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The farnesoid X receptor (FXR) is a crucial therapeutic target for treating non-alcoholic steatohepatitis (NASH). Although obeticholic acid (OCA) as a FXR agonist presents good efficacy, the safety data such as severe pruritus should be carefully considered. To discover new medications, we screen and choose the optimal compounds from ZINC15 database that may agonistically interact with FXR. We utilized the DS19 software to assist us in conducting the computer-aided structure based virtual screening to discover potential FXR agonists. After LibDock scores were determined by screening, their absorption, distribution, metabolism, excretion and toxicity predictions were examined. To determine the binding affinity between the chosen drugs and FXR, molecule docking was utilized. Molecular dynamics simulation was utilized to evaluate the stabilization of the ligand-FXR complex in its native environment. Higher binding affinity and stability with FXR were observed for ZINC000013374322 and ZINC000006036327, as two novel natural compounds, with lower rodent carcinogenicity, Ames mutagenicity, no hepatotoxicity and non-inhibitors of CYP2D6. They could stably exist in the environment, possess favorable potential energy and exert pharmacological effects at lower doses. Furthermore, ZINC000006036327 had lower skin irritancy and sensitization potential compared to OCA, also suggest the possibility of improved skin itching occurrence. ZINC000013374322 and ZINC000006036327 were found to be the best leading compounds to be FXR agonists. They are chosen as safe candidates for FXR target medicine, which play comparable pharmacological effects at lower doses.

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In recent years, significant progress has been made in the subject of nanotechnology, with a range of methods developed to synthesize precise-sized and shaped nanoparticles according to particular requirements. Often, the nanoparticles are created by employing dangerous reducing chemicals to reduce metal ions into uncharged nanoparticles. Green synthesis or biological approaches have been used recently to circumvent this issue because biological techniques are simple, inexpensive, safe, clean, and extremely productive. Nowadays, much research is being conducted on how different kinds of nanoparticles connect to proteins and nucleic acids using molecular docking models. Therefore, this review discusses the most recent advancements in molecular docking capacity to predict the interactions between various nanoparticles (NPs), such as ZnO, CuO, Ag, Au, and Fe3O4, and biological macromolecules.

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Histone deacetylases (HDACs) are critical epigenetic drug targets that have gained significant attention in the scientific community for the treatment of cancer. The currently marketed HDAC inhibitors lack selectivity for the various HDAC isoenzymes. Here, we describe our protocol for the discovery of novel potential hydroxamic acid based HDAC3 inhibitors through pharmacophore modeling, virtual screening, docking, molecular dynamics (MD) simulation and toxicity studies. The ten pharmacophore hypotheses were established, and their reliability was validated by different ROC (receiving operator curve) analysis. Among them, the best model (Hypothesis 9 or RRRA) was employed for searching SCHEMBL, ZINC and MolPort database to screen out hit molecules as selective HDAC3 inhibitors, followed by different docking stages. MD simulation (50 ns) and MMGBSA study were performed to study the stability of ligand binding modes and with the help of trajectory analysis, to calculate the ligand-receptor complex RMSD (root-mean-square deviation), RMSF (root-mean-square fluctuation) and H-bond distance, etc. Finally, in-silico toxicity studies were performed on top screened molecules and compared with reference drug SAHA and established structure-activity relationship (SAR). The results indicated that compound 31, with high inhibitory potency and less toxicity (probability value 0.418), is suitable for further experimental analysis.Communicated by Ramaswamy H. Sarma.

Pharmacophore modeling and virtual screening were performed with hydroxamic acid derivatives as HDAC3 inhibitors.MD simulation was performed for 50 ns time duration for selected protein-ligand complexes.SAR and toxicity studies (using TOPKAT tool) were performed.The results of these studies might be valuable in the further design and development of more potent HDAC3 inhibitors.

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Natural product-based structural templates have immensely shaped small molecule drug discovery, and new biogenic natural products have randomly provided the leads and molecular targets in anti-analgesic activity spheres. Pain relief achieved through opiates and non-steroidal anti-inflammatory drugs (NSAIDs) has been under constant scrutiny owing to their tolerance, dependency, and other organs toxicities and tissue damage, including harm to the gastrointestinal tract (GIT) and renal tissues. A new, 3',4',6'-triacetylated-glucoside, 2-O-ß-D-(3',4',6'-tri-acetyl)-glucopyranosyl-3-methyl pentanoic acid was obtained from Ficus populifolia, and characterized through a detailed NMR spectroscopic analysis, i.e., 1H-NMR, 13C-DEPT-135, and the 2D nuclear magnetic resonance (NMR) correlations. The product was in silico investigated for its analgesic prowess, COX-2 binding feasibility and scores, drug likeliness, ADMET (absorption, distribution, metabolism, excretion, and toxicity) properties, possible biosystem's toxicity using the Discovery Studio®, and other molecular studies computational software programs. The glycosidic product showed strong potential as an analgesic agent. However, an in vivo evaluation, though at strong levels of pain-relieving action, was estimated on the compound's extract owing to the quantity and yield issues of the glycosidic product. Nonetheless, the F. populifolia extract showed the analgesic potency in eight-week-old male mice on day seven of the administration of the extract's dose in acetic acid-induced writhing and hot-plate methods. Acetic acid-induced abdominal writhing for all the treated groups decreased significantly (p < 0.0001), as compared to the control group (n = 6) by 62.9%, 67.9%, and 70.9% of a dose of 100 mg/kg (n = 6), 200 mg/kg (n = 6), and 400 mg/kg (n = 6), respectively. Similarly, using the analgesia meter, the reaction time to pain sensation increased significantly (p < 0.0001), as compared to the control (n = 6). The findings indicated peripheral and central-nervous-system-mediated analgesic action of the product obtained from the corresponding extract.

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As a class I carcinogen, aflatoxin B1 (AFB1) contamination in foods and feeds accounts for 75 % of the total mycotoxin contamination. In this work, a simple and reliable surface-enhanced Raman spectroscopy (SERS) method for sensitive and selective detection of AFB1 in peanut samples integrated with dummy molecularly imprinted polymers (DMIPs) is developed. N-isopropylacrylamide (NIPAM) and 7-ethoxycoumarin (7-EOC) are chosen as monomer and dummy template, respectively and their ratio was screened through molecular design in both of kinetic and static adsorption views to form the optimal DMIPs. As-prepared dummy molecularly imprinted solid-phase extraction (DMISPE) could selectively enrich AFB1 from peanut samples. Finally, a liquid-liquid interface self-assembly constructed thioctic acid-decorated AgNPs monolayer film (TA-AgNPs MF) as a SERS-active substrate is employed to determine the amount of AFB1 eluted from DMISPE. SERS assay shows high detection sensitivity for AFB1 in peanut samples with limit of detection of 0.1 µg L-1 and a linear concentration relationship range from 0.1 to 10 µg L-1.

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Despite great progress, the current cancer treatments often have obvious toxicity and side effects. and a poor prognosis (some patients). One of the reasons for the poor prognosis is that certain enzymes prevent anticancer drugs from killing tumor cells. AKT1 is involved in regulating PI3K/AKT/mTOR, a tumor-generating pathway. Ipatasertib, a highly selective inhibitor of AKT1, is widely used in the treatment of tumors. In this study, many structural and biochemical methodswere used to find better AKT1(Threonine Kinase 1) inhibitors, which laid a foundation for the further development of AKT1 inhibitors and provided new drugs for the treatment of tumors. ZINC15 database and Discovery Studio 4.5, a computer-aided drug screening software with many modules (LibDock for virtual screening, ADME (Absorption, Distribution, Metabolism, Excretion) and TOPKAT (toxicity prediction module) for the toxicity and properties analysis, and MD simulation for stability prediction), were employed. CCK8 assay, ELISA assay genicity and higher tolerance to cytochrome P4502D6. MD simulations indicated they could bind with AKT1 stably in the natural environment. The cell experiment and specific assay for AKT1 inhibition showed they could inhibit the proliferation and AKT1 expression of MG63 cells (Osteosarcoma cells). Moreover, these novel compounds with structural modifications can be potential contributors that lead to further rational drug design for targeting AKT1.AbbreviationAKT1, AKT Serine/Threonine Kinase 1; ADME, absorption, distribution, metabolism, excretion; TOPKAT, toxicity prediction by Computer assisted technology; CCK8, Cell Counting Kit 8; ELISA, Enzyme-linked immunosorbent assay; CYP2D6, cytochrome P4502D6 inhibition; GBM, Glioblastoma; AGC kinase, protein kinase A, G, and C families (PKA, PKC, PKG); PKB, protein kinase B; PAM pathway, PI3K/AKT/mTOR pathway; OS, overall survival; PFS, progression-free survival; LD50, lethal dose half in rats; LOAEL, lowest observed adverse effect level; NPT, normal pressure and temperature; PME, particle mesh Ewald; LINCS, linear constraint solver; RMSD, root-mean-square deviation; BBB, blood-brain barrier; DS, Discovery Studio; DTP, Developmental toxicity potential; PPB, Plasma protein binding; MTD, Maximum Tolerated Dosage; AB, Aerobic Biodegradability; NTP, US. National Toxicology Program; DTP, developmental toxicity potential.

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Cysteine-based mesenchymal-epithelial transition (c-Met) is a receptor tyrosine kinase that plays a definitive role during cancer progression and was identified as a possible target for anti-angiogenesis drugs. In the present study, different protocols of computer-based drug design were performed. Construction of predictive pharmacophore model using HypoGen algorithm resulted in a validated model of four features of positive ionizable, hydrogen bond acceptor, hydrophobic, and ring aromatic features with a correlation coefficient of 0.87, a configuration cost of 14.95, and a cost difference of 357.92. The model revealed a promising predictive power and had >90% probability of representing true correlation with the activity data. The model was established using Fisher's validation test at the 95% confidence level and test set prediction (r = 0.96), furthermore, the model was validated by mapping of set of compounds undergoing clinical trials as class Ⅱ c-met inhibitors. The generated valid pharmacophore model was then anticipated for virtual screening of three data bases. Moreover, scaffold hopping using replace fragments protocol was implemented. Hits generated were filtered according to Lipinski's rule; 510 selected hits were anatomized and subjected to molecular docking studies into the crystal structure of c-Met kinase. The good correlation between docking scores and ligand pharmacophore mapping fit values provided a reliable foundation for designing new potentially active candidates that may target c-Met kinase. Eventually, eight hits were selected as potential leads. Subsequently, seven (Hits) have displayed a higher dock score and demonstrated key residue interactions with stable molecular dynamics simulation. Therefore, these c-Met kinase inhibitors may further serve as new chemical spaces in designing new compounds.

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Introduction: Phosphoinositide 3-kinase gamma (PI3Kγ) has been regarded as a promising drug target for the treatment of various diseases, and the diverse physiological roles of class I PI3K isoforms (α, ß, δ, and γ) highlight the importance of isoform selectivity in the development of PI3Kγ inhibitors. However, the high structural conservation among the PI3K family makes it a big challenge to develop selective PI3Kγ inhibitors. Objectives: A novel machine learning-based virtual screening with multiple PI3Kγ protein structures was developed to discover novel PI3Kγ inhibitors. Methods: A large chemical database was screened using the virtual screening model, the top-ranked compounds were then subjected to a series of bio-evaluations, which led to the discovery of JN-KI3. The selective inhibition mechanism of JN-KI3 against PI3Kγ was uncovered by a theoretical study. Results: 49 hits were identified through virtual screening, and the cell-free enzymatic studies found that JN-KI3 selectively inhibited PI3Kγ at a concentration as low as 3,873 nM but had no inhibitory effect on Class IA PI3Ks, leading to the selective cytotoxicity on hematologic cancer cells. Meanwhile, JN-KI3 potently blocked the PI3K signaling, finally led to distinct apoptosis of hematologic cell lines at a low concentration. Lastly, the key residues of PI3Kγ and the structural characteristics of JN-KI3, which both would influence γ isoform-selective inhibition, were highlighted by systematic theoretical studies. Conclusion: The developed virtual screening model strongly manifests the robustness to find novel PI3Kγ inhibitors. JN-KI3 displays a specific cytotoxicity on hematologic tumor cells, and significantly promotes apoptosis associated with the inhibition of the PI3K signaling, which depicts PI3Kγ as a potential target for the hematologic tumor therapy. The theoretical results reveal that those key residues interacting with JN-KI3 are less common compared to most of the reported PI3Kγ inhibitors, indicating that JN-KI3 has novel structural characteristics as a selective PIK3γ inhibitor.

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A large analysis of the signal transducer and activator of transcription (STAT3) in cancer is currently being carried out. It regulates gene expression, which is required for normal cellular functions such as differentiation, cell growth, proliferation, survival, maturation, and immunity. A ligand-based pharmacophore model was created using 3 D QSAR pharmacophore generation methodology in Discovery studio 4.1 clients to imagine structurally diverse novel chemical entities as STAT3 inhibitors with improved efficacy. Chemical properties of 48 different derivatives were included in the training package. Hypo1 was chosen as the query model for screening 1,45,000 drug-like molecules from the SPECS database, with these molecules subjected to the Lipinski rule of 5, Verber's rule, and SMART filtration. After filtration, the molecule was examined further using molecular docking analysis on the active site of STAT3. The binding interaction(s) and pharmacophore mapping were used to select the 19 possible inhibitory molecules. These 19 hits were then tested for toxicity using the TOPKAT software. In MD simulations and MM-PBSA calculations, the tested compound specs 28 provided the best results, suggesting that this ligand has the ability to inhibit more effectively. Based in-silico finding 19 compounds are subjected to in vitro anticancer activity against MDA-MB-231 and MCF-7 cell lines. Based on results compounds specs 11 and specs 13 shows significant activity compared to other compounds and these compounds were subjected to apoptosis assay. The tested compounds induced morphologic changes were dose and time dependent by which all the tested compound exhibits stronger anti-tumor effects.Communicated by Ramaswamy H. Sarma.

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Two series of fluoro substituted-anilino derivatives of naturally occurring hydroxybenzoquinone and hydroxynaphthoquinone were synthesized using TFA as catalyst to improve the product yield. Recently, fluorine containing compounds are being used as anticancer drugs. The aim of this study is to find compounds that are active against melanoma cells. This six new fluoro substituted quinone compounds were synthesized and characterized. All of these compounds were then subjected to molecular docking studies against B-raf protein using Discovery Studio 4.0 and the binding affinities were calculated. The energy scores of in silico analysis revealed that all the compounds exhibited better binding affinity towards B-raf protein. Moreover, all the derivatives and the parent compounds, embelin and plumbagin along with standard drug, PLX4032 were investigated for its in vitro cytotoxicity in A375 cell lines (Melanoma) and in vitro ELISA assay in B-raf isolated from melanoma cells. Among them, 5-(3-chloro-4-trifluoromethoxy-phenylamino)-2-hydroxy-3-undecyl-[1,4]benzoquinone exhibited lower cell viability with lowest LC50 of 12.25 µg/mL and thus poses suitability to be a lead molecule for further drug discovery.Communicated by Ramaswamy H. Sarma.

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Targeting Polo-like kinase 1 (Plk1) by molecular inhibitors is being a promising approach for tumor therapy. Nevertheless, insufficient methodical analyses have been done to characterize the interactions inside the Plk1 binding pocket. In this study, an extensive combined ligand and structure-based drug design workflow was conducted to data-mine the structural requirements for Plk1 inhibition. Consequently, the binding modes of 368 previously known Plk1 inhibitors were investigated by pharmacophore generation technique. The resulted pharmacophores were engaged in the context of Genetic function algorithm (GFA) and Multiple linear regression (MLR) analyses to search for a prognostic QSAR model. The most successful QSAR model was with statistical criteria of (r2277 = 0.76, r2adj = 0.76, r2pred = 0.75, Q2 = 0.73). Our QSAR-selected pharmacophores were validated by Receiver Operating Characteristic (ROC) curve analysis. Later on, the best QSAR model and its associated pharmacophoric hypotheses (HypoB-T4-5, HypoI-T2-7, HypoD-T4-3, and HypoC-T3-3) were used to identify new Plk1 inhibitory hits retrieved from the National Cancer Institute (NCI) database. The most potent hits exhibited experimental anti-Plk1 IC50 of 1.49, 3.79. 5.26 and 6.35 µM. Noticeably, our hits, were found to interact with the Plk1 kinase domain through some important amino acid residues namely, Cys67, Lys82, Cys133, Phe183, and Asp194.

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The aim of this research was to screen the ZINC15 database to select lead compounds and drug candidates which can inhibit B-RAF (V600E). In order to identify drugs potentially inhibited B-RAF (V600E), numerous modules of Discovery Studio 4.5 were employed. Structure-based screening using LibDock was carried out followed by ADME (absorption, distribution, metabolism, excretion) and toxicity prediction. CDOCKER was performed to demonstrate the binding affinity and mechanism between ligands and B-RAF(V600E). To evaluate whether ligand-receptor complexes were stable, molecular dynamics were employed. Two novel natural compounds (ZINC000100168592 and ZINC000049784088) from ZINC15 database were found binding to B-RAF(V600E) with more favorable interaction energy in comparison with the reference drug Vemurafenib. Also, they were predicted with less ames mutagenicity, rodent carcinogenicity, non-developmental toxic potential and tolerance to cytochrome P450 2D6 (CYP2D6). The molecular dynamics simulation analysis indicated that the compound-B-RAF(V600E) complexes had more favorable potential energy compared with Vemurafenib and they can exist in natural environments stably. The result of this study shows that ZINC000100168592 and ZINC000049784088 are ideal leading potential compounds to inhibit B-RAF(V600E). The findings of this study and these selected drug candidates greatly contributed to the medication design and improvement of B-RAF(V600E) and other proteins.

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Phosphorylation of myosin regulatory light chain (MRLC) can regulate muscle contraction and thus affect actomyosin dissociation and meat quality. The objective of this study was to explore the mechanism by how MRLC phosphorylation regulates actomyosin dissociation and thus develop strategies for improving meat quality. Here, the phosphorylation status of MRLC was modulated by myosin light chain kinase and myosin light chain kinase inhibitor. MRLC phosphorylation at Ser17 decreased the kinetic energy and total energy of actomyosin, thus stabilized the structure, facilitating the interaction between myosin and actin; this was one possible way that MRLC phosphorylation at Ser17 negatively affects actomyosin dissociation. Moreover, MRLC phosphorylation at Ser17 was beneficial to the formation of ionic bonds, hydrogen bonds, and hydrophobic interaction between myosin and actin, and was the second possible way that MRLC phosphorylation at Ser17 negatively affects actomyosin dissociation.

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This study aimed to identify effective targets for carcinogenesis of primary myelofibrosis (PMF), as well as to screen ideal lead compounds with potential inhibition effect on Janus kinase 2 to contribute to the medication design and development. Gene expression profiles of GSE26049, GSE53482, GSE61629 were obtained from the Gene Expression Omnibus database. The differentially expressed genes were identified, and functional enrichment analyses such as Gene Ontology, protein-protein interaction network etc., were performed step by step. Subsequently, highly-precise computational techniques were conducted to identify potential inhibitors of JAK2. A series of structural biology methods including virtual screening, ADMET (absorption, distribution, metabolism, excretion, and toxicity) prediction, molecule docking, molecular dynamics simulation etc., were implemented to discover novel natural compounds. Results elucidated that PMF patients had abnormal LCN2, JAK2, MMP8, CAMP, DEFA4, LTF, MPO, HBD, STAT4, EBF1 mRNA expression compared to normal patients. Functional enrichment analysis revealed that these genes were mainly enriched in erythrocyte differentiation, neutrophil degranulation and killing cells of other organisms. Two novel natural compounds, ZINC000013513540 and ZINC000004099068 were found binding to JAK2 with favorable interaction energy together with high binding affinity. They were predicted with non-Ames mutagenicity, low-rodent carcinogenicity, less developmental toxicity potential as well as non-toxicity with liver. Molecular dynamics simulation demonstrated that these two complexes: ZINC000013513540-JAK2 and ZINC000004099068-JAK2 could exist stably under natural circumstances. In conclusion, this study revealed hub genes in the carcinogenesis of PMF. ZINC000013513540 and ZINC000004099068 were promising drugs in dealing with PMF. This study may also accelerate exploration of new drugs.

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Background: Lack of treatment of novel Coronavirus disease led to the search of specific antivirals that are capable to inhibit the replication of the virus. The plant kingdom has demonstrated to be an important source of new molecules with antiviral potential. Purpose: The present study aims to utilize various computational tools to identify the most eligible drug candidate that have capabilities to halt the replication of SARS-COV-2 virus by inhibiting Main protease (Mpro) enzyme. Methods: We have selected plants whose extracts have inhibitory potential against previously discovered coronaviruses. Their phytoconstituents were surveyed and a library of 100 molecules was prepared. Then, computational tools such as molecular docking, ADMET and molecular dynamic simulations were utilized to screen the compounds and evaluate them against Mpro enzyme. Results: All the phytoconstituents showed good binding affinities towards Mpro enzyme. Among them laurolitsine possesses the highest binding affinity i.e. -294.1533 kcal/mol. On ADMET analysis of best three ligands were simulated for 1.2 ns, then the stable ligand among them was further simulated for 20 ns. Results revealed that no conformational changes were observed in the laurolitsine w.r.t. protein residues and low RMSD value suggested that the Laurolitsine-protein complex was stable for 20 ns. Conclusion: Laurolitsine, an active constituent of roots of Lindera aggregata, was found to be having good ADMET profile and have capabilities to halt the activity of the enzyme. Therefore, this makes laurolitsine a good drug candidate for the treatment of COVID-19.

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BACKGROUND: A newer trend has been seen recently to reuse the conventional drugs with distinct indications for the newer applications to speed up the drug discovery and development based on earlier records and safety data. Most of the non-cancerous agents could afford a little or tolerable side effects in individuals. However, the repositioning of these non-cancerous agents for successful anticancer therapy is an outstanding strategy for future anti-cancer drug development. Since more diverse and selective cancer drug targets are being discovered and developed, the approved drug collections are particularly useful to quickly identify clinically advanced anticancer drugs against those targets. OBJECTIVE: Antihelminthic drugs such as Mebendazole and Albendazole (Benzimidazole class) have been reported to exhibit cytotoxicity (or anticancer activities) against several types of cancer. Therefore, this study aims to repurpose the benzimidazole scaffold for breast cancer treatment. METHODS: In the present study, three hydrazone analogs having a benzimidazole motif in their structural frame were synthesized. Their in-silico binding studies against HER2 receptor (PDB ID: 4LQM) and ADMET studies were carried out using Accelrys drug discovery studio 4.1. Cytotoxicity of the synthesized compounds against HER2 overexpressed MCF-7 cell lines was determined by MTT assay. RESULTS: One of the compounds 2-[2-(2,4-dinitrophenyl)hydrazinylidene]-2,3-dihydro-1H-benzimidazole (U1) has shown good cytotoxicity when compared to the standard Lapatinib, which is a well known HER2 inhibitor. CONCLUSIONS: Thus, the designed benzimidazole scaffold might serve as the best leads for treating breast cancer, which is additionally confirmed by performing their docking study via Accelrys discovery studio.

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It has been shown that methylene blue has antimicrobial properties although few studies have determined its minimum inhibitory concentration (MIC), which is the gold standard used to measure antimicrobial activity. The exact antimicrobial mode of action of methylene blue is still unclear and to our knowledge no pharmacophore model has yet been created to investigate methylene blue's mode of action. The aim of this study was to determine the MIC of methylene blue and a number of its analogous against Staphylococcus aureus, Staphylococcus epidermidis, Escherichia coli, Klebsiella pneumoniae, Salmonella enterica and Candida albicans, and to use these data to develop and validate a common feature pharmacophore model. Three statistical metrics, i.e. the enrichment factor (EF), hit rate (HR) and the area under the curve of a receiver operator characteristic (ROC-AUC), were used to determine the pharmacophore model's ability to differentiate between active/decoy compounds. The validated pharmacophore model was used to map similar antibacterial compounds in an attempt to elucidate methylene blue's antimicrobial mode of action. Most test compounds only had activity against S. aureus, S. epidermidis and K. pneumoniae. Dimethyl methylene blue, new methylene blue and acriflavine proved to be the most active compounds against S. aureus [1 µg/ml (dimethyl methylene blue); 4 µg/ml (new methylene blue); 8 µg/ml (acriflavine)], S. epidermidis [1 µg/ml (dimethyl methylene blue); 4 µg/ml (new methylene blue); 2 µg/ml (acriflavine)] and K. pneumoniae [8 µg/ml (dimethyl methylene blue); 0.5 µg/ml (new methylene blue); 2 µg/ml (acriflavine)]. A common feature pharmacophore model was created (rank score: 26.664, max. fit value: 4), which was able to accurately identify active methylene blue analogous out of the test set (EF2%: 51, HR2%: 100%, ROC-AUC: 1.00 ± 0.00). Six phenothiazine derivatives with known antibacterial activity had high fit values when mapped with the validated pharmacophore model, i.e. >3.4. Dimethyl methylene blue, new methylene blue and acriflavine had potent antibacterial activity against S. aureus, S. epidermidis and K. pneumoniae. The MIC data will allow other researchers to compare the activity across different laboratories. The common feature pharmacophore model was able to identify methylene blue analogous with known in vitro antibacterial activity out of a database containing active/decoy compounds and highlighted the importance of two hydrophobic features, an aromatic feature and a hydrogen bond acceptor. The validated pharmacophore model also correctly mapped six phenothiazine derivatives with known antibacterial activity suggesting that they may share a common antibacterial mechanism of action.

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Alzheimer's disease (AD), apparently the most widespread reason behind dementia, is delineated by a continuous cognitive weakening in the aged. During its progression, N-methyl-D-aspartate receptor (NMDAR) antagonists are known to play a pivotal part in the mechanisms of learning and memory. Since there is an unmet medical need for the treatment of AD, we aim to identify possible chemical compounds targeted toward N-methyl-D-aspartate receptors. Three-dimensional models are developed to unveil some of the essential characteristics of the N-methyl-D-aspartate receptors by using a collection of already discovered N-methyl-D-aspartate receptor inhibitors. This is followed by virtual screening, which results in novel chemical compounds having the potential to inhibit N-methyl-D-aspartate receptors. Molecular docking studies and analysis promulgated two lead compounds with a high LibDock score. The compounds are shortlisted based on high estimated activity, fit values, LibDock score, no violation of Lipinski's, and availability for procuring. Finally, the shortlisted compounds are tested by employing in vivo studies, which we further propose as potential NMDA inhibitors for treating AD.

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OBJECTIVES: To screen and identify ideal leading compounds from a drug library (ZINC15 database) with potential inhibition of aminopeptidase N(CD13) to contribute to medication design and development. RESULTS: Two novel natural compounds, ZINC000000895551 and ZINC000014820583, from the ZINC15 database were found to have a higher binding affinity and more favorable interaction energy binding with CD13 with less rodent carcinogenicity, Ames mutagenicity, and non-inhibition with cytochrome P-450 2D6. Molecular dynamics simulation analysis suggested that the 2 complexes, ZINC000000895551-CD13 and ZINC000014820583-CD13, have favorable potential energy, and exist stably in the natural circumstances. CONCLUSION: This study discovered that ZINC000000895551 and ZINC000014820583 were ideal leading compounds to be inhibitions targeting to CD13. These compounds were selected as safe drug candidates as CD13 target medication design and improvement. MATERIALS AND METHOD: Potential inhibitors of CD13 were identified using a series of computer-aided structural and chemical virtual screening techniques. Structure-based virtual screening was carried out to calculate LibDock scores, followed by analyzing their absorption, distribution, metabolism, and excretion and toxicity predictions. Molecule docking was employed to reveal binding affinity between the selected compounds and CD13. Molecular dynamics simulation was applied to evaluate stability of the ligand-CD13 complex under natural environment.

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BACKGROUND: 3-Phosphoinositide Dependent Protein Kinase-1 (PDK1) is being lately considered as an attractive and forthcoming anticancer target. A Protein Data Bank (PDB) cocrystallized crystal provides not only rigid theoretical data but also a realistic molecular recognition data that can be explored and used to discover new hits. OBJECTIVE: This incited us to investigate the co-crystallized ligands' contacts inside the PDK1 binding pocket via a structure-based receptor-ligand pharmacophore generation technique in Discovery Studio 4.5 (DS 4.5). METHODS: Accordingly, 35 crystals for PDK1 were collected and studied. Every single receptorligand interaction was validated and the significant ones were converted into their corresponding pharmacophoric features. The generated pharmacophores were scored by the Receiver Operating Characteristic (ROC) curve analysis. RESULTS: Consequently, 169 pharmacophores were generated and sorted, 11 pharmacophores acquired good ROC-AUC results of 0.8 and a selectivity value above 8. Pharmacophore 1UU3_2_01 was used in particular as a searching filter to screen NCI database because of its acceptable validity criteria and its distinctive positive ionizable feature. Several low micromolar PDK1 inhibitors were revealed. The most potent hit illustrated anti-PDK1 IC50 values of 200 nM with 70% inhibition against SW480 cell lines. CONCLUSION: Eventually, the active hits were docked inside the PDK1 binding pocket and the recognition points between the active hits and the receptor were analyzed that led to the discovery of new scaffolds as potential PDK1 inhibitors.

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