In silico exploration of lignin peroxidase for unraveling the degradation mechanism employing lignin model compounds

Purification, characterization and three-dimensional structure prediction of multicopper oxidase Laccases from Trichoderma lixii FLU1 and Talaromyces pinophilus FLU12

Broad-spectrum biocatalysts enzymes, Laccases, have been implicated in the complete degradation of harmful pollutants into less-toxic compounds. In this study, two extracellularly produced Laccases were purified to homogeneity from two different Ascomycetes spp. Trichoderma lixii FLU1 (TlFLU1) and Talaromyces pinophilus FLU12 (TpFLU12). The purified enzymes are monomeric units, with a molecular mass of 44 kDa and 68.7 kDa for TlFLU1 and TpFLU12, respectively, on SDS-PAGE and zymogram. It reveals distinct properties beyond classic protein absorption at 270-280 nm, with TlFLU1's peak at 270 nm aligning with this typical range of type II Cu site (white Laccase), while TpFLU12's unique 600 nm peak signifies a type I Cu2+ site (blue Laccase), highlighting the diverse spectral fingerprints within the Laccase family. The Km and kcat values revealed that ABTS is the most suitable substrate as compared to 2,6-dimethoxyphenol, caffeic acid and guaiacol for both Laccases. The bioinformatics analysis revealed critical His, Ile, and Arg residues for copper binding at active sites, deviating from the traditional two His and a Cys motif in some Laccases. The predicted biological functions of the Laccases include oxidation-reduction, lignin metabolism, cellular metal ion homeostasis, phenylpropanoid catabolism, aromatic compound metabolism, cellulose metabolism, and biological adhesion. Additionally, investigation of degradation of polycyclic aromatic hydrocarbons (PAHs) by purified Laccases show significant reductions in residual concentrations of fluoranthene and anthracene after a 96-h incubation period. TlFLU1 Laccase achieved 39.0% and 44.9% transformation of fluoranthene and anthracene, respectively, while TpFLU12 Laccase achieved 47.2% and 50.0% transformation, respectively. The enzyme structure-function relationship study provided insights into the catalytic mechanism of these Laccases for possible biotechnological and industrial applications.

In Silico Insights into the Arsenic Binding Mechanism Deploying Application of Computational Biology-Based Toolsets

An assortment of environmental matrices includes arsenic (As) in its different oxidation states, which is often linked to concerns that pose a threat to public health worldwide. The current difficulty lies in addressing toxicological concerns and achieving sustained detoxification of As. Multiple conventional degradation methods are accessible; however, they are indeed labor-intensive, expensive, and reliant on prolonged laboratory evaluations. Molecular interaction and atomic level degradation mechanisms for enzyme-As exploration are, however, underexplored in those approaches. A feasible approach in this case for tackling this accompanying concern of As might be to cope with undertaking multivalent computational methodologies and tools. This work aimed to provide molecular-level insight into the enzyme-aided As degradation mechanism. AutoDock Vina, CABS-flex 2.0, and Desmond high-performance molecular dynamics simulation (MDS) were utilized in the current investigation to simulate multivalent molecular processes on two protein sets: arsenate reductase (ArsC) and laccase (LAC) corresponding arsenate (ART) and arsenite (AST), which served as model ligands to comprehend binding, conformational, and energy attributes. The structural configurations of both proteins exhibited variability in flexibility and structure framework within the range of 3.5-4.5 Å. The LAC-ART complex exhibited the lowest calculated binding affinity, measuring -5.82 ± 0.01 kcal/mol. Meanwhile, active site residues ILE-200 and HIS-206 were demonstrated to engage in H-bonding with the ART ligand. In contrast to ArsC, the ligand binding affinity of this bound complex was considerably greater. Additional validation of docked complexes was carried out by deploying Desmond MDS of 100 ns to capture protein and ligand conformation behavior. The system achieved stability during the 100 ns simulation run, as confirmed by the average P-L RMSD, which was ∼1 Å. As a preliminary test of the enzyme's ability to catalyze As species, corresponding computational insights might be advantageous for bridging gaps and regulatory consideration.

Preparation of tobacco pyrolysis liquids in subcritical/supercritical ethanol and their application in the aroma enhancement of heated cigarettes

For the aroma enhancement research of heated cigarettes, it is worth exploring whether tobacco can be pyrolyzed into pyrolysis liquids containing a large number of volatile aroma components. In this study, tobacco pyrolysis liquids were prepared in subcritical/supercritical ethanol, and their applications in the aroma enhancement of heated cigarettes were investigated. The optimal conditions of supercritical liquefaction reactions were determined by optimizing the reaction time, liquid/solid mass ratio and temperature conditions. Moreover, the effect of supercritical liquefaction conditions on volatile aroma components in tobacco pyrolysis liquids was investigated by GC-MS. The results indicated that the reaction temperature had the most significant impact on the tobacco pyrolysis reaction, and higher reaction temperature promoted the pyrolysis conversion of tobacco, resulting in enhanced tobacco conversion and a high content of volatile components in the tobacco pyrolysis liquid. The optimal reaction conditions for the preparation of tobacco pyrolysis liquid were found to be a temperature of 220°C, a liquid/solid mass ratio = 15, and a 2-h reaction time. Meanwhile, the content of ester compounds and nicotine in the tobacco pyrolysis liquid increased significantly with the increase of reaction temperature. Sub/supercritical ethanol treatment significantly destroyed the surface structure of tobacco, and the degree of tobacco depolymerization increased when temperature rised. The analysis of aroma compounds in the smoke of heated cigarettes indicated that the tobacco pyrolysis liquid could significantly increase the release of aromatic substances and has a significant aroma-enhancing effect. This article proposed and prepared tobacco pyrolysis liquid in subcritical/supercritical ethanol and explored its potential application in the aroma enhancement of heated cigarettes, offering a new route for flavor enhancement technology for this type of product.

Exploring the role of microbial proteins in controlling environmental pollutants based on molecular simulation

Molecular simulation has been widely used to study microbial proteins' structural composition and dynamic properties, such as volatility, flexibility, and stability at the microscopic scale. Herein, this review describes the key elements of molecular docking and molecular dynamics (MD) simulations in molecular simulation; reviews the techniques combined with molecular simulation, such as crystallography, spectroscopy, molecular biology, and machine learning, to validate simulation results and bridge information gaps in the structure, microenvironmental changes, expression mechanisms, and intensity quantification; illustrates the application of molecular simulation, in characterizing the molecular mechanisms of interaction of microbial proteins with four different types of contaminants, namely heavy metals (HMs), pesticides, dyes and emerging contaminants (ECs). Finally, the review outlines the important role of molecular simulations in the study of microbial proteins for controlling environmental contamination and provides ideas for the application of molecular simulation in screening microbial proteins and incorporating targeted mutagenesis to obtain more effective contaminant control proteins.

Deciphering insights into the binding mechanism and plasticity of Telacebec with M. tuberculosis cytochrome bcc-aa3 supercomplex through an unbiased molecular dynamics simulation, free-energy analysis, and DFT study

The cytochrome bcc-aa3 supercomplex, a key component in the electron transport chain pathway involved in bacterial energy production and homeostasis, is a clinically validated target for tuberculosis (TB), leading to Telacebec (Q203). Telacebec is a potent candidate drug under Phase II clinical development for the treatment of drug-sensitive and drug-resistant TB. Recently, the cryo-electron microscopy structure of this supercomplex from Mycobacterium tuberculosis (Mtb) complexed with Q203 was resolved at 6.9 Å resolution (PDB ID: 7E1W). To understand the binding site (QP site) flexibility and Q203's stability at the QP site of the Mtb cytochrome bcc complex, we conducted molecular dynamics (MD) simulation and free energy analysis on this complex in an explicit hydrated lipid bilayer environment for 500 ns. Through this study, the persistence of a range of direct and indirect interactions was observed over the course of the simulation. The significance of the interactions with His375, Tyr161, Ala178, Ala179, Ile183, His355, Leu356, and Thr313 is underlined. Electrostatic energy was the primary source of the net binding free energy, regardless of the important interacting residues. The overall binding free energy for Q203 was -112.84 ± 7.73 kcal/mol, of which the electrostatic and lipophilic energy contributions were -116.31 ± 1.14 and -21.32 ± 2.35 kcal/mol, respectively. Meanwhile, DFT calculations were utilized to elucidate Q203's molecular properties. Overall, this study deciphers key insights into the cytochrome bcc-aa3 supercomplex with Q203 on the ground of molecular mechanics and quantum mechanics that may facilitate structure-based drug design and optimization for the discovery of the next-generation antitubercular drug(s).Communicated by Ramaswamy H. Sarma.

Bio-mitigation of organic pollutants using horseradish peroxidase as a promising biocatalytic platform for environmental sustainability

A wide array of environmental pollutants is often generated and released into the ecosystem from industrial and human activities. Antibiotics, phenolic compounds, hydroquinone, industrial dyes, and Endocrine-Disrupting Chemicals (EDCs) are prevalent pollutants in water matrices. To promote environmental sustainability and minimize the impact of these pollutants, it is essential to eliminate such contaminants. Although there are multiple methods for pollutants removal, many of them are inefficient and environmentally unfriendly. Horseradish peroxidase (HRP) has been widely explored for its ability to oxidize the aforementioned pollutants, both alone and in combination with other peroxidases, and in an immobilized way. Numerous positive attributes make HRP an excellent biocatalyst in the biodegradation of diverse environmentally hazardous pollutants. In the present review, we underlined the major advancements in the HRP for environmental research. Numerous immobilization and combinational studies have been reviewed and summarized to comprehend the degradability, fate, and biotransformation of pollutants. In addition, a possible deployment of emerging computational methodologies for improved catalysis has been highlighted, along with future outlook and concluding remarks.

Structural insights, biocatalytic characteristics, and application prospects of lignin-modifying enzymes for sustainable biotechnology-A review

Lignin modifying enzymes (LMEs) have gained widespread recognition in depolymerization of lignin polymers by oxidative cleavage. LMEs are a robust class of biocatalysts that include lignin peroxidase (LiP), manganese peroxidase (MnP), versatile peroxidase (VP), laccase (LAC), and dye-decolorizing peroxidase (DyP). Members of the LMEs family act on phenolic, non-phenolic substrates and have been widely researched for valorization of lignin, oxidative cleavage of xenobiotics and phenolics. LMEs implementation in the biotechnological and industrial sectors has sparked significant attention, although its potential future applications remain underexploited. To understand the mechanism of LMEs in sustainable pollution mitigation, several studies have been undertaken to assess the feasibility of LMEs in correlating to diverse pollutants for binding and intermolecular interactions at the molecular level. However, further investigation is required to fully comprehend the underlying mechanism. In this review we presented the key structural and functional features of LMEs, including the computational aspects, as well as the advanced applications in biotechnology and industrial research. Furthermore, concluding remarks and a look ahead, the use of LMEs coupled with computational frameworks, built upon artificial intelligence (AI) and machine learning (ML), has been emphasized as a recent milestone in environmental research.

Bioremediation potential of laccase for catalysis of glyphosate, isoproturon, lignin, and parathion: Molecular docking, dynamics, and simulation

The present study aimed to investigate the catalytic degradation produced by laccase in the detoxification of glyphosate, isoproturon, lignin polymer, and parathion. We explored laccase-glyphosate, laccase-lignin polymer, laccase-isoproturon, and laccase-parathion using molecular docking (MD) and molecular dynamics simulation (MDS) approaches. The results suggest that laccase interacts well with glyphosate, lignin polymer, isoproturon, and parathion during biodegradation. We calculated the root mean square deviations (RMSD) of laccase-glyphosate, laccase-lignin polymer, laccase-isoproturon, and laccase-parathion as 0.24 ± 0.02, 0.59 ± 0.32, 0.43 ± 0.07, and 0.43 ± 0.06 nm, respectively. In an aqueous solution, the stability of laccase with glyphosate, lignin polymer, isoproturon, and parathion is mediated through the formation of hydrophobic interactions, hydrogen bonds, and van der Waals interactions. The presence of xenobiotic toxic compounds in the active site changed the conformation of laccase. MDS of the laccase-substrate complexes confirmed their stability during catalytic degradation. Laccase assay results confirmed that the degradation of syringol, dihydroconiferyl alcohol, guaiacol, parathion, isoproturon, and glyphosate were 100%, 99.31%, 95.69%, 60.96%, 54.51%, and 48.34% within 2 h, respectively. Taken together, we describe a novel method to understand the molecular-level biodegradation of xenobiotic compounds through laccase and its potential application in contaminant removal.

Assessing chemical hazard and unraveling binding affinity of priority pollutants to lignin modifying enzymes for environmental remediation

Lignin-modifying enzymes (LMEs) are impactful biocatalysts in environmental remediation applications. However, LMEs-assisted experimental degradation neglects the molecular basis of pollutant degradation. Furthermore, throughout the remediation process, the inherent hazards of environmental pollutants remain untapped for in-depth toxicological endpoints. In this investigation, a predictive toxicological framework and a computational framework adopting LMEs were employed to assess the hazards of Priority Pollutants (PP) and its possible LMEs-assisted catalytic screening. The potential hazardous outcomes of PP were assessed using Quantitative structure-activity relationship (QSARs)-based techniques including Toxtree, ECOSAR, and T.E.S.T. tools. Toxicological findings revealed positive outcomes in a multitude of endpoints for all PP. The PP compound 2,3,7,8-TCDD (dioxin) was found to exhibit the lowest concentration of aquatic toxicity implementing aquatic model systems; LC₅₀ as 0.01, 0.01, 0.04 (mg L^-1) for Fish (96 H), Daphnid (48 H), Green algae (96 H) respectively. T.E.S.T. results revealed that chloroform, and 2-chlorophenol both seem to be developmental toxicants. Subsequently, LMEs-assisted docking procedure was employed in predictive mitigation of PP. The docking approach as predicted degradation revealed the far lowest docking energy score for Versatile peroxidase (VP)- 2,3,7,8-TCDD docked complex with a binding energy of -9.2 (kcal mol^-1), involved PHE-46, PRO-139, PRO-141, ILE-148, LEU-165, HIS-169, LEU-228, MET-262, and MET-265 as key interacting amino acid residues. Second most ranked but lesser than VP, Lignin peroxidase (LiP)- 2,3,7,8-TCDD docked complex exhibited a rather lower binding affinity score (-8.8 kcal mol^-1). Predictive degradation screening employing comparative docking revealed varying binding affinities, portraying that each LMEs member has independent feasibility to bind PP as substrate. Predictive findings endorsed the hazardous nature of associated PP in a multitude of endpoints, which could be attenuated by undertaking LMEs as a predictive approach to protect the environment and implement it in regulatory considerations.

In silico analysis of peroxidase from Luffa acutangula

Peroxidases are oxidoreductase enzymes that widely gained attention as biocatalysts for their robust catalytic activity, specificity, and regioselective functionality for phenolic compounds. The study of molecular aspects of peroxidases is as crucial as that of the physicochemical aspects. A bioinformatics approach is utilized in this study to investigate the structural aspects and functions of luffa peroxidase (LPrx) from Luffa acutangula. The evolutionary relationship of LPrx with other class III peroxidases was studied by constructing a neighbour-joining phylogenetic tree. An analysis of the phylogenetic tree revealed that plant peroxidases share a common ancestor. The gene ontology term showed that LPrx had a molecular functionality of the oxidation-reduction process, heme binding and peroxidase-like activity, and the biological function of hydrogen peroxide scavenging activity. The enzyme-ligand interactions were studied from a catalytic point of view using the molecular docking technique. The molecular docking was carried out with LPrx as a receptor and guaiacol, m-cresol, p-cresol, catechol, quinol, pyrogallol, 2,4-dimethoxyphenol, gallic acid, aniline, and o-phenylenediamine as ligands. The results presented in the current communication will have a significant implication in proteomics, biochemistry, biotechnology, and the potential applications of peroxidases in the biotransformations of organic compounds.

Supplementary Information

The online version contains supplementary material available at 10.1007/s13205-022-03432-8.

Plant catalase in silico characterization and phylogenetic analysis with structural modeling

Background

Catalase (EC 1.11.1.6) is a heme-containing tetrameric enzyme that plays a critical role in signaling and hydrogen peroxide metabolism. It was the first enzyme to be crystallized and isolated. Catalase is a well-known industrial enzyme used in diagnostic and analytical methods in the form of biomarkers and biosensors, as well as in the textile, paper, food, and pharmaceutical industries. In silico analysis of CAT genes and proteins has gained increased interest, emphasizing the development of biomarkers and drug designs. The present work aims to understand the catalase evolutionary relationship of plant species and analyze its physicochemical characteristics, homology, phylogenetic tree construction, secondary structure prediction, and 3D modeling of protein sequences and its validation using a variety of conventional computational methods to assist researchers in better understanding the structure of proteins.

Results

Around 65 plant catalase sequences were computationally evaluated and subjected to bioinformatics assessment for physicochemical characterization, multiple sequence alignment, phylogenetic construction, motif and domain identification, and secondary and tertiary structure prediction. The phylogenetic tree revealed six unique clusters where diversity of plant catalases was found to be the largest for Oryza sativa. The thermostability and hydrophilic nature of these proteins were primarily observed, as evidenced by a relatively high aliphatic index and negative GRAVY value. The distribution of 5 sequence motifs was uniformly distributed with a width length of 50 with the best possible amino residue sequences that resemble the plant catalase PLN02609 superfamily. Using SOPMA, the predicted secondary structure of the protein sequences revealed the predominance of the random coil. The predicted 3D CAT model from Arabidopsis thaliana was a homotetramer, thermostable protein with 59-KDa weight, and its structural validation was confirmed by PROCHECK, ERRAT, Verify3D, and Ramachandran plot. The functional relationships of our query sequence revealed the glutathione reductase as the closest interacting protein of query protein.

Conclusions

This theoretical plant catalases in silico analysis provide insight into its physiochemical characteristics and functional and structural understanding and its evolutionary behavior and exploring protein structure-function relationships when crystal structures are unavailable.

In Silico Elucidation of Potent Inhibitors from Natural Products for Nonstructural Proteins of Dengue Virus

Medicinal plants have been used from the beginning of human civilization against various health complications. Dengue virus (DENV) has emerged as one of the most widespread viruses in tropical and subtropical countries. Yet no clinically approved antiviral drug is available to combat DENV infection. Consequently, the search for novel antidengue agents from medicinal plants has assumed more insistence than in previous days. This study has focused on 31 potential antidengue molecules from secondary metabolites to examine their inhibitory activity against DENV nonstructural proteins through molecular docking and pharmacokinetics studies. In this research, the wet lab experiments were tested on a computational platform. Agathisflavone and pectolinarin are the top-scored inhibitors of DENV NS2B/NS3 protease and NS5 polymerase, respectively. Epigallocatechin gallate, Pinostrobin, Panduratin A, and Pectolinarin could be potential lead compounds against NS2B/NS3 protease, while acacetin-7-O-rutinoside against NS5 polymerase. Moreover, agathisflavone (LD50= 1430 mg/kg) and pectolinarin (LD50= 5000 mg/kg) exhibited less toxicity than nelfinavir (LD50= 600 mg/kg) and balapiravir (LD50 = 824 mg/kg), and the reference drugs. Further research on clinical trials is required to analyze the therapeutic efficacy of these metabolites to develop new potential drug candidates against different serotypes of DENV.

A predictive toolset for the identification of degradation pattern and toxic hazard estimation of multimeric hazardous compounds persists in water bodies

An array of industrial processing units generates many multimeric hazardous compounds, such as complex technical lignin and its toxic derivatives, thereby persist in expelled water bodies. The inclusion of some group of motifs in the complex technical lignin structure helps it resist degrade biologically, most often even recalcitrant. Relatively small concentrations of lignin are harmful to aquatic organisms and can trigger environmental hazards. Sadly, the entire biotransformation pathway and insightful information about these toxic derivatives are incomplete and missing in the literature. This is mainly because the current conventional treatments often fail to identify all transformed compounds and their environmental fate. Thus, a robust toolset is much needed to cover this literature gap. Inadequate performance of conventional remediation processes and biological degradation patterns can be maximally optimized with the aid of predictive toolset methods that could offer better degradability and complete transformed compound information. A predictive toolset-assisted biodegradation pattern determination is a multifaceted and reliable analytical technique that can help to overcome existing shortcomings by providing an entire transformation pathway. Considering the above critiques, this work reports on the degradation pattern, and toxicological endpoints of five hazardous compounds, i.e., 2-chlorosyringaldehyde, 5-chlorovanillin, catechol, guaiacyl 4-O-5 guaiacyl, and syringyl β-O-4 syringyl β-O-4 sinapyl alcohol, that persists in water matrices. The predictive transformation pattern was revealed notably less complex end-products of catechol as; succinate, and 2-Oxo-4-pentenoate. The gastrointestinal (GI) absorption rate was found high for all tested compounds, excluding trimer compound, i.e., syringyl β-O-4 syringyl β-O-4 sinapyl alcohol. The toxicity and persistence profile tested via Toxtree showed that the Cramer Rules, Verhaar Scheme, and Structural Alerts for Reactivity, (START) biodegradation ability as positive, and all five target compounds were found as class-II persistent compounds. Furthermore, the Ecological Structure-Activity Relationships (ECOSAR)assisted testing specifies that all tested derivatives have multiple aquatic toxic levels. In summary, the current findings endorse the hazardous compounds and undertake prescreening of the deprivation policy to protect the environment.

In silico analytical toolset for predictive degradation and toxicity of hazardous pollutants in water sources

Different phenolic compounds, including multimeric lignin derivatives in the β-O-4 form, are among the most prevalent compounds in wastewater, often generated from paper industries. Relatively small concentrations of lignin are hazardous to aquatic organisms and can trigger severe environmental hazards. Herein, we present a predictive toolset to insight the induced toxic hazards prediction, and their Lignin peroxidase (LiP)-assisted degradation mechanism of selected multimeric lignin model compounds. T.E.ST and Toxtree toolset were deployed for toxic hazards estimation in different endpoints. To minimize the concerning hazards, we screened multimeric compounds for binding affinity with LiP. The binding affinity was found to be significantly lower than the reference compound. An Extra precision (XP) Glide score of -6.796 kcal/mol was found for dimer (guaiacyl 4-O-5 guaiacyl) complex as lowest compared to reference compound (-4.007 kcal/mol). The active site residues ASP-153, HIP-226, VAL-227, ARG-244, GLU-215, 239, PHE-261 were identified as site-specific key binding AA residues actively involved with corresponding ligands, forming Hydrophobic, H-Bond, π-Stacking, π-π type interactions. The DESMOND-assisted molecular dynamics simulation's (MDS) trajectories of protein-ligand revealed the considerable binding behavior and attained stability and system equilibrium state. Such theoretical and predictive conclusions indicted the feasibility of LiP assisted sustainable mitigation of lignin-based compounds, and such could be used to protect the environment from the potential hazards posed by recognized similar pollutants.

Artificial intelligence modeling and molecular docking to analyze the laccase delignification process of rice straw by Comamonas testosteroni FJ17

The laccase enzymatic characteristics and delignification processes of rice straw by Comamonas testosteroni FJ17 were investigated. Artificial intelligence modeling and molecular docking revealed the specific functional properties involved in the interaction between laccase and lignin compounds with a maximum laccase activity of 2016.7 U L^-1 at 24 h. Scanning electron microscopy and X-ray diffractometer analysis confirmed that laccase caused fractures and holes on the surface of rice straw, where crystallinity decrease from 45.3 to 39.9%, and lignin content decreased from 19.0 to 10.3%. Gas chromatography-mass spectrometry and liquid chromatography-mass spectrometry analysis showed that the main delignification process for laccase was via β-o-4 and α-aryl ether cleavage, which generated several small molecular products. The laccase gene was cloned and bioinformatics analysis presented 317 amino acids with a predicted molecular weight of 33.13 kDa. Finally, laccase protein was found to have low binding energies with all lignin compounds tested, and lignin compounds were oxidized by laccase through hydrogen-bonding interactions with the amino acid residues.