Pharmacoinformatics-based identification of anti-bacterial catalase-peroxidase enzyme inhibitors

AI-Driven Multiscale Study on the Mechanism of Polygonati Rhizoma in Regulating Immune Function in STAD

Polygonati Rhizoma, a traditional Chinese medicine, has demonstrated immunomodulatory and anticancer properties, yet its precise mechanisms in stomach adenocarcinoma (STAD) remain underexplored. This study aims to uncover the multitarget mechanisms of Polygonati Rhizoma in regulating the tumor immune microenvironment in STAD using artificial intelligence (AI)-driven network pharmacology, bioinformatics, and single-cell RNA sequencing, offering new insights into its immunotherapeutic potential. This study harnessed the power of AI to unravel the molecular mechanisms underlying Polygonati Rhizoma's effects. AI-driven methodologies screened 38 putative constituents, retaining 8 based on ADME criteria. Machine Learning algorithms predicted potential targets, which were cross-referenced with 5,569 immune-related genes from GeneCards, revealing 52 immune-associated targets. Differential expression analysis of the STAD data set identified 18 overlapping DEGs with prognostic significance and immune cell infiltration correlations. Key targets (AKT1, TP53, PTGS2 and VEGFA) emerged as central nodes in the network, with AI-assisted molecular docking confirming strong binding affinities, particularly between diosgenin and these core proteins. Molecular dynamics simulations further validated these interactions. Single-cell RNA sequencing revealed distinct target-gene expression patterns across malignant, stromal, and immune cell subsets in digestive-system tumors. In vitro, Polygonati Rhizoma extract significantly inhibited HGC-27 cell viability and increased intracellular ROS levels. These findings underscore the critical role of AI in integrating multiscale analyses, unveiling a multitarget immunomodulatory and antitumor mechanism for Polygonati Rhizoma in STAD, and providing a foundation for future preclinical and clinical studies.

Unveiling the hydrolase Oph2876 mediated chlorpyrifos degradation mechanism in Pseudomonas nitroreducens and its potential for environmental bioremediation

Chlorpyrifos contamination is a currently on-going issue with significant environmental impacts. As such, rapid and effective techniques that remove chlorpyrifos from the environment are urgently required. Here, a strain of Pseudomonas nitroreducens W-7 exhibited exceptional degradation ability towards both chlorpyrifos and its major metabolite 3,5,6-trichloro-2-pyridinol (TCP). W-7 can effectively reduce the toxicity of chlorpyrifos and TCP towards a variety of sensitive organisms through its superior degradation capacity. W-7 demonstrated efficient soil bioremediation by removing over 50 % of chlorpyrifos (25 mg/kg) from both sterile and non-sterile soils within 5 days, with significantly reduced half-lives. Additionally, 16S rDNA high-throughput sequencing of the soil revealed that the introduction of W-7 had no significant impact on the soil microbial community. A pivotal hydrolase Oph2876 containing conserved motif (HxHxDH) and a bimetallic catalytic center was identified from W-7. Oph2876 was a heat- and alkali-resistant enzyme with low sequence similarity (< 44 %) with other reported organophosphorus hydrolases, with a better substrate affinity for hydrolysis of chlorpyrifos to TCP. The molecular docking and site-directed mutagenesis studies indicated that the amino acid residues Asp235, His214, and His282, which were associated with the conserved sequence "HxHxDH", were crucial for the activity of Oph2876. These findings contribute to a better understanding of the biodegradation mechanism of chlorpyrifos and present useful agents for the development of effective chlorpyrifos bioremediation strategies.

Systematic investigation of the multi-scale mechanisms of herbal medicine on treating ventricular remodeling: Theoretical and experimental studies

BACKGROUND

To explore the underlying molecule mechanism of herbal medicine in preventing ventricular remodeling (VR), we take a herbal formula that is clinically effective for preventing VR as an example, which composed of Pachyma hoelen Rumph, Atractylodes macrocephala Koidz., Cassia Twig and Licorice. Due to multi-components and multi-targets in herbal medicine, it is extremely difficult to systematically explain its mechanisms of action.

METHODS

An innovative systematic investigation framework which combines with pharmacokinetic screening, target fishing, network pharmacology, DeepDDI algorithm, computational chemistry, molecular thermodynamics, in vivo and in vitro experiments was performed for deciphering the underlying molecular mechanisms of herbal medicine for treating VR.

RESULTS

ADME screening and SysDT algorithm determined 75 potentially active compounds and 109 corresponding targets. Then, systematic analysis of networks reveals the crucial active ingredients and key targets in herbal medicine. Additionally, transcriptomic analysis identifies 33 key regulators during VR progression. Moreover, PPI network and biological function enrichment present four crucial signaling pathways, i.e. NF-κB and TNF, PI3K-AKT and C-type lectin receptor signaling pathways involved in VR. Besides, both molecular experiments at animal and cell levels reveal the beneficial effect of herbal medicine on preventing VR. Finally, MD simulations and binding free energy validate the reliability of drug-target interactions.

CONCLUSION

Our novelty is to build a systematic strategy which combines various theoretical methods combined with experimental approaches. This strategy provides a deep understanding for the study of molecular mechanisms of herbal medicine on treating diseases from systematic level, and offers a new idea for modern medicine to explore drug interventions for complex diseases as well.

Systematic investigation of the mechanism of herbal medicines for the treatment of prostate cancer

Due to various unpleasant side effects and general ineffectiveness of current treatments for prostate cancer (PCa), more and more people with PCa try to look for complementary and alternative medicine such as herbal medicine. However, since herbal medicine has multi-components, multi-targets and multi-pathways features, its underlying molecular mechanism of action is not yet known and still needs to be systematically explored. Presently, a comprehensive approach consisting of bibliometric analysis, pharmacokinetic assessment, target prediction and network construction is firstly performed to obtain PCa-related herbal medicines and their corresponding candidate compounds and potential targets. Subsequently, a total of 20 overlapping genes between DEGs in PCa patients and the target genes of the PCa-related herbs, as well as five hub genes, i.e., CCNA2, CDK2, CTH, DPP4 and SRC were determined employing bioinformatics analysis. Further, the roles of these hub genes in PCa were also investigated through survival analysis and tumour immunity analysis. Moreover, to validate the reliability of the C-T interactions and to further explore the binding modes between ingredients and their targets, the molecular dynamics (MD) simulations were carried out. Finally, based on the modularization of the biological network, four signaling pathways, i.e., PI3K-Akt, MAPK, p53 and cell cycle were integrated to further analyze the therapeutic mechanism of PCa-related herbal medicine. All the results show the mechanism of action of herbal medicines on treating PCa from the molecular to systematic levels, providing a reference for the treatment of complex diseases using TCM.

Streptococcus agalactiae npx Is Required for Survival in Human Placental Macrophages and Full Virulence in a Model of Ascending Vaginal Infection during Pregnancy

Streptococcus agalactiae, also known as group B Streptococcus (GBS), is a Gram-positive encapsulated bacterium that colonizes the gastrointestinal tract of 30 to 50% of humans. GBS causes invasive infection during pregnancy that can lead to chorioamnionitis, funisitis, preterm prelabor rupture of membranes (PPROM), preterm birth, neonatal sepsis, and maternal and fetal demise. Upon infecting the host, GBS encounters sentinel innate immune cells, such as macrophages, within reproductive tissues. Once phagocytosed by macrophages, GBS upregulates the expression of the gene npx, which encodes an NADH peroxidase. GBS mutants with an npx deletion (Δnpx) are exquisitely sensitive to reactive oxygen stress. Furthermore, we have shown that npx is required for GBS survival in both THP-1 and placental macrophages. In an in vivo murine model of ascending GBS vaginal infection during pregnancy, npx is required for invading reproductive tissues and is critical for inducing disease progression, including PPROM and preterm birth. Reproductive tissue cytokine production was also significantly diminished in Δnpx mutant-infected animals compared to that in animals infected with wild-type (WT) GBS. Complementation in trans reversed this phenotype, indicating that npx is critical for GBS survival and the initiation of proinflammatory signaling in the gravid host. IMPORTANCE This study sheds new light on the way that group B Streptococcus (GBS) defends itself against oxidative stress in the infected host. The enzyme encoded by the GBS gene npx is an NADH peroxidase that, our study reveals, provides defense against macrophage-derived reactive oxygen stress and facilitates infections of the uterus during pregnancy. This enzyme could represent a tractable target for future treatment strategies against invasive GBS infections.

Structure-based identification of galectin-1 selective modulators in dietary food polyphenols: a pharmacoinformatics approach

Abstract

In this study, a set of dietary polyphenols was comprehensively studied for the selective identification of the potential inhibitors/modulators for galectin-1. Galectin-1 is a potent prognostic indicator of tumor progression and a highly regarded therapeutic target for various pathological conditions. This indicator is composed of a highly conserved carbohydrate recognition domain (CRD) that accounts for the binding affinity of β-galactosides. Although some small molecules have been identified as galectin-1 inhibitors/modulators, there are limited studies on the identification of novel compounds against this attractive therapeutic target. The extensive computational techniques include potential drug binding site recognition on galectin-1, binding affinity predictions of ~ 500 polyphenols, molecular docking, and dynamic simulations of galectin-1 with selective dietary polyphenol modulators, followed by the estimation of binding free energy for the identification of dietary polyphenol-based galectin-1 modulators. Initially, a deep neural network-based algorithm was utilized for the prediction of the druggable binding site and binding affinity. Thereafter, the intermolecular interactions of the polyphenol compounds with galectin-1 were critically explored through the extra-precision docking technique. Further, the stability of the interaction was evaluated through the conventional atomistic 100 ns dynamic simulation study. The docking analyses indicated the high interaction affinity of different amino acids at the CRD region of galectin-1 with the proposed five polyphenols. Strong and consistent interaction stability was suggested from the simulation trajectories of the selected dietary polyphenol under the dynamic conditions. Also, the conserved residue (His44, Asn46, Arg48, Val59, Asn61, Trp68, Glu71, and Arg73) associations suggest high affinity and selectivity of polyphenols toward galectin-1 protein.

Graphic Abstract

Systematic analyses on the potential immune and anti-inflammatory mechanisms of Shufeng Jiedu Capsule against Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2)-caused pneumonia

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A systematic study integrated is proposed to illustrate the potential immune and anti-inflammatory mechanisms of SFJDC against SARS-CoV-2.

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SFJDC regulates related targets, showing the potential anti-novel coronavirus effect.

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The work can provide a better understanding of the therapeutic mechanism of SFJDC for treating SARS-CoV-2.

The outbreak of Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2)-caused pneumonia (Coronavirus disease −19, COVID-19), has resulted in a global health emergency. However, there is no vaccine or effective antiviral treatment against the newly emerged coronavirus and identifying the available therapeutics as soon as possible is critical for the response to the spread of SARS-CoV-2. Shufeng Jiedu Capsule (SFJDC), a well-known prescription of Traditional Chinese Medicine (TCM) in China, has been widely used in treating upper respiratory tract infections and acute lung injury, owing to its immunomodulatory and anti-inflammatory effects. Despite the definite evidence of effective use of SFJDC in the diagnosis and treatment of pneumonia caused by SARS-CoV-2, the underlying action mechanism remains unknown. Currently, a systematic study integrated with absorption, distribution, metabolism and excretion (ADME) evaluation, target prediction, network construction and functional bioinformatics analyses is proposed to illustrate the potential immune and anti-inflammatory mechanisms of SFJDC against SARS-CoV-2. Additionally, to further validate the reliability of the interactions and binding affinities between drugs and targets, docking, Molecular dynamics Simulations (MD) simulations and Molecular Mechanics/Poisson-Boltzmann Surface Area approach (MM-PBSA) calculations were carried out. The results demonstrate that SFJDC regulates the immunomodulatory and anti-inflammatory related targets on multiple pathways through its active ingredients, showing the potential anti-novel coronavirus effect. Overall, the work can provide a better understanding of the therapeutic mechanism of SFJDC for treating SARS-CoV-2 pneumonia from multi-scale perspectives, and may also offer a valuable clue for developing novel pharmaceutical strategies to control the current coronavirus.

Identification of potential anti-TMPRSS2 natural products through homology modelling, virtual screening and molecular dynamics simulation studies

Recent outbreak of severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) has led to a pandemic of COVID-19. The absence of a therapeutic drug and vaccine is causing severe loss of life and economy worldwide. SARS-CoV and SARS-CoV-2 employ the host cellular serine protease TMPRSS2 for spike (S) protein priming for viral entry into host cells. A potential way to reduce the initial site of SARS-CoV-2 infection may be to inhibit the activity of TMPRSS2. In the current study, the three-dimensional structure of TMPRSS2 was generated by homology modelling and subsequently validated with a number of parameters. The structure-based virtual screening of Selleckchem database was performed through 'Virtual Work Flow' (VSW) to find out potential lead-like TMPRSS2 inhibitors. Camostat and bromhexine are known TMPRSS2 inhibitor drugs, hence these were used as control molecules throughout the study. Based on better dock score, binding-free energy and binding interactions compared to the control molecules, six molecules (Neohesperidin, Myricitrin, Quercitrin, Naringin, Icariin, and Ambroxol) were found to be promising against the TMPRSS2. Binding interactions analysis revealed a number of significant binding interactions with binding site amino residues of TMPRSS2. The all-atoms molecular dynamics (MD) simulation study indicated that all proposed molecules retain inside the receptor in dynamic states. The binding energy calculated from the MD simulation trajectories also favour the strong affinity of the molecules towards the TMPRSS2. Proposed molecules belong to the bioflavonoid class of phytochemicals and are reported to possess antiviral activity, our study indicates their possible potential for application in COVID-19.

Designing novel inhibitors against cyclopropane mycolic acid synthase 3 (PcaA): targeting dormant state of Mycobacterium tuberculosis

Mycobacterium tuberculosis can sustain inside the host in dormant (non-replicating) state for years. It suppresses the host immune system by residing in the host alveolar macrophage, resulting in the development of latent tuberculosis. Despite many antibiotics available for the treatment of tuberculosis, the major hurdle in complete elimination is the ability of the bacilli to undergo dormancy and develop resistance against the existing drugs. Cyclopropanation of mycolic acids present in the cell wall of mycobacteria is required for its persistence and virulence. Cyclopropane synthases such as PcaA, CmaA1 and CmaA2, introduce site-specific modifications in mycolic acids. PcaA expression levels are high during dormancy and the gene mutants fails to persist, showing reduced survival in host macrophage. Hence, PcaA appears as a potential target to develop inhibitors against the dormant bacilli. In this study, we have identified compounds with maximum binding affinity against PcaA by in-silico virtual screening of anti-tuberculosis compounds and their structural analogues. In-silico docking followed molecular dynamic simulations and free energy calculations of the compounds with highest docking score in their respective libraries. This study reports novel inhibitors that can act as better anti-tuberculosis compounds targeting PcaA.Communicated by Ramaswamy H. Sarma.

Structure-Based Screening of DNA GyraseB Inhibitors for Therapeutic Applications in Tuberculosis: a Pharmacoinformatics Study

Tuberculosis (TB) is an infectious disease caused by Mycobacterium tuberculosis (MTB) and considered as serious public health concern worldwide which kills approximately five thousand people every day. Therefore, TB drug development efforts are in gigantic need for identification of new potential chemical agents to eradicate TB from the society. The bacterial DNA gyrase B (GyrB) protein as an experimentally widely accepted effective drug target for the development of TB chemotherapeutics. In the present study, advanced pharmacoinformatics approaches were used to screen the Mcule database against the GyrB protein. Based on a number of chemometric parameters, five molecules were found to be crucial to inhibit the GyrB. A number of molecular binding interactions between the proposed inhibitors and important active site residues of GyrB were observed. The predicted drug-likeness properties of all molecules were indicated that compounds possess characteristics to be the drug-like candidates. The dynamic nature of each molecule was explored through the molecular dynamics (MD) simulation study. Various analyzing parameters from MD simulation trajectory have suggested rationality of the molecules to be potential GyrB inhibitor. Moreover, the binding free energy was calculated from the entire MD simulation trajectories highlighted greater binding free energy values for all newly identified compounds also substantiated the strong binding affection towards the GyrB in comparison to the novobiocin. Therefore, the proposed molecules might be considered as potential anti-TB chemical agents for future drug discovery purposes subjected to experimental validation. Graphical Abstract.

Pharmacophore model and atom-based 3D quantitative structure activity relationship (QSAR) of human immunodeficiency virus-1 (HIV-1) capsid assembly inhibitors

A potential anti-Human Immunodeficiency Virus (HIV) agent with novel mode of action is urgently needed to fight against drug resistance HIV. The HIV capsid protein is important for both late and early stages of the viral replication cycle and emerged as a promising target for the developing of small molecule inhibitors of HIV. We design a Pharmacophore and 3D Quantitative structure activity relationship (QSAR) model for HIV Capsid Protein inhibitors, which helps to identify overall aspects of molecular structure that govern activity and for the prediction of novel HIV Capsid inhibitors. The hypothesis was developed with a survival score of 3.6.The features, that is, two aromatic rings, one hydrophobic site and two acceptor regions were present in all the active compounds with good fitness score. Pharmacophore model was then validated by a partial least square and regression-based PHASE 3D QSAR cross-validation. The leave-n-out cross validation for test set (Q²) of the hypothesis is 0.636, the standard deviation (SD) value is 0.338, and the variance ratio (F-test) value is 74.5. Hypothesis also showed a leave-n-out cross validation for training set (R², 0.928). Interestingly, the predicted activity of true test set compounds was found in the close vicinity of their experimental activity suggesting the methodology used and models generated can be applied to identify potential new chemical entities with better HIV-1 capsid assembly inhibition.Communicated by Ramaswamy H. Sarma.