Molecular docking of potential antifungal compounds from Ulva fasciatamethanolic extract against Pseudopestalotiopsistheae

ISSN 1391-0256 Journal of the Sri Lanka Association for the Advancement of Science Volume 7 Issue 1, 2025 Founded in 1944 and incorporated by the Act of Parliament No 11 of 1966. JSLAAS 1 Journal of the Sri Lanka Association for the Advancement of Science is a biannual publication. Selected research work from annual research sessions (based on scientific merit) as well as other research articles are invited to submit research manuscripts as per the guidelines provided by SLAAS. SLAAS members may also separately submit their papers for publication. 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All rights reserve. e-ISSN: 2682-6992 2 Table of Contents Page 1 Molecular docking of potential antifungal compounds from Ulva fasciatamethanolic extract gainst Pseudopestalotiopsistheae A. H. D. Alahakoon, B.K. D. M. Rodrigo, B.M. Chathuranga, M. Balasooriya, H. M. Herath, R. P. Wanigatunge 03 2 Dosimetric Impact on IMRT Plans of Altering Per Control Point Statistical Uncertainty in Monaco TPS K. L. I. Gunawardhana, J. Jeyasugiththan, P. De Silva and D. Satharasinghe 16 3 Development of a Solar - Powered, Automated Water Ionizer Using Graphite-Based Electrodes for Alkaline and Acidic Water Production A.M.K.L Abeykoon, M.D.Y Milani, H.M. B. I. Gunathilaka ,R. C. W. Arachchige, D.M.K Muthumala 40 3 Molecular docking of potential antifungal compounds from Ulva fasciatamethanolic extract against Pseudopestalotiopsistheae A. H. D. Alahakoon1, B.K. D. M. Rodrigo1, B.M. Chathuranga M. Balasooriya2, H. M. Herath1, R. P. Wanigatunge1* 1Department of Plant and Molecular Biology, Faculty of Science, University of Kelaniya, Sri Lanka 2School of Science, Mae Fah Luang University, Thailand. ABSTRACT Plant diseases caused by fungal pathogens significantly threaten global food security, accounting for nearly 40% of annual crop losses and incurring over US$220 billion in management costs worldwide. Among these, Pseudopestalotiopsistheae has emerged as notable phytopathogen in Sri Lanka, causing chlorosis in Solanum melongena. Its virulence is largely attributed to the secretion of pectinase enzymes, which degrade plant cell walls and facilitate host colonization. Excessive use of synthetic fungicides to manage such pathogens has led to environmental degradation, health risks, and the emergence of fungicide-resistant strains. Consequently, there is a growing interest in eco-friendly alternatives such as natural products derived from marine organisms. Marine macroalgae, particularly Ulva fasciata, commonly found in Thalpe reef, are known to produce a wide range of bioactive secondary metabolites with antifungal potential. In a previous study, methanolic extract of U. fasciata revealed numerous bioactive compounds with potential antifungal activity. The present studyaimed to evaluate the inhibitory potential of these compounds against the pectinase enzyme of P. theae using molecular docking, a powerful in silico approach for predicting interactions between small molecules and target proteins. The findings are expected to contribute to the development of sustainable, ecofriendly strategies for managing plant diseases, offering a cost-effective alternative to synthetic fungicides.This study highlights the potential of marine bioresources and computational tools in the discovery of novel antifungal agents targeting emerging phytopathogens. Key words-Antifungal compounds, Ulva fasciata, Molecular docking, Pseudopestalotiopsistheae INTRODUCTION Approximately 40% of global crop production is lost each year due to attacks by pests and pathogens, including numerous bacterial and fungal species. To combat these plant diseases, more than US$ 220 billion is spent annually worldwide (FAO, 2022). Among emerging fungal pathogens, Pseudopestalotiopsistheaeishas been identified as a significant threat in Sri Lanka, causing chlorosis in Solanum melongena (Koshila et al., 2023). Its virulence is primarily attributed to secretion of extracellular pectinase enzymes which degrade plant cell walls and facilitate host colonization(Sopalun&Iamtham, 2020). Pectinases are a group of enzymes that hydrolyze glycosidic linkages in pectic polymers and are functionally categorized into polygalacturonases, pectin esterases, pectin lyases and pectate lyase (Aryaet al., 2022). Pseudopestalotiopsis, Neopestalotiopsis, and Pestalotiopsis are closely related genera within the family Amphisphaeriaceaeand are known to cause various plant diseases, including cankers, shoot dieback, leaf spots, blights, severe chlorosis, and fruit A. H. D. Alahakoon et al., JSLAAS,Vol. 7, Issue 1 (2025) 03-15 4 rot(Maharachchikumbura, 2014;Sane et al., 2019). Although chemical fungicides are widely used to control fungal infections,their excessive usage leads to serious environmental consequences, including contamination of aquatic ecosystems, residue accumulation in crops, and the emergence of resistant fungal strains. Moreover, fungicides pose risks to non-target organisms and human health(Goswami et al., 2018). Biocontrol has been explored as a natural and sustainable alternative to chemical fungicides for managing various fungal infections in agriculture (Bubiciet al., 2019). It involves mechanisms such as competition for space and nutrients, production of antifungal compounds and secondary metabolites (Rashad & Moussa, 2020), and the biological triggering of plant resistance (Hermosa et al., 2013). Plants, animals, and marine organisms are sources of natural products with inherent fungicidal activity (Dong et al., 2020). Marine macroalgae (seaweeds) are multicellular, eukaryotic and photosynthetic organisms known to be rich in bioactive compounds (Makkar et al., 2016).Ulva fasciata, a common macroalgae in Thalpe reef of Sri Lanka, showed potent antifungal activity against P. theaein a previous study through its methanolic extract (Rodrigo et al., 2025).Gas Chromatography-Mass Spectrometry (GC-MS) analysis of the extract revealed several potential antifungal compounds, includingPhenylephrine, Palmitic acid, 17-Octadecenal, 4-Hydroxy-2-butanone, Heptadecene and 3Methoxyamphetamine. However, the specific mechanism by which these compounds inhibit the fungal activityremain unclear. Molecular docking has become a valuable computational technique for exploring the therapeutic potential of natural products. This method simulates the interactions between bioactive compounds and target proteins, predicting binding affinity and interaction modes. By virtually testing thousands of molecules, molecular docking enables the identification of promising compounds efficiently, and costeffectively, significantly reducing the need for extensive laboratory screening (Agu et al., 2023). In antifungal research, docking is particularly useful for identifying inhibitors of fungal enzymes or proteins that contribute to pathogenicity. It provides insights into how candidate molecules interact with target sites at the atomic level, assessing the strength and stability of these interactions (Hendra et al., 2024). Hence, the present study aimed to employ molecular docking techniques to investigate the binding interactions between the most potent bioactive compounds from the methanolic extract of U. fasciataand the extracellular enzymes of P. theae, with the objective of inhibiting their enzymatic activity. Though the fungus P. theae secretes pectinase as an extracellular enzyme to maintain its pathogenicity, the amino acid sequences or 3D structures of pectinase enzymes from P. theaeare not currently available in databases. Therefore, the polygalacturonase sequence from Pestalotiopsis sp. NC0098 (KAI0138346.1) was used to construct a homology model for subsequent analysis as it is the only available related amino acid sequence in the databases. METHODOLOGY Homology modeling of polygalacturonase enzyme of Pestalotiopsis sp. Polygalacturonase enzyme of Pestalotiopsis sp. NC0098 (KAI0138346.1) was used for generating the homology model as amino acid sequences or 3D structures of pectinases of the fungus P. theaewere not available inthe NCBI GenBank protein database. Polygalacturonaseamino acid sequence was searched against the Protein Data Bank (PDB) using the NCBI Protein BLAST tool to identify suitable homologous templates. Four template structures with A. H. D. Alahakoon et al., JSLAAS,Vol. 7, Issue 1 (2025) 03-15 5 sequence identities ranging from 54.87% to 55.46% were retrieved. Multiple sequence alignment was performed using the CLUSTALW online tool and homology modeling was carried out using MODELLER software (version 10.1).From the generated models, the one with the lowest DOPE (Discrete Optimized Protein Energy) score was selected for further analysis, as lower DOPE scores indicate higher model reliability (Selvam et al., 2017). The selected model was further refined in MODELLER, and energy minimization was performed using the GROMOS simulation package within Swiss-PdbViewer. Model validation was conducted using several structure assessment tools: PROCHECK, Verify3D, and ERRAT to assess stereochemical quality and 3D structure compatibility. Additionally, PROSA was used to calculate the Z-score, and the QMEAN score was evaluated using its corresponding web server to assess the overall quality and stability of the predicted structure (Selvam et al., 2017). Active compound identification in the U. fasciata– methanolicextract Potential antifungal compounds present in U. fasciata-methanolic extract were identified by GC-MS analysis as described by Kamal et al. (2011) in our previous study (Rodrigo et al., 2025). Molecular docking Molecular docking analysis was carried out using the AutoDock Vina software (Version 1.1.2). The homology-modeled polygalacturonase protein served as the receptor, and the receptor was prepared using Auto Dock Tools software (Version 1.5.7). The molecule was checked for adding polar H molecules and missing amino acid residues. Kollman charges were added to the molecule by equally distributing the charge across the protein surface (Phosrithong & Ungwitayatorn, 2010). Ligand structures were based on the chemical compounds previously identified through GC-MS analysis (Rodrigo et al., 2025). Structures of the selected chemical molecules were obtained from the PubChem database, and energy was minimized using AVOGADRO software (Version 1.2.0). The minimized structures were then converted into a Protein Data Bank file format (pdb) using Open Babel software (Version 3.1.1). Potential ligand-binding pockets on the receptor were identified using the DoGSiteScorertool of the ProteinsPlus server. The binding pocket with the highest drug score value was selected for docking the ligands (Selvam et al., 2017). Nine independent docking runs were carried out for each ligand and the best binding mode with the lowest (most negative) binding free energy was selected as the best conformation (Phosrithong & Ungwitayatorn, 2010). RESULTS AND DISCUSSION Homology modeling of the Polygalacturonase enzyme The extracellular enzymes are the pathogenicity determinant factors in many plant pathogens as they facilitate host invasion by degrading plant cell wall components. Enzymes are proteins that catalyze chemical reactions in living organisms, and their activity can be inhibited by certain bioactive compounds. Marine algae are known to produce diverse secondary metabolites capable of interferingwith such enzymes present in the plant pathogenic fungi and lead to the inhibition of their activity (Agu et al., 2023). In this study, a homology model of the polygalacturonase enzyme was generated with 4 similar crystal structures available in the protein data bank using the MODELLER software (Figure 1). Then the loops of the structures were refined, and energy was minimized. The best model was evaluated using online servers of PROCHECK, Verfiy3D, ERRAT, PROSA, and QMEAN. A. H. D. Alahakoon et al., JSLAAS,Vol. 7, Issue 1 (2025) 03-15 6 Figure 1. Homology model of polygalacturonase enzyme of Pestalotiopsis sp. (a) cartoon diagram (b) surface view diagram of the energy-minimized protein model Each tool assesses different aspects of protein structure quality. PROCHECK evaluates the stereochemical quality of a protein structure including parameters like bond lengths, bond angles and planarity using Ramachandran plot analysis (Figure 2) (Wlodawer, 2017). A high percentage of residues in the most favored regions is indicative of a well-refined model. Values above 90% are considered excellent, while those exceeding 80% are generally acceptable. In this study, PROCHECK analysis revealed that 84.4% of residues (Table 1) were located in the most favoured regions of the Ramachandran plot, which falls within the acceptable range and is comparable to previous models developed for Aspergillus nigerenzymes (Gundampatiet al., 2012).This suggests that the overall stereochemical quality of the model is acceptable. Furthermore, no residues were observed in the generally allowed or disallowed regions (0.0%), proving the reliability of the model. The additional allowed regions (%) ideally range between 1–15%, and this model exhibited 15.6% (Table 1), which, although at the upper threshold, still falls within the acceptable range. This value is slightly higher than the percentage reported in the additionally allowed regions for A. niger (Gundampatiet al., 2012). However, the overall results support the structural validity of the predicted model. A. H. D. Alahakoon et al., JSLAAS,Vol. 7, Issue 1 (2025) 03-15 7 Figure 2. Ramachandran plot of the model Table 1. Model evaluation results of PROCHECK, Verfiy3D, and ERRAT Program PROCHECK Verfiy3D ERRAT Most favored regions Additional allowed regions Generally allowed regions Disallowed regions 3D-ID Score Quality Factor Value 84.4% 15.6% 0.0% 0.0% 81.07% 76.03% Table 2. Model evaluation results of QMEAN and PROSA Program QMEAN PROSA QMEAN4 Value Z-Score Value -0.46 -6.49 Verfiy3D assesses the compatibility of the 3D model with its own amino acid sequence by assigning a 3D environment score to each residue and compares it with known preferences based on experimentally determined structures (Eisenberg et al., 1997).A model is generally considered reliable if a 3D-1D scoreis more than 80%.In this study, Verfy3D analysis showed 81.07% of the residues had an acceptable 3D-1D score (Table 1), indicating that the residue environments are biochemically plausible and structurally consistent. ERRAT analyzes non-bonded atomic interactions to identify statistical deviations by comparing the input protein structure to high-resolution crystallographic data, and it computes an overall error function that reflects the model’s reliability. A quality factor above 90% is indicative of an excellent model, while values between 70% and 90% are generally considered acceptable. In this study, the model achieved 76.03% quality factor,suggesting that the non-bonded interactions are largely consistent with those found in experimentally validated structures. Although this value is slightly lower A. H. D. Alahakoon et al., JSLAAS,Vol. 7, Issue 1 (2025) 03-15 8 than the 83.97% reported for Trichoderma longibrachiatum (Tamboliet al., 2017), it remains within the acceptable range for functional docking studies, thereby supporting the structural plausibility of the model. QMEAN (Qualitative Model Energy Analysis) is another important tool used to assess the quality of predicted protein structures. It is a composite scoring function that evaluates local geometry (torsion angles, solvation, hydrogen bonding), long-range interactions and agreement with high-resolution structures (Benkert et al., 2008). The QMEAN score typically ranges from 0 to –4, with values closer to 0 indicating a high-quality model. In this study, the QMEAN score was -0.46 (Table 2), which is close to 0 and comparable to the QMEAM values reported for Aspergillus ficuum, where scores were -3 or higher (Chikkeruret al., 2018).This suggests that the modeled structure is of good quality and comparable to experimentally determined protein structures. PROSA provides a Z-score that indicated the energy separation of the native and average of the misfolds in the units of standard deviation (Heydari-Zarnaghet al., 2015). If z-score falls –4 to –10 typically indicates that global structure resembles real proteins. In our study, the PROSA Z-score was – 6.49 (Table 2), which falls well within this acceptable range, suggesting that the modeled structure is realistic and reliable. This is comparable to the Z-score reported in the PROSA analysis for Trichoderma longibrachiatumwhich had a Z-score of -6.78 (Tamboliet al., 2017). Figure 3. ProSA Z-score plot of the model. The value of Z-score is highlighted as a black dot and is in the range of native conformations This multi-angle validation is essential to build trust in the accuracy of a predicted or experimentally determined protein model before using it in downstream applications like molecular docking, drug design, or structural biology research. The scores received for these tests indicate that the model generated was of good quality, and it has higher reliability (Selvam et al., 2017). Biologically active compounds in the U. fasciata– methanolic extract Nine different chemical compounds were identified in our previous study by Rodrigo et al. (2025) using GC-MS analysis (Table 3). Various aromatic and non-aromatic compounds were found in different abundances (Figure 3). 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