Discovery and characterization of dual inhibitors of human Vanin-1 and Vanin-2 enzymes through molecular docking and dynamic simulation-based approach

Mechanism of Regio- and Enantioselective Hydroxylation of Arachidonic Acid Catalyzed by Human CYP2E1: A Combined Molecular Dynamics and Quantum Mechanics/Molecular Mechanics Study

Regio- and enantioselective hydroxylation of free fatty acids by human cytochrome P450 2E1 (CYP2E1) plays an important role in metabolic regulation and has significant pathological implications. Despite extensive research, the detailed hydroxylation mechanism of CYP2E1 remains incompletely understood. To clarify the origins of regioselectivity and enantioselectivity observed for CYP2E1-mediated fatty acid hydroxylation, molecular dynamics (MD) simulations and quantum mechanics/molecular mechanics (QM/MM) calculations were performed. MD simulations provided key insights into the proximity of arachidonic acid's carbon atoms to the reactive iron(IV)-oxo moiety in compound I (Cpd I), with the ω-1 position being closest, indicating higher reactivity at this site. QM/MM calculations identified hydrogen abstraction as the rate-determining step, with the ω-1S transition state exhibiting the lowest energy barrier, consistent with experimentally observed enantioselectivity. Energy decomposition analysis revealed that variations in quantum mechanical energy (ΔEQM) significantly influence reaction barriers, with the most efficient hydrogen abstraction occurring at the ω-1S and ω-2R positions. These findings underscore the importance of substrate positioning within the active site in determining product selectivity. Comparisons with two related P450s, P450BM3 and P450SPα, further highlighted the critical role of active site architecture and substrate positioning in modulating selectivity. While surrounding residues do not directly dictate product selectivity, they shape the active site environment and influence substrate positioning. Furthermore, our analysis revealed a previously unrecognized catalytic role of Ala299. These findings provide a deeper mechanistic understanding of human CYP2E1 and offer valuable insights for its precise engineering in targeted C-H functionalization.

VNN2 regulates hepatic steroid synthesis in response to dietary changes

Peroxisome proliferator-activated receptor alpha (PPARα) plays a crucial role in regulating hepatic fat oxidation. Previous studies have identified VNN2 as a potential PPARα target gene in chicken liver. However, the specific function of VNN2 in hepatic lipid metabolism remains unclear. We utilized datasets GSM5764402, GSM5764403, GSE128340, GSE129840, and PRJEB44038 to investigate the expression pattern and potential function of VNN2 in chicken liver. Our analysis included RNA sequencing, qPCR, and triglyceride and total cholesterol assays for verification. Through analysis of single-cell RNA sequencing (scRNA-seq) data, we localized VNN2 expression at the cellular level and identified potential downstream targets of VNN2. We further examined these potential targets in VNN2 overexpressed and knockdown Leghorn male hepatoma (LMH) cells. Our findings revealed that VNN2 is highly expressed in hepatocytes with elevated lipid metabolism and steroid biosynthesis activity. This study confirms that VNN2 promotes steroid biosynthesis by upregulating MSMO1 and FDPS, providing new insights into its role in hepatic lipid metabolism.

Elucidating the bioremediation potential of laccase and peroxidase enzymes from Bacillus ligniniphilus L1 in antibiotic degradation: A computationally guided study

This study showcased the antibiotic degradation abilities of laccase and catalase-peroxidase from Bacillus ligniniphilus L1, an extremophile, against 18 common antibiotics using computationally guided approach. Molecular docking and simulation identified six enzyme-antibiotic complexes for laccase and four for catalase-peroxidase, demonstrating significant binding affinity and stability. Enzyme activity assays corroborated computational results, indicating both enzymes could degrade all tested antibiotics with varying efficiencies. L1 laccase outperformed commercial laccase against five antibiotics, notably vancomycin, levofloxacin, tobramycin, linezolid, and rifamycin, with enhanced degradation potential upon ABTS addition. Catalase-peroxidase from L1 exhibited superior degradation efficiency over commercial peroxidase against vancomycin, linezolid, tobramycin, and clindamycin. Overall, this study underscores the computational approach's utility in understanding enzyme-mediated antibiotic degradation, offering insights into environmental contaminant remediation.

Evaluating the estrogen degradation potential of laccase and peroxidase from Bacillus ligniniphilus L1 through integrated computational and experimental approaches

This study investigated the degradation potential of laccase and catalase-peroxidase from the extremophilic marine bacterium Bacillus ligniniphilus L1 against endogenous and synthetic estrogen compounds using an integrated computational and experimental approach. Molecular docking identified five estrogen compounds exhibiting reliable bindings with enzymes, which were then subjected to enzyme activity assays. The degradation potential of the two enzymes against five selected estrogen compounds were investigated and compared with their commercial counterparts. Laccase from L1 showed higher degradation potential against estrone (47.02 % without and 62.21 % with ABTS) compared to commercial laccase (39 % without and 54.20 % with ABTS). For estradiol valerate, commercial laccase showed a slightly higher degradation (52.47 %) than L1 laccase (49.94 %), but with ABTS, L1 laccase performed better (74.15 % vs. 68.03 %). Notably, L1 catalase-peroxidase demonstrated significantly higher degradation for all tested compounds compared to its commercial counterpart with efficiencies of 96.16 %, 89.09 %, 74.94 %, 64.91 %, and 62.80 % against estropipate, quinestrol, estradiol valerate, estriol and estrone, respectively, revealing its potential for commercial applications. Molecular dynamics simulations revealed the interaction and stability of enzyme-estrogen complexes, with MMGBSA binding energy calculations supporting experimental results. These findings highlight the usefulness of the computational approach in elucidating the molecular mechanisms underlying enzyme-mediated bioremediation of environmental contaminants.

Discovery of putative inhibitors of human Pkd1 enzyme: Molecular docking, dynamics and simulation, QSAR, and MM/GBSA

Polycystic kidney disease is the most prevalent hereditary kidney disease globally and is mainly linked to the overexpression of a gene called PKD1. To date, there is no effective treatment available for polycystic kidney disease, and the practicing treatments only provide symptomatic relief. Discovery of the compounds targeting the PKD1 gene by inhibiting its expression under the disease condition could be crucial for effective drug development. In this study, a molecular docking and molecular dynamic simulation, QSAR, and MM/GBSA-based approaches were used to determine the putative inhibitors of the Pkd1 enzyme from a library of 1379 compounds. Initially, fourteen compounds were selected based on their binding affinities with the Pkd1 enzyme using MOE and AutoDock tools. The selected drugs were further investigated to explore their properties as drug candidates and the stability of their complex formation with the Pkd1 enzyme. Based on the physicochemical and ADMET (Absorption, Distribution, Metabolism, Excretion, and Toxicity) properties, and toxicity profiling, two compounds including olsalazine and diosmetin were selected for the downstream analysis as they demonstrated the best drug-likeness properties and highest binding affinity with Pkd1 in the docking experiment. Molecular dynamic simulation using Gromacs further confirmed the stability of olsalazine and diosmetin complexes with Pkd1 and establishing interaction through strong bonding with specific residues of protein. High biological activity and binding free energies of two complexes calculated using 3D QSAR and Schrodinger module, respectively further validated our results. Therefore, the molecular docking and dynamics simulation-based in-silico approach used in this study revealed olsalazine and diosmetin as potential drug candidates to combat polycystic kidney disease by targeting Pkd1 enzyme.

Exploring of multi-functional umami peptides from Stropharia rugosoannulata: Saltiness-enhancing effect and mechanism, antioxidant activity and potential target sites

Umami peptides enhance flavor and offer potential health benefits. We analyzed the taste-value profiles of five novel umami peptides from Stropharia rugosoannulata using E-tongue, exhibiting significant saltiness characteristics. While the peptides PHEMQ and SEPSHF exhibited higher saltiness, their mixture with salt did not enhance saltiness compared to individual peptides. Surprisingly, SGCVNEL, which was initially weak in saltiness, showed remarkably enhanced saltiness when mixed with salt, possibly due to have strong binding with receptors. Molecular docking elucidated the salt-forming mechanism of TMC4, highlighting the P2-domain and hydrogen bonds' role in the composite structure stability. Evaluation of the antioxidant activity evaluation demonstrated dose-dependent effects primarily through free radical scavenging via the single-electron transfer potential mechanism for SGCVNEL, EPLCNQ, and ESCAPQL. Docking experiments with antioxidant targets revealed varied binding stabilities, indicating diverse antioxidant effects of the peptides. These findings provide valuable insights into the exploration and application of versatile bioactive flavor peptides.

Rational Design of Dual Inhibitors for Alzheimer's Disease: Insights from Computational Screening of BACE1 and GSK-3β

BACKGROUND

Alzheimer's disease (AD) is one of the most concerned neurodegenerative disorders across the world characterized by amyloid-beta (Aβ) plaques and neurofibrillary tangles (NFTs), leading to cognitive decline and memory loss. Targeting key pathways involved in AD like Aβ and NFT pathways, are crucial for the development of effective therapeutic strategies. In this study, we aimed to identify and establish promising dual inhibitors targeting BACE1 and GSK-3β, two proteins implicated in Aβ and NFT formation respectively.

METHODS

We have used molecular docking, ADME property analysis, and MMGBSA calculations for the identification of hit molecules and further evaluation of binding affinity, drug-like properties, and stability against BACE1 and GSK-3β.

RESULTS

Our results demonstrated strong binding affinities of ZINC000034853956 towards the active sites of both proteins, with favorable interactions involving key residues crucial for inhibitory activity. Additionally, ZINC000034853956 exhibited favorable drug-like properties. MD simulations revealed the stable binding of ZINC000034853956 to both BACE1 and GSK-3β over a 50 ns period, with consistent ligand-protein interactions, such as hydrogen bonding and hydrophobic contacts. These findings highlight the potential of ZINC000034853956 as a promising candidate for AD treatment, acting as a dual inhibitor targeting both BACE1 and GSK-3β. Overall, our study provides valuable insights into the potential of ZINC000034853956 as a dual inhibitor for AD. The strong binding affinity, favorable drug-like properties, and stability observed in MD simulations support its suitability for further optimization and preclinical studies.

CONCLUSION

Further investigations are warranted to elucidate the precise molecular mechanisms and therapeutic benefits of ZINC000034853956. Our findings offer hope for the development of novel therapeutic interventions targeting crucial pathways involved in AD neurodegeneration.

Upregulated Vanins and their potential contribution to periodontitis

BACKGROUND

Although Vanins are closely related to neutrophil regulation and response to oxidative stress, and play essential roles in inflammatory diseases with clinical significance, their contribution to periodontitis remains to be determined. This research was designed to assess the expression of Vanins in human gingiva, and to define the relationship between Vanins and periodontitis.

METHODS

Forty-eight patients with periodontitis and forty-two periodontal healthy individuals were enrolled for gingival tissue sample collection. Expression levels of VNN1, VNN2 and VNN3 were evaluated by RT-qPCR and validated in datasets GSE10334 and GSE16134. Western blot and immunohistochemistry identified specific proteins within gingiva. The histopathological changes in gingival sections were investigated using HE staining. Correlations between Vanins and clinical parameters, PD and CAL; between Vanins and inflammation, IL1B; and between Vanins and MPO in periodontitis were investigated by Spearman's correlation analysis respectively. Associations between VNN2 and indicators of neutrophil adherence and migration were further validated in two datasets.

RESULTS

Vanins were at higher concentrations in diseased gingival tissues in both RT-qPCR and dataset analysis (p < 0.01). Assessment using western blot and immunohistochemistry presented significant upregulations of VNN1 and VNN2 in periodontitis (p < 0.05). The higher expression levels of Vanins, the larger the observed periodontal parameters PD and CAL (p < 0.05), and IL1B (p < 0.001). Moreover, positive correlations existed between VNN2 and MPO, and between VNN2 and neutrophil-related indicators.

CONCLUSION

Our study demonstrated upregulation of Vanins in periodontitis and the potential contribution of VNN2 to periodontitis through neutrophils-related pathological processes.

Application of Mathematical Modeling and Computational Tools in the Modern Drug Design and Development Process

The conventional drug discovery approach is an expensive and time-consuming process, but its limitations have been overcome with the help of mathematical modeling and computational drug design approaches. Previously, finding a small molecular candidate as a drug against a disease was very costly and required a long time to screen a compound against a specific target. The development of novel targets and small molecular candidates against different diseases including emerging and reemerging diseases remains a major concern and necessitates the development of novel therapeutic targets as well as drug candidates as early as possible. In this regard, computational and mathematical modeling approaches for drug development are advantageous due to their fastest predictive ability and cost-effectiveness features. Computer-aided drug design (CADD) techniques utilize different computer programs as well as mathematics formulas to comprehend the interaction of a target and drugs. Traditional methods to determine small-molecule candidates as a drug have several limitations, but CADD utilizes novel methods that require little time and accurately predict a compound against a specific disease with minimal cost. Therefore, this review aims to provide a brief insight into the mathematical modeling and computational approaches for identifying a novel target and small molecular candidates for curing a specific disease. The comprehensive review mainly focuses on biological target prediction, structure-based and ligand-based drug design methods, molecular docking, virtual screening, pharmacophore modeling, quantitative structure-activity relationship (QSAR) models, molecular dynamics simulation, and MM-GBSA/MM-PBSA approaches along with valuable database resources and tools for identifying novel targets and therapeutics against a disease. This review will help researchers in a way that may open the road for the development of effective drugs and preventative measures against a disease in the future as early as possible.