High-throughput Molecular Docking Research Articles

Pharmacoinformatics-based prediction of Checkpoint Kinase-1 inhibitors from Momordica charantia Linn. for cancer

Checkpoint kinase 1 (Chk-1), a serine/threonine kinase family protein, is an emerging target in cancer research owing to its crucial role in cell cycle arrest. Therefore, we aimed to predict potential Chk-1 inhibitors from Momordica charantia Linn., using high-throughput molecular docking. We used a graph theoretical network approach to determine the target protein, Chk-1. Among 86 compounds identified from M. charantia L., five molecules such as α-spinasterol (-9.7kcal × mol−1), stigmasterol (-9.6kcal × mol−1), stigmasta-7,22,25-trienol (-9.5kcal × mol−1), campesterol (-9.5kcal × mol−1), and stigmasta-7,25-dien-3beta-ol (-9.5kcal × mol−1) and standard drug CCT245737 (-8.3kcal×mol-1) displayed highest binding affinity with Chk-1. Besides, pharmacokinetic studies have demonstrated the non-toxic and drug-like properties of these compounds. Furthermore, molecular dynamics (MD) simulation studies confirmed the strong intermolecular interactions and stability of the compounds with Chk-1. The estimation of binding free-energy derived from molecular docking was fully recognized by the Molecular Mechanics-Generalized Born Surface Area (MM-GBSA) produced from the MD simulation paths. Altogether, these five compounds may serve as effective inhibitors of Chk-1, thereby could be used to develop new medications for cancer treatment.

High Throughput Screening and Molecular Docking Analysis on DNA Polymerase (Pol) Β Cancer Variant K289M

DNA polymerase (pol) β plays a critical role in DNA repair mechanisms, and mutations in this enzyme have been implicated in various cancers. Because it may play a role in oncogenesis by altering the fidelity of DNA synthesis, the K289M variation of pol β is particularly interesting. This study uses Python molecular graphic, Cavity based docking, SwissDock, Structure validation server among other computational tools to undertake high-throughput screening and molecular docking investigations of DNA pol β cancer variant K289M (PDB ID: 6NKR). Ligands such as Boceprevir, Nirmatrelvir, Ritonavir, Carmofur, and Lopinavir were docked to identify potential inhibitors targeting this variant. Structural validation using the SAVES server and topology analysis using PDBSum helped assess the quality of the protein structure. Our results highlight several binding pockets with strong ligand affinities, suggesting potential therapeutic interventions for targeting pol β K289M in cancer.

Proteomic Profiling of Serum Extracellular Vesicles Identifies Diagnostic Signatures and Therapeutic Targets in Breast Cancer.

Analysis of extracellular vesicles (EV) is a promising noninvasive liquid biopsy approach for breast cancer detection, prognosis, and therapeutic monitoring. A comprehensive understanding of the characteristics and proteomic composition of breast cancer-specific EVs from human samples is required to realize the potential of this strategy. In this study, we applied a mass spectrometry-based, data-independent acquisition proteomic approach to characterize human serum EVs derived from patients with breast cancer (n = 126) and healthy donors (n = 70) in a discovery cohort and validated the findings in five independent cohorts. Examination of the EV proteomes enabled the construction of specific EV protein classifiers for diagnosing breast cancer and distinguishing patients with metastatic disease. Of note, TALDO1 was found to be an EV biomarker of distant metastasis of breast cancer. In vitro and in vivo analysis confirmed the role of TALDO1 in stimulating breast cancer invasion and metastasis. Finally, high-throughput molecular docking and virtual screening of a library consisting of 271,380 small molecules identified a potent TALDO1 allosteric inhibitor, AO-022, which could inhibit breast cancer migration in vitro and tumor progression in vivo. Together, this work elucidates the proteomic alterations in the serum EVs of breast cancer patients to guide the development of improved diagnosis, monitoring, and treatment strategies. Significance: Characterization of the proteomic composition of circulating extracellar vesicles in breast cancer patients identifies signatures for diagnosing primary and metastatic tumors and reveals tumor-promoting cargo that can be targeted to improve outcomes.

Chicoric acid acts as an ALOX15 inhibitor to prevent ferroptosis in asthma

BackgroundChicoric acid (CA) is a crucial immunologically active compound found in chicory and echinacea, possessing a range of biological activities. Ferroptosis, a type of iron-dependent cell death induced by lipid peroxidation, plays a key role in the development and advancement of asthma. Targeting ferroptosis could be a potential therapeutic strategy for treating asthma. PurposeThe purpose of this study was to explore the screening of ALOX15, a pivotal target of ferroptosis in asthma, and potential therapeutic agents, as well as to investigate the promising potential of CA as an ALOX15 inhibitor for modulating ferroptosis in asthma. MethodsThrough high-throughput data processing of bronchial epithelial RNA from asthma patients using bioinformatics and machine learning, the key target of ferroptosis in asthma, ALOX15, was identified. An inhibitor of ALOX15 was then obtained through high-throughput molecular docking and molecular dynamics simulation tests. In vitro experiments were conducted using a 16HBE cell model induced by house dust mite (HDM) and lipopolysaccharide (LPS), which were treated with the ALOX15 inhibitor (PD146176), CA treatment, or ALOX15 knockdown. In vivo experiments were also carried out using a mouse model induced by HDM and LPS. ResultsThe composite model of ALOX15 and CA in molecular dynamics simulations shows good stability and flexibility. Network pharmacological analysis reveals that CA regulates ferroptosis through ALOX15 in treating asthma. In vitro studies show that ALOX15 is highly expressed in HDM and LPS treatments, while CA inhibits HDM and LPS-induced ferroptosis in 16HBE cells by reducing ALOX15 expression. Knockdown of ALOX15 has the opposite effect. Metabolomics analysis identifies key compounds associated with ferroptosis, including L-Targinine, eicosapentaenoic acid, 16-hydroxy hexadecanoic acid, and succinic acid. In vivo experiments demonstrate that CA suppresses ALOX15 expression, inhibits ferroptosis, and improves asthma symptoms in mice. ConclusionOur research initially identified CA as a promising asthma treatment that effectively blocks ferroptosis by specifically targeting ALOX15. This study not only highlights CA as a potential therapeutic agent for asthma but also introduces novel targets and treatment options for this condition, along with innovative approaches for utilizing natural compounds to target diseases associated with ferroptosis.

Unveiling key genes in esophageal and lung adenocarcinoma progression: A combined high-throughput analysis and molecular docking approach for targeted therapies

BackgroundEsophageal carcinoma (ESCA) and Lung adenocarcinoma (LUAD) are the prominent causes of death worldwide. There is an urgent need to identify and characterize potential biomarkers for these malignancies to enhance early cancer prognosis. Integrating computational-based early cancer detection with wet lab-based research offers a promising approach toward early-stage cancer prognosis. MethodologyTwo ESCA datasets (GSE17351, GSE23400) with 58 cancerous and 58 normal samples, along with two LUAD datasets (GSE18842, GSE74706) totaling 64 cancer samples and 63 controls, were used to identify DEGs. Visualization of DEGs was achieved using heat-maps, volcano plots, and Venn diagrams. Hub genes were predicted via PPI analysis and the cytoHubba plugin in Cytoscape. Potential hub gene expressions were evaluated with box plots, stage plots, and survival plots for prognostic assessment via GEPIA2. AutoDockVina wizard of PyRx was utilized for molecular docking to determine optimal binding interactions between proteins and hit compounds. FindingsSixty common DEGs were identified, focusing on significant pathways in ESCA and LUAD. The top ten hub genes (KIF4A, HMMR, CENPF, CDK1, ASPM, CDKN3, KIF2C, TTK, UBE2C, and MELK) were found to be linked to both cancers via PPI analysis. Notably, high expression of CDK1 was significantly associated with ESCA and LUAD progression, as evidenced by box plots, stage plots, and survival analysis. Upregulated expression of the targeted genes (CDK1) promotes multi-variant cancer progression that is observed by analyzing and comparing of all findings. Molecular docking with CDK1 highlighted four top compounds: Tanshinone I, Withanolide, Artemether, and Epigallocatechin, suggesting their potential as drug candidates for ESCA and LUAD treatment. ConclusionsIn conclusion, our discoveries unveil potential biomarker candidates, offer insights into ESCA and LUAD treatment strategies, and outline directions for further investigation, enriching our understanding of the pathogenesis of ESCA and LUAD.

Construction of IRAK4 inhibitor activity prediction model based on machine learning.

Interleukin-1 receptor-associated kinase 4 (IRAK4) is a crucial serine/threonine protein kinase that belongs to the IRAK family and plays a pivotal role in Toll-like receptor (TLR) and Interleukin-1 receptor (IL-1R) signaling pathways. Due to IRAK4's significant role in immunity, inflammation, and malignancies, it has become an intriguing target for discovering and developing potent small-molecule inhibitors. Consequently, there is a pressing need for rapid and accurate prediction of IRAK4 inhibitor activity. Leveraging a comprehensive dataset encompassing activity data for 1628 IRAK4 inhibitors, we constructed a prediction model using the LightGBM algorithm and molecular fingerprints. This model achieved an R2 of 0.829, an MAE of 0.317, and an RMSE of 0.460 in independent testing. To further validate the model's generalization ability, we tested it on 90 IRAK4 inhibitors collected in 2023. Subsequently, we applied the model to predict the activity of 13,268 compounds with docking scores less than -9.503kcal/mol. These compounds were initially screened from a pool of 1.6 million molecules in the chemdiv database through high-throughput molecular docking. Among these, 259 compounds with predicted pIC50 values greater than or equal to 8.00 were identified. We then performed ADMET predictions on these selected compounds. Finally, through a rigorous screening process, we identified 34 compounds that adhere to the four complementary drug-likeness rules, making them promising candidates for further investigation. Additionally, molecular dynamics simulations confirmed the stable binding of the screened compounds to the IRAK4 protein. Overall, this work presents a machine learning model for accurate prediction of IRAK4 inhibitor activity and offers new insights for subsequent structure-guided design of novel IRAK4 inhibitors.

Identification of Novel GANT61 Analogs with Activity in Hedgehog Functional Assays and GLI1-Dependent Cancer Cells.

Aberrant activation of hedgehog (Hh) signaling has been implicated in various cancers. Current FDA-approved inhibitors target the seven-transmembrane receptor Smoothened, but resistance to these drugs has been observed. It has been proposed that a more promising strategy to target this pathway is at the GLI1 transcription factor level. GANT61 was the first small molecule identified to directly suppress GLI-mediated activity; however, its development as a potential anti-cancer agent has been hindered by its modest activity and aqueous chemical instability. Our study aimed to identify novel GLI1 inhibitors. JChem searches identified fifty-two compounds similar to GANT61 and its active metabolite, GANT61-D. We combined high-throughput cell-based assays and molecular docking to evaluate these analogs. Five of the fifty-two GANT61 analogs inhibited activity in Hh-responsive C3H10T1/2 and Gli-reporter NIH3T3 cellular assays without cytotoxicity. Two of the GANT61 analogs, BAS 07019774 and Z27610715, reduced Gli1 mRNA expression in C3H10T1/2 cells. Treatment with BAS 07019774 significantly reduced cell viability in Hh-dependent glioblastoma and lung cancer cell lines. Molecular docking indicated that BAS 07019774 is predicted to bind to the ZF4 region of GLI1, potentially interfering with its ability to bind DNA. Our findings show promise in developing more effective and potent GLI inhibitors.

Preparation, Characterization, and Oral Bioavailability of Solid Dispersions of Cryptosporidium parvum Alternative Oxidase Inhibitors.

The phenylpyrazole derivative 5-amino-3-[1-cyano-2-(3-phenyl-1H-pyrazol-4-yl) vinyl]-1-phenyl-1H-pyrazole-4-carbonitrile (LN002), which was screened out through high-throughput molecular docking for the AOX target, exhibits promising efficacy against Cryptosporidium. However, its poor water solubility limits its oral bioavailability and therapeutic utility. In this study, solid dispersion agents were prepared by using HP-β-CD and Soluplus® and characterized through differential scanning calorimetry, Fourier transform infrared, powder X-ray diffraction, and scanning electron microscopy. Physical and chemical characterization showed that the crystal morphology of LN002 transformed into an amorphous state, thus forming a solid dispersion of LN002. The solid dispersion prepared with an LN002/HP-β-CD/Soluplus® mass ratio of 1:3:9 (w/w/w) exhibited significantly increased solubility and cumulative dissolution. Meanwhile, LN002 SDs showed good preservation stability under accelerated conditions of 25 °C and 75% relative humidity. The complexation of LN002 with HP-β-CD and Soluplus® significantly improved water solubility, pharmacological properties, absorption, and bioavailability.

Pharmaceutical Potential of Remedial Plants and Helminths for Treating Inflammatory Bowel Disease.

Research is increasingly revealing that inflammation significantly contributes to various diseases, particularly inflammatory bowel disease (IBD). IBD is a major medical challenge due to its chronic nature, affecting at least one in a thousand individuals in many Western countries, with rising incidence in developing nations. Historically, indigenous people have used natural products to treat ailments, including IBD. Ethnobotanically guided studies have shown that plant-derived extracts and compounds effectively modulate immune responses and reduce inflammation. Similarly, helminths and their products offer unique mechanisms to modulate host immunity and alleviate inflammatory responses. This review explored the pharmaceutical potential of Aboriginal remedial plants and helminths for treating IBD, emphasizing recent advances in discovering anti-inflammatory small-molecule drug leads. The literature from Scopus, MEDLINE Ovid, PubMed, Google Scholar, and Web of Science was retrieved using keywords such as natural product, small molecule, cytokines, remedial plants, and helminths. This review identified 55 important Aboriginal medicinal plants and 9 helminth species that have been studied for their anti-inflammatory properties using animal models and in vitro cell assays. For example, curcumin, berberine, and triptolide, which have been isolated from plants; and the excretory-secretory products and their protein, which have been collected from helminths, have demonstrated anti-inflammatory activity with lower toxicity and fewer side effects. High-throughput screening, molecular docking, artificial intelligence, and machine learning have been engaged in compound identification, while clustered regularly interspaced short palindromic repeats (CRISPR) gene editing and RNA sequencing have been employed to understand molecular interactions and regulations. While there is potential for pharmaceutical application of Aboriginal medicinal plants and gastrointestinal parasites in treating IBD, there is an urgent need to qualify these plant and helminth therapies through reproducible clinical and mechanistic studies.

A New Optimized Hybridization Approach for in silico High Throughput Molecular Docking on FPGA Platform.

The development process of a new drug should be a subject of continuous evolution and rapid improvement as drugs are essential to treat a wide range of diseases of which many are life-threatening. The advances in technology resulted in a novel track in drug discovery and development known as in silico drug design. The molecular docking phase plays a vital role in in silico drug development process. In this phase, thousands of 3D conformations of both the ligand and receptor are generated and the best conformations that create the most stable drug-receptor complex are determined. The speed in finding accurate and high-quality complexes depends on the efficiency of the search function in the molecular docking procedure. The objective of this research is to propose and implement a novel hybrid approach called hABCDE to replace the EMC searching part inside the BUDE docking algorithm. This helps in reaching the best solution in a much accelerated time and higher solution quality compared to using the ABC and DE algorithms separately. In this work, we have employed a new approach of hybridization between the Artificial Bee Colony (ABC) algorithm and the Differential Evolution (DE) algorithm as an alternative searching part of the Bristol University Docking Engine (BUDE) in order to accelerate the search for higher quality solutions. Moreover, the proposed docking approach was implemented on Field Programmable Gate Array (FPGA) parallel platform using Vivado High-Level Synthesis Tool (HLST) in order to optimize and enhance the execution time and overall efficiency. The NDM-1 protein was used as a model receptor in our experiments to demonstrate the efficiency of our approach. The NDM-1 protein was used as a model receptor in our experiments to demonstrate the efficiency of our approach. The results showed that the execution time for the BUDE with the new proposed hybridization approach was improved by 9,236 times. Our novel approach was significantly effective to improve the functionality of docking algorithms (Bristol University Docking Engine (BUDE)).

Discovery of potent antimycobacterial agents targeting lumazine synthase (RibH) of Mycobacterium tuberculosis

Tuberculosis (TB) continues to be a global health crisis, necessitating urgent interventions to address drug resistance and improve treatment efficacy. In this study, we validate lumazine synthase (RibH), a vital enzyme in the riboflavin biosynthetic pathway, as a potential drug target against Mycobacterium tuberculosis (M. tb) using a CRISPRi-based conditional gene knockdown strategy. We employ a high-throughput molecular docking approach to screen ~ 600,000 compounds targeting RibH. Through in vitro screening of 55 shortlisted compounds, we discover 3 compounds that exhibit potent antimycobacterial activity. These compounds also reduce intracellular burden of M. tb during macrophage infection and prevent the resuscitation of the nutrient-starved persister bacteria. Moreover, these three compounds enhance the bactericidal effect of first-line anti-TB drugs, isoniazid and rifampicin. Corroborating with the in silico predicted high docking scores along with favourable ADME and toxicity profiles, all three compounds demonstrate binding affinity towards purified lumazine synthase enzyme in vitro, in addition these compounds exhibit riboflavin displacement in an in vitro assay with purified lumazine synthase indicative of specificity of these compounds to the active site. Further, treatment of M. tb with these compounds indicate reduced production of flavin adenine dinucleotide (FAD), the ultimate end product of the riboflavin biosynthetic pathway suggesting the action of these drugs on riboflavin biosynthesis. These compounds also show acceptable safety profile in mammalian cells, with a high selective index. Hence, our study validates RibH as an important drug target against M. tb and identifies potent antimycobacterial agents.

Analysis of the anti-PCV2 mechanism of Lactobacillus acidophilus based on non-target metabolomics and high-throughput molecular docking.

Our previous studies have revealed that L. acidophilus possesses inhibitory effects on PCV2 proliferation in vivo, although the underlying mechanisms remain elusive. Probiotics like L. acidophilus are known to exert antiviral through their metabolites. Therefore, in this study, non-targeted metabolomics was used to detect the changes in metabolites of L. acidophilus after 24 h of proliferation. Subsequently, high-throughput molecular docking was utilized to analyze the docking scores of these metabolites with PCV2 Cap and Rep, aiming to identify compounds with potential anti-PCV2 effects. The results demonstrated that 128 compounds such as Dl-lactate were significantly increased. The results of high-throughput molecular docking indicated that compounds such as ergocristine, and telmisartan formed complexes with Cap and Rep, suggesting their potential anti-PCV2 properties. Furthermore, compounds like vitamin C, exhibit pharmacological effects consistent with L. acidophilus adding credence to the idea that L. acidophilus may exert pharmacological effects through its metabolites. These results will provide a foundation for the study of L. acidophilus.

Repurposing diacerein to suppress colorectal cancer growth by inhibiting the DCLK1/STAT3 signaling pathway

Double cortin-like kinase 1 (DCLK1) exhibits high expression levels across various cancers, notably in human colorectal cancer (CRC). Diacerein, a clinically approved interleukin (IL)-1β inhibitor for osteoarthritis treatment, was evaluated for its impact on CRC proliferation and migration, alongside its underlying mechanisms, through both in vitro and in vivo analyses. The study employed MTT assay, colony formation, wound healing, transwell assays, flow cytometry, and Hoechst 33342 staining to assess cell proliferation, migration, and apoptosis. Additionally, proteome microarray assay and western blotting analyses were conducted to elucidate diacerein's specific mechanism of action. Our findings indicate that diacerein significantly inhibits DCLK1-dependent CRC growth in vitro and in vivo. Through high-throughput proteomics microarray and molecular docking studies, we identified that diacerein directly interacts with DCLK1. Mechanistically, the suppression of p-STAT3 expression following DCLK1 inhibition by diacerein or specific DCLK1 siRNA was observed. Furthermore, diacerein effectively disrupted the DCLK1/STAT3 signaling pathway and its downstream targets, including MCL-1, VEGF, and survivin, thereby inhibiting CRC progression in a mouse model, thereby inhibiting CRC progression in a mouse model.

High-throughput virtual search of small molecules for controlling the mechanical stability of human CD4

Protein mechanical stability determines the function of a myriad of proteins, especially proteins from the extracellular matrix. Failure to maintain protein mechanical stability may result in diseases and disorders such as cancer, cardiomyopathies, or muscular dystrophy. Thus, developing mutation-free approaches to enhance and control the mechanical stability of proteins using pharmacology-based methods, may have important implications in drug development and discovery. Here, we present the first approach that employs computational High-Throughput Virtual Screening (HTVS) and Molecular Docking to search for small-molecules in chemical libraries that function as mechano-regulators of the stability of human CD4, receptor of HIV-1. Using single-molecule force spectroscopy we prove that these small-molecules can increase the mechanical stability of CD4D1D2 domains over 4-fold in addition to modifying the mechanical unfolding pathways. Our experiments demonstrate that chemical libraries are a source of mechanoactive molecules and that drug discovery approaches provide the foundation of a new type of molecular function, i.e., mechano-regulation, paving the way towards mechanopharmacology.

Computational exploration of novel ROCK2 inhibitors for cardiovascular disease management; insights from high-throughput virtual screening, molecular docking, DFT and MD simulation.

Cardiovascular disorders are the world's major cause of death nowadays. To treat cardiovascular diseases especially coronary artery diseases and hypertension, researchers found potential ROCK2 (Rho-associated coiled-coil-containing protein kinase 2) target due to its substantial role in NO-cGMP and RhoA/ROCK pathway. Available drugs for ROCK2 are less effective and some of them depict side effects. Therefore, a set of novel compounds were screened that can potentially inhibit the activity of ROCK2 and help to treat cardiovascular diseases by employing In-silico techniques. In this study, we undertook ligand based virtual screening of 50 million compound's library, to that purpose shape and features (contain functional groups) based pharmacophore query was modelled and validated by Area Under Curve graph (AUC). 2000 best hits were screened for Lipinski's rule of 5 compliance. Subsequently, these selected compounds were docked into the binding site of ROCK2 to gain insights into the interactions between hit compounds and the target protein. Based on binding affinity and RMSD scores, a final cohort of 15 compounds were chosen which were further refined by pharmacokinetics, ADMET and bioactivity scores. 2 potential hits were screened using density functional theory, revealing remarkable biological and chemical activity. Potential inhibitors (F847-0007 and 9543495) underwent rigorous examination through MD Simulations and MMGBSA analysis, elucidating their stability and strong binding affinities. Results of current study unveil the potential of identified novel hits as promising lead compounds for ROCK2 associated with cardiovascular diseases. These findings will further investigate via In-vitro and In-vivo studies to develop novel druglike molecules against ROCK2.

Evaluation of the FDA-approved kinase inhibitors to uncover the potential repurposing candidates targeting ABC transporters in multidrug-resistant cancer cells: an in silico approach

Multiple drug resistance (MDR) is characterized by the resistance of cancer cells to a broad spectrum of anticancer drugs. The main mechanism underlying the MDR phenotype is the overexpression of ATP-binding cassette (ABC) transporters by promoting active drug efflux from cancer cells. Some small-molecule protein kinase inhibitors have been found to overcome MDR by inhibiting ABC transporters as substrates or modulators. This study investigated the chemical activity of 58 FDA-approved anticancer kinase inhibitors against three multidrug resistance-related proteins. The studied proteins are ATP-Binding Cassette Sub-Family B Member 1 (ABCB1), ATP-Binding Cassette Subfamily C Member 1 (ABCC1), and ATP-binding cassette superfamily G member 2 (ABCG2). The drug-binding domain and ATP binding sites of the proteins were considered the kinase inhibitors’ probable target. High-throughput virtual screening and molecular docking were employed to find the hit drugs, and the drugs with the highest binding affinity were further evaluated using the molecular dynamics (MD) simulation. The virtual screening revealed that several kinase inhibitors could be considered potential inhibitors of ABCB1, ABCC1, and ABCG2, among which larotrectinib, entrectinib, and infigratinib showed the highest binding affinity, respectively. Based on the obtained results from MD simulation, these drugs can form strong interactions with the essential residues of the target proteins. In silico investigation revealed that larotrectinib, entrectinib, and infigratinib can target the key residues of the studied proteins. Therefore, these approved kinase inhibitors could be considered potential therapies for MDR cancers by targeting these transporters. Communicated by Ramaswamy H. Sarma

In Silico Study of Potential Small Molecule TIPE2 Inhibitors for the Treatment of Cancer

Context: Chronic inflammation has been linked to cancer since the 19th century. Tumor growth is supported by the proangiogenic factors that chronic inflammation requires. Polarized leukocytes initiate these angiogenic and tumorigenic factors. TIPE2, a transport protein, manages the cytoskeletal rearrangement that gives a polarized leukocyte its motility. Inhibition of this protein could lead to a therapeutic option for solid tumor cancers; however, no such inhibitors have been developed so far due to the large cavity size of the TIPE2 protein. Here we have examined possible small molecule inhibitors by combining structure-based and fragment-based drug design approaches. The highest binding ligands were complexed with the protein, and fragment libraries were docked with the complex with the intention of linking the hit compounds and fragments to design a more potent ligand. Three hit compounds were identified by in silico structure-based screening and a linked compound, C2–F14, of excellent binding affinity, was identified by linking fragments to the hit compounds. C2–F14 demonstrates good binding stability in molecular dynamic simulations and great predicted ADME properties. Methods: High throughput molecular docking calculations of mass libraries were performed using AutoDock Vina 1.1.2. Molecular docking of individual ligands was performed using AutoDock Vina with PyRx. Ligand libraries were prepared using OpenBabel, linked ligands were prepared using Avogadro. The protein was prepared using AutoDockTools-1.5.6. Protein-ligand complexes were visualized with PyMOL. Two- and three-dimensional representations of protein–ligand interactions were plotted with BIOVIA Discovery Studio Visualizer. In silico absorption, distribution, metabolism, and excretion (ADME) properties were calculated using SwissADME. Molecular dynamics simulations were conducted with GROMACS.

Integrated multi-omics analyses reveal Jorunnamycin A as a novel suppressor for muscle-invasive bladder cancer by targeting FASN and TOP1

BackgroundBladder cancer is a urological carcinoma with high incidence, among which muscle invasive bladder cancer (MIBC) is a malignant carcinoma with high mortality. There is an urgent need to develop new drugs with low toxicity and high efficiency for MIBC because existing medication has defects, such as high toxicity, poor efficacy, and side effects. Jorunnamycin A (JorA), a natural marine compound, has been found to have a high efficiency anticancer effect, but its anticancer function and mechanism on bladder cancer have not been studied.MethodsTo examine the anticancer effect of JorA on MIBC, Cell Counting Kit 8, EdU staining, and colony formation analyses were performed. Moreover, a xenograft mouse model was used to verify the anticancer effect in vivo. To investigate the pharmacological mechanism of JorA, high-throughput quantitative proteomics, transcriptomics, RT-qPCR, western blotting, immunofluorescence staining, flow cytometry, pulldown assays, and molecular docking were performed.ResultsJorA inhibited the proliferation of MIBC cells, and the IC50 of T24 and UM-UC-3 was 0.054 and 0.084 μM, respectively. JorA-induced significantly changed proteins were enriched in “cancer-related pathways” and “EGFR-related signaling pathways”, which mainly manifested by inhibiting cell proliferation and promoting cell apoptosis. Specifically, JorA dampened the DNA synthesis rate, induced phosphatidylserine eversion, and inhibited cell migration. Furthermore, it was discovered that fatty acid synthase (FASN) and topoisomerase 1 (TOP1) are the JorA interaction proteins. Using DockThor software, the 3D docking structures of JorA binding to FASN and TOP1 were obtained (the binding affinities were − 8.153 and − 7.264 kcal/mol, respectively).ConclusionsThe marine compound JorA was discovered to have a specific inhibitory effect on MIBC, and its potential pharmacological mechanism was revealed for the first time. This discovery makes an important contribution to the development of new high efficiency and low toxicity drugs for bladder cancer therapy.Graphical

In-vitro high-throughput library screening-Kinetics and molecular docking studies of potent inhibitors of α-glucosidase.

High throughput screening of synthetic compounds against vital enzymes is the way forward for the determination of potent enzyme inhibitors. In-vitro high throughput library screening of 258 synthetic compounds (comp. 1-258), was performed against α-glucosidase. The active compounds out of this library were investigated for their mode of inhibition and binding affinities towards α-glucosidase through kinetics as well as molecular docking studies. Out of all the compounds selected for this study, 63 compounds were found active within the IC50 range of 3.2 μM to 50.0 μM. The most potent inhibitor of α-glucosidase out of this library was the derivative of an oxadiazole (comp. 25). It showed the IC50 value of 3.23 ± 0.8 μM. Other highly active compounds were the derivatives of ethyl-thio benzimidazolyl acetohydrazide with IC50 values of 6.1 ± 0.5 μM (comp. 228), 6.84 ± 1.3 μM (comp. 212), 7.34 ± 0.3 μM (comp. 230) and 8.93 ± 1.0 μM (comp. 210). For comparison, the standard (acarbose) showed IC50 = 378.2 ± 0.12 μM. Kinetic studies of oxadiazole (comp. 25) and ethylthio benzimidazolyl acetohydrazide (comp. 228) derivatives indicated that Vmax and Km, both change with changing concentrations of inhibitors which suggests an un-competitive mode of inhibition. Molecular docking studies of these derivatives with the active site of α-glucosidase (PDB ID:1XSK), revealed that these compounds mostly interact with acidic or basic amino acid residues through conventional hydrogen bonds along with other hydrophobic interactions. The binding energy values of compounds 25, 228, and 212 were -5.6, -8.7 and -5.4 kcal.mol-1 whereas RMSD values were 0.6, 2.0, and 1.7 Å, respectively. For comparison, the co-crystallized ligand showed a binding energy value of -6.6 kcal.mol-1 along with an RMSD value of 1.1 Å. Our study predicted several series of compounds as active inhibitors of α-glucosidase including some highly potent inhibitors.

Structure based High-Throughput Virtual Screening, Molecular Docking and Molecular Dynamics Study of anticancer natural compounds against fimbriae (FimA) protein of Porphyromonas gingivalis in oral squamous cell carcinoma.

Oral cancer is among the most common cancer in the world. Tobacco, alcohol, and viruses have been regarded as a well- known risk factors of OCC however, 15% of OSCC cases occurred each year without these known risk factors. Recently a myriad of studies has shown that bacterial infections lead to cancer. Accumulated shreds of evidence have demonstrated the role of Porphyromonas gingivalis (P. gingivalis) in OSCC. The virulence factor FimA ofP. gingivalisactivates the oncogenic pathways in OSCC by upregulating various cytokines. It also led to the inactivation of a tumor suppressor protein p53. The present Insilico study uses High-Throughput Virtual Screening, molecular docking, and molecular dynamics techniques to find the potential compounds against the target protein FimA. The goal of this study is to identify the anti-cancer lead compounds retrieved from natural sources that can be used to develop potent drug molecules to treat P.gingivalis-related OSCC. The anticancer natural compounds library was screened to identify the potential lead compounds. Furthermore, these lead compounds were subjected to precise docking, and based on the docking score potential lead compounds were identified. The top docked receptor-ligand complex was subjected to molecular dynamics simulation. A study of this insilico finding provides potent lead molecules which help in the development of therapeutic drugs against the target protein FimA in OSCC.