Research Article

Theoretical study on binding interactions of laccase-enzyme from Ganoderma weberianum with multiples ligand substrates with environmental impact

Yosberto Cárdenas-Moreno*, Luis Ariel Espinosa, Julio Cesar Vieyto, Michael González-Durruthy, Alberto del Monte-Martinez, Gilda Guerra-Rivera and Maria Isabel Sánchez López

Published: 12/19/2019 | Volume 3 - Issue 1 | Pages: 001-009


Laccase catalyzes oxidation of lignin and aromatic compound with similar structure to this one. Their low substrate specificity results on degradation of similar phenolic compounds. In this context, Molecular Docking was performed with different ligands suggesting potential bio-degradation. Binding active-sites prediction of fungal laccase (access number uniprotkb: A0A166P2X0), from Ganoderma weberianum was performed using machine learning algorithm based on Deep Convolutional Neural Networks (DeepSite-CNNs chemoinformatic tool). Herein, ligands like 2,4 - dichlorophenol, benzidine, sulfisoxazole, trimethoprim and tetracycline were analyzed and two additional reference controls which were 2,2 – azinobis 3 – ethylbenzothiazoline – 6 - sulfonic acid (ABTS) and 2,6 - dimetoxyphenol (2,6 DMP) were used in comparison with the other former mentioned ligands based on high laccase affinity. The five ligands were carried out because their potential biotechnological interest: the antibiotics sulfisoxazole, trimethoprim and tetracycline, and xenobiotics 2,4 - dichlorophenol and benzidine. Molecular docking experiments returned Gibbs free energy of binding (FEB or affinity) for laccase-ligand complexes. The best docking binding-interaction from each laccase-ligand conformation complexes suggest great ability of these ligands to interact with the laccase active-binding site. Herein, FEB values (kcal/mol) were obtained with higher affinity values for reference controls like 2,6 - dimethoxyphenol with -4.8 Kcal/mol and ABTS with -7.1 Kcal/mol. Furthermore, the FEB values were -4.7, -6.5, -6.8, -5.2 and -6.5 Kcal/mol, for 2,4 - dichlorophenol, benzidine, sulfisoxazole, tetracycline and trimethoprim respectively with high prevalence of hydrophobic interaction with functional laccase binding residues. Lastly, this study presents for first time at the bioinformatics field a molecular docking approach for the prediction of potential substrate of laccase from Ganoderma weberianum towards biotechnological application.

Read Full Article HTML DOI: 10.29328/journal.apb.1001007 Cite this Article


  1. Viswanath B, Rajesh B, Janardhan A, Kumar AP, Narasimha G. Fungal Laccases and Their Applications in Bioremediation. Enzyme Res. 2014: 2014: 1-21.
  2.  Baldrian P. Fungal laccases - occurrence and properties. FEMS Microbiol Rev. 2006; 30: 215-242. PubMed:
  3. Cázares-García SV, Vázquez-Garcidueñas MS, Vázquez-Marrufo G. Structural and Phylogenetic Analysis of Laccases from Trichoderma: A Bioinformatic Approach. PLoS One. 2013; 8: 55295. PubMed:
  4. Rivera-Hoyos CM, Morales-Álvarez ED, Poveda-Cuevas SA, Reyes-Guzmán EA, Poutou-Piñales RA, et al. Computational analysis and low-scale constitutive expression of laccases synthetic genes GLLCC1 from Ganoderma lucidum and POXA 1B from pleurotus ostreatus in pichia pastoris. PLoS One. 2015; 10: 0116524. PubMed:
  5. Bugg TD, Ahmad M, Hardiman EM, Rahmanpour R Pathways for degradation of lignin in bacteria and fungi. Nat Prod Rep. 2011; 28: 1883-1896. PubMed:
  6. Latch DE, Packer JL, Stender BL, VanOverbeke J, Arnold WA, et al. Aqueous photochemistry of triclosan: Formation of 2,4 - dichlorophenol, 2,8 - dichlorodibenzo-p-dioxin, and oligomerization products. Environ Toxicol Chem. 2005; 24: 517-525. PubMed:
  7. Zhuo R, Ma L, Fan F, Gong Y, Wan X, et al. Decolorization of different dyes by a newly isolated white-rot fungi strain Ganoderma sp.En3 and cloning and functional analysis of its laccase gene. J Hazard Mater. 2011; 192: 855-873. PubMed:
  8. Philip PR, Lee R, Lin C. The Antibiotic Paradox: How the Misuse of Antibiotics Destroys Their Curative Powers (review). Perspect Biol Med. 2007.
  9. Kümmerer K. Promoting resistance by the emission of antibiotics from hospitals and households into effluent. Clin Microbiol Infect. 2003; 9: 1203-1214. PubMed:  
  10. Miao XS, Bishay F, Chen M, Metcalfe CD. Occurrence of antimicrobials in the final effluents of wastewater treatment plants in Canada. Environ Sci Technol. 2004; 38: 3533-3541. PubMed:
  11. Suda T, Hata T, Kawai S, Okamura H, Nishida T. Treatment of tetracycline antibiotics by laccase in the presence of 1-hydroxybenzotriazole. Bioresour Technol. 2012; 103: 498-501. PubMed:
  12. Hata T, Shintate H, Kawai S, Okamura H, Nishida T. Elimination of carbamazepine by repeated treatment with laccase in the presence of 1-hydroxybenzotriazole. J Hazard Mater. 2010; 181: 1175-1178. PubMed:
  13. Ding H, Wu Y, Zou B, Lou Q, Zhang W, et al. Simultaneous removal and degradation characteristics of sulfonamide, tetracycline, and quinolone antibiotics by laccase-mediated oxidation coupled with soil adsorption. J Hazard Mater. 2016; 307: 350-358. PubMed:
  14. Prieto A, Möder M, Rodil R, Adrian L, Marco-Urrea E. Degradation of the antibiotics norfloxacin and ciprofloxacin by a white-rot fungus and identification of degradation products. Bioresour Technol. 2011; 102: 10987-10995. PubMed:
  15. Macellaro G, Pezzella C, Cicatiello P, Sannia G, Piscitelli A. Fungal Laccases Degradation of Endocrine Disrupting Compounds. Biomed Res Int. 2014; 2014: 614038. PubMed:  
  16. House WA, Leach D, Long JLA, Cranwell P, Smith C, et al. Micro-organic compounds in the Humber rivers. Sci Total Environ. 1997.
  17. Gao J, Liu L, Liu X, Zhou H, Huang S, et al. Levels and spatial distribution of chlorophenols - 2,4-Dichlorophenol, 2,4,6-trichlorophenol, and pentachlorophenol in surface water of China. Chemosphere. 2008; 71: 1181-1187.  PubMed:
  18. Jin X, Zha J, Xu Y, Wang Z, Kumaran SS. Derivation of aquatic predicted no-effect concentration (PNEC) for 2,4-dichlorophenol: Comparing native species data with non-native species data. Chemosphere. 2011; 84: 1506-1511. PubMed:
  19. Yin D, Jin H, Yu L, Hu S. Deriving freshwater quality criteria for 2,4-dichlorophenol for protection of aquatic life in China. Environ Pollut. 2003; 122: 217-222. PubMed:
  20. Bhadauria V, Zhao WS, Wang LX, Zhang Y, Liu JH, et al. Advances in fungal proteomics. Microbiol Res. 2007.
  21. Chemical Advisory and Notice of Potential Risk: Skin exposure to molten 2,4 - Dichlorophenol can Cause Rapid Death, USEPA.
  22. Amer SM, Aly FAE. Genotoxic effect of 2,4 - dichlorophenoxy acetic acid and its metabolite 2,4 - dichlorophenol in mouse. Mutat. Res. 2001; 494: 1-12. PubMed:
  23. Agency for Toxic Substances and Disease Registry. 2019.
  24. Choudhary G. Human health perspectives on environmental exposure to benzidine: A review. Chemosphere. 1996. PubMed:
  25. Karagoz B, Bayramoglu G, Altintas B, Bicak N, Yakup MA. Amine functional monodisperse microbeads via precipitation polymerization of N-vinyl formamide: Immobilized laccase for benzidine based dyes degradation. Bioresour Technol. 2011. PubMed:
  26. Kalme SD, Parshetti GK, Jadhav SU, Govindwar SP. Biodegradation of benzidine based dye Direct Blue-6 by Pseudomonas desmolyticum NCIM 2112. Bioresour Technol. 2007. PubMed:
  27. Martínez-Sotres C, Rutiaga-Quiñones JG, Herrera-Bucio R, Gallo M, López-Albarrán P. Molecular docking insights into the inhibition of laccase activity by medicarpin. Wood Sci Technol. 2015.
  28. Kameshwar AKS, Barber R, Qin W. Comparative modeling and molecular docking analysis of white, brown and soft rot fungal laccases using lignin model compounds for understanding the structural and functional properties of laccases. J Mol Graph Model. 2018. PubMed:
  29. Wagner JR, Lee CT, Durrant JD, Malmstrom RD, Feher VA, et al. Emerging Computational Methods for the Rational Discovery of Allosteric Drugs. Chem. Rev. 2016; 116: 6370-6390. PubMed:
  30. Zsila F, Bikadi Z, Malik D, Hari P, Pechan I, et al. Evaluation of drug-human serum albumin binding interactions with support vector machine aided online automated docking. Bioinformatics. 2011; 27: 1806-1813. PubMed:
  31. Trott O, Olson AJ. Software news and update AutoDock Vina: Improving the speed and accuracy of docking with a new scoring function, efficient optimization, and multithreading. J Comput Chem. 2010; 31: 455-461.
  32. Zhou YP, Chen QH, Xiao YN, Ke DS, Tian CE. Gene cloning and characterization of a novel laccase from the tropical white-rot fungus Ganoderma weberianum TZC-1. Appl Biochem Microbiol. 2014.
  33. Kelley LA, Mezulis S, Yates CM, Wass MN, Sternberg MJE. The Phyre2 web portal for protein modeling, prediction and analysis. Nat Protoc. 2015; 10: 845-858. PubMed:
  34. Kim S, Thiessen PA, Bolton EE, Chen J, Fu G, et al. PubChem substance and compound databases. Nucleic Acids Res. 2016; 44: 1202-1213.
  35. McNamara JP, Hillier IH. Semi-empirical molecular orbital methods including dispersion corrections for the accurate prediction of the full range of intermolecular interactions in biomolecules. Phys Chem Chem Phys. 2007; 9: 2362-2370. PubMed:
  36. Govender K, Gao J, Naidoo KJ. AM1/d-CB1: A semiempirical model for QM/MM simulations of chemical glycobiology systems. J Chem Theory Comput. 2014; 10: 4694-4707. PubMed:
  37. Liu J, Wang R. Classification of current scoring functions. J Chem Inf Model. 2015; 55: 475-482. PubMed:
  38. Quiroga R, Villarreal MA. Vinardo: A scoring function based on autodock vina improves scoring, docking, and virtual screening. PLoS One. 2016; 11. PubMed:
  39. Jiménez J, Doerr S, Martínez-Rosell G, Rose AS, De Fabritiis G. DeepSite: Protein-binding site predictor using 3D-convolutional neural networks. Bioinformatics. 2017; 33: 3036-3042. PubMed:
  40. Desaphy J, Bret G, Rognan D, Kellenberger E. Sc-PDB: A 3D-database of ligandable binding sites-10 years on. Nucleic Acids Res. 2015; 43: 399-404. PubMed:
  41. Gasteiger J, Marsili M. Iterative partial equalization of orbital electronegativity-a rapid access to atomic charges. Tetrahedron. 1980.
  42. Morris GM, Huey R, Lindstrom W, Sanner MF, Belew RK, et al. AutoDock4 and AutoDockTools4: Automated docking with selective receptor flexibility. J Comput Chem. 2009; 30: 2785-2791. PubMed:
  43. González-Durruthy M, Werhli AV, Seus V, Machado KS, et al, Decrypting Strong and Weak Single-Walled Carbon Nanotubes Interactions with Mitochondrial Voltage-Dependent Anion Channels Using Molecular Docking and Perturbation Theory. Sci Rep. 2017; 7: 13271. PubMed:
  44. Chen VB, Arendall WB, Headd JJ, Keedy DA, Immormino RM, et al. MolProbity: all-atom structure validation for macromolecular crystallography. Acta Crystallogr Sect D Biol Crystallogr. 2010; 66: 12-21. PubMed:
  45. Weirick T, Sahu SS, Mahalingam R, Kaundal R. LacSubPred: Predicting subtypes of Laccases, an important lignin metabolism-related enzyme class, using in silico approaches, BMC Bioinformatics. 2014; 15: 15. PubMed:
  46. Awasthi M, Jaiswal N, Singh S, Pandey VP, Dwivedi UN. Molecular docking and dynamics simulation analyses unraveling the differential enzymatic catalysis by plant and fungal laccases with respect to lignin biosynthesis and degradation. J Biomol Struct Dyn. 2015; 33: 1835-1849. PubMed:
  47. Frasconi M, Favero G, Boer H, Koivula A, Mazzei F. Kinetic and biochemical properties of high and low redox potential laccases from fungal and plant origin. Biochim Biophys Acta - Proteins Proteomics. 2010; 1804: 899-908. PubMed:
  48. Madzak C, Mimmi MC, Caminade E, Brault A, Baumberger S, et al. Shifting the optimal pH of activity for a laccase from the fungus Trametes versicolor by structure-based mutagenesis. Protein Eng Des Sel. 2006; 19: 77-84. PubMed:  
  49. Gorbacheva MA, Shumakovich GP, Morozova OV, Zaitseva EA, Shleev SV. Comparative Study of Biocatalytic Reactions of High and Low Redox Potential Fungal and Plant Laccases. Vestn Mosk Univ. 2008.
  50. Madhavi V, Lele SS. Laccase properties, use. Bio Resources. 2009; 4: 1694-1717.