In silico mutation on a mutant lipase from Acinetobacter haemolyticus towards enhancing alkaline stability

Biological and molecular approaches of the degradation or decolorization potential of the hypersaline Lake Tuz Bacillus megaterium H2 isolate

The presence of synthetic dyes in water bodies and soil is one of the major issues affecting the global ecology, possibly impacting societal well-being adversely due to the colorants' recalcitrance and toxicity. Herein, the study spectrophotometrically monitored the ability of the Bacillus megaterium H2 azoreductase (AzrBmH2) to degrade four synthetic dyes, reactive blue 4, remazol brilliant red, thymol blue, and methyl red, followed by in-silico assessment using GROMACS. We found that the bacterium degraded as much as 60% of all four synthetic dyes at various tested concentrations. The genome analysis revealed five different azoreductase genes, which were then modeled into the AzrBmH21, AzrBmH22/3, and AzrBmH24/5 templates. The AzrBmH2-substrate complexes showed binding energies with all the dyes of between -10.6 to -6.9 kcal/mol and formed 4-6 hydrogen bonds with the predicted catalytic binding residues (His10, Glu 14, Ser 58, Met 99, Val 107, His 183, Asn184 and Gln 191). In contrast, the lowest binding energies were observed for the AzrBmH21-substrates (-10.6 to -7.9). Molecular dynamic simulations revealed that the AzrBmH21-substrate complexes were more stable (RMSD 0.2-0.25 nm, RMSF 0.05 - 0.3 nm) and implied strong bonding with the dyes. The Molecular Mechanics Poisson-Boltzmann Surface Area results also mirrored this outcome, showing the lowest azoreductase-dye binding energy in the order of AzrBmH21-RB4 (-78.18 ± 8.92 kcal/mol), AzrBmH21-RBR (-67.51 ± 7.74 kcal/mol), AzrBmH21-TB (-46.62 ± 5.23 kcal/mol) and AzrBmH21-MR (-40.78 ± 7.87 kcal/mol). In short, the study demonstrated the ability of the B. megaterium H2 to efficiently decolorize the above-said synthetic dyes, conveying the bacterium's promising use for large-scale dye remediation.Communicated by Ramaswamy H. Sarma.

Comparative modeling and enzymatic affinity of novel haloacid dehalogenase from Bacillus megaterium strain BHS1 isolated from alkaline Blue Lake in Turkey

This study presents the initial structural model of L-haloacid dehalogenase (DehLBHS1) from Bacillus megaterium BHS1, an alkalotolerant bacterium known for its ability to degrade halogenated environmental pollutants. The model provides insights into the structural features of DehLBHS1 and expands our understanding of the enzymatic mechanisms involved in the degradation of these hazardous pollutants. Key amino acid residues (Arg40, Phe59, Asn118, Asn176, and Trp178) in DehLBHS1 were identified to play critical roles in catalysis and molecular recognition of haloalkanoic acid, essential for efficient binding and transformation of haloalkanoic acid molecules. DehLBHS1 was modeled using I-TASSER, yielding a best TM-score of 0.986 and an RMSD of 0.53 Å. Validation of the model using PROCHECK revealed that 89.2% of the residues were located in the most favored region, providing confidence in its structural accuracy. Molecular docking simulations showed that the non-simulated DehLBHS1 preferred 2,2DCP over other substrates, forming one hydrogen bond with Arg40 and exhibiting a minimum energy of -2.5 kJ/mol. The simulated DehLBHS1 exhibited a minimum energy of -4.3 kJ/mol and formed four hydrogen bonds with Arg40, Asn176, Asp9, and Tyr11, further confirming the preference for 2,2DCP. Molecular dynamics simulations supported this preference, based on various metrics, including RMSD, RMSF, gyration, hydrogen bonding, and molecular distance. MM-PBSA calculations showed that the DehLBHS1-2,2-DCP complex had a markedly lower binding energy (-21.363 ± 1.26 kcal/mol) than the DehLBHS1-3CP complex (-14.327 ± 1.738 kcal/mol). This finding has important implications for the substrate specificity and catalytic function of DehLBHS1, particularly in the bioremediation of 2,2-DCP in contaminated alkaline environments. These results provide a detailed view of the molecular interactions between the enzyme and its substrate and may aid in the development of more efficient biocatalytic strategies for the degradation of halogenated compounds.Communicated by Ramaswamy H. Sarma.

Exploring the prognostic significance of PKCε variants in cervical cancer

BACKGROUND

Protein Kinase C-epsilon (PKCε) is a member of the novel subfamily of PKCs (nPKCs) that plays a role in cancer development. Studies have revealed that its elevated expression levels are associated with cervical cancer. Previously, we identified pathogenic variations in its different domains through various bioinformatics tools and molecular dynamic simulation. In the present study, the aim was to find the association of its variants rs1553369874 and rs1345511001 with cervical cancer and to determine the influence of these variants on the protein-protein interactions of PKCε, which can lead towards cancer development and poor survival rates.

METHODS

The association of the variants with cervical cancer and its clinicopathological features was determined through genotyping analysis. Odds ratio and relative risk along with Fisher exact test were calculated to evaluate variants significance and disease risk. Protein-protein docking was performed and docked complexes were subjected to molecular dynamics simulation to gauge the variants impact on PKCε's molecular interactions.

RESULTS

This study revealed that genetic variants rs1553369874 and rs1345511001 were associated with cervical cancer. Smad3 interacts with PKCε and this interaction promotes cervical cancer angiogenesis; therefore, Smad3 was selected for protein-protein docking. The analysis revealed PKCε variants promoted aberrant interactions with Smad3 that might lead to the activation of oncogenic pathways. The data obtained from this study suggested the prognostic significance of PRKCE gene variants rs1553369874 and rs1345511001.

CONCLUSION

Through further in vitro and in vivo validation, these variants can be used at the clinical level as novel prognostic markers and therapeutic targets against cervical cancer.

In silico analysis of marine natural product for protein arginine methyltransferase 5(PRMT5) inhibitors based on pharmacophore and molecular docking

Over the past few decades, various inhibitors of PRMT5 have been developed because of its involvement in a variety of tumor development processes. As of now, no drugs targeting PRMT5 have been approved, and multiple drugs entering clinical trials have proven to have side effects. In this study, PRMT5 was used to perform virtual screening of 52119 marine natural compounds by combining various methods. We constructed 20 pharmacophore models based on multiple ligands. The best pharmacophore model AARR_2 was selected by analyzing the statistical parameters of the pharmacophore model and the binding characteristics of the ligand active site, and then 3552 compounds were screened out. Compared with the positive compound, 46 compounds were selected based on the molecular docking fraction and docking mode analysis. Then, 3D-QSAR was used to analyze the relationship between structure and activity of the compounds. Then, in addition to marine compounds 36404, 36405 and 14436, we selected compound 46 (the positive control compound) and used the CLC-Pred online Web server to predict their cytotoxicity to human cell lines, making cell experiments possible. Finally, we conducted the prediction of ADMET in order to better promote clinical trials. After comprehensive judgment, we screened out the marine natural compounds 36404 and 36405 as candidates for PRMT5 substrate competitive inhibitors.Communicated by Ramaswamy H. Sarma.

Virtual Screening Based on Machine Learning Explores Mangrove Natural Products as KRASG12C Inhibitors

Mangrove secondary metabolites have many unique biological activities. We identified lead compounds among them that might target KRAS^G12C. KRAS is considered to be closely related to various cancers. A variety of novel small molecules that directly target KRAS are being developed, including covalent allosteric inhibitors for KRAS^G12C mutant, protein–protein interaction inhibitors that bind in the switch I/II pocket or the A59 site, and GTP-competitive inhibitors targeting the nucleotide-binding site. To identify a candidate pool of mangrove secondary metabolic natural products, we tested various machine learning algorithms and selected random forest as a model for predicting the targeting activity of compounds. Lead compounds were then subjected to virtual screening and covalent docking, integrated absorption, distribution, metabolism and excretion (ADME) testing, and structure-based pharmacophore model validation to select the most suitable compounds. Finally, we performed molecular dynamics simulations to verify the binding mode of the lead compound to KRAS^G12C. The lazypredict function package was initially used, and the Accuracy score and F1 score of the random forest algorithm exceeded 60%, which can be considered to carry a strong ability to distinguish the data. Four marine natural products were obtained through machine learning identification and covalent docking screening. Compound 44 and compound 14 were selected for further validation after ADME and toxicity studies, and pharmacophore analysis indicated that they had a favorable pharmacodynamic profile. Comparison with the positive control showed that they stabilized switch I and switch II, and like MRTX849, retained a novel binding mechanism at the molecular level. Molecular dynamics analysis showed that they maintained a stable conformation with the target protein, so compound 44 and compound 14 may be effective inhibitors of the G12C mutant. These findings reveal that the mangrove-derived secondary metabolite compound 44 and compound 14 might be potential therapeutic agents for KRAS^G12C.

Comparative molecular docking and molecular-dynamic simulation of wild-type- and mutant carboxylesterase with BTA-hydrolase for enhanced binding to plastic

According to the literature review, microbial degradation of polyethylene terephthalate by PETases has been detected effective and eco-friendly. However, the number of microorganisms capable of such feats is limited with some undesirable bioprospecting results. BTA-hydrolase has been already reported capable of degrading polyethylene terephthalate. Therefore, mutation by in silico site-directed mutagenesis means to introduce current isomer of PETase for polyethylene terephthalate degradative capability as a better approach to resolve this issue. This study aimed to use in silico site-directed mutagenesis to convert a carboxylesterase from Archaeoglobus fulgidus to BTA-hydrolase from Thermobifida fusca by replacing six amino acids in specific locations. This work was followed by molecular docking analysis with polyethylene terephthalate and polypropylene to compare their interactions. The best-docked enzyme-substrate complex was further subjected to molecular dynamics simulation to gauge the binding quality of the BTA-hydrolase, wild-type and mutant-carboxylesterase with only polyethylene terephthalate as a substrate. Results of molecular docking revealed lowest binding energy for the wild-type carboxylesterase-polypropylene complex (-7.5 kcal/mol). The root-mean-square deviation value was observed stable for BTA-hydrolase. Meanwhile, root-mean-square fluctuation was assessed with higher fluctuation for the mutated residue Lys178. Consequently, the Rg value for BTA-hydrolase-ligand complex (∼1.68 nm) was the lowest compared to the mutant and wild-type carboxylesterase. The collective data conveyed that mutations imparted a minimal change in the ability of the mutant carboxylesterase to bind to polyethylene terephthalate.

Thermodynamic stability, in-vitro permeability, and in-silico molecular modeling of the optimal Elaeis guineensis leaves extract water-in-oil nanoemulsion

Nanoemulsion is a delivery system used to enhance bioavailability of plant-based compounds across the stratum corneum. Elaeis guineensis leaves are rich source of polyphenolic antioxidants, viz. gallic acid and catechin. The optimal E. guineensis leaves extract water-in-oil nanoemulsion was stable against coalescence, but it was under significant influence of Ostwald ripening over 90 days at 25 °C. The in-vitro permeability revealed a controlled and sustained release of the total phenolic compounds (TPC) of EgLE with a cumulative amount of 1935.0 ± 45.7 µgcm-2 after 8 h. The steady-state flux and permeation coefficient values were 241.9 ± 5.7 µgcm-2 h-1 and 1.15 ± 0.03 cm.h-1, respectively. The kinetic release mechanism for TPC of EgLE was best described by the Korsmeyer-Peppas model due to the highest linearity of R2 = 0.9961, indicating super case II transport mechanism. The in-silico molecular modelling predicted that the aquaporin-3 protein in the stratum corneum bonded preferably to catechin over gallic acid through hydrogen bonds due to the lowest binding energies of - 57.514 kcal/mol and - 8.553 kcal/mol, respectively. Thus, the in-silico study further verified that catechin could improve skin hydration. Therefore, the optimal nanoemulsion could be used topically as moisturizer to enhance skin hydration based on the in-silico prediction.

Molecular docking and molecular dynamics simulation of Bacillus thuringiensis dehalogenase against haloacids, haloacetates and chlorpyrifos

The high dependency and surplus use of agrochemical products have liberated enormous quantities of toxic halogenated pollutants into the environment and threaten the well-being of humankind. Herein, this study performed molecular docking, molecular dynamic (MD) simulations, molecular mechanics-Poisson Boltzmann Surface Area (MM-PBSA) calculations on the DehH2 from Bacillus thuringiensis, to identify the order of which the enzyme degrades different substrates, haloacids, haloacetate and chlorpyrifos. The study discovered that the DehH2 favored the degradation of haloacids and haloacetates (-3.3 - 4.6 kcal/mol) and formed three hydrogen bonds with Asp125, Arg201 and Lys202. Despite the inconclusive molecular docking result, chlorpyrifos was consistently shown to be the least favored substrate of the DehH2 in MD simulations and MM-PBSA calculations. Results of MD simulations revealed the DehH2-haloacid- (RMSD 0.15 - 0.25 nm) and DehH2-haloacetates (RMSF 0.05 - 0.25 nm) were more stable, with the DehH2-L-2CP complex being the most stable while the least was the DehH2-chlorpyrifos (RMSD 0.295 nm; RMSF 0.05 - 0.59 nm). The Molecular Mechanics Poisson-Boltzmann Surface Area calculations showed the DehH2-L-2CP complex (-24.27 kcal/mol) having the lowest binding energy followed by DehH2-MCA (-22.78 kcal/mol), DehH2-D-2CP (-21.82 kcal/mol), DehH2-3CP (-21.11 kcal/mol), DehH2-2,2-DCP (-18.34 kcal/mol), DehH2-2,3-DCP (-8.34 kcal/mol), DehH2-TCA (-7.62 kcal/mol), while chlorpyrifos was unable to spontaneously bind to DehH2 (+127.16 kcal/mol). In a nutshell, the findings of this study offer valuable insights into the rational tailoring of the DehH2 for expanding its substrate specificity and catalytic activity in the near future.Communicated by Ramaswamy H. Sarma.