longer than a month or that do not heal back to their former state after three months—often referred to as "non-healing wounds"—are all included in the category of chronic wounds[ 1 ]. The majority of patients with chronic wounds typically present with pain, which is sometimes referred to as "persistent pain." Poor nutritional status, improper wound care, and the existence of underlying disorders are a few common variables that may lead to the development of chronic wounds[ 2 ]. Due to its negative effects on society and the economy, the widespread problem of managing chronic wounds in global healthcare systems continues to pose a serious danger to public health. In terms of money, the past ten years have seen a sharp increase in the costs associated with managing chronic wounds because of factors such as escalating healthcare costs, an aging population, and the need for long-term care[ 3 ]. In the meanwhile, a number of research have been published on the psychosocial effects of chronic wounds, which are linked to feelings of guilt and helplessness, as well as pain and immobility and social isolation[ 4 ]. According to Businaro et al. (2016), optimizing traditional wound care is therefore much more crucial to maximizing the yield of favorable results at every stage of wound healing. When looking at wound healing from a clinical standpoint, the process typically proceeds through three stages: inflammation, proliferation, and tissue remodelling. When you examine a wound more closely, you'll see that it heals as a result of several cellular interactions between platelets, leukocytes, fibroblasts, and soluble mediators like proteases and cytokines like TNF-α, ILs, and platelet-derived growth factor (PDGF). Fibroblasts and collagen fibers become more noticeable in the later proliferative and tissue remodelling stage of wound healing, even though cytokines and growth factors are primarily important for regulating the inflammatory phase of wound healing (Yussof, Omar, Pai & Sood, 2012). Tissue inhibitors of metalloproteinases (TIMPs) and matrix metalloproteinases (MMPs) are zinc-containing enzymes found in the protease family that are released by pro-inflammatory cells and connective tissue. The extracellular matrix (ECM) of both acute and chronic wounds contains structural proteins that are undesirable and damaged. MMPs are the main molecules that aid in their removal. Conversely, TIMPs are the tissue inhibitors that control MMP activity since excessive protease activity may cause wounds to heal more slowly[ 5 ]. In summary, one of the most essential conditions for effective wound healing is the carefully monitored regulation of MMPs. Furthermore, according to reports[ 6 ], MMPs are also important players in physiological processes including angiogenesis and bone remodeling. Because of their substantial correlation with delayed wound healing, MMPs have emerged as one of the most sought-after therapeutic targets in the study of chronic non-healing wounds. Since ancient times, plant-based treatments have been one of the most popular options for complementary and alternative medicine, particularly among older generations. This is probably because of their greater accessibility and less adverse effects. Many medicinal plants have demonstrated biological benefits in the past for treating wounds; Curcuma longa, Centella asiatica, Gingko biloba, and Morinda citrifolia are a few well-liked candidates[ 7 ]. Ethnomebotanical studies have advanced in Malaysia since antiquity as a result of the nation's potential and underutilized botanical resources[ 8 ]. Labisia pumila, sometimes referred to as the "queen of herbs" or Kacip Fatimah, is a well-known herb in Malaysia that is listed as one of the key herbal plants under the National Key Economic Areas. Malay women have long used it to enhance reproductive processes and make childbirth easier[ 9 ]. In addition to its traditional applications, studies on L. pumila's anti-inflammatory, antioxidant, phytoestrogenic, anti-osteoporosis, and cardioprotective properties have been reported in the past[ 10 ]. However, there have been very few, if any, scientific research conducted on this plant's ability to heal wounds up to this point. METHODOLOGY Computational Softwares: Raw structures of desired protein targets and chemical compounds were retrieved from free-source databases like RCSB Protein Data Bank (PDB), PubChem, ChEMBL as well as ChemSpider. Thereafter, study was carried out via computational softwares such as PyRx 0.8, Swiss-PdbViewer 4.1, BIOVIA Discovery Studio Visualiser 2020, PyMOL 2.4 and online web servers like CASTp 3.0 for active site prediction. Descriptions of each utilised software are summarised as below (Table 1 & Table 2). Table 1: M.O.I.S.T. Concept in Local Treatment of Chronic Wounds Components M Moisture balance O Oxygen balance I Control of infections S Support T Tissue Management Table 1: The Clinical Framework (M.O.I.S.T.) This table outlines a clinical methodology used by healthcare professionals to manage chronic wounds (like diabetic ulcers or pressure sores). It is an evolution of the older "T.I.M.E." acronym, expanded to include modern treatment priorities. Table 2: Computational Softwares and Servers Utilised in Virtual Screening Softwares / Servers Description 1 PyRx 0.8 A free virtual screening tool that has features like AutoDock 4, AutoDock Vina and Open Babel (Dallakyan and Olson, 2015) 2 Swiss-PdbViewer 4.1 A molecular graphics software created for the viewing and analysis of protein structures (Guex & Peitsch, 1997) 3 BIOVIA Discovery Studio Visualiser 2020 A free viewer software that suits for the analysis and modelling of molecular structures and sequences (BIOVIA, 2020). 4 PyMOL 2.4.0 An open source molecular visualisation software that allows the rendering and animating of 3D structures (DeLano, 2002). 5 CASTp 3.0 A web server that aims to provide online services like locating and measuring the geometric as well as topological properties of desired protein structures (Tian et al., 2018). Table 2: The Digital Research Tools (Virtual Screening) This table lists the bioinformatics toolkit used by researchers to discover or test new drugs "in silico" (on a computer) before ever trying them on a human or in a lab. Screening of Potential Phytochemicals: Peer-reviewed scientific literature databases, such as PubMed, ScienceDirect, Google Scholar, ClinicalKey, and SAGE Journals, were searched for many phytochemicals identified in L. pumila. During the literature search, terms including "Labisia pumila," "Kacip Fatimah," "phytochemical," "active compounds," and "secondary metabolites" were used. Thereafter, corresponding three-dimensional (3D) structures and physicochemical properties were obtained as input files in Structure Data File (SDF) format from freely accessible chemical databases like Pub Chem ( https:// pubchem. ncbi. nlm. nih. gov/), Chem Spider ( https:// www.chemspider.com/) and ChEMBL (https://www.ebi.ac.uk/chembl/). The drug- likeness of the selected phytochemical compounds were first evaluated via the Lipinski’s Rule of Five (RO5) filter (http://www.scfbio-iitd.res.in/software/ drugdesign/lipinski.jsp/) formulated by Christoper A. Lipinski. It serves as a rule of thumb to evaluate whether tested chemical molecules possess the physiochemical characteristics that will make them likely candidates of orally administered drugs in humans (Kumari & J. S. Rana, 2013). Prior to substances going through a virtual screening process, the five factors in Lipinski's RO5 (Table 3) were evaluated[11]. Table 3: Lipinski’s Rule of Five Drug-Likeness Parameters Parameters Conditions 1 Molecular Mass < 500 daltons 2 Hydrogen donor numbers < 5 3 Hydrogen acceptor numbers < 10 4 Lipophilicity (log P) value ≤ 5 5 Molar Refractivity 40 - 130 Preparation of Ligand Structures: Before the virtual screening procedure, BIOVIA Discovery Studio Visualiser 2020 was used to import the SDF files containing the filtered compounds that met Lipinski's RO5 filter. These data were then clustered into a single SDF file. The clustered ligand file was then imported into PyRx's workspace, and using the OpenBabel toolbox located under the control panel, each constituent was transformed into the PDBQT file format—the default format needed for AutoDock Vina. In order to obtain a stable molecular conformation, energy minimization was also carried out to each constituent that was going to be screened prior to format conversion[12]. To guarantee the flexibility of the ligand molecules during the docking process, the number of active torsions was also recorded, and the torsional degree of freedom was determined[13]. Retrieval and Preparation of Protein Targets: Four protein targets were chosen, and their 3D structures were obtained in PDB file format from the RCSB Protein Data Bank (https://www.rcsb.org/). The targets are MMP-1 (PDB ID: 966C), MMP-8 (PDB ID: 1A86), MMP-9 (PDB ID: 5CUH), and MMP-12 (PDB ID: 1JIZ). Under Swiss-PdbViewer's "BUILD" feature, water molecules and ligands that were pre-attached to target structures were eliminated. The protein targets that had been analyzed were then saved, loaded, and converted into a macromolecules file in PDBQT format within PyRx's working environment[13]. Swiss-PdbViewer and the CASTp server were used to predict and cross-check the active binding sites of the chosen molecular targets prior to virtual screening[14]. Structure-Based Virtual Screening via AutoDock Vina: Molecular docking was carried out for the screened compounds using the specified target proteins in AutoDock Vina using the PyRx platform once the ligand and protein structures were prepared. Figure 1 depicts the workflow graphically. The 'Analyze findings' tab is where you can keep an eye on the virtual screening findings once docking is finished. For additional analysis, the findings were exported in SDF and Comma Separated Values (CSV) formats. The complexes that exhibited the optimal conformations were identified through the utilization of the generated binding affinities (kcal/mol). To investigate the protein-ligand interactions of the outputs with the lowest binding energy for each molecular target, PyMOL visualisation tools and BIOVIA Discovery Studio Visualiser 2020 were used. Based on the docking scores and the interactions at the binding sites, the study's conclusions and debates were made. RESULTS Construction of Phytochemical Library: Through a variety of published literature journals, a total of forty phytochemicals of L. pumila were found and identified. Table 4 contains a list of the built phytochemical libraries together with the corresponding PUBChem ID. Prior to carrying out the screening stage, the phytochemicals from the library were projected to the evaluation of Lipinski's filter. Screening Results of Potential Phytochemicals: After applying Lipinski's filter, AutoDock Vina was used to perform an in silico screening of the chosen phytochemicals of L. pumila on the four primary protein targets of wound healing (MMP-1, MMP-8, MMP-9, and MMP-12). According to their physiochemical characteristics, substances that are drug-like or non-drug-like can be distinguished using an index called Lipinski's rule of five (RO5) (Lipinski, 2004). Following two or more of the five preset rules—molecular mass < 500 Dalton, logP value < 5, hydrogen bond donors number < 5, hydrogen bond acceptors number < 10, and molar refractivity 40 < x < 130—is the general guideline in RO5. Before the entire project moves forward to further pre-clinical and clinical stages, these filters act as a checkpoint in the early pre-clinical stage of novel drug development. Twenty-four active compounds in total were projected to the virtual screening in accordance with RO5 (Table 5 ). Table 5 Phytochemical Database of Labisia pumila Compound PubChem ID Compound PubChem ID 1 Gallic acid 370 21 Oleic acid 445639 2 Caffeic acid 689043 22 Linoleic acid 5280450 3 Pyrogallol 1057 23 α-linolenic acid 5280934 4 Benzoic acid 243 24 Stearic acid 5281 5 Cinnamic acid 444539 25 Soyacerebroside I 11104507 6 Methyl gallate 7428 26 Ardisicrenoside A 10260582 7 Quercetin 5280343 27 Ardisicrenoside B 10373894 8 Myricetin 5281672 28 Ardisiacrispin A 10328746 9 Kaempferol 5280863 29 Ardisimamilloside H 101248954 10 Catechin 9064 30 Demethylbelamcandaquinone B 54597440 11 Epigallocatechin 72277 31 Irisresorcinol 5054 12 Naringin 442428 32 Belamcandol B 1096951 13 Rutin 5280805 33 Fatimahol 54597441 14 Apigenin 5280443 34 Dexyloprimulanin 101961815 15 Daidzein 5281708 35 Primulanin 44419565 16 Genistein 5280961 36 α-tocopherol 14985 17 Beta carotene 5280489 37 Protocatechuic acid 72 18 Ascorbic acid 54670067 38 Vanillic acid 8468 19 Palmitic acid 985 39 Syringic acid 10742 20 Palmitoleic acid 445638 40 Salicylic acid 338 Table 5 Potential Labisia pumila Phytochemicals Conformed to Lipinski’s Rules of Drug-Likeliness Compound Molecular Mass Log P H Bond Donors H Bond Acceptors Molar Refractivity Gallic acid 170.00 0.50 4 5 38.395699 Caffeic acid 180.00 1.20 3 4 46.441399 Pyrogallol 126.00 0.80 3 3 31.436398 Benzoic acid 122.00 1.38 1 2 33.401295 Cinnamic acid 148.00 1.78 1 2 43.111797 Methyl gallate 184.00 0.59 3 5 42.775898 Quercetin 302.00 2.01 5 7 74.050476 Myricetin 318.00 1.72 6 8 75.715279 Kaempferol 286.00 2.31 4 6 72.385681 Catechin 290.00 1.55 5 6 72.622978 Epigallocatechin 306.00 1.25 6 7 72.622978 Apigenin 270.00 2.42 3 5 70.813881 Daidzein 254.00 2.71 2 4 69.149086 Genistein 270.00 2.42 3 5 70.813881 Ascorbic acid 176.00 -1.41 4 6 35.256191 Protocatechuic acid 154.00 0.80 3 4 36.730900 Vanillic acid 168.00 1.10 2 4 41.618092 Syringic acid 198.00 1.11 2 5 48.170090 Salicylic acid 138.00 1.09 2 3 35.066097 Palmitic acid 256.00 5.55 1 2 77.947777 Palmitoleic acid 254.00 5.33 1 2 77.853775 Oleic acid 282.00 6.11 1 2 87.087776 Linoleic acid 280.00 5.88 1 2 86.993774 α-linolenic acid 278.00 5.66 1 2 86.899773 Ligands Preparation : Only 24 compounds in total, meeting the requirements of Lipinski's RO5 characteristics (molecular mass, log P value, number of hydrogen bond donors and acceptors, and molar refractivity), were included in the virtual screening study for the chosen phytochemicals of L. pumila. Table 6 displays the structures of these filtered compounds (n = 24) from L. pumila . Table 6 Structures of Potential Labisia pumila Phytochemicals Conformed to Lipinski’s Rules of Drug-Likeliness Compound Molecular Formula CompoundMolecular Formula Gallic acid C7H6O5 DaidzeinC15H10O4 Caffeic acid C9H8O4 GenisteinC15H10O5 Pyrogallol C6H6O3 Ascorbic acidC6H8O6 Benzoic acid C7H6O2 Protocatechuic acidC7H6O4 Cinnamic acid C9H8O2 Vanillic acidC8H8O4 Methyl gallate C8H8O5 Syringic acidC9H10O5 Quercetin C15H10O7 Salicylic acidC7H6O3 Myricetin C15H10O8 Palmitic acidC16H32O2 Kaempferol C15H10O6 Palmitoleic acidC16H30O2 Catechin C15H14O6 Oleic acidC18H34O2 Epigallocatechin C15H14O7 Linoleic acidC18H32O2 Apigenin C15H10O5 α-linolenic acidC18H30O2 Binding Affinity Results of Phytochemicals against MMPs : The twenty four phytochemicals of L. pumila which agreed to the Lipinski’s RO5 filter were proceeded to virtual screening with molecular targets MMP-1, MMP-8, MMP-9 and MMP-12, respectively. The entire docking results were summarised in Table 7 with the best eight phytochemicals listed. The potential ligands with binding affinity score > 9 were subjected to further conformational analysis. In the present study, the result findings were based solely on the docking affinity and the protein-ligand interactions at their separate binding sites. The more negative the value of binding affinity, the stronger the interactions are between the protein-ligand complexes. In another words, complexes with the more negative affinity scores possess more stable conformations as more energy of dissociation is needed to break apart their interactions. Table 7 Binding Affinity of Phytochemicals in Labisia pumila against Targets of Wound Healing Binding Affinity (kcal/mol) against Therapeutic Targets of Wound Healing Phytochemicals of Labisia pumila MMP-1 MMP-8 MMP-9 MMP-12 1Quercetin -10.0 -10.0 -9.4 -9.8 2Catechin -9.8 -9.9 -9.6 -9.5 3Apigenin -9.6 -9.4 -9.4 -9.3 4Genistein -9.4 -9.1 -9.3 -9.9 5Daidzein -9.2 -9.1 -9.4 -9.7 6Myricetin -9.7 -9.4 -9.1 -8.3 7Epigallocatechin -8.8 -9.8 -9.1 -9.7 8Kaempferol -9.5 -9.5 -8.9 -9.2 DISCUSSIONS Because they are frequently linked to high-risk complications that have significantly increased morbidity and mortality among the vulnerable population, such as the elderly, the diabetic, and those with compromised immune systems, chronic and non-healing wounds have placed a tremendous financial and social strain on the global healthcare system[ 15 ]. These days, scientists are delving into a wide spectrum of wound-related research in an effort to find the most effective and optimal treatment choice for patients with chronic wounds. Studies on microRNA as therapeutic targets of chronic wound healing have been reported; these studies indicate the promise of microRNA as a therapeutic alternative; however, further research is needed to determine an acceptable delivery strategy[ 16 ]. The use of therapeutic herbal plants for the candidate search in the management of chronic wounds is a significant benefit of our current study. A common herb in Malaysia and other countries in Southeast Asia is labisia pumila, a traditional Malay herb. There are actually three different types of L. pumila that can be found in our nation; the two most widely utilized forms in medicinal compositions are var. alata and var. pumila . It was also evident from the many phytochemical tests carried out on L. pumila that these plants are abundant in active substances such as flavonoids and phenolics[ 17 ]. These are also the active ingredients that show promise and may be further developed into novel drugs for wound healing. Among the forty selected phytochemicals from L. pumila, 24 lead compounds were remaining after being filtered by the Lipinski’s RO5 index for their drug-likeness properties. These filtered compounds belong to different classes, which are ranging from phenolics, flavonoids, saponins, carotenoids and phenols. This filter does not only help to cut down the number of potential lead candidates, but also facilitating the betterment of the screening results. The following virtual screening was carried out using AutoDock Vina via PyRx software. The affinity scores of the top eight compounds out of the forty preliminary compounds are shown in Table 3 . The top eight lead phytochemicals that showed binding affinities of > 9 kcal/mol against the respective wound healing therapeutic targets MMP-1, MMP-8, MMP-9 and MMP-12 were further analysed using PyMOL and BIOVIA Discovery Studio Visualiser 2020 to validate the binding conformations and hydrogen bond interactions in both 3D and 2D graphical representations. CONCLUSION In our present in silico study, a total of 24 phytochemical lead candidates from medicinal herb Labisia pumila were subjected to the virtual screening process via AutoDock Vina after the application of Lipinski’s Rule of Five drug-likeness filter. Through the structure-based screening, eight flavonoid compounds were identified as the best lead molecules against the therapeutic targets of wound healing. These compounds also exhibited good non- covalent interactions such as hydrogen bonding, van der Waals and hydrophobic interactions with the respective targets. With this pharmacoinformatic approach, the appreciable binding affinities between the phytoconstituents and their protease targets have shown their great potentials as cost-effective lead candidates for wound healing drug design and discovery in the near future. Declarations Acknowledgment: Not Applicable Funding: No targeted funding was reported. Availability of data and materials: All data and materials are presented in this manuscript. No additional materials are available. Competing interests: Authors declare no competing interest Ethics declaration: Not Applicable Author information: Corresponding Author: Pugazhandhi Bakthavatchalam, Department of Anatomy and Physiology, American University of Antigua, University Park, Jabberwock Beach Road, PO Box W1451, Coolidge, Antigua, West Indies, North America. First Author: Ashok Gnanasekaran, Professor of Microbiology, Faculty of Medicine, Director, Centre for Botanicals and Clinical Research (CBCR), Quest International University (QIU), Ipoh, Perak, Malaysia. Authors’ contributions: a. Study planning: Ashok Gnanasekaran, Pugazhandhi Bakthavatchalam b. Literature search: Paula Chia Siaw Jun, Sarah Stephenie, c. Manuscript writing: Ashok Gnanasekaran, Paula Chia Siaw Jun, Pugazhandhi Bakthavatchalam d. Manuscript revision: Ashok Gnanasekaran, Paula Chia Siaw Jun, Sarah Stephenie e. Final approval: Ashok Gnanasekaran, Paula Chia Siaw Jun, Sarah Stephenie, Pugazhandhi Bakthavatchalam References Sen, C. K. Human wounds and its burden: an updated compendium of estimates . 2019, Mary Ann Liebert, Inc., publishers 140 Huguenot Street, 3rd Floor New … pp. 39–48. Iqbal, A., et al. (2017). Management of chronic non-healing wounds by hirudotherapy. World journal of plastic surgery , 6 (1), 9. Sen, C. K., et al. (2009). Human skin wounds: a major and snowballing threat to public health and the economy. Wound repair and regeneration , 17 (6), 763–771. McCaughan, D., et al. (2018). Patients’ perceptions and experiences of living with a surgical wound healing by secondary intention: a qualitative study. International journal of nursing studies , 77 , 29–38. Armstrong, D. G., & Jude, E. B. (2002). The role of matrix metalloproteinases in wound healing. Journal of the American Podiatric Medical Association , 92 (1), 12–18. Löffek, S., Schilling, O., & Franzke, C. W. (2011). Biological role of matrix metalloproteinases: a critical balance. European Respiratory Journal , 38 (1), 191–208. Nagori, B. P., & Solanki, R. (2011). Role of medicinal plants in wound healing. Research Journal of Medicinal Plant , 5 (4), 392–405. Sabran, S. F., Mohamed, M., Abu, M. F., & Bakar (2016). Ethnomedical knowledge of plants used for the treatment of tuberculosis in Johor, Malaysia. Evidence-based complementary and alternative medicine, 2016. Manda, V. K., et al. (2014). Evaluation of drug interaction potential of Labisia pumila (Kacip Fatimah) and its constituents. Frontiers in Pharmacology , 5 , 178. Nadia, M. (2012). The anti-inflammatory, phytoestrogenic, and antioxidative role of Labisia pumila in prevention of postmenopausal osteoporosis. Advances in Pharmacological Sciences, 2012. Lipinski, C. A. (2004). Lead-and drug-like compounds: the rule-of-five revolution. Drug discovery today: Technologies , 1 (4), 337–341. Mackay, D., Cross, A., & Hagler, A. (1989). The role of energy minimization in simulation strategies of biomolecular systems. Prediction of protein structure and the principles of protein conformation (pp. 317–358). Springer. Buckley, M., et al. (2016). Enhancer scanning to locate regulatory regions in genomic loci. Nature protocols , 11 (1), 46–60. Tian, W., et al. (2018). CASTp 3.0: computed atlas of surface topography of proteins. Nucleic acids research , 46 (W1), W363–W367. Järbrink, K., et al. (2016). Prevalence and incidence of chronic wounds and related complications: a protocol for a systematic review. Systematic reviews , 5 , 1–6. Mulholland, E. J., Dunne, N., & McCarthy, H. O. (2017). MicroRNA as therapeutic targets for chronic wound healing. Molecular Therapy-Nucleic Acids , 8 , 46–55. Karimi, E., Jaafar, H. Z., & Ahmad, S. (2011). Phenolics and flavonoids profiling and antioxidant activity of three varieties of Malaysian indigenous medicinal herb Labisia pumila Benth. J Med Plant Res , 5 , 1200–1206. Additional Declarations No competing interests reported. Cite Share Download PDF Status: Posted Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-9108521","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":613057797,"identity":"5d3a6a48-d182-48c0-97c3-a17d90e4b4d3","order_by":0,"name":"Ashok Gnanasekaran¹","email":"","orcid":"","institution":"Quest International University","correspondingAuthor":false,"prefix":"","firstName":"Ashok","middleName":"","lastName":"Gnanasekaran¹","suffix":""},{"id":613057798,"identity":"f2b23a9d-a13d-4d89-8861-719ac460d40d","order_by":1,"name":"Paula Chia Siaw","email":"","orcid":"","institution":"Quest International University","correspondingAuthor":false,"prefix":"","firstName":"Paula","middleName":"Chia","lastName":"Siaw","suffix":""},{"id":613057799,"identity":"8416cab6-d9c7-474a-82fd-190cba3fb104","order_by":2,"name":"Sarah Stephenie³","email":"","orcid":"","institution":"Quest International University","correspondingAuthor":false,"prefix":"","firstName":"Sarah","middleName":"","lastName":"Stephenie³","suffix":""},{"id":613057800,"identity":"28f32274-c6e5-4668-a692-85d791b4f2d7","order_by":3,"name":"Pugazhandhi Bakthavatchalam","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA00lEQVRIiWNgGAWjYLACxoYDDPwgRkIBKVokG0BaDEjRYnAAxCJGi7lE+sWPP3fcyTM+vzrxwwMDBnl+sQP4tVjOyCmWkDzzrNjsxtvNEkCHGc6cnYBfi8GNnAQJw7bDidtunN0A0pJgcJuwluQfiUAtm2ec3fyDSC3pxyQOArVs4O/dRpwtlj1v2Cwb254VS9zg3WaRYCBB2C/m7OmPb/5su5PH3392880fFTby/NKEHMbAA46LBAYJsEoJ/MohWtgfQLTwHyCsehSMglEwCkYmAACl6068EK9UXwAAAABJRU5ErkJggg==","orcid":"","institution":"American University of Antigua","correspondingAuthor":true,"prefix":"","firstName":"Pugazhandhi","middleName":"","lastName":"Bakthavatchalam","suffix":""}],"badges":[],"createdAt":"2026-03-12 22:23:56","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-9108521/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-9108521/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":105756757,"identity":"609e5acd-d09f-47f4-b842-73f81d4e24d4","added_by":"auto","created_at":"2026-03-30 16:43:27","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":138264,"visible":true,"origin":"","legend":"\u003cp\u003eSchematic Diagram for the Workflow of Virtual Screening\u003c/p\u003e","description":"","filename":"1.png","url":"https://assets-eu.researchsquare.com/files/rs-9108521/v1/eac64b78d265a906a8be796a.png"},{"id":106854772,"identity":"78fbd140-a755-416f-91f6-a2f33064429c","added_by":"auto","created_at":"2026-04-14 07:13:15","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1161117,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-9108521/v1/d7c68d72-ef66-4dd6-82d2-9fa73c2f0cd3.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Evaluating Phytochemicals from Labisia pumila for Potential Healing Properties in Silico compared with the Specified Therapeutic Objectives","fulltext":[{"header":"INTRODUCTION","content":"\u003cp\u003eIn general, wounds that are left open for longer than a month or that do not heal back to their former state after three months\u0026mdash;often referred to as \"non-healing wounds\"\u0026mdash;are all included in the category of chronic wounds[\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e]. The majority of patients with chronic wounds typically present with pain, which is sometimes referred to as \"persistent pain.\" Poor nutritional status, improper wound care, and the existence of underlying disorders are a few common variables that may lead to the development of chronic wounds[\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e]. Due to its negative effects on society and the economy, the widespread problem of managing chronic wounds in global healthcare systems continues to pose a serious danger to public health. In terms of money, the past ten years have seen a sharp increase in the costs associated with managing chronic wounds because of factors such as escalating healthcare costs, an aging population, and the need for long-term care[\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e]. In the meanwhile, a number of research have been published on the psychosocial effects of chronic wounds, which are linked to feelings of guilt and helplessness, as well as pain and immobility and social isolation[\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e]. According to Businaro et al. (2016), optimizing traditional wound care is therefore much more crucial to maximizing the yield of favorable results at every stage of wound healing. When looking at wound healing from a clinical standpoint, the process typically proceeds through three stages: inflammation, proliferation, and tissue remodelling. When you examine a wound more closely, you'll see that it heals as a result of several cellular interactions between platelets, leukocytes, fibroblasts, and soluble mediators like proteases and cytokines like TNF-α, ILs, and platelet-derived growth factor (PDGF). Fibroblasts and collagen fibers become more noticeable in the later proliferative and tissue remodelling stage of wound healing, even though cytokines and growth factors are primarily important for regulating the inflammatory phase of wound healing (Yussof, Omar, Pai \u0026amp; Sood, 2012). Tissue inhibitors of metalloproteinases (TIMPs) and matrix metalloproteinases (MMPs) are zinc-containing enzymes found in the protease family that are released by pro-inflammatory cells and connective tissue. The extracellular matrix (ECM) of both acute and chronic wounds contains structural proteins that are undesirable and damaged. MMPs are the main molecules that aid in their removal. Conversely, TIMPs are the tissue inhibitors that control MMP activity since excessive protease activity may cause wounds to heal more slowly[\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e]. In summary, one of the most essential conditions for effective wound healing is the carefully monitored regulation of MMPs. Furthermore, according to reports[\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e], MMPs are also important players in physiological processes including angiogenesis and bone remodeling. Because of their substantial correlation with delayed wound healing, MMPs have emerged as one of the most sought-after therapeutic targets in the study of chronic non-healing wounds. Since ancient times, plant-based treatments have been one of the most popular options for complementary and alternative medicine, particularly among older generations. This is probably because of their greater accessibility and less adverse effects. Many medicinal plants have demonstrated biological benefits in the past for treating wounds; Curcuma longa, Centella asiatica, Gingko biloba, and Morinda citrifolia are a few well-liked candidates[\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e]. Ethnomebotanical studies have advanced in Malaysia since antiquity as a result of the nation's potential and underutilized botanical resources[\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e]. Labisia pumila, sometimes referred to as the \"queen of herbs\" or Kacip Fatimah, is a well-known herb in Malaysia that is listed as one of the key herbal plants under the National Key Economic Areas. Malay women have long used it to enhance reproductive processes and make childbirth easier[\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e]. In addition to its traditional applications, studies on L. pumila's anti-inflammatory, antioxidant, phytoestrogenic, anti-osteoporosis, and cardioprotective properties have been reported in the past[\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e]. However, there have been very few, if any, scientific research conducted on this plant's ability to heal wounds up to this point.\u003c/p\u003e"},{"header":"METHODOLOGY","content":"\u003cp\u003e\u003cstrong\u003eComputational Softwares:\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eRaw structures of desired protein targets and chemical compounds were retrieved from free-source databases like RCSB Protein Data Bank (PDB), PubChem, ChEMBL as well as ChemSpider. Thereafter, study was carried out via computational softwares such as PyRx 0.8, Swiss-PdbViewer 4.1, BIOVIA Discovery Studio Visualiser 2020, PyMOL 2.4 and online web servers like CASTp 3.0 for active site prediction. Descriptions of each utilised software are summarised as below (Table 1 \u0026amp; Table 2).\u003c/p\u003e\n\u003cp\u003eTable 1: M.O.I.S.T. Concept in Local Treatment of Chronic Wounds\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" width=\"633\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 141px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 491px;\"\u003e\n \u003cp\u003eComponents\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 141px;\"\u003e\n \u003cp\u003eM\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 491px;\"\u003e\n \u003cp\u003eMoisture balance\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 141px;\"\u003e\n \u003cp\u003eO\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 491px;\"\u003e\n \u003cp\u003eOxygen balance\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 141px;\"\u003e\n \u003cp\u003eI\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 491px;\"\u003e\n \u003cp\u003eControl of infections\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 141px;\"\u003e\n \u003cp\u003eS\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 491px;\"\u003e\n \u003cp\u003eSupport\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 141px;\"\u003e\n \u003cp\u003eT\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 491px;\"\u003e\n \u003cp\u003eTissue Management\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u003cstrong\u003eTable 1:\u003c/strong\u003e The Clinical Framework (M.O.I.S.T.)\u003c/p\u003e\n\u003cp\u003eThis table outlines a clinical methodology used by healthcare professionals to manage chronic wounds (like diabetic ulcers or pressure sores). It is an evolution of the older \u0026quot;T.I.M.E.\u0026quot; acronym, expanded to include modern treatment priorities.\u003c/p\u003e\n\u003cp\u003eTable 2: Computational Softwares and Servers Utilised in Virtual Screening\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" width=\"641\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 56px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 312px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eSoftwares / Servers\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 272px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eDescription\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 56px;\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 312px;\"\u003e\n \u003cp\u003ePyRx 0.8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 272px;\"\u003e\n \u003cp\u003eA free virtual screening tool that has features like AutoDock 4, AutoDock Vina and Open Babel (Dallakyan and Olson, 2015)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 56px;\"\u003e\n \u003cp\u003e2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 312px;\"\u003e\n \u003cp\u003eSwiss-PdbViewer 4.1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 272px;\"\u003e\n \u003cp\u003eA molecular graphics software created for the viewing and\u003c/p\u003e\n \u003cp\u003eanalysis of protein structures (Guex \u0026amp; Peitsch, 1997)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 56px;\"\u003e\n \u003cp\u003e3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 312px;\"\u003e\n \u003cp\u003eBIOVIA Discovery Studio Visualiser 2020\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 272px;\"\u003e\n \u003cp\u003eA free viewer software that suits for the analysis and modelling of molecular structures and sequences (BIOVIA, 2020).\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 56px;\"\u003e\n \u003cp\u003e4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 312px;\"\u003e\n \u003cp\u003ePyMOL 2.4.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 272px;\"\u003e\n \u003cp\u003eAn open source molecular visualisation software that allows\u003c/p\u003e\n \u003cp\u003ethe rendering and animating of 3D structures (DeLano, 2002).\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 56px;\"\u003e\n \u003cp\u003e5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 312px;\"\u003e\n \u003cp\u003eCASTp 3.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 272px;\"\u003e\n \u003cp\u003eA web server that aims to provide online services like locating and measuring the geometric as well as topological properties of desired protein structures (Tian et al., 2018).\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u003cstrong\u003eTable 2:\u003c/strong\u003e The Digital Research Tools (Virtual Screening)\u003c/p\u003e\n\u003cp\u003eThis table lists the bioinformatics toolkit used by researchers to discover or test new drugs \u0026quot;in silico\u0026quot; (on a computer) before ever trying them on a human or in a lab.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eScreening of Potential Phytochemicals:\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003ePeer-reviewed scientific literature databases, such as PubMed, ScienceDirect, Google Scholar, ClinicalKey, and SAGE Journals, were searched for many phytochemicals identified in L. pumila. During the literature search, terms including \u0026quot;Labisia pumila,\u0026quot; \u0026quot;Kacip Fatimah,\u0026quot; \u0026quot;phytochemical,\u0026quot; \u0026quot;active compounds,\u0026quot; and \u0026quot;secondary metabolites\u0026quot; were used. Thereafter, corresponding three-dimensional (3D) structures and physicochemical properties were obtained as input files in Structure Data File (SDF) format from freely accessible chemical databases like Pub Chem ( https:// pubchem. ncbi. nlm. nih. gov/), Chem Spider ( https:// www.chemspider.com/) and ChEMBL (https://www.ebi.ac.uk/chembl/). The drug- likeness of the selected phytochemical compounds were first evaluated via the Lipinski\u0026rsquo;s Rule of Five (RO5) filter (http://www.scfbio-iitd.res.in/software/ drugdesign/lipinski.jsp/) formulated by Christoper A. Lipinski. It serves as a rule of thumb to evaluate whether tested chemical molecules possess the physiochemical characteristics that will make them likely candidates of orally administered drugs in humans (Kumari \u0026amp; J. S. Rana, 2013). Prior to substances going through a virtual screening process, the five factors in Lipinski\u0026apos;s RO5 (Table 3) were evaluated[11].\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eTable 3: Lipinski\u0026rsquo;s Rule of Five Drug-Likeness Parameters\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" width=\"614\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 64px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 257px;\"\u003e\n \u003cp\u003eParameters\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 293px;\"\u003e\n \u003cp\u003eConditions\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 64px;\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 257px;\"\u003e\n \u003cp\u003eMolecular Mass\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 293px;\"\u003e\n \u003cp\u003e\u0026lt; 500 daltons\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 64px;\"\u003e\n \u003cp\u003e2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 257px;\"\u003e\n \u003cp\u003eHydrogen donor numbers\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 293px;\"\u003e\n \u003cp\u003e\u0026lt; 5\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 64px;\"\u003e\n \u003cp\u003e3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 257px;\"\u003e\n \u003cp\u003eHydrogen acceptor numbers\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 293px;\"\u003e\n \u003cp\u003e\u0026lt; 10\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 64px;\"\u003e\n \u003cp\u003e4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 257px;\"\u003e\n \u003cp\u003eLipophilicity (log P) value\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 293px;\"\u003e\n \u003cp\u003e\u0026le; 5\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 64px;\"\u003e\n \u003cp\u003e5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 257px;\"\u003e\n \u003cp\u003eMolar Refractivity\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 293px;\"\u003e\n \u003cp\u003e40 - 130\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u003cstrong\u003ePreparation of Ligand Structures:\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eBefore the virtual screening procedure, BIOVIA Discovery Studio Visualiser 2020 was used to import the SDF files containing the filtered compounds that met Lipinski\u0026apos;s RO5 filter. These data were then clustered into a single SDF file. The clustered ligand file was then imported into PyRx\u0026apos;s workspace, and using the OpenBabel toolbox located under the control panel, each constituent was transformed into the PDBQT file format\u0026mdash;the default format needed for AutoDock Vina. In order to obtain a stable molecular conformation, energy minimization was also carried out to each constituent that was going to be screened prior to format conversion[12]. To guarantee the flexibility of the ligand molecules during the docking process, the number of active torsions was also recorded, and the torsional degree of freedom was determined[13].\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eRetrieval and Preparation of Protein Targets:\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eFour protein targets were chosen, and their 3D structures were obtained in PDB file format from the RCSB Protein Data Bank (https://www.rcsb.org/). The targets are MMP-1 (PDB ID: 966C), MMP-8 (PDB ID: 1A86), MMP-9 (PDB ID: 5CUH), and MMP-12 (PDB ID: 1JIZ). Under Swiss-PdbViewer\u0026apos;s \u0026quot;BUILD\u0026quot; feature, water molecules and ligands that were pre-attached to target structures were eliminated. The protein targets that had been analyzed were then saved, loaded, and converted into a macromolecules file in PDBQT format within PyRx\u0026apos;s working environment[13]. Swiss-PdbViewer and the CASTp server were used to predict and cross-check the active binding sites of the chosen molecular targets prior to virtual screening[14].\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eStructure-Based Virtual Screening via AutoDock Vina:\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eMolecular docking was carried out for the screened compounds using the specified target proteins in AutoDock Vina using the PyRx platform once the ligand and protein structures were prepared. Figure 1 depicts the workflow graphically. The \u0026apos;Analyze findings\u0026apos; tab is where you can keep an eye on the virtual screening findings once docking is finished. For additional analysis, the findings were exported in SDF and Comma Separated Values (CSV) formats. The complexes that exhibited the optimal conformations were identified through the utilization of the generated binding affinities (kcal/mol). To investigate the protein-ligand interactions of the outputs with the lowest binding energy for each molecular target, PyMOL visualisation tools and BIOVIA Discovery Studio Visualiser 2020 were used. Based on the docking scores and the interactions at the binding sites, the study\u0026apos;s conclusions and debates were made.\u003c/p\u003e"},{"header":"RESULTS","content":"\u003cdiv id=\"Sec9\" class=\"Section2\"\u003e \u003ch2\u003eConstruction of Phytochemical Library:\u003c/h2\u003e \u003cp\u003eThrough a variety of published literature journals, a total of forty phytochemicals of L. pumila were found and identified. Table\u0026nbsp;4 contains a list of the built phytochemical libraries together with the corresponding PUBChem ID. Prior to carrying out the screening stage, the phytochemicals from the library were projected to the evaluation of Lipinski's filter.\u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003eScreening Results of Potential Phytochemicals:\u003c/h3\u003e\n\u003cp\u003eAfter applying Lipinski's filter, AutoDock Vina was used to perform an in silico screening of the chosen phytochemicals of L. pumila on the four primary protein targets of wound healing (MMP-1, MMP-8, MMP-9, and MMP-12). According to their physiochemical characteristics, substances that are drug-like or non-drug-like can be distinguished using an index called Lipinski's rule of five (RO5) (Lipinski, 2004). Following two or more of the five preset rules\u0026mdash;molecular mass\u0026thinsp;\u0026lt;\u0026thinsp;500 Dalton, logP value\u0026thinsp;\u0026lt;\u0026thinsp;5, hydrogen bond donors number\u0026thinsp;\u0026lt;\u0026thinsp;5, hydrogen bond acceptors number\u0026thinsp;\u0026lt;\u0026thinsp;10, and molar refractivity 40\u0026thinsp;\u0026lt;\u0026thinsp;x\u0026thinsp;\u0026lt;\u0026thinsp;130\u0026mdash;is the general guideline in RO5. Before the entire project moves forward to further pre-clinical and clinical stages, these filters act as a checkpoint in the early pre-clinical stage of novel drug development. Twenty-four active compounds in total were projected to the virtual screening in accordance with RO5 (Table\u0026nbsp;\u003cspan refid=\"Tab5\" class=\"InternalRef\"\u003e5\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab4\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 5\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003ePhytochemical Database of \u003cem\u003eLabisia pumila\u003c/em\u003e\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"4\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCompound\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePubChem ID\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eCompound\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003ePubChem ID\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003e1\u003c/b\u003e Gallic acid\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e370\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e21\u003c/b\u003e Oleic acid\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e445639\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003e2\u003c/b\u003e Caffeic acid\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e689043\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e22\u003c/b\u003e Linoleic acid\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e5280450\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003e3\u003c/b\u003e Pyrogallol\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1057\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e23\u003c/b\u003e α-linolenic acid\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e5280934\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003e4\u003c/b\u003e Benzoic acid\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e243\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e24\u003c/b\u003e Stearic acid\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e5281\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003e5\u003c/b\u003e Cinnamic acid\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e444539\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e25\u003c/b\u003e Soyacerebroside I\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e11104507\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003e6\u003c/b\u003e Methyl gallate\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e7428\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e26\u003c/b\u003e Ardisicrenoside A\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e10260582\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003e7\u003c/b\u003e Quercetin\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e5280343\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e27\u003c/b\u003e Ardisicrenoside B\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e10373894\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003e8\u003c/b\u003e Myricetin\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e5281672\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e28\u003c/b\u003e Ardisiacrispin A\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e10328746\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003e9\u003c/b\u003e Kaempferol\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e5280863\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e29\u003c/b\u003e Ardisimamilloside H\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e101248954\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003e10\u003c/b\u003e Catechin\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e9064\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e30\u003c/b\u003e Demethylbelamcandaquinone B\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e54597440\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003e11\u003c/b\u003e Epigallocatechin\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e72277\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e31\u003c/b\u003e Irisresorcinol\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e5054\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003e12\u003c/b\u003e Naringin\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e442428\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e32\u003c/b\u003e Belamcandol B\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1096951\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003e13\u003c/b\u003e Rutin\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e5280805\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e33\u003c/b\u003e Fatimahol\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e54597441\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003e14\u003c/b\u003e Apigenin\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e5280443\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e34\u003c/b\u003e Dexyloprimulanin\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e101961815\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003e15\u003c/b\u003e Daidzein\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e5281708\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e35\u003c/b\u003e Primulanin\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e44419565\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003e16\u003c/b\u003e Genistein\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e5280961\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e36\u003c/b\u003e α-tocopherol\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e14985\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003e17\u003c/b\u003e Beta carotene\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e5280489\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e37\u003c/b\u003e Protocatechuic acid\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e72\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003e18\u003c/b\u003e Ascorbic acid\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e54670067\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e38\u003c/b\u003e Vanillic acid\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e8468\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003e19\u003c/b\u003e Palmitic acid\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e985\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e39\u003c/b\u003e Syringic acid\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e10742\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003e20\u003c/b\u003e Palmitoleic acid\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e445638\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e40\u003c/b\u003e Salicylic acid\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e338\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab5\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 5\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003ePotential \u003cem\u003eLabisia pumila\u003c/em\u003e Phytochemicals Conformed to Lipinski\u0026rsquo;s Rules of Drug-Likeliness\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"7\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCompound\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMolecular Mass\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eLog P\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eH Bond Donors\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eH Bond Acceptors\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003eMolar Refractivity\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGallic acid\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e170.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.50\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e38.395699\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCaffeic acid\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e180.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1.20\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e46.441399\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePyrogallol\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e126.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.80\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e31.436398\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBenzoic acid\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e122.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1.38\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e33.401295\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCinnamic acid\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e148.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1.78\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e43.111797\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMethyl gallate\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e184.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.59\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e42.775898\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eQuercetin\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e302.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e2.01\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e74.050476\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMyricetin\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e318.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1.72\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e75.715279\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eKaempferol\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e286.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e2.31\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e72.385681\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCatechin\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e290.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1.55\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e72.622978\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eEpigallocatechin\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e306.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1.25\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e72.622978\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eApigenin\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e270.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e2.42\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e70.813881\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDaidzein\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e254.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e2.71\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e69.149086\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGenistein\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e270.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e2.42\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e70.813881\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAscorbic acid\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e176.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e-1.41\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e35.256191\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eProtocatechuic acid\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e154.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.80\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e36.730900\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eVanillic acid\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e168.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1.10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e41.618092\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSyringic acid\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e198.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1.11\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e48.170090\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSalicylic acid\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e138.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1.09\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e35.066097\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePalmitic acid\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e256.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e5.55\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e77.947777\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePalmitoleic acid\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e254.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e5.33\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e77.853775\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eOleic acid\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e282.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e6.11\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e87.087776\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLinoleic acid\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e280.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e5.88\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e86.993774\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eα-linolenic acid\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e278.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e5.66\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e86.899773\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003cb\u003eLigands Preparation\u003c/b\u003e:\u003c/p\u003e \u003cp\u003eOnly 24 compounds in total, meeting the requirements of Lipinski's RO5 characteristics (molecular mass, log P value, number of hydrogen bond donors and acceptors, and molar refractivity), were included in the virtual screening study for the chosen phytochemicals of L. pumila. Table\u0026nbsp;\u003cspan refid=\"Tab6\" class=\"InternalRef\"\u003e6\u003c/span\u003e displays the structures of these filtered compounds (n\u0026thinsp;=\u0026thinsp;24) from \u003cem\u003eL. pumila\u003c/em\u003e.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab6\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 6\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eStructures of Potential Labisia pumila Phytochemicals Conformed to Lipinski\u0026rsquo;s Rules of Drug-Likeliness\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"6\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCompound\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMolecular Formula\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eCompoundMolecular Formula\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGallic acid\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eC7H6O5\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eDaidzeinC15H10O4\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCaffeic acid\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eC9H8O4\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eGenisteinC15H10O5\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePyrogallol\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eC6H6O3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eAscorbic acidC6H8O6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBenzoic acid\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eC7H6O2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eProtocatechuic acidC7H6O4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCinnamic acid\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eC9H8O2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eVanillic acidC8H8O4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMethyl gallate\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eC8H8O5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eSyringic acidC9H10O5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eQuercetin\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eC15H10O7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eSalicylic acidC7H6O3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMyricetin\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eC15H10O8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003ePalmitic acidC16H32O2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eKaempferol\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eC15H10O6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003ePalmitoleic acidC16H30O2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCatechin\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eC15H14O6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eOleic acidC18H34O2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eEpigallocatechin\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eC15H14O7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eLinoleic acidC18H32O2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eApigenin\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eC15H10O5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eα-linolenic acidC18H30O2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003cb\u003eBinding Affinity Results of Phytochemicals against MMPs\u003c/b\u003e:\u003c/p\u003e \u003cp\u003eThe twenty four phytochemicals of L. pumila which agreed to the Lipinski\u0026rsquo;s RO5 filter were proceeded to virtual screening with molecular targets MMP-1, MMP-8, MMP-9 and MMP-12, respectively. The entire docking results were summarised in Table\u0026nbsp;\u003cspan refid=\"Tab7\" class=\"InternalRef\"\u003e7\u003c/span\u003e with the best eight phytochemicals listed. The potential ligands with binding affinity score\u0026thinsp;\u0026gt;\u0026thinsp;9 were subjected to further conformational analysis. In the present study, the result findings were based solely on the docking affinity and the protein-ligand interactions at their separate binding sites. The more negative the value of binding affinity, the stronger the interactions are between the protein-ligand complexes. In another words, complexes with the more negative affinity scores possess more stable conformations as more energy of dissociation is needed to break apart their interactions.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab7\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 7\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eBinding Affinity of Phytochemicals in Labisia pumila against Targets of Wound Healing \u003cb\u003eBinding Affinity (kcal/mol) against Therapeutic Targets of Wound Healing\u003c/b\u003e\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"5\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePhytochemicals of\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"4\" nameend=\"c5\" namest=\"c2\"\u003e\u0026nbsp;\u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eLabisia pumila\u003c/em\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMMP-1\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eMMP-8\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eMMP-9\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eMMP-12\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003e1Quercetin\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e-10.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e-10.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e-9.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e-9.8\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003e2Catechin\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e-9.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e-9.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e-9.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e-9.5\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003e3Apigenin\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e-9.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e-9.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e-9.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e-9.3\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003e4Genistein\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e-9.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e-9.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e-9.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e-9.9\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003e5Daidzein\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e-9.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e-9.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e-9.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e-9.7\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003e6Myricetin\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e-9.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e-9.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e-9.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e-8.3\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003e7Epigallocatechin\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e-8.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e-9.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e-9.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e-9.7\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003e8Kaempferol\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e-9.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e-9.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e-8.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e-9.2\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e"},{"header":"DISCUSSIONS","content":"\u003cp\u003eBecause they are frequently linked to high-risk complications that have significantly increased morbidity and mortality among the vulnerable population, such as the elderly, the diabetic, and those with compromised immune systems, chronic and non-healing wounds have placed a tremendous financial and social strain on the global healthcare system[\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e]. These days, scientists are delving into a wide spectrum of wound-related research in an effort to find the most effective and optimal treatment choice for patients with chronic wounds. Studies on microRNA as therapeutic targets of chronic wound healing have been reported; these studies indicate the promise of microRNA as a therapeutic alternative; however, further research is needed to determine an acceptable delivery strategy[\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e]. The use of therapeutic herbal plants for the candidate search in the management of chronic wounds is a significant benefit of our current study. A common herb in Malaysia and other countries in Southeast Asia is labisia pumila, a traditional Malay herb. There are actually three different types of \u003cem\u003eL. pumila\u003c/em\u003e that can be found in our nation; the two most widely utilized forms in medicinal compositions are \u003cem\u003evar. alata\u003c/em\u003e and \u003cem\u003evar. pumila\u003c/em\u003e. It was also evident from the many phytochemical tests carried out on \u003cem\u003eL. pumila\u003c/em\u003e that these plants are abundant in active substances such as flavonoids and phenolics[\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e]. These are also the active ingredients that show promise and may be further developed into novel drugs for wound healing. Among the forty selected phytochemicals from L. pumila, 24 lead compounds were remaining after being filtered by the Lipinski\u0026rsquo;s RO5 index for their drug-likeness properties. These filtered compounds belong to different classes, which are ranging from phenolics, flavonoids, saponins, carotenoids and phenols. This filter does not only help to cut down the number of potential lead candidates, but also facilitating the betterment of the screening results. The following virtual screening was carried out using AutoDock Vina via PyRx software.\u003c/p\u003e \u003cp\u003eThe affinity scores of the top eight compounds out of the forty preliminary compounds are shown in Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e. The top eight lead phytochemicals that showed binding affinities of \u0026gt;\u0026thinsp;9 kcal/mol against the respective wound healing therapeutic targets MMP-1, MMP-8, MMP-9 and MMP-12 were further analysed using PyMOL and BIOVIA Discovery Studio Visualiser 2020 to validate the binding conformations and hydrogen bond interactions in both 3D and 2D graphical representations.\u003c/p\u003e"},{"header":"CONCLUSION","content":"\u003cp\u003eIn our present in silico study, a total of 24 phytochemical lead candidates from medicinal herb Labisia pumila were subjected to the virtual screening process via AutoDock Vina after the application of Lipinski\u0026rsquo;s Rule of Five drug-likeness filter. Through the structure-based screening, eight flavonoid compounds were identified as the best lead molecules against the therapeutic targets of wound healing. These compounds also exhibited good non- covalent interactions such as hydrogen bonding, van der Waals and hydrophobic interactions with the respective targets. With this pharmacoinformatic approach, the appreciable binding affinities between the phytoconstituents and their protease targets have shown their great potentials as cost-effective lead candidates for wound healing drug design and discovery in the near future.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eAcknowledgment:\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot Applicable\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding:\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNo targeted funding was reported.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAvailability of data and materials:\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAll data and materials are presented in this manuscript. No additional materials are available.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting interests:\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAuthors declare no competing interest\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eEthics declaration:\u003c/strong\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eNot Applicable\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthor information:\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cu\u003eCorresponding Author:\u003c/u\u003e\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003ePugazhandhi Bakthavatchalam, Department of Anatomy and Physiology, American University of Antigua, University Park, Jabberwock Beach Road, PO Box W1451, Coolidge, Antigua, West Indies, North America.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cu\u003eFirst Author:\u0026nbsp;\u003c/u\u003e\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAshok Gnanasekaran, Professor of Microbiology, Faculty of Medicine, Director, Centre for Botanicals and Clinical Research (CBCR), Quest International University (QIU), Ipoh, Perak, Malaysia.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthors’ contributions:\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003ea.\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;Study planning: Ashok Gnanasekaran, Pugazhandhi Bakthavatchalam\u003c/p\u003e\n\u003cp\u003eb.\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;Literature search: Paula Chia Siaw Jun, Sarah Stephenie,\u003c/p\u003e\n\u003cp\u003ec.\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;Manuscript writing: Ashok Gnanasekaran, Paula Chia Siaw Jun, Pugazhandhi Bakthavatchalam\u003c/p\u003e\n\u003cp\u003ed.\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;Manuscript revision: Ashok Gnanasekaran, Paula Chia Siaw Jun, Sarah Stephenie\u003c/p\u003e\n\u003cp\u003ee.\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;Final approval: Ashok Gnanasekaran, Paula Chia Siaw Jun, Sarah Stephenie, Pugazhandhi Bakthavatchalam\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eSen, C. K. \u003cem\u003eHuman wounds and its burden: an updated compendium of estimates\u003c/em\u003e. 2019, Mary Ann Liebert, Inc., publishers 140 Huguenot Street, 3rd Floor New \u0026hellip; pp. 39\u0026ndash;48.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eIqbal, A., et al. (2017). Management of chronic non-healing wounds by hirudotherapy. \u003cem\u003eWorld journal of plastic surgery\u003c/em\u003e, \u003cem\u003e6\u003c/em\u003e(1), 9.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eSen, C. K., et al. (2009). Human skin wounds: a major and snowballing threat to public health and the economy. \u003cem\u003eWound repair and regeneration\u003c/em\u003e, \u003cem\u003e17\u003c/em\u003e(6), 763\u0026ndash;771.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eMcCaughan, D., et al. (2018). Patients\u0026rsquo; perceptions and experiences of living with a surgical wound healing by secondary intention: a qualitative study. \u003cem\u003eInternational journal of nursing studies\u003c/em\u003e, \u003cem\u003e77\u003c/em\u003e, 29\u0026ndash;38.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eArmstrong, D. G., \u0026amp; Jude, E. B. (2002). The role of matrix metalloproteinases in wound healing. \u003cem\u003eJournal of the American Podiatric Medical Association\u003c/em\u003e, \u003cem\u003e92\u003c/em\u003e(1), 12\u0026ndash;18.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eL\u0026ouml;ffek, S., Schilling, O., \u0026amp; Franzke, C. W. (2011). Biological role of matrix metalloproteinases: a critical balance. \u003cem\u003eEuropean Respiratory Journal\u003c/em\u003e, \u003cem\u003e38\u003c/em\u003e(1), 191\u0026ndash;208.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eNagori, B. P., \u0026amp; Solanki, R. (2011). Role of medicinal plants in wound healing. \u003cem\u003eResearch Journal of Medicinal Plant\u003c/em\u003e, \u003cem\u003e5\u003c/em\u003e(4), 392\u0026ndash;405.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eSabran, S. F., Mohamed, M., Abu, M. F., \u0026amp; Bakar (2016). \u003cem\u003eEthnomedical knowledge of plants used for the treatment of tuberculosis in Johor, Malaysia.\u003c/em\u003e Evidence-based complementary and alternative medicine, 2016.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eManda, V. K., et al. (2014). Evaluation of drug interaction potential of Labisia pumila (Kacip Fatimah) and its constituents. \u003cem\u003eFrontiers in Pharmacology\u003c/em\u003e, \u003cem\u003e5\u003c/em\u003e, 178.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eNadia, M. (2012). \u003cem\u003eThe anti-inflammatory, phytoestrogenic, and antioxidative role of Labisia pumila in prevention of postmenopausal osteoporosis.\u003c/em\u003e Advances in Pharmacological Sciences, 2012.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eLipinski, C. A. (2004). Lead-and drug-like compounds: the rule-of-five revolution. \u003cem\u003eDrug discovery today: Technologies\u003c/em\u003e, \u003cem\u003e1\u003c/em\u003e(4), 337\u0026ndash;341.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eMackay, D., Cross, A., \u0026amp; Hagler, A. (1989). The role of energy minimization in simulation strategies of biomolecular systems. \u003cem\u003ePrediction of protein structure and the principles of protein conformation\u003c/em\u003e (pp. 317\u0026ndash;358). Springer.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eBuckley, M., et al. (2016). Enhancer scanning to locate regulatory regions in genomic loci. \u003cem\u003eNature protocols\u003c/em\u003e, \u003cem\u003e11\u003c/em\u003e(1), 46\u0026ndash;60.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eTian, W., et al. (2018). CASTp 3.0: computed atlas of surface topography of proteins. \u003cem\u003eNucleic acids research\u003c/em\u003e, \u003cem\u003e46\u003c/em\u003e(W1), W363\u0026ndash;W367.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eJ\u0026auml;rbrink, K., et al. (2016). Prevalence and incidence of chronic wounds and related complications: a protocol for a systematic review. \u003cem\u003eSystematic reviews\u003c/em\u003e, \u003cem\u003e5\u003c/em\u003e, 1\u0026ndash;6.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eMulholland, E. J., Dunne, N., \u0026amp; McCarthy, H. O. (2017). MicroRNA as therapeutic targets for chronic wound healing. \u003cem\u003eMolecular Therapy-Nucleic Acids\u003c/em\u003e, \u003cem\u003e8\u003c/em\u003e, 46\u0026ndash;55.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eKarimi, E., Jaafar, H. Z., \u0026amp; Ahmad, S. (2011). Phenolics and flavonoids profiling and antioxidant activity of three varieties of Malaysian indigenous medicinal herb Labisia pumila Benth. \u003cem\u003eJ Med Plant Res\u003c/em\u003e, \u003cem\u003e5\u003c/em\u003e, 1200\u0026ndash;1206.\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"Labisia pumila, phytochemicals, wound healing, virtual screening, matrix metalloproteinases","lastPublishedDoi":"10.21203/rs.3.rs-9108521/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-9108521/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eProlonged inflammatory reactions and a lack of discernible progress in tissue regeneration beyond thirty days are common characteristics of chronic wounds. They also have a close relationship to extracellular matrix unbalanced protease activity. A thorough understanding of the underlying mechanism of chronic wounds is crucial for the development of target-specific treatment agents. Numerous research regarding chronic wounds have reported higher expressions of matrix metalloproteinases (MMPs). This in silico study has chosen MMPs as its therapeutic target because they are one of the key molecular players in chronic cutaneous wounds. Utilizing Lipinski's Rule of Five filter, phytochemicals from the native medicinal plant Labisia pumila were extracted from chemical databases and assessed for drug-likeness. Using AutoDock Vina via PyRx, a total of 24 lead compounds that met the predetermined criteria were virtual screened against the therapeutic targets MMP-1, MMP-8, MMP-9, and MMP-12. Eight of the best flavonoid compounds (quercetin, catechin, apigenin, genistein, daidzein, myricetin, epigallocatechin, and kaempferol) with binding affinity scores ranging from \u0026minus;\u0026thinsp;8.3 to -10.0 kcal/mol were identified as promising candidates for future wound healing drug design and development based on their conformations and binding affinity scores.\u003c/p\u003e","manuscriptTitle":"Evaluating Phytochemicals from Labisia pumila for Potential Healing Properties in Silico compared with the Specified Therapeutic Objectives","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2026-03-30 16:43:22","doi":"10.21203/rs.3.rs-9108521/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"ebe5f1b8-4b96-47ca-a0bb-f43ea0642ddb","owner":[],"postedDate":"March 30th, 2026","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2026-04-14T07:12:22+00:00","versionOfRecord":[],"versionCreatedAt":"2026-03-30 16:43:22","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-9108521","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-9108521","identity":"rs-9108521","version":["v1"]},"buildId":"XKTyCvWXoU3ODBz1xrDgd","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}