Cysteine proteases secreted by the pinewood nematode, Bursaphelenchus xylophilus: In silico analysis

Optimization, gene cloning, expression, and molecular docking insights for enhanced cellulase enzyme production by Bacillus amyloliquefaciens strain elh1

BACKGROUND

In this study, we isolated a cellulase-producing bacterium, Bacillus amyloliquefaciens strain elh, from rice peel. We employed two optimization methods to enhance the yield of cellulase. Firstly, we utilized a one-variable-at-a-time (OVAT) approach to evaluate the impact of individual physical and chemical parameters. Subsequently, we employed response surface methodology (RSM) to investigate the interactions among these factors. We heterologously expressed the cellulase encoding gene using a cloning vectorin E. coli DH5α. Moreover, we conducted in silico molecular docking analysis to analyze the interaction between cellulase and carboxymethyl cellulose as a substrate.

RESULTS

The bacterial isolate eh1 exhibited an initial cellulase activity of 0.141 ± 0.077 U/ml when cultured in a specific medium, namely Basic Liquid Media (BLM), with rice peel as a substrate. This strain was identified as Bacillus amyloliquefaciens strain elh1 through 16S rRNA sequencing, assigned the accession number OR920278 in GenBank. The optimal incubation time was found to be 72 h of fermentation. Urea was identified as the most suitable nitrogen source, and dextrose as the optimal sugar, resulting in a production increase to 5.04 ± 0.120 U/ml. The peak activity of cellulase reached 14.04 ± 0.42 U/ml utilizing statistical optimization using Response Surface Methodology (RSM). This process comprised an initial screening utilizing the Plackett-Burman design and further refinement employing the BOX -Behnken Design. The gene responsible for cellulase production, egl, was effectively cloned and expressed in E. coli DH5α. The transformed cells exhibited a cellulase activity of 22.3 ± 0.24 U/ml. The egl gene sequence was deposited in GenBank with the accession number PP194445. In silico molecular docking revealed that the two hydroxyl groups of carboxymethyl cellulose bind to the residues of Glu169 inside the binding pocket of the CMCase. This interaction forms two hydrogen bonds, with an affinity score of -5.71.

CONCLUSIONS

Optimization of cultural conditions significantly enhances the yield of cellulase enzyme when compared to unoptimized culturing conditions. Additionally, heterologous expression of egl gene showed that the recombinant form of the cellulase is active and that a valid expression system can contribute to a better yield of the enzyme.

Silencing Ditylenchus destructor cathepsin L-like cysteine protease has negative pleiotropic effect on nematode ontogenesis

Ditylenchus destructor is a migratory plant-parasitic nematode that severely harms many agriculturally important crops. The control of this pest is difficult, thus efficient strategies for its management in agricultural production are urgently required. Cathepsin L-like cysteine protease (CPL) is one important protease that has been shown to participate in various physiological and pathological processes. Here we decided to characterize the CPL gene (Dd-cpl-1) from D. destructor. Analysis of Dd-cpl-1 gene showed that Dd-cpl-1 gene contains a signal peptide, an I29 inhibitor domain with ERFNIN and GNFD motifs, and a peptidase C1 domain with four conserved active residues, showing evolutionary conservation with other nematode CPLs. RT-qPCR revealed that Dd-cpl-1 gene displayed high expression in third-stage juveniles (J3s) and female adults. In situ hybridization analysis demonstrated that Dd-cpl-1 was expressed in the digestive system and reproductive organs. Silencing Dd-cpl-1 in 1-cell stage eggs of D. destructor by RNAi resulted in a severely delay in development or even in abortive morphogenesis during embryogenesis. The RNAi-mediated silencing of Dd-cpl-1 in J2s and J3s resulted in a developmental arrest phenotype in J3 stage. In addition, silencing Dd-cpl-1 gene expression in female adults led to a 57.43% decrease in egg production. Finally, Dd-cpl-1 RNAi-treated nematodes showed a significant reduction in host colonization and infection. Overall, our results indicate that Dd-CPL-1 plays multiple roles in D. destructor ontogenesis and could serve as a new potential target for controlling D. destructor.

Evolution of parasitism genes in the plant parasitic nematodes

The plant-parasitic nematodes are considered as one of the most destructive pests, from which the migratory and sedentary endoparasitic plant parasitic nematodes infect more than 4000 plant species and cause over $100 billion crop losses annually worldwide. These nematodes use multiple strategies to infect their host and to establish a successful parasitism inside the host such as cell-wall degradation enzymes, inhibition of host defense proteins, and molecular mimicry. In the present study, the main parasitism-associated gene families were identified and compared between the migratory and sedentary endoparasitic nematodes. The results showed that the migratory and sedentary endoparasitic nematodes share a core conserved parasitism mechanism established throughout the evolution of parasitism. However, genes involved in pectin degradation and hydrolase activity are rapidly evolving in the migratory endoparasitic nematodes. Additionally, cell-wall degrading enzymes such as GH45 cellulases and pectate lyase and peptidase and peptidase inhibitors were expanded in the migratory endoparasitic nematodes. The molecular mimicry mechanism was another key finding that differs between the endoparasitic and sedentary parasitic nematodes. The PL22 gene family, which is believed to play a significant role in the molecular mechanisms of nematode parasitism, has been found to be present exclusively in migratory endoparasitic nematodes. Phylogenetic analysis has suggested that it was de novo born in these nematodes. This discovery sheds new light on the molecular evolution of these parasites and has significant implications for our understanding of their biology and pathogenicity. This study contributes to our understanding of core parasitism mechanisms conserved throughout the nematodes and provides unique clues on the evolution of parasitism and the direction shaped by the host.

Pine wilt disease: what do we know from proteomics?

Pine wilt disease (PWD) is a devastating forest disease caused by the pinewood nematode (PWN), Bursaphelenchus xylophilus, a migratory endoparasite that infects several coniferous species. During the last 20 years, advances have been made for understanding the molecular bases of PWN-host trees interactions. Major advances emerged from transcriptomic and genomic studies, which revealed some unique features related to PWN pathogenicity and constituted fundamental data that allowed the development of postgenomic studies. Here we review the proteomic approaches that were applied to study PWD and integrated the current knowledge on the molecular basis of the PWN pathogenicity. Proteomics has been useful for understanding cellular activities and protein functions involved in PWN-host trees interactions, shedding light into the mechanisms associated with PWN pathogenicity and being promising tools to better clarify host trees PWN resistance/susceptibility.

Structure-based virtual screening against multiple Plasmodium falciparum kinases reveals antimalarial compounds

The continuous emergence of resistance against most frontline antimalarial drugs has led to countless deaths in malaria-endemic countries, counting 619,000 deaths in 2021, with mutation in drug targets being the sole cause. As mutation is correlated frequently with fitness cost, the likelihood of mutation emergence in multiple targets at a time is extremely low. Hence, multitargeting compounds may seem promising to address drug resistance issues with additional benefits like increased efficacy, improved safety profile, and the requirement of fewer pills compared to traditional single and combinational drugs. In this study, we attempted to use the High Throughput Virtual Screening approach to predict multitarget inhibitors against six chemically validated Plasmodium falciparum (Pf) kinases (PfPKG, PfMAP2, PfCDPK4, PfTMK, PfPK5, PfPI4K), resulting in 21 multitargeting hits. The molecular dynamic simulation of the top six complexes (Myricetin-MAP2, Quercetin-CDPK4, Myricetin-TMK, Quercetin-PKG, Salidroside-PK5, and Salidroside-PI4K) showed stable interactions. Moreover, hierarchical clustering reveals the structural divergence of the compounds from the existing antimalarials, indicating less chance of cross-resistance. Additionally, the top three hits were validated through parasite growth inhibition assays, with quercetin and myricetin exhibiting an IC50 value of 1.84 and 3.93 µM, respectively.

Exploring potential inhibitors against Kyasanur forest disease by utilizing molecular dynamics simulations and ensemble docking

Kyasanur forest disease (KFD) is a tick-borne, neglected tropical disease, caused by KFD virus (KFDV) which belongs to Flavivirus (Flaviviridae family). This emerging viral disease is a major threat to humans. Currently, vaccination is the only controlling method against the KFDV, and its effectiveness is very low. An effective control strategy is required to combat this emerging tropical disease using the existing resources. In this regard, in silico drug repurposing method offers an effective strategy to find suitable antiviral drugs against KFDV proteins. Drug repurposing is an effective strategy to identify new use for approved or investigational drugs that are outside the scope of their initial usage and the repurposed drugs have lower risk and higher safety compared to de novo developed drugs, because their toxicity and safety issues are profoundly investigated during the preclinical trials in human/other models. In the present work, we evaluated the effectiveness of the FDA approved and natural compounds against KFDV proteins using in silico molecular docking and molecular simulations. At present, no experimentally solved 3D structures for the KFD viral proteins are available in Protein Data Bank and hence their homology model was developed and used for the analysis. The present analysis successfully developed the reliable homology model of NS3 of KFDV, in terms of geometry and energy contour. Further, in silico molecular docking and molecular dynamics simulations successfully presented four FDA approved drugs and one natural compound against the NS3 homology model of KFDV. Communicated by Ramaswamy H. Sarma.

Bioengineering and computational analysis of programmed cell death ligand-1 monoclonal antibody

The trans-membrane proteins of the B7 family programmed cell death ligand-1 (PD-L1) and programmed death-1 (PD-1) play important roles in inhibiting immune responses and enhancing self-tolerance via T-cell modulation. Several therapeutic antibodies are used to promote T-cell proliferation by preventing interactions between PD-1/PD-L1. Recombinant technology appears to be quite useful in the production of such potent antibodies. In this study, we constructed recombinant molecules by cloning variable regions of the PD-L1 molecule into pMH3 vectors and transferring them into mammalian cell lines for expression. G418 supplementation was used to screen the recombinant clones, which were then maintained on serum-free medium. The full-length antibody was isolated and purified from the medium supernatant at a concentration of 0.5-0.8 mg/ml. Antibody binding affinity was investigated using ELISA and immunofluorescence methods. The protein-protein interactions (PPI) were determined using a docking approach. The SWISS model was utilized for homology modeling, while ZDOCK, Chimera, and PyMOL were used to validate 3D models. The Ramachandran plots were constructed using the SWISS model, which revealed that high-quality structures had a value of more than 90%. Current technologies allow for the accurate determination of antigen-antibody interactions.

Chemical system biology approach to identify multi-targeting FDA inhibitors for treating COVID-19 and associated health complications

In view of many European countries and the USA leading to the second wave of COVID-19 pandemic, winter season, the evolution of new mutations in the spike protein, and no registered drugs and vaccines for COVID-19 treatment, the discovery of effective and novel therapeutic agents is urgently required. The degrees and frequencies of COVID-19 clinical complications are related to uncontrolled immune responses, secondary bacterial infections, diabetes, cardiovascular disease, hypertension, and chronic pulmonary diseases. It is essential to recognize that the drug repurposing strategy so far remains the only means to manage the disease burden of COVID-19. Despite some success of using single-target drugs in treating the disease, it is beyond suspicion that the virus will acquire drug resistance by acquiring mutations in the drug target. The possible synergistic inhibition of drug efficacy due to drug-drug interaction cannot be avoided while treating COVID-19 and allied clinical complications. Hence, to avoid the unintended development drug resistance and loss of efficacy due to drug-drug interaction, multi-target drugs can be promising tools for the most challenging disease. In the present work, we have carried out molecular docking studies of compounds from the FDA approved drug library, and the FDA approved and passed phase -1 drug libraries with ten therapeutic targets of COVID-19. Results showed that known drugs, including nine anti-inflammatory compounds, four antibiotics, six antidiabetic compounds, and one cardioprotective compound, could effectively inhibit multiple therapeutic targets of COVID-19. Further in-vitro, in vivo, and clinical studies will guide these drugs' proper allocation to treat COVID-19.Communicated by Ramaswamy H. Sarma.

Structural characterization of cassava linamarase-linamarin enzyme complex: an integrated computational approach

Cassava linamarase is a hydrolyzing enzyme that belongs to a glycoside hydrolase family 1 (GH1). It is responsible for breaking down linamarin to toxic cyanide. The enzyme provides a defensive mechanism for plants against herbivores and has various applications in many fields. Understanding the structure of linamarase at the molecular level is a key to avail its reaction mechanism. In this study, the three-dimensional (3D) structure of linamarase was built for the first time using homology modelling and used to study its interaction with linamarin. Molecular docking calculations established the binding and orientation nature of linamarin, while molecular dynamics (MD) simulation established protein-ligand complexes' stability. Binding-free energy based on MM/PBSA was further used to rescore the docking results. An ensemble structure was found to be relatively stable compared to the modelled structure. This study sheds light on the exploration of linamarase towards understanding its reaction mechanisms.Communicated by Ramaswamy H. Sarma.

Beneficial effects of minocycline on the ovary of polycystic ovary syndrome mouse model: Molecular docking analysis and evaluation of TNF-α, TNFR2, TLR-4 gene expression

Polycystic ovary syndrome (PCOS) is the most common cause of ovulatory infertility. Inflammation may be involved in the pathogenesis and development of PCOS. We investigated the anti-inflammatory effect of minocycline on TNF-α, TNFR2, and TLR4 expression levels and the key features of PCOS in a mouse model. Molecular docking was performed by Molecular Operating Environment software. PCOS was induced by estradiol valerate injection (EV) (2 mg/kg/day) in 40 mice. After 28 days, the mice were divided into five groups, including control, PCOS, minocycline control, minocycline PCOS model (50 mg/kg), and letrozole PCOS (0.5 mg/kg). The Levels of FSH, LH, E2, and testosterone were determined by ELISA. H&E staining was used for histological analysis in the ovarian tissues. Docking scores were -10.35, -10.57, and -12.45 kcal/mol for TNFα, TLR-4, and TNFR2, respectively. The expression levels of TNF-α, TNFR2, and TLR4 were detected by Real-Time PCR. PCOS models exhibited acyclicity, a significant increase in E2 levels (P < 0.01), and no difference in FSH, LH, and testosterone. The expression levels of TNF-α, TNFR2, and TLR-4 significantly increased in PCOS (2.70, 7.90, and 14.83-fold, respectively). EV treatment significantly increased graafian follicles (P < 0.001) and decreased corpus luteum (CL) (P < 0.01). Minocycline treatment in PCOS led to a significant decrease in E2 (P < 0.01) and graafian follicles (P < 0.001) and a significant increase in the CL numbers (P < 0.05). Our findings showed the positive effects of minocycline on estradiol level, CL and graafian follicles counts, suggesting that minocycline might inhibit these proteins and improve ovulation in our mouse model of PCOS.

Virulence Biomarkers of Bursaphelenchus xylophilus: A Proteomic Approach

The pinewood nematode (PWN), Bursaphelenchus xylophilus, one of the most serious forest pests worldwide, is considered the causal agent of the pine wilt disease (PWD). The main host species belong to the genus Pinus, and a variation in the susceptibility of several pine species to PWN infection is well-known. It is also recognized that there is variation in the virulence among B. xylophilus isolates. In the present study, we applied a quantitative mass spectrometry-based proteomics approach to perform a deep characterization of proteomic changes across two B. xylophilus isolates with different virulence from different hosts and geographical origins. A total of 1,456 proteins were quantified and compared in the two isolates secretomes, and a total of 2,741 proteins were quantified and compared in the nematode proteomes in pine tree extract and fungus stimuli conditions. From the proteomic analyses, a group of proteins was selected and identified as potential virulence biomarkers and shed light on putative most pathogenic proteins of this plant-parasitic nematode. Proteomic data are available via ProteomeXchange with identifier PXD029377.

High throughput virtual screening reveals SARS-CoV-2 multi-target binding natural compounds to lead instant therapy for COVID-19 treatment

The present-day world is severely suffering from the recently emerged SARS-CoV-2. The lack of prescribed drugs for the deadly virus has stressed the likely need to identify novel inhibitors to alleviate and stop the pandemic. In the present high throughput virtual screening study, we used in silico techniques like receptor-ligand docking, Molecular dynamic (MD), and ADME properties to screen natural compounds. It has been documented that many natural compounds display antiviral activities, including anti–SARS-CoV effect. The present study deals with compounds of Natural Product Activity and Species Source (NPASS) database with known biological activity that probably impedes the activity of six essential enzymes of the virus. Promising drug-like compounds were identified, demonstrating better docking score and binding energy for each druggable targets. After an extensive screening analysis, three novel multi-target natural compounds were predicted to subdue the activity of three/more major drug targets simultaneously. Concerning the utility of natural compounds in the formulation of many therapies, we propose these compounds as excellent lead candidates for the development of therapeutic drugs against SARS-CoV-2.

Homology Modelling and Molecular Docking Studies of Selected Substituted Benzo[d]imidazol-1-yl)methyl)benzimidamide Scaffolds on Plasmodium falciparum Adenylosuccinate Lyase Receptor

Plasmodium falciparum adenylosuccinate lyase (PfADSL) is an important enzyme in purine metabolism. Although several benzimidazole derivatives have been commercially developed into drugs, the template design as inhibitor against PfADSL has not been fully explored. This study aims to model the 3-dimensional (3D) structure of PfADSL, design and predict in silico absorption, distribution, metabolism, excretion and toxicity (ADMET) of 8 substituted benzo[d]imidazol-1-yl)methyl)benzimidamide compounds as well as predict the potential interaction modes and binding affinities of the designed ligands with the modelled PfADSL. PfADSL 3D structure was modelled using SWISS-MODEL, whereas the compounds were designed using ChemDraw Professional. ADMET predictions were done using OSIRIS Property Explorer and Swiss ADME, whereas molecular docking was done with AutoDock Tools. All designed compounds exhibited good in silico ADMET properties, hence can be considered safe for drug development. Binding energies ranged from -6.85 to -8.75 kcal/mol. Thus, they could be further synthesised and developed into active commercial antimalarial drugs.