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RESEARCH PAPER
Predictive characterization and molecular docking of lignocellulolytic enzymes: comparative analyses of Moroccan fungal species
1
Laboratory of Biotechnology and Bioresources Valorization, Faculty of Sciences, Moulay Ismail University, BP 11201 Zitoune Meknes, Morocco
2
Laboratory of Biodiversity, Ecology and Genome, Plant and Microbial Biotechnology, Biodiversity and Environment Research Centre, Faculty of Sciences, Mohammed V University, BP 1014 RP, Rabat, Morocco
Submission date: 2025-10-09
Final revision date: 2026-03-01
Acceptance date: 2026-04-27
Publication date: 2026-08-20
Corresponding author
Arif Soukaina
Laboratory of Biotechnology and Bioresources Valorization, Faculty of Sciences, Moulay Ismail University, BP 11201 Zitoune Meknes, Morocco
Laboratory of Biotechnology and Bioresources Valorization, Faculty of Sciences, Moulay Ismail University, BP 11201 Zitoune Meknes, Morocco
KEYWORDS
TOPICS
ABSTRACT
Background:
Lignocellulosic biomass has significant potential as a renewable feedstock for the production of biofuels and bioproducts. However, its structural complexity, particularly the crystalline nature of cellulose and protective lignin matrix, poses considerable challenges for enzymatic degradation. Fungi isolated from diverse lignocellulosic wastes, particularly olive pomace in Morocco, are a significant, yet underutilized resource of lignocellulolytic enzymes with a potential to overcome these challenges.
Material and methods:
This study investigated the structural and functional properties of lignocellulolytic enzymes derived from 9 filamentous fungi. A total of 80 curated sequences were systematically categorized into cellulases and ligninases. Phylogenetic analysis was conducted on representative endoglucanases, β-glucosidases, and laccases to assess their diversity. Physicochemical parameters, secondary structure content, and thermostability indices were determined using ExPASy ProtParam and SOPMA. Homology models were generated with SWISS-MODEL and validated through PROCHECK, ERRAT, and ProSA. Molecular docking with AutoDock was used to evaluate the interactions of β-glucosidase with cellobiose.
Results:
Phylogenetic analysis revealed high evolutionary diversity among the examined species. Several enzymes showed favorable aliphatic indices and GRAVY scores, suggesting thermostability and hydrophilicity. β-Glucosidase from Fusarium equiseti showed the strongest predicted binding energy to cellobiose (–5.32 kcal/mol), with hydrogen bonding mediated by key residues, including Asp88, Arg94, Lys185, Gln197, Asp276, and Gln278, at optimal distances (1.95–2.58 Å).
Conclusions:
This integrative in silico study highlights the predictive potential of Moroccan fungal β-glucosidases, particularly from F. equiseti, for future applications in lignocellulose bioconversion.
Lignocellulosic biomass has significant potential as a renewable feedstock for the production of biofuels and bioproducts. However, its structural complexity, particularly the crystalline nature of cellulose and protective lignin matrix, poses considerable challenges for enzymatic degradation. Fungi isolated from diverse lignocellulosic wastes, particularly olive pomace in Morocco, are a significant, yet underutilized resource of lignocellulolytic enzymes with a potential to overcome these challenges.
Material and methods:
This study investigated the structural and functional properties of lignocellulolytic enzymes derived from 9 filamentous fungi. A total of 80 curated sequences were systematically categorized into cellulases and ligninases. Phylogenetic analysis was conducted on representative endoglucanases, β-glucosidases, and laccases to assess their diversity. Physicochemical parameters, secondary structure content, and thermostability indices were determined using ExPASy ProtParam and SOPMA. Homology models were generated with SWISS-MODEL and validated through PROCHECK, ERRAT, and ProSA. Molecular docking with AutoDock was used to evaluate the interactions of β-glucosidase with cellobiose.
Results:
Phylogenetic analysis revealed high evolutionary diversity among the examined species. Several enzymes showed favorable aliphatic indices and GRAVY scores, suggesting thermostability and hydrophilicity. β-Glucosidase from Fusarium equiseti showed the strongest predicted binding energy to cellobiose (–5.32 kcal/mol), with hydrogen bonding mediated by key residues, including Asp88, Arg94, Lys185, Gln197, Asp276, and Gln278, at optimal distances (1.95–2.58 Å).
Conclusions:
This integrative in silico study highlights the predictive potential of Moroccan fungal β-glucosidases, particularly from F. equiseti, for future applications in lignocellulose bioconversion.
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