Computational approach for drug discovery against Gardnerella vaginalis in quest for safer and effective treatments for bacterial vaginosis.

Bacterial vaginosis (BV), primarily attributed to Gardnerella vaginalis, poses significant challenges due to antibiotic resistance and suboptimal treatment outcomes. This study presents an integrated approach to identify potential drug targets and screen compounds against this bacterium by leveraging a computational methodology. Subtractive proteomics of the reference strain ASM286196v1/UMB0386 (assembly accession: GCA_002861965.1) facilitated the prioritization of proteins with essential bacterial functions and pathways as potential drug targets. We selected 3-deoxy-7-phosphoheptulonate synthase (aroG gene product; also known as DAHP synthase) for downstream analysis. Molecular docking was employed in PyRx (AutoDock Vina) to predict binding affinities between aroG inhibitors from the ZINC database and 3-deoxy-7-phosphoheptulonate synthase. Molecular dynamics simulations of 100 ns, using GROMACS, validated the stability of drug-target interactions. Additionally, ADMET profiling aided in the selection of compounds with favorable pharmacokinetic properties and safety profile for human hosts. PBPK profiling showed that ZINC98088375 had the highest bioavailability and efficient systemic circulation. Conversely, ZINC5113880 demonstrated the lowest absorption rate (39.661%). Moreover, cirrhosis, steatosis, and renal impairment appeared to influence blood concentration of the drug, impacting bioavailability. The integrative -omics approach utilized in this study underscores the potential of computer-aided drug design and offers a rational strategy for targeted inhibitor discovery against G. vaginalis. The strategy is an attempt to address the limitations of current BV treatments, including antibiotic resistance, and pave way for the development of safer and more effective therapeutics.

Navigating the complexities of docking tools with nicotinic receptors and acetylcholine binding proteins in the realm of neonicotinoids.

Molecular docking, pivotal in predicting small-molecule ligand binding modes, struggles with accurately identifying binding conformations and affinities. This is particularly true for neonicotinoids, insecticides whose impacts on ecosystems require precise molecular interaction modeling. This study scrutinizes the effectiveness of prominent docking software (Ledock, ADFR, Autodock Vina, CDOCKER) in simulating interactions of environmental chemicals, especially neonicotinoid-like molecules with nicotinic acetylcholine receptors (nAChRs) and acetylcholine binding proteins (AChBPs). We aimed to assess the accuracy and reliability of these tools in reproducing crystallographic data, focusing on semi-flexible and flexible docking approaches. Our analysis identified Ledock as the most accurate in semi-flexible docking, while Autodock Vina with Vinardo scoring function proved most reliable. However, no software consistently excelled in both accuracy and reliability. Additionally, our evaluation revealed that none of the tools could establish a clear correlation between docking scores and experimental dissociation constants (Kd) for neonicotinoid-like compounds. In contrast, a strong correlation was found with drug-like compounds, bringing to light a bias in considered software towards pharmaceuticals, thus limiting their applicability to environmental chemicals. The comparison between semi-flexible and flexible docking revealed that the increased computational complexity of the latter did not result in enhanced accuracy. In fact, the higher computational cost of flexible docking with its lack of enhanced predictive accuracy, rendered this approach useless for this class of compounds. Conclusively, our findings emphasize the need for continued development of docking methodologies, particularly for environmental chemicals. This study not only illuminates current software capabilities but also underscores the urgency for advancements in computational molecular docking as it is a relevant tool to environmental sciences.

MzDOCK: A free ready-to-use GUI-based pipeline for molecular docking simulations.

Molecular docking is by far the most preferred approach in structure-based drug design for its effectiveness to predict the scoring and posing of a given bioactive small molecule into the binding site of its pharmacological target. Herein, we present MzDOCK, a new GUI-based pipeline for Windows operating system, designed with the intent of making molecular docking easier to use and higher reproducible even for inexperienced people. By harmonic integration of python and batch scripts, which employs various open source packages such as Smina (docking engine), OpenBabel (file conversion) and PLIP (analysis), MzDOCK includes many practical options such as: binding site configuration based on co-crystallized ligands; generation of enantiomers from SMILES input; application of different force fields (MMFF94, MMFF94s, UFF, GAFF, Ghemical) for energy minimization; retention of selectable ions and cofactors; sidechain flexibility of selectable binding site residues; multiple input file format (SMILES, PDB, SDF, Mol2, Mol); generation of reports and of pictures for interactive visualization. Users can download for free MzDOCK at the following link: https://github.com/Muzatheking12/MzDOCK.

A Novel Tetramethylpyrazine Chalcone Hybrid- HCTMPPK, as a Potential Anti-Lung Cancer Agent by Downregulating MELK.

Purpose: Lung adenocarcinoma currently ranks the leading causes of cancer-related mortality worldwide. Many anti-inflammation herbs, like tetramethylpyrazine, have shown their anti-tumor potentials. Here, we evaluated the role of a novel chalcone derivative of tetramethylpyrazine ((E) -1- (E) -1- (2-hydroxy-5-chlorophenyl) -3- (3,5,6-trimethylpyrazin-2-yl) -2-propen-1, HCTMPPK) in lung adenocarcinoma. Methods: The effects of HCTMPPK on cell proliferation, apoptosis, and invasion were investigated by in-vitro assays, including CCK-8, colony formation assay, flow cytometry, transwell assay, and wound-healing assay. The therapeutic potential of HCTMPPK in vivo was evaluated in xenograft mice. To figure out the target molecules of HCTMPPK, a network pharmacology approach and molecular docking studies were employed, and subsequent experiments were conducted to confirm these candidate molecules. Results: HCTMPPK effectively suppressed the proliferative activity and migration, as well as enhanced the apoptosis of A549 cells in a concentration-dependent manner. Consistent with this, tumor growth was inhibited by HCTMPPK significantly in vivo. Regarding the mechanisms, HCTMPPK down-regulated Bcl-2 and MMP-9 and up-regulating Bax and cleaved-caspase-3. Subsequently, we identified 601 overlapping DEGs from LUAD patients in TCGA and GEO database. Then, 15 hub genes were identified by PPI network and CytoHubba. Finally, MELK was verified to be the HCTMPPK targeted site, through the molecular docking studies and validation experiments. Conclusion: Overall, our study indicates HCTMPPK as a potential MELK inhibitor and may be a promising candidate for the therapy of lung cancer.

Enhancing plant-based cheese formulation through molecular docking and dynamic simulation of tocopherol and retinol complexes with zein, soy and almond proteins via SVM-machine learning integration.

The current study addresses the growing demand for sustainable plant-based cheese alternatives by employing molecular docking and deep learning algorithms to optimize protein-ligand interactions. Focusing on key proteins (zein, soy, and almond protein) along with tocopherol and retinol, the goal was to improve texture, nutritional value, and flavor characteristics via dynamic simulations. The findings demonstrated that the docking analysis presented high accuracy in predicting conformational changes. Flexible docking algorithms provided insights into dynamic interactions, while analysis of energetics revealed variations in binding strengths. Tocopherol exhibited stronger affinity (-5.8Kcal/mol) to zein compared to retinol (-4.1Kcal/mol). Molecular dynamics simulations offered comprehensive insights into stability and behavior over time. The integration of machine learning algorithms improved the classification and the prediction accuracy, achieving a rate of 71.59%. This study underscores the significance of molecular understanding in driving innovation in the plant-based cheese industry, facilitating the development of sustainable alternatives to traditional dairy products.

Comprehensive structural and functional analysis of hVEGFR1: Insights into phosphorylation, molecular interactions, and potential inhibitors through docking and dynamics simulations.

Vascular Endothelial Growth Factor Receptor 1 (VEGFR1), is an enzyme with tyrosine kinase activity that plays a pivotal role in angiogenesis, the process of new blood vessel formation. This receptor is of significant clinical importance as it is implicated in various cancers, particularly non-small cell lung cancer (NSCLC), where its dysregulation leads to uncontrolled cell growth through ligand-induced phosphorylation. While commercially available drugs target VEGFR1, their prolonged use often leads to drug resistance and the emergence of mutations in cancer patients. To address these challenges, researchers have identified the human tyrosine kinase (hTK) domain of VEGFR1 as a potential therapeutic marker for lung malignancies. The 3D crystal structure of the hTK domain, obtained from Protein Data Bank (PDB ID: 3HNG), has provided vital structural insights of hVEGFR1. This study has revealed variations within the hVEGFR1 tyrosine kinase domain, distinguishing between regions associated with phosphorylase kinase and transferase activities. We identified numerous potential phosphorylation sites within the TK domain, shedding light on the protein's regulation and signaling possible. Detailed molecular interaction analyses have elucidated the binding forces between lead molecules and hVEGFR1, including hydrogen bonds, electrostatic, hydrophobic, and π-sigma interactions. The stability observed during molecular dynamics simulations further underscores the biological relevance of these interactions. Furthermore, docked complexes has highlighted localized structural fluctuations, offering insight into potential allosteric effects and dynamic conformational changes induced by lead molecules. These findings not only provide a comprehensive characterization of hVEGFR1 but also pave the way for the development of targeted therapies. Eventually, this study has the potential in identifying drug to combat diseases associated with hVEGFR1 dysregulation, including cancer and angiogenesis-related disorders, contributing to effective treatment strategies.

Cyanidin prevents cardiomyocyte apoptosis in mice after myocardial infarction.

Myocardial infarction is a worldwide disease with high morbidity and mortality and a major cause of chronic heart failure, seriously affecting patients' quality of life. Natural medicine has been used to cure or prevent cardiovascular disease for decades. As a natural flavonoid, anthocyanidin has been used to treat many diseases due to its antioxidative, anti-inflammatory, and other properties. A mouse model (C57BL/6) weighing 30-40 g was utilized to induce myocardial infarction by ligating the left anterior descending coronary artery. Cyanidin (30 mg/kg) was administered orally to mice for four weeks. A variety of assessments were used to evaluate cardiac function. The gene expression was measured using RNAseq and Western blot. Histological changes in myocardial tissue were assessed using staining techniques, including Masson, Hematoxylin Eosin (HE), and transmission electron microscopy. Tunnel staining was implemented as a method to detect cellular apoptosis. For the quantification of B-type natriuretic peptide (BNP) and atrial natriuretic peptide (ANP) in the serum, an enzyme-linked immunosorbent assay (ELISA) was employed. Furthermore, autodock simulation was executed in order to assess the interaction between cyanidin and a subset of genes. Cyanidin treatment inhibited myocardial cell apoptosis, improved cardiac function, and reduced serum concentrations of BNP and atrial natriuretic peptide ANP, as well as mitigated histological cardiac tissue damage. Cyanidin also inhibited the activity of matrix metalloproteinases (MMP2/9) and Fibronectin 1 (Fn1). Cyanidin improves heart function and reduces myocardial damage in mice after MI. Furthermore, cyanidin can prevent cardiomyocyte apoptosis. These effects are most likely caused by suppression of MMP9/2 and control of the Akt signaling pathway, suggesting an appropriate therapeutic target.

VSpipe-GUI, an Interactive Graphical User Interface for Virtual Screening and Hit Selection.

Virtual screening of large chemical libraries is essential to support computer-aided drug development, providing a rapid and low-cost approach for further experimental validation. However, existing computational packages are often for specialised users or platform limited. Previously, we developed VSpipe, an open-source semi-automated pipeline for structure-based virtual screening. We have now improved and expanded the initial command-line version into an interactive graphical user interface: VSpipe-GUI, a cross-platform open-source Python toolkit functional in various operating systems (e.g., Linux distributions, Windows, and Mac OS X). The new implementation is more user-friendly and accessible, and considerably faster than the previous version when AutoDock Vina is used for docking. Importantly, we have introduced a new compound selection module (i.e., spatial filtering) that allows filtering of docked compounds based on specified features at the target binding site. We have tested the new VSpipe-GUI on the Hepatitis C Virus NS3 (HCV NS3) protease as the target protein. The pocket-based and interaction-based modes of the spatial filtering module showed efficient and specific selection of ligands from the virtual screening that interact with the HCV NS3 catalytic serine 139.

Identification of Phytochemicals with Inhibitory Potential Against Beta-lactamase Enzymes via Computer-aided Approach.

INTRODUCTION: Antibacterial drugs have been widely used for the past century to treat diseases, but their efficacy has been limited by multi-resistant pathogens, particularly those that utilize beta-lactamase enzymes. The inhibition of beta-lactamase enzymes holds great promise for reducing the influence of such pathogens. OBJECTIVE: This study aims to evaluate the mechanism of inhibition of phytochemicals with antibacterial activity against two classes of beta-lactamases using computational methods. METHODS: To achieve this objective, a total of thirty phytochemicals were docked against SHV-1 beta-lactamase and AmpC beta-lactamase after procurement from Protein Data Bank. The pharmacokinetics (ADMET) and density functional theory (DFT) analysis study were also conducted to unravel the nature of the top six most promising compounds on each protein. RESULTS: The results showed that a significant percentage of the compounds had binding affinities greater than that of avibactam, the positive control. Quercetin-3-O-rutinoside showed the most promising results against SHV-1 beta-lactamase with an affinity of -9.4 kcal/mol, while luteolin was found to be the most promising candidate against AmpC beta-lactamase with an affinity of -8.5 kcal/mol. DFT analysis demonstrated the reactivity of these compounds, and the ADMET study indicated that they were relatively safe. CONCLUSION: In conclusion, the study's findings suggest that the selected compounds have significant potential to inhibit beta-lactamase and may be used in combination with antibiotics against organisms that produce beta-lactamase. This study provides a basis for further research in a wet-lab setting to validate the results.

Computational modelling and optimization studies of electropentamer for molecular imprinting of DJ-1.

Parkinson's disease (PD) is the most prevalent type of incurable movement disorder. Recent research findings propose that the familial PD-associated molecule DJ-1 exists in cerebrospinal fluid (CSF) and that its levels may be altered as Parkinson's disease advances. By using a molecularly imprinted polymer (MIP) as an artificial receptor, it becomes possible to create a functional MIP with predetermined selectivity for various templates, particularly for the DJ-1 biomarker associated with Parkinson's disease. It mostly depends on molecular recognition via interactions between functional monomers and template molecules. So, the computational methods for the appropriate choice of functional monomers for creating molecular imprinting electropolymers (MIEPs) with particular recognition for the detection of DJ-1, a pivotal biomarker involved in PD, are undertaken in this study. Here, molecular docking, molecular dynamics simulations (MD), molecular mechanics Poisson-Boltzmann surface area (MM-PBSA) methods, and quantum mechanical calculation have been applied to investigate the intermolecular interaction between DJ-1 and several functional electropentamers, viz., polypyrrole (PPy), poly(3,4-ethylenedioxythiophene) (PEDOT), poly(o-aminophenol) (POAP), and polythiophene (PTS). In this context, the electropentamers were selected to mimic the imprinted electropolymer system. We analyzed the most stable configurations of the formed complexes involving DJ-1 and electropentamers as a model system for MIEPs. Among these, PEDOT exhibited a more uniform arrangement around DJ-1, engaging in numerous van der Waals, H-bond, electrostatic, and hydrophobic interactions. Hence, it can be regarded as a preferable choice for synthesizing a MIP for DJ-1 recognition. Thus, it will aid in selecting a suitable functional monomer, which is of greater significance in the design and development of selective DJ-1/MIP sensors.

Behenic Acid as a multi-target inhibiting antibacterial phytochemical against Vibrio parahaemolyticus and Aeromonas hydrophila for effective management of aquaculture infections: an in-silico, in-vitro & in-vivo experimentation.

Multi-Target Inhibitors are the upcoming frontrunners of the antibiotic world as they provide significant advantage over drug resistance development. Antibacterial drug discovery research, requires more robust and innovative approaches such as multi-target inhibiting drugs, which over comes the innate hurdles in the field of antibiotics. In this current study, a curated set of 5,112 phytochemical molecules were virtually screened for its multi-target inhibition potential against 7 antibacterial protein drug-targets. Behenic Acid was identified to be the most significant phytochemical molecule with potential to inhibit Catalase Peroxidase (KatG), Adenylosuccinate Synthetase (ADSS) and Pyridoxine 5'-Phosphate Synthase (PdxJ), based on SeeSAR and AutoDock Vina results. Further, the inhibition potential of Behenic Acid was validated using 500 ns Molecular Dynamics (MD) Simulation based on Desmond analysis. Behenic Acid was further investigated in-vitro using agar-well-diffusion and Minimal Inhibitory Concentration (MIC) assay, where it demonstrated 20 ± 1mm zone-of-inhibition and 50 µg/ml MIC value against both Vibrio parahaemolyticus and Aeromonas hydrophila. Zebrafish based investigations was carried to confirm the in-vivo antibacterial efficacy of Behenic Acid. It was observed that, there is a progressive dose-dependent recovery from the bacterial infection, with highest recovery and survival observed in fishes fed with 100 µg/day of Behenic Acid. Results of the in-vitro and in-vivo assays strongly support the in-silico prediction of the antibacterial activity of Behenic Acid. Based on the results presented in this study, it is concluded that, Behenic Acid is a strong multi-target antibacterial phytochemical, that exerts antagonism against aquaculture bacterial pathogens such as V. parahaemolytics and A. hydrophila.Communicated by Ramaswamy H. Sarma.

An Integrated Computational Approaches for Designing of Potential Piperidine based Inhibitors of Alzheimer Disease by Targeting Cholinesterase and Monoamine Oxidases Isoenzymes.

The study aimed to evaluate the potential of piperidine-based 2H chromen-2-one derivatives against targeted enzymes, i.e., cholinesterase's and monoamine oxidase enzymes. The compounds were divided into three groups, i.e., 4a-m ((3,4-dimethyl-7-((1-methylpiperidin-4-yl)oxy)-2H-chromen-2-one derivatives), 5a-e (3,4-dimethyl-7-((1-methypipridin-3-yl)methoxy)-2H-chromen-2-one derivatives), and 7a-b (7-(3-(3,4-dihydroisoquinolin-2(1H)-yl)propoxy)-3,4-dimethyl-2H-chromen-2-one derivatives) with slight difference in the basic structure. The comprehensive computational investigations were conducted including density functional theories studies (DFTs), 2D-QSAR studies, molecular docking, and molecular dynamics simulations. The QSAR equation revealed that the activity of selected chromen-2-one-based piperidine derivatives is being affected by the six descriptors, i.e., Nitrogens Count, SdssCcount, SssOE-Index, T-2-2-7, ChiV6chain, and SssCH2E-Index. These descriptor values were further used for the preparation of chromen-2-one based piperidine derivatives. Based on this, 83 new derivatives were created from 7 selected parent compounds. The QSAR model predicted their IC50 values, with compound 4 k and 4kk as the most potent multi-targeted derivative. Molecular docking results exhibited these compounds as the best inhibitors; however, 4kk exhibited greater activity than the parent compounds. The results were further validated by molecular dynamic simulation studies along with the suitable physicochemical properties. These results prove to be an essential guide for the further design and development of new piperidine based chromen-2-one derivatives having better activity against neurodegenerative disorder.

Development of Novel Indazolyl-Acyl Hydrazones as Antioxidant and Anticancer Agents that Target VEGFR-2 in Human Breast Cancer Cells.

The increased expression of VEGFR-2 in a variety of cancer cells promotes a cascade of cellular responses that improve cell survival, growth, and proliferation. Heterocycles are common structural elements in medicinal chemistry and commercially available medications that target several biological pathways and induce cell death in cancer cells. Herein, the evaluation of indazolyl-acyl hydrazones as antioxidant and anticancer agents is reported. Compounds 4e and 4j showed inhibitory activity in free radical scavenging assays (DPPH and FRPA). The titled compounds were employed in cell viability studies using MCF-7 cells, and it was observed that compounds 4f and 4j exhibited IC50 values 15.83 µM and 5.72 µM, respectively. In silico docking revealed the favorable binding energies of -7.30 kcal/mol and -8.04 kcal/mol for these compounds towards Vascular Endothelial Growth Factor Receptor-2 (VEGFR-2), respectively. In conclusion, compounds with antioxidant activity and that target VEGFR-2 in breast cancer cells are reported.

Virtual screening of flavonoids as potential RIPK1 inhibitors for neurodegeneration therapy.

Background: Global prevalence of neurodegenerative diseases such as Alzheimer's disease and Parkinson's disease is increasing gradually, whereas approvals of successful therapeutics for central nervous system disorders are inadequate. Accumulating evidence suggests pivotal roles of the receptor-interacting serine/threonine-protein kinase 1 (RIPK1) in modulating neuroinflammation and necroptosis. Discoveries of potent small molecule inhibitors for RIPK1 with favorable pharmacokinetic properties could thus address the unmet medical needs in treating neurodegeneration. Methods: In a structure-based virtual screening, we performed site-specific molecular docking of 4,858 flavonoids against the kinase domain of RIPK1 using AutoDock Vina. We predicted physicochemical descriptors of the top ligands using the SwissADME webserver. Binding interactions of the best ligands and the reference ligand L8D were validated using replicated 500-ns Gromacs molecular dynamics simulations and free energy calculations. Results: From Vina docking, we shortlisted the top 20 flavonoids with the highest binding affinities, ranging from -11.7 to -10.6 kcal/mol. Pharmacokinetic profiling narrowed down the list to three orally bioavailable and blood-brain-barrier penetrant flavonoids: Nitiducarpin, Pinocembrin 7-O-benzoate, and Paratocarpin J. Next, trajectories of molecular dynamics simulations of the top protein-ligand complexes were analyzed for binding interactions. The root-mean-square deviation (RMSD) was 1.191 Å (±0.498 Å), 1.725 Å (±0.828 Å), 1.923 Å (±0.942 Å), 0.972 Å (±0.155 Å) for Nitiducarpin, Pinocembrin 7-O-benzoate, Paratocarpin J, and L8D, respectively. The radius of gyration (Rg) was 2.034 nm (±0.015 nm), 2.0.39 nm (± 0.025 nm), 2.053 nm (±0.021 nm), 2.037 nm (±0.016 nm) for Nitiducarpin, Pinocembrin 7-O-benzoate, Paratocarpin J, and L8D, respectively. The solvent accessible surface area (SASA) was 159.477 nm2 (±3.021 nm2), 159.661 nm2 (± 3.707 nm2), 160.755 nm2 (±4.252 nm2), 156.630 nm2 (±3.521 nm2), for Nitiducarpin, Pinocembrin 7-O-benzoate, Paratocarpin J, and L8D complexes, respectively. Therefore, lower RMSD, Rg, and SASA values demonstrated that Nitiducarpin formed the most stable complex with the target protein among the best three ligands. Finally, 2D protein-ligand interaction analysis revealed persistent hydrophobic interactions of Nitiducarpin with the critical residues of RIPK1, including the catalytic triads and the activation loop residues, implicated in the kinase activity and ligand binding. Conclusion: Our target-based virtual screening identified three flavonoids as strong RIPK1 inhibitors, with Nitiducarpin exhibiting the most potent inhibitory potential. Future in vitro and in vivo studies with these ligands could offer new hope for developing effective therapeutics and improving the quality of life for individuals affected by neurodegeneration.

EasyDock: customizable and scalable docking tool.

Docking of large compound collections becomes an important procedure to discover new chemical entities. Screening of large sets of compounds may also occur in de novo design projects guided by molecular docking. To facilitate these processes, there is a need for automated tools capable of efficiently docking a large number of molecules using multiple computational nodes within a reasonable timeframe. These tools should also allow for easy integration of new docking programs and provide a user-friendly program interface to support the development of further approaches utilizing docking as a foundation. Currently available tools have certain limitations, such as lacking a convenient program interface or lacking support for distributed computations. In response to these limitations, we have developed a module called EasyDock. It can be deployed over a network of computational nodes using the Dask library, without requiring a specific cluster scheduler. Furthermore, we have proposed and implemented a simple model that predicts the runtime of docking experiments and applied it to minimize overall docking time. The current version of EasyDock supports popular docking programs, namely Autodock Vina, gnina, and smina. Additionally, we implemented a supplementary feature to enable docking of boron-containing compounds, which are not inherently supported by Vina and smina, and demonstrated its applicability on a set of 55 PDB protein-ligand complexes.

ReverseDock: a web server for blind docking of a single ligand to multiple protein targets using AutoDock Vina.

Several platforms exist to perform molecular docking to computationally predict binders to a specific protein target from a library of ligands. The reverse, that is, docking a single ligand to various protein targets, can currently be done by very few web servers, which limits the search to a small set of pre-selected human proteins. However, the possibility to in silico predict which targets a compound identified in a high-throughput drug screen bind would help optimize and reduce the costs of the experimental workflow needed to reveal the molecular mechanism of action of a ligand. Here, we present ReverseDock, a blind docking web server based on AutoDock Vina specifically designed to allow users with no computational expertise to dock a ligand to 100 protein structures of their choice. ReverseDock increases the number and type of proteins a ligand can be docked to, making the task of in silico docking of a ligand to entire families of proteins straightforward. We envision ReverseDock will support researchers by providing the possibility to apply inverse docking computations using web browser. ReverseDock is available at: https://reversedock.biologie.uni-freiburg.de/.

Fenretinide induces apoptosis and synergises the apoptosis inducing effect of gemcitabine through inhibition of key signalling molecules involved in A549 cell survival in in silico and in vitro analyses.

Fenretinide is a synthetic retinoid compound, which induces apoptosis via generating reactive oxygen species (ROS) and modulating PI3K/Akt/mTOR signalling pathway. We hypothesise that fenretinide's mechanism of action in triggering apoptosis may involve other targets, beside mTOR signalling pathway and it may augment apoptosis inducing effects of chemotherapeutic drugs in lung cancer. Time-lapse microscopy and Western blotting were used to evaluate apoptosis and apoptotic marker cleaved-Caspase 3 in A549 cells. Relative levels of protein phosphorylation and ROS were quantified by Human Phospho-Kinase Array Kit and CellROX® Green Reagent, respectively. Docking and simulation analyses of proteins and fenretinide interactions were identified and visualised by Discovery Studio Visualizer and AutoDock Vina software. Our results showed that fenretinide induced apoptosis in a dose dependant manner and combinations of fenretinide (5 µg/mL) and gemcitabine (1, 2, 4, 8 and 16 µg/mL) synergistically enhanced apoptosis in A549 cells. Fenretinide caused significant increase of cleaved-Caspase 3, de-phosphorylated p-S473 of Akt and failed to inhibit mTORC1 downstream targets. In silico results revealed that Akt required the lowest energy (-10.2 kcal/mol) to interact with fenretinide in comparison with other proteins. In conclusion, Akt may be exploited as a good target for induction of apoptosis in A549 cells and fenretinide has great potentials to fulfil this task. The mechanism by which fenretinide boosts the apoptosis inducing effects of gemcitabine, which is likely expected to be via inhibiting mTORC2 downstream targets. However, docking investigation revealed that fenretinide lacks specificity as it may also interact with several secondary targets beside Akt.

Raloxifene, a SERM targets PD-L1: an in-silico study.

OBJECTIVES: Immunotherapeutic interventions in cancer have been considerably successful and widely accepted for cancer treatment, but are costly and cannot be afforded by all patients. Because of the high cost, the pharmaceutical research groups across the world are sufficiently motivated to discover or design small molecule inhibitors to treat cancer through inhibition of the immune checkpoint proteins previously targeted with monoclonal antibodies. The presented study was designed with an aim to establish raloxifene, a selective estrogen receptor modulator (SERM) as a potential ligand of the immune checkpoint protein Programmed death ligand-1 (PD-L1). METHODS: In the presented study, the in-silico approach was used for identifying a lead molecule against PD-L1. The hits were screened using the similarity-search method, and drug-likeliness analysis, and the leads were identified through ligand-docking using Autodock. In-vitro cytotoxicity analysis was carried out using the standard sulphorhodamine B (SRB) assay and the wound healing analysis to show the inhibition of cellular migration was performed using the standard scratch assay. RESULTS: The in-silico study revealed that raloxifene showed a high drug likelihood and higher binding affinity with PD-L1 as compared to the positive control (BMS-1166; BMS is Bristol Myers Squibb). The binding of raloxifene was shown to occur in the same region as the FDA-approved monoclonal antibodies atezolizumab and durvalumab, indicating the potential of raloxifene for PD1/PD-L1 blockade. In the in-vitro studies, raloxifene showed a time-dependent reduction in IC50 values for the cell line HCT116 (colon cancer). The scratch assay also revealed that raloxifene significantly reduced the migratory potential of HCT-116 cells in-vitro. CONCLUSIONS: PD-L1 is a potential target of the SERM raloxifene in-silico. Overall, this study is one step further towards immune checkpoint blockade using small-molecule inhibitors.

Bisphenol analogues inhibit human and rat 17ß-hydroxysteroid dehydrogenase 1: 3D-quantitative structure-activity relationship (3D-QSAR) and in silico docking analysis.

Bisphenols, estrogenic endocrine-disrupting chemicals, disrupt at least one of three endocrine pathways (estrogen, androgen, and thyroid). 17ß-Hydroxysteroid dehydrogenase 1 (17ß-HSD1) is a steroidogenic enzyme that catalyzes the activation of estradiol from estrone in human placenta and rat ovary. However, whether bisphenols inhibit 17ß-HSD1 and the mode of action remains unclear. This study we screened 17 bisphenols for inhibiting human 17ß-HSD1 in placental microsomes and rat 17ß-HSD1 in ovarian microsomes and determined 3D-quantitative structure-activity relationship (3D-QSAR) and mode of action. We observed some bisphenols with substituents were found to significantly inhibit both human and rat 17ß-HSD1 with the most potent inhibition on human enzyme by bisphenol H (IC50 = 0.90 µM) when compared to bisphenol A (IC50 = 113.38 µM). Rat enzyme was less sensitive to the inhibition of bisphenols than human enzyme with bisphenol H (IC50 = 32.94 µM) for rat enzyme. We observed an inverse correlation between IC50 and hydrophobicity (expressed as Log P). Docking analysis showed that they bound steroid-binding site of 17ß-HSD1. The 3D-QSAR models demonstrated that hydrophobic region, hydrophobic aromatic, ring aromatic, and hydrogen bond acceptor are key factors for the inhibition of steroid synthesis activity of 17ß-HSD1.

A novel small molecule inhibitor of p38⍺ MAP kinase augments cardiomyocyte cell cycle entry in response to direct cell cycle stimulation.

BACKGROUND AND PURPOSE: Myocardial infarction (MI) is the leading cause of mortality globally due in part to the limited ability of cardiomyocytes (CMs) to regenerate. Recently, we demonstrated that overexpression of four-cell cycle factors, CDK1, CDK4, cyclin B1 and cyclin D1 (4F), induced cell division in ~20% of the post-mitotic CMs overexpressed 4F. The current study aims to identify a small molecule that augments 4F-induced CM cycle induction. EXPERIMENTAL APPROACH, KEY RESULTS: Screening of small molecules with a potential to augment 4F-induced cell-cycle induction in 60-day-old mature human induced pluripotent cardiomyocytes (hiPS-CMs) revealed N-(4,6-Dimethylpyridin-2-yl)-4-(pyridine-4-yl)piperazine-1-carbothioamide (NDPPC), which activates cell cycle progression in 4F-transduced hiPS-CMs. Autodock tool and Autodock vina computational methods showed that NDPPC has a potential interaction with the binding site at the human p38⍺ mitogen-activated protein kinase (p38⍺ MAP kinase), a critical negative regulator of the mammalian cell cycle. A p38 MAP kinase activity assay showed that NDPPC inhibits p38⍺ with 5-10 times lower IC50 compared to the other P38 isoforms in a dose-dependent manner. Overexpression of p38⍺ MAP kinase in CMs inhibited 4F cell cycle induction, and treatment with NDPPC reversed the cell cycle inhibitory effect. CONCLUSION AND IMPLICATIONS: NDPPC is a novel inhibitor for p38 MAP kinase and is a promising drug to augment CM cell cycle response to the 4F. NDPPC could become an adjunct treatment with other cell cycle activators for heart failure treatment.