In Silico evaluation and identification of fungi capable of producing endo-inulinase enzyme

Abstract

The enzyme endo-inulinase hydrolyzes inulin to short chain fructooligosaccharides (FOS) that are potential prebiotics with many health promoting benefits. Although the raw materials for inulin production are inexpensive and readily available, commercial production of FOS from inulin is limited due to inadequate availability of the enzyme source. This study aimed to identify the fungi capable of producing endo-inulinase based on the in silico analysis of proteins retrieved from non-redundant protein sequence database. The endo-inulinase of Aspergillus ficuum was used as reference sequence. The amino acid sequences with >90% sequence coverage, belonging to different fungi were retrieved from the database and used for constructing three-dimensional (3D) protein models using SWISS-MODEL and Bagheerath H. The 3D models of comparable quality as that of the reference endo-inulinase were selected based on QMEAN Z score. The selected models were evaluated and validated for different structural and functional qualities using Pro-Q, ProSA, PSN-QA, VERIFY-3D, PROCHECK, PROTSAV metaserver, STRAP, molecular docking, and molecular dynamic simulation analyses. A total of 230 proteins belonging to 53 fungal species exhibited sequence coverage >90%. Sixty one protein sequences with >60% sequence identity were modeled as endo-inulinase with higher QMEAN Z Score. The evaluations and validations of these 61 selected models for different structural and functional qualities revealed that 60 models belonging to 22 fungal species exhibited native like structure and unique motifs and residues as that of the reference endo-inulinase. Further, these models also exhibited similar kind of interaction between the active site around the conserved glutamate residue and substrate as that of the reference endo-inulinase. In conclusion, based on the current study, 22 fungal species could be identified as endo-inulinase producer. Nevertheless, further biological assessment of their capability for producing endo-inulinase is imminent if they are to be used for commercial endo-inulinase production for application in FOS industry.

Optimization of Inulin Hydrolysis by Penicillium lanosocoeruleum Inulinases and Efficient Conversion Into Polyhydroxyalkanoates

“…Penla1_371227, instead, resulted to be related to fungal endoinulinases, displaying 74.7 and 69.6% identities with Penicillium subrubescens endoinulinase Inu2 and A. niger InuA, respectively. Consistently, the Penla1_371227 sequence reveals the presence of all the conserved motifs and the unique aminoacidic residues described for fungal endoinulinases ( Chikkerur et al, 2018 ; Singh et al, 2020a ; Figure 4 ).…”

“…A similar profile was already reported for inulinase production in shake-flask fermentations of many fungal species, i.e., Penicillium sp. ( Rawat et al, 2015b ), Aspergillus fumigatus ( Chikkerur et al, 2018 ), Aspergillus niger ( Mahmoud et al, 2011 ), and Aspergillus tritici ( Singh et al, 2020b ).…”

Sweet Immunity Aspects during Levan Oligosaccharide-Mediated Priming in Rocket against Botrytis cinerea

“…Although FOS priming also led to similar sugar dynamics in the apoplast (Figure 10), the inefficiency of disease priming can most probably be explained by the fact that B. cinerea harbors inulinase activity [114], indicating it can use FOS as a food source, further confirmed by our own analysis (Figure 10c). This is different from the case of LOS priming, since fungal fructanases have no affinity towards levan-type substrates [137]. Additionally, in the case of the Venturia/apple pathosystem, inulin proved inefficient in priming as compared to levan, and this could be linked to the fact that the fungus was able to grow on inulin but not on levan [78].…”

In Silico Evaluation, Phylogenetic Analysis, and Structural Modeling of the Class II Hydrophobin Family from Different Fungal Phytopathogens

“…The accuracy of the HFBII protein model was measured using a Ramachandran plot [85] and the result (97.5%) was satisfactory (Figure S1). The PROSA web server was used to analyze the protein structure by matching the predicted with the experimental structures using the statistics of the Cα of the mean force to evaluate the quality of the predicted proteins [86]. The output Z-score plots from the PROSA server revealed that the predicted protein models were within the range of the experimentally determined structures using the NMR method (Figure S2).…”