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A novel series of 4-aminopiperidin-3,4-dihyroquinazoline-2-uracil derivatives (9a-9 L) were logically designed and synthesized as potent DPP4 inhibitors as antidiabetic agents. Chemical structure of all new compounds were confirmed by different spectroscopic methods. The designed compounds were evaluated using a MAK 203 kit as DPP4 inhibitors in comparison with Sitagliptin. The biological evaluation revealed that compound 9i bearing chloro substitution on phenyl moiety of 6-bromo quinazoline ring had promising inhibitory activity with IC 50  = 9.25 ± 0.57 µM. The toxicity test of all compounds confirmed safety profile of them. Kinetic studies showed that compound 9i exhibited a competitive-type inhibition with a K i value of 12.01 µM. Computational approach supported the rationality of our design strategy, as 9i represented appropriate binding interactions with the active sites of DPP4 target. MD simulation outputs validated the stability of ligand 9i at DPP4 active site. Also, Density functional theory (DFT) including HOMO-LUMO energies, ESP map, thermochemical parameters, and theoretical IR spectrum was employed to study the reactivity descriptors of 9i and 9a as the most and least potent compounds respectively. Based on the DFT study, compound 9i was softer and, as a result, more reactive than 9a. Taken together, our results showed the potential of 4-aminopiperidin-3,4-dihyroquinazoline-2-uracil derivatives as promising candidates for developing some novel DPP4 inhibitors for managing of type 2 diabetes., (© 2024. The Author(s).)

Tyrosinase, a metalloprotein enzyme, plays a crucial role in melanin synthesis by hydroxylating L-tyrosine to L-dopa. However, the accumulation of melanin can lead to hyperpigmented spots, raising aesthetic concerns. In this study, we developed a pipeline to repurpose FDA-approved drugs as potential tyrosinase inhibitors. A structure-based screening study was conducted using 1,650 drugs to identify probable inhibitors based on binding energies. From the cluster analysis of binding interaction profiles, 16 compounds were selected as candidates. Montelukast emerged as the final candidate due to its favorable ADME properties. Bioassay evaluation revealed an IC50 value of 14.79±0.87 μM for Montelukast, compared to kojic acid (IC50=31.02±2.01 μM). Molecular dynamics simulation and g_MMPBSA free energy calculation studies were performed for the Tyrosinase-Montelukast complex. These findings enhance our understanding of Tyrosinase-Montelukast interactions and underscore Montelukast's potential as a tyrosinase inhibitor. This could have implications in dermatological applications and beyond, suggesting Montelukast as a promising candidate for further development in this regard., (© 2024 Wiley-VHCA AG, Zurich, Switzerland.)

Inflammation is an immune system response triggered by pathogens, damaged cells, or stimuli. Some regulatory enzymes, such as phosphodiesterase, hyaluronidase, collagenase, and lipoxygenase, play an essential role in the inflammatory process. Polyphenolic compounds, such as flavonoids, are active suppressors of inflammatory cytokines, modulators of transcription factors, and inflammation-related pathways. A set of flavonoid structures was screened and docked against inflammation pathway enzymes. Amentoflavone has been shown to cause interactions with phosphodiesterase enzymes, while Bilobetin and Silibinin demonstrated an increase in binding energy with collagenase enzymes. The retrieved compounds from the docking study were subjected to DFT theory. The results showed that the LUMO orbital is located on the flavonoid part. The thermochemical parameters indicated that Silibinin is more stable than other compounds. The ADMET profile predicted that Silibinin can be used orally among the compounds. Silibinin can be introduced as a promising anti-inflammatory agent demonstrating phosphodiesterase and collagenase inhibitory properties.

Lysine deacetylase inhibitors (KDACis) are approved drugs for cutaneous T cell lymphoma (CTCL), peripheral T cell lymphoma (PTCL), and multiple myeloma, but many aspects of their cellular mechanism of action (MoA) and substantial toxicity are not well understood. To shed more light on how KDACis elicit cellular responses, we systematically measured dose-dependent changes in acetylation, phosphorylation, and protein expression in response to 21 clinical and pre-clinical KDACis. The resulting 862,000 dose-response curves revealed, for instance, limited cellular specificity of histone deacetylase (HDAC) 1, 2, 3, and 6 inhibitors; strong cross-talk between acetylation and phosphorylation pathways; localization of most drug-responsive acetylation sites to intrinsically disordered regions (IDRs); an underappreciated role of acetylation in protein structure; and a shift in EP300 protein abundance between the cytoplasm and the nucleus. This comprehensive dataset serves as a resource for the investigation of the molecular mechanisms underlying KDACi action in cells and can be interactively explored online in ProteomicsDB., Competing Interests: Declaration of interests B.K. is a cofounder and shareholder of OmicScouts and MSAID. He has no operational role in either company. J.Z. is currently employed at AstraZeneca, and R.S. is employed at Servier, but all work in this study was conducted while they were at TUM and DKFZ, respectively., (Copyright © 2024 The Author(s). Published by Elsevier Inc. All rights reserved.)

Proteomics is making important contributions to drug discovery, from target deconvolution to mechanism of action (MoA) elucidation and the identification of biomarkers of drug response. Here we introduce decryptE, a proteome-wide approach that measures the full dose-response characteristics of drug-induced protein expression changes that informs cellular drug MoA. Assaying 144 clinical drugs and research compounds against 8,000 proteins resulted in more than 1 million dose-response curves that can be interactively explored online in ProteomicsDB and a custom-built Shiny App. Analysis of the collective data provided molecular explanations for known phenotypic drug effects and uncovered new aspects of the MoA of human medicines. We found that histone deacetylase inhibitors potently and strongly down-regulated the T cell receptor complex resulting in impaired human T cell activation in vitro and ex vivo. This offers a rational explanation for the efficacy of histone deacetylase inhibitors in certain lymphomas and autoimmune diseases and explains their poor performance in treating solid tumors., (© 2024. The Author(s).)

DPP4 inhibitors can control glucose homeostasis by increasing the level of GLP-1 incretins hormone due to dipeptidase mimicking. Despite the potent effects of DPP4 inhibitors, these compounds cause unwanted toxicity attributable to their effect on other enzymes. As a result, it seems essential to find novel and DPP4 selective compounds. In this study, we introduce a potent and selective DPP4 inhibitor via structure-based virtual screening, molecular docking, molecular dynamics simulation, MM/PBSA calculations, DFT analysis, and ADMET profile. The screened compounds based on similarity with FDA-approved DPP4 inhibitors were docked towards the DPP4 enzyme. The compound with the highest docking score, ZINC000003015356, was selected. For further considerations, molecular docking studies were performed on selected ligands and FDA-approved drugs for DPP8 and DPP9 enzymes. Molecular dynamics simulation was run during 200 ns and the analysis of RMSD, RMSF, Rg, PCA, and hydrogen bonding were performed. The MD outputs showed stability of the ligand-protein complex compared to available drugs in the market. The total free binding energy obtained for the proposed DPP4 inhibitor was more negative than its co-crystal ligand (N7F). ZINC000003015356 confirmed the role of the five Lipinski rule and also, have low toxicity parameter according to properties. Finally, DFT calculations indicated that this compound is sufficiently soft., (© 2024. The Author(s).)

Some studies have investigated the potential role of transposable elements (TEs) in COVID-19 pathogenesis and complications. However, to the best of our knowledge, there is no study to examine the possible association of TE expression in cell functions and its potential role in COVID-19 immune response at the single-cell level. In this study, we reanalyzed single-cell RNA seq data of bronchoalveolar lavage (BAL) samples obtained from six severe COVID-19 patients and three healthy donors to assess the probable correlation of TE expression with the immune responses induced by the severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) in COVID-19 patients. Our findings indicate that the expansion of myeloid-derived suppressor cells (MDSCs) may be a characteristic feature of COVID-19. Additionally, a significant increase in TE expression in MDSCs was observed. This upregulation of TEs in COVID-19 may be linked to the adaptability of these cells in response to their microenvironments. Furthermore, it appears that the identification of overexpressed TEs by pattern recognition receptors (PRRs) in MDSCs may enhance the suppressive capacity of these cells. Thus, this study emphasizes the crucial role of TEs in the functionality of MDSCs during COVID-19.

Kinase inhibitors (KIs) are important cancer drugs but often feature polypharmacology that is molecularly not understood. This disconnect is particularly apparent in cancer entities such as sarcomas for which the oncogenic drivers are often not clear. To investigate more systematically how the cellular proteotypes of sarcoma cells shape their response to molecularly targeted drugs, we profiled the proteomes and phosphoproteomes of 17 sarcoma cell lines and screened the same against 150 cancer drugs. The resulting 2550 phenotypic profiles revealed distinct drug responses and the cellular activity landscapes derived from deep (phospho)proteomes (9-10,000 proteins and 10-27,000 phosphorylation sites per cell line) enabled several lines of analysis. For instance, connecting the (phospho)proteomic data with drug responses revealed known and novel mechanisms of action (MoAs) of KIs and identified markers of drug sensitivity or resistance. All data is publicly accessible via an interactive web application that enables exploration of this rich molecular resource for a better understanding of active signalling pathways in sarcoma cells, identifying treatment response predictors and revealing novel MoA of clinical KIs., (© 2023. The Author(s).)

Substantial efforts are underway to deepen our understanding of human brain morphology, structure, and function using high-resolution imaging as well as high-content molecular profiling technologies. The current work adds to these approaches by providing a comprehensive and quantitative protein expression map of 13 anatomically distinct brain regions covering more than 11,000 proteins. This was enabled by the optimization, characterization, and implementation of a high-sensitivity and high-throughput microflow liquid chromatography timsTOF tandem mass spectrometry system (LC-MS/MS) capable of analyzing more than 2,000 consecutive samples prepared from formalin-fixed paraffin embedded (FFPE) material. Analysis of this proteomic resource highlighted brain region-enriched protein expression patterns and functional protein classes, protein localization differences between brain regions and individual markers for specific areas. To facilitate access to and ease further mining of the data by the scientific community, all data can be explored online in a purpose-built R Shiny app (https://brain-region-atlas.proteomics.ls.tum.de)., (© 2023 The Authors. Published under the terms of the CC BY NC ND 4.0 license.)

Glucocorticoids have been used in the treatment of many diseases including inflammatory and autoimmune diseases. Despite the wide therapeutic effects of synthetic glucocorticoids, the use of these compounds has been limited due to side effects such as osteoporosis, immunodeficiency, and hyperglycaemia. To this end, extensive studies have been performed to discover new glucocorticoid modulators with the aim of increasing affinity for the receptor and thus less side effects. In the present work, structure-based virtual screening was used for the identification of novel potent compounds with glucocorticoid effects. The molecules derived from ZINC database were screened on account of structural similarity with some glucocorticoid agonists as the template. Subsequently, molecular docking was performed on 200 selected compounds to obtain the best steroidal and non-steroidal conformations. Three compounds, namely ZINC_000002083318, ZINC_000253697499 and ZINC_000003845653, were selected with the binding energies of -11.5, -10.5, and -9.5 kcal/mol, respectively. Molecular dynamic simulations on superior structures were accomplished with the glucocorticoid receptor. Additionally, root mean square deviations, root mean square fluctuation, radius of gyration, hydrogen bonds, and binding-free energy analysis showed the binding stability of the proposed compounds compared to budesonide as an approved drug. The results demonstrated that all the compounds had suitable binding stability compared to budesonide, while ZINC_000002083318 showed a tighter binding energy compared to the other compounds.Communicated by Ramaswamy H. Sarma.

Protein aggregates composed of tau fibrils are major pathologic findings in different tauopathies. An ideal agent for imaging tau fibrils must be highly selective. The molecular basis for the binding of current available compounds to tau aggregates is not well understood. Herein, we provide insights into previously studied positron emission tomography tracers using various computational methods, including machine learning-based quantitative structure-activity relationship (QSAR) classification, docking, and molecular dynamics (MD) simulations to investigate the structural basis of selective tau aggregate binding for potential compounds. The QSAR classification model based on the Random Forest algorithm with an accuracy of 96.6% for the selective and 97.6% for the nonselective class of compounds revealed essential selective moieties. The combination of molecular docking, MD simulations, and molecular mechanics Poisson-Boltzmann surface area (MM/PBSA) binding free-energy calculation showed superior binding energy of ligand 63 toward tau and PHF6, a key hexapeptide in tau aggregation, as the most selective compound in the data set. Dissecting the binding properties of ligand 63 and ligand 8 (the least selective compound) within tau and Aβ structures confirmed that these two compounds favor different binding sites of tau; however, the preferential binding site in Aβ was similar for both with lower binding energies calculated for ligand 8. Results revealed that the number of N -heterocycles, the position of nitrogen atoms, and the presence of tertiary amine are important components of selective binding moieties, and they should be maintained in molecules for selective binding to tau aggregates. The predicted structure-selectivity relationship will facilitate the rational design and further development of selective tau imaging agents.

Plants are an indispensable cornerstone of sustainable global food supply. While immense progress has been made in decoding the genomes of crops in recent decades, the composition of their proteomes, the entirety of all expressed proteins of a species, is virtually unknown. In contrast to the model plant Arabidopsis thaliana , proteomic analyses of crop plants have often been hindered by the presence of extreme concentrations of secondary metabolites such as pigments, phenolic compounds, lipids, carbohydrates or terpenes. As a consequence, crop proteomic experiments have, thus far, required individually optimized protein extraction protocols to obtain samples of acceptable quality for downstream analysis by liquid chromatography tandem mass spectrometry (LC-MS/MS). In this article, we present a universal protein extraction protocol originally developed for gel-based experiments and combined it with an automated single-pot solid-phase-enhanced sample preparation (SP3) protocol on a liquid handling robot to prepare high-quality samples for proteomic analysis of crop plants. We also report an automated offline peptide separation protocol and optimized micro-LC-MS/MS conditions that enables the identification and quantification of ~10,000 proteins from plant tissue within 6 h of instrument time. We illustrate the utility of the workflow by analyzing the proteomes of mature tomato fruits to an unprecedented depth. The data demonstrate the robustness of the approach which we propose for use in upcoming large-scale projects that aim to map crop tissue proteomes.

Herein, we reported the synthesis of nineteen novel 1,2,4-triazole derivatives including 1,3-diphenyl-2-(1H-1,2,4-triazol-1-yl) propan-1-ones (7a-e), 1-(1,3-diphenylpropan-2-yl)-1H-1,2,4-triazole (8a-c) and 1,4-diphenyl-2-(1H-1,2,4-triazol-1-yl) butane-1,4-diones (10a-k). The structures of these derivatives were confirmed by spectroscopic techniques like IR, 1 H-NMR, Mass spectroscopy and Elemental analysis. The cytotoxic activities of the synthesized compounds were evaluated against three human cancer cell lines including MCF-7, Hela and A549 using MTT assay. Compounds 7d, 7e, 10a and 10d showed a promising cytotoxic activity lower than 12 μM against Hela cell line. The safety of these compounds was also, evaluated on MRC-5 as a normal cell line and relieved that most of the synthesized compounds have proper selectivity against normal and cytotoxic cancerous cell lines. Finally, molecular docking studies were also, done to understand the mechanism and binding modes of these derivatives in the binding pocket of aromatase enzyme as a possible target., (© 2022. The Author(s).)

Background: Salvia extracts have various biological activities and are rich sources of bioactive metabolites., Objectives: We identified five phytochemicals from S. compressa extract and assessed its biological properties., Methods: The plant's shoots were extracted using dichloromethane, and the constituents were isolated using column chromatography. High-resolution NMR spectroscopy characterized the chemical structures of the compounds (1 - 5). The cytotoxic effect of the extract was examined against MCF-7 cells by MTT reduction assay, while cisplatin was tested as a reference cytotoxic compound. The antibacterial activity was assessed using nutrient broth micro-dilution (NBMD), and chloramphenicol was used as the positive control., Results: Citrostadienol (1), β-sitosterol (2), two glyceride esters of linolenic, linoleic, and palmitic acids (3, 4), and geraniol (5) were isolated from S. compressa for the first time. The extract showed activity against MCF-7 breast cancer cells and reduced cell viability to 68.2 ± 13.1% compared to the control drug at the concentration of 50 µg/mL, while it was not active against seven test bacteria., Conclusions: The anti-complementary activity of the isolated steroids suggests S. compressa for future anti-inflammatory research., Competing Interests: Conflict of Interests: ARJ is reviewer of IJPR. The paper was supported by a NIMAD Grant. There is no support from any company in which the authors have stock shares. No patents and no consultant fees are earned regarding this manuscript. Omidreza Firuzi is not an editorial member of IJPR but may be a reviewer of some papers in IJPR., (Copyright © 2022, Author(s).)

A series of 2-aryl/alkyl-2,3-dihydro-1H-naphtho[1,2-e][1,3]oxazines (S 1 -S 11 ) were synthesized with an eco-friendly and recoverable nanocatalyst (GO-Fe 3 O 4 -Ti (IV) ) as an efficient magnetic composite. The new nanocatalyst was characterized by FT-IR, XRD and, EDS analysis. A conformable procedure, easy to work up and having a short reaction time with high yields are some advantages of this method. The new catalyst is also thermal-stable, reusable and, environment-friendly. The chemical structures of the synthesized 1,3-oxazine compounds were confirmed by comparing their melting points with those reported in literature. Then, the anticonvulsant activity of these compounds was assessed by the intraperitoneal pentylenetetrazole test (ipPTZ). Compounds S 10 and S 11 displayed considerable activity against chemically-induced seizure tests. The molecular simulation was also done to achieve their binding affinities as γ-aminobutyric acid A (GABA-A) receptor agonists as an assumptive mechanism of their anticonvulsant action. The result of molecular studies represented strongly matched with biological activity. Molecular docking simulation of the potent compound (S 10 ) and diazepam as the positive control was performed and some critical residues like Thr262, Asn265, Met286, Phe289, and Val290 were identified. Based on the anticonvulsant results and also in silico ADME predictions, S 11 can be to become a potential drug candidate as an anticonvulsant agent., (© 2022. The Author(s).)

A deep insight into the 3D structures of the proteins is essential to understand their functions and will be helpful in drug design and making decisions for the treatment of diseases. The 3D structure for less than one-thousandth of the protein sequences has been determined so far due to the slow structure elucidation procedures with experimental methods, such as X-ray. For this reason, different computational methods were used to determine the structure of the proteins, including template-based and de novo approaches. Much software has been developed to facilitate the computational approaches in protein modeling, some of which need user expertise and extensive knowledge in bioinformatics. The present study attempted to provide a user-friendly environment to motivate the researchers in computational biology, a Python-based interface based on MODELLER software. PyProtModel can be used as a toolbox in structural bioinformatics for protein modeling from sequence to the prediction of 3D structure. In addition, the users can take benefits of PyProtModel in order to prepare and evaluate protein PDB files prior to other in silico experiments. PyProtModel allows the user to apply different MODELLER options, automates, and speeds up time-consuming homology modeling steps. Different aspects of PyProtModel and a comprehensive view of the application will be discussed in this paper. The application is available for download and use at: https://github.com/msisakht/pyprotmodel.git., (Copyright © 2022 Elsevier Inc. All rights reserved.)

Chemokines are the large family of chemotactic cytokines that play an important role in leukocyte movement and migration stimulation. Until now, several antibody-cytokine (chemokine) fusion proteins have been investigated in clinical trials because of their ability to evoke the circulating leukocytes far from the tumor site. In this case, creating the concentration gradient regarding the chemokine is very important to recruit the circulating leukocytes with maximum performance to the tumor environment. To achieve a proper gradient, the chemokine separation from the tumor antigen-bounded antibody can be very crucial. Thus, we designed a novel linker that can be cleaved by enzymes presented around the tumor site including cathepsin B, urokinase-type plasminogen activator (uPA) and matrix metalloproteinases (MMPs). Also, it can inhibit tumor progression by competing with the native substrate of key proteases in the tumor microenvironment. The proposed linker was evaluated using some bioinformatics approaches. In silico results showed that the linker is structurally stable and could be detected and cleaved using the mentioned enzymes.Communicated by Ramaswamy H. Sarma.

Purpose: Endocrine disruptors are a rising concern due to the wide array of health issues that it can cause. Although there are tools for mode of action (MoA)-based prediction of endocrine disruption (e.g. QSAR Toolbox and iSafeRat), none of them is based on toxicogenomics data. Here, we present EDTox, an R Shiny application enabling users to explore and use a computational method that we have recently published to identify and prioritize endocrine disrupting (ED) chemicals based on toxicogenomic data. The EDTox pipeline utilizes previously trained toxicogenomic-driven classifiers to make predictions on new untested compounds by using their molecular initiating events. Furthermore, the proposed R Shiny app allows users to extend the prediction systems by training and adding new classifiers based on new available toxicogenomic data. This functionality helps users to explore the ED potential of chemicals in new, untested exposure scenarios., Availability and Implementation: This tool is available as web application (www.edtox.fi) and stand-alone software on GitHub and Zenodo (https://doi.org/10.5281/zenodo.5817093)., Supplementary Information: Supplementary data are available at Bioinformatics online., (© The Author(s) 2022. Published by Oxford University Press.)

Cabazitaxel (CTX) is an anti-neoplastic agent of second-generation taxane derivatives, characterized by very low water solubility. The currently marketed formulation of CTX contains high concentrations of surfactant and ethanol, which causes severe hypersensitivity reactions in patients. To deal with aforementioned side effects, our previous study attempted to develop the prodrugs of CTX with dextran. Here our approach differs through synthesizing folate containing prodrug and also investigating cytotoxicity and pharmacokinetics parameters obtained with dextran and dextran-folate nanoconjugates versus free CTX. MCF-7 with medium folate receptor expression and MDA-MB-231 as high folate receptor expression cell lines were selected for cytotoxicity assay. Pharmacokinetics properties were studied by injecting prodrugs and CTX to Wistar rats, analyzing serum and selected tissue samples and the obtained results were sibjected to data modeling study. The size of synthesized prodrugs was mostly less than 90 nm. Folate conjugates provided higher toxicity in comparison with dextran conjugates on both cell lines. In vivo non-compartmental pharmacokinetics analysis revealed enhanced area under the curve (about 3-5 fold for different samples) and longer half-life (approximately 1.3-1.8 fold higher) which led to increased serum residence time of prodrugs in comparison to free CTX. Tissue accumulation data showed that liver was the major organ with high accumulation of CTX. The accumulation of folate conjugates was remarkably higher than dextran samples (p < 0.05 in samples of 2, 10 and 24 h). Data modeling by Principal Component Analysis (PCA) and Hierarchical Cluster models showed a significant difference between pharmacokinetics properties of CTX and prodrugs. In summary, prodrugs seem to be proper and promising CTX delivery systems as substitution for the current market formulation., (Copyright © 2021 Elsevier B.V. All rights reserved.)

The main protease of SARS-CoV-2 is a critical target for the design and development of antiviral drugs. 2.5 M compounds were used in this study to train an LSTM generative network via transfer learning in order to identify the four best candidates capable of inhibiting the main proteases in SARS-CoV-2. The network was fine-tuned over ten generations, with each generation resulting in higher binding affinity scores. The binding affinities and interactions between the selected candidates and the SARS-CoV-2 main protease are predicted using a molecular docking simulation using AutoDock Vina. The compounds selected have a strong interaction with the key MET 165 and Cys145 residues. Molecular dynamics (MD) simulations were run for 150ns to validate the docking results on the top four ligands. Additionally, root-mean-square deviation (RMSD), root-mean-square fluctuation (RMSF), and hydrogen bond analysis strongly support these findings. Furthermore, the MM-PBSA free energy calculations revealed that these chemical molecules have stable and favorable energies, resulting in a strong binding with Mpro's binding site. This study's extensive computational and statistical analyses indicate that the selected candidates may be used as potential inhibitors against the SARS-CoV-2 in-silico environment. However, additional in-vitro, in-vivo, and clinical trials are required to demonstrate their true efficacy., (Copyright © 2021 Elsevier Ltd. All rights reserved.)

A series of ethyl 2-amino-4H-benzo[h]chromene-3-carboxylate derivatives, having phenyl ring with diverse substituents at C 4 position of 4H-benzochromene nucleus, were synthesized via one-pot three-component reaction between various aromatic aldehydes, α-naphthol, and ethyl cyanoacetate. The synthesized compounds were screened for their antityrosinase activity. Compound 4i, bearing 4-dimethylamino substitution on C 4 -phenyl ring, was the most potent tyrosinase inhibitor (IC 50  = 34.12 μM). The inhibition kinetic analysis of 4i indicated that the compound was a competitive tyrosinase inhibitor. Compounds 4a, 4g, 4i and 4j were the effective radical scavengers with EC 50 s in the range of 0.144-0.943 mM. According to the in silico drug-like and ADME predictions, 4i can be considered as a suitable candidate. Molecular docking results confirmed that the derivative was well accommodated within the mushroom tyrosinase binding site. Therefore, 4i can be introduced as a novel tyrosinase inhibitor that might be a promising lead in medicine, cosmetics, and food industry., (© 2020. Springer Nature Switzerland AG.)

A series of symmetrical azine derivatives containing different substituted benzyl moieties were designed, synthesized, and evaluated for their inhibitory activity against tyrosinase. The results showed that compounds 3e, 3f, 3h, 3i, 3j, and 3k possess effective tyrosinase inhibition with IC 50 values ranging from 7.30 μM to 62.60 μM. Particularly, compounds 3f displayed around three-fold improvement in the potency (IC 50  = 7.30 ± 1.15 μM) compared to that of kojic acid (IC 50  = 20.24 ± 2.28 μM) as the positive control. Kinetic study of compound 3f confirmed uncompetitive inhibitory activity towards tyrosinase indicating that it can bind to enzyme-substrate complex. Next, molecular docking analysis was performed to study the interactions and binding mode of the most potent compound 3f in the tyrosinase active site. Besides, the cytotoxicity of 3f, as well as its potency to reduce the melanin content were also measured on invasive melanoma B16F10 cell line. Also, 3f exhibited above 82% cell viability in the A375 cell line at 10 µM. Consequently, compounds 3f could be introduced as a potent tyrosinase inhibitor that might be a promising candidate in the cosmetics, medicine, and food industry., (© 2021. The Author(s).)

The main protease of SARS-CoV-2 is one of the key targets to develop and design antiviral drugs. There is no general agreement on the use of non-steroidal anti-inflammatory drugs (NSAIDs) in COVID-19. In this study, we investigated NSAIDs as potential inhibitors for chymotrypsin-like protease (3CLpro) and the main protease of the SARS-CoV-2 to find out the best candidates, which can act as potent inhibitors against the main protease. We also predicted the effect of NSAIDs on the arachidonic pathway and evaluated the hepatotoxicity of the compounds using systems biology techniques. Molecular docking was conducted via AutoDock Vina to estimate the interactions and binding affinities between selected NSAIDs and the main protease. Molecular docking results showed the presence of 10 NSAIDs based on lower binding energy (kcal/mol) toward the 3CLpro inhibition site compared to the co-crystal native ligand Inhibitor N3 (-6.6 kcal/mol). To validate the docking results, molecular dynamic (MD) simulations on the top inhibitor, Talniflumate, were performed. To obtain differentially-expressed genes under the 27 NSAIDs perturbations, we utilized the L1000 final Z-scores from the NCBI GEO repository (GSE92742). The obtained dataset included gene expression profiling signatures for 27 NSAIDs. The hepatotoxicity of NSAIDs was studied by systems biology modeling of Disturbed Metabolic Pathways. This study highlights the new application of NSAIDs as anti-viral drugs used against COVID-19. NSAIDs may also attenuate the cytokine storm through the downregulation of inflammatory mediators in the arachidonic acid pathway., (Copyright © 2021 Elsevier Ltd. All rights reserved.)

Multi-walled carbon nanotubes (MWCNTs) can be applied for pH-sensitive delivery of anticancer drugs. Due to the importance of 5-fluorouracil (5-FU) in different tumor therapy regimens, it has been widely used in different pH dependent drug delivery systems. To investigate the pH effects on loading (and release) of 5-FU on (and from) the functionalized MWCNTs and propose the optimum condition for drug delivery, both macroscopic and microscopic studies were carried out using chromatography and molecular dynamic simulation at different conditions. For both levels of studies, different analytical approaches were performed to assess the validity of the methods. The experimental results revealed that 5-FU has more binding affinity to the surface of the nanocarrier at physiological pH (pH = 7.4) and showed more release at acidic conditions (pH = 5.0). Meanwhile it has been observed that basic pH (pH = 9.0) can lead to a dramatic decrease effect on loading of the drug. The results of this study can be used to suggest the optimum pH levels for nanocarbon based formulations of 5-FU in cancer therapy., (Copyright © 2021. Published by Elsevier B.V.)

Aging is correlated with several complex diseases, including type 2 diabetes, neurodegeneration diseases, and cancer. Identifying the nature of this correlation and treatment of age-related diseases has been a major subject of both modern and traditional medicine. Traditional Persian Medicine (TPM) embodies many prescriptions for the treatment of ARDs. Given that autophagy plays a critical role in antiaging processes, the present study aimed to examine whether the documented effect of plants used in TPM might be relevant to the induction of autophagy? To this end, the TPM-based medicinal herbs used in the treatment of the ARDs were identified from modern and traditional references. The known phytochemicals of these plants were then examined against literature for evidence of having autophagy inducing effects. As a result, several plants were identified to have multiple active ingredients, which indeed regulate the autophagy or its upstream pathways. In addition, gene set enrichment analysis of the identified targets confirmed the collective contribution of the identified targets in autophagy regulating processes. Also, the protein-protein interaction (PPI) network of the targets was reconstructed. Network centrality analysis of the PPI network identified mTOR as the key network hub. Given the well-documented role of mTOR in inhibiting autophagy, our results hence support the hypothesis that the antiaging mechanism of TPM-based medicines might involve autophagy induction. Chemoinformatics study of the phytochemicals using docking and molecular dynamics simulation identified, among other compounds, the cyclo-trijuglone of Juglans regia L. as a potential ATP-competitive inhibitor of mTOR. Our results hence, provide a basis for the study of TPM-based prescriptions using modern tools in the quest for developing synergistic therapies for ARDs.

Aim: Aromatherapy products, hydrosol beverages and distillates containing essential oils are widely used for cardiovascular conditions. Investigation of the possible activity of their major constituents with the cardiovascular-related receptors may lead to developing new therapeutics. It also may prevent unwanted side effects and drug-herb interactions., Materials and Methods: A list of 243 volatile molecules (mainly monoterpene and sesquiterpene) was prepared from a literature survey in Scopus and PubMed (2000-2019) on hydrosols and essential oils which are used for Cardiovascular Diseases (CVD) and its risk factors (diabetes mellitus and hyperlipidemia). The PDB files of the receptors (229 native PDB files) included alpha-glucosidase, angiotensin- converting enzymes, beta-2 adrenergic receptor, glucocorticoid, HMG-CoA reductase, insulin, mineralocorticoid, potassium channel receptors and peroxisome proliferator-activated receptoralpha, were downloaded from Protein Data Bank. An in silico study using AutoDock 4.2 and Vina in parallel mode was performed to investigate possible interaction of the molecules with the receptors. Drug likeliness of the most active molecules was investigated using DruLiTo software., Results: Spathulenol, bisabolol oxide A, bisabolone oxide, bergapten, bergamotene, dill apiole, pcymene, methyl jasmonate, pinocarveol, intermedeol, α-muurolol, S-camphor, ficusin, selinen-4-ol, iso-dihydrocarveol acetate, 3-thujanone, linanool oxide and cadinol isomers made a better interaction with some of the named receptors. All of the named molecules had an acceptable dug likeliness except for α-bergamotene. In addition, all of the named molecules had the ability to pass the bloodbrain barrier and it is possible to produce unwanted side effects., Conclusion: Some ingredients of essential oils might be active on cardiovascular-related receptors., (Copyright© Bentham Science Publishers; For any queries, please email at epub@benthamscience.net.)

Background and Purpose: The aim of this study was to evaluate the in vitro and in vivo anti- Toxoplasma gondii ( T. gondii ) effect of 5-oxo-hexahydroquinoline compounds. Moreover, molecular docking study of the compounds into the active site of enoyl-acyl carrier protein reductase (ENR) as a necessary enzyme for the vitality of apicoplast was carried out., Experimental Approach: A number of 5-oxo-hexahydoquinoline derivatives (Z1-Z4) were synthesized. The T. gondii tachyzoites of RH strain were treated by different concentrations (1-64 μg/mL) of the compounds. The viability of the encountered parasites with compounds was assessed using flow cytometry and propidium iodide (PI) staining. Due to the high mortality effect of Z3 and Z4 in vitro , their chemotherapy effect was assessed by inoculation of tachyzoites to four BALB/c mice groups ( n = 5), followed by the gavage of various concentrations of the compounds to the mice. Molecular docking was done to study the binding affinity of the synthesized 5-oxo-hexahydroquinolines into ENR enzyme active site byusing AutoDock Vina® software. Docking was performed by a Lamarckian Genetic Algorithm with 100 runs., Findings / Results: Flow cytometry assay results indicated compounds Z3 and Z4 had relevant mortality effect on parasite tachyzoites. Besides, in vivo experiments were also performed and a partial increase of mice longevity between control and experiment groups was recorded. Molecular docking of Z3 and Z4 in the binding site of ENR enzyme indicated that the compounds were well accommodated within the binding site. Therefore, it could be suggested that these compounds may exert their anti- T. gondii activity through the inhibition of the ENR enzyme., Conclusion and Implications: Compounds Z3 and Z4 are good leads in order to develop better anti- T. gondii agents as they demonstrated both in vitro and in vivo inhibitory effects on tachyzoites viability and infection. Further studies on altering the route of administration along with additional pharmacokinetics evaluations are needed to improve the anti- T. gondii impacts of 5-oxo-hexahydroquinoline compounds., (Copyright: © 2020 Research in Pharmaceutical Sciences.)

Aromatic herbal remedies, hydrosols, and essential oils are widely used for women's hormonal health. Scientific investigation of their major constituents may prevent unwanted infertility cases, fetal abnormalities, and drug-herb interactions. It also may lead to development of new medications. A list of 265 volatile molecules (mainly monoterpenes and sesquiterpenes) were prepared from a literature survey in Scopus and PubMed (2000-2019) on hydrosols and essential oils that are used for women's hormonal and reproductive health conditions. The PDB (protein data bank) files of the receptors (136 native PDB files) that involve with oxytocin, progesterone, estrogen, prolactin, acetyl choline, androgen, dopamine, human chorionic gonadotropin, luteinizing hormone, follicle-stimulating hormone, aromatase, and HER2 receptors were downloaded from Protein Data Bank. An in silico study using AutoDock 4.2 and Vina in parallel mode was performed to investigate possible interactions of the ligands with the receptors. Drug likeliness was investigated for the most active molecules using DruLiTo software. Aristola-1(10),8-diene, bergapten (5-methoxypsoralen), α-bergamotene, bicyclogermacrene, α-bisabolol oxide A, α-bisabolone oxide, p -cymen-8-ol, 10-epi elemol, α-elemol, β-eudesmol, 7- epi -β-eudesmol, ficusin, β-humulene, methyl jasmonate, nerolidol, pinocarvone, (+)-spathulenol, and thujone had better interactions with some androgen, aromatase, estrogen, progesterone, HER2, AChR, and/or dopamine receptors. Most of these molecules had an acceptable drug likeliness except for α-bergamotene, bicyclogermacrene, β-humulene, and aristola-1(10),8-diene. Some volatile natural molecules can be considered as lead compound for drug development to treat hormonal conditions.

Sweet taste receptor (STR) is a C GPCR family member and a suggested drug target for metabolic disorders such as diabetes. Detailed characteristics of the molecule as well as its ligand interactions mode are yet considerably unclear due to experimental study limitations of transmembrane proteins. An in silico study was designed to find the putative carbohydrate binding sites on STR. To this end, α-D-glucose and its α-1,4-oligomers (degree of polymerization up to 14) were chosen as probes and docked into an ensemble of different conformations of the extracellular region of STR monomers (T1R2 and T1R3), using AutoDock Vina. Ensembles had been sampled from an MD simulation experiment. Best poses were further energy-minimized in the presence of water molecules with Amber14 forcefield. For each monomer, four distinct binding regions consisting of one or two binding pockets could be distinguished. These regions were further investigated with regard to hydrophobicity and hydrophilicity of the residues, as well as residue compositions and non-covalent interactions with ligands. Popular binding regions showed similar characteristics to carbohydrate binding modules (CBM). Observation of several conserved or semi-conserved residues in these binding regions suggests a possibility to extrapolate the results to other C GPCR family members. In conclusion, presence of CBM in STR and, by extrapolation, in other C GPCR family members is suggested, similar to previously proposed sites in gut fungal C GPCRs, through transcriptome analyses. STR modes of interaction with carbohydrates are also discussed and characteristics of non-covalent interactions in C GPCR family are highlighted.

Iron is an essential element used as supplement in different dosage-forms. Different time and expenditure-consuming methods introduced for detection and determination of elemental ions such as Atomic Absorption Spectroscopy. In this research, two different and routine methods containing ATR-IR and atomic absorption were applied to define the amount of iron in 198 samples containing different concentrations of commercial iron drops and syrups and the output data of the methods was transferred to chemometric model to compare the accuracy and robustness of the methods. By applying this mathematical model, in addition to the confirmation of ATR-IR (a time and energy-saving method) as a replacement of Atomic Absorption Spectroscopy to produce the same results, chemometrical model was used to evaluate the output data in a faster and easier method. At first, ATR-IR spectra data converted to normal matrix by SNV preprocessing approach. Then, a relationship between iron concentrations achieved by AAS and ATR-IR data was established using PLS-LS-SVM. Consequently, model was able to predict ~99% of the samples with low error-values (root mean square-error of cross-validation equal to 0.98). Y-permutation test performed to confirm that the model was not assessed accidentally. Although, chemometric methods for detection of some heavy metals have been reported in the literature, combination of PLS-LS-SVM with ATR-IR was not cited. In this study a fast and robust method for iron assay was suggested.As a result, ATR-IR can be a suitable method in detection and qualification of iron-content in pharmaceutical dosage forms with less energy-consumption but similar accuracy.

Microtubule affinity-regulating kinase 4 (MARK4) is a Ser/Thr protein kinase, best known for its role in phosphorylating microtubule associated proteins, causing their detachment from microtubules. In the current study, the non-phosphorylated conformation of the activation loop was modeled in a structure representing the enzymatically inactive form of this protein, and its dynamics were evaluated through a 100 ns initial all-atom simulation, which was prolonged by another 2 μs. Although the activation loop was folding on itself and was leaning toward ATP site in the initial modeled structure, soon after the initiating the simulation, this loop stretched away from the ATP binding site and stably settled in its new position for the rest of simulation time. A network of hydrogen bonds, mainly between the activation segment residues, αC-helix and the catalytic loop reinforced this conformation. Interestingly, several features of active kinase conformation such as formation of R-spine, Glu106-Lys88 salt-bridge, and DFG-In motif were observed during a considerable number of trajectory frames. However, they were not sustainably established during the simulation time, except for the DFG-In motif. Consequently, this study introduces a stable conformation of the non-phosphorylated form of MARK4 protein with a partially stretched activation loop conformation as well as partial formation of R-spine, closely resembling the active kinase.

The structure of sweet taste receptor (STR), a heterodimer of class C G-protein coupled receptors comprising T1R2 and T1R3 molecules, is still undetermined. In this study, a new enhanced model of the receptor is introduced based on the most recent templates. The improvement, stability, and reliability of the model are discussed in details. Each domain of the protein, i.e., VFTM, CR, and TMD, were separately constructed by hybrid-model construction methods and then assembled to build whole monomers. Overall, 680 ns molecular dynamics simulation was performed for the individual domains, the whole monomers and the heterodimer form of the VFTM orthosteric binding site. The latter's structure obtained from 200 ns simulation was docked with aspartame; among various binding sites suggested by FTMAP server, the experimentally suggested binding domain in T1R2 was retrieved. Local three-dimensional structures and helices spans were evaluated and showed acceptable accordance with the template structures and secondary structure predictions. Individual domains and whole monomer structures were found stable and reliable to be used. In conclusion, several validations have shown reliability of the new and enhanced models for further molecular modeling studies on structure and function of STR and C GPCRs.

We present a detailed investigation of the effect of the crystallographic structure of the HIV-1 protease (PR) on the binding energy of different classes of inhibitors obtained from docking simulations. The crystal structures of 222 HIV-1 proteases (in wild-type and mutant forms) and 202 inhibitors were downloaded from appropriate databases. A cross-docking approach (docking of all 202 inhibitors to all 222 PR structures) using Autodock Vina was implemented. The protease structures were clustered using a Kohonen self-organization map analysis of the data matrix of docking energies. The obtained clusters of PRs were correlated with the x-y-z coordinates of the PR structures to identify structural segments underlying this clustering. The PR structures were clustered into 4 classes. One of these classes exhibits rather strong binding with almost all inhibitors, while another class exhibits rather weak binding. The remaining two classes are intermediate in binding strength. The selectivity ratio indices for the carbon-alpha atoms of the PR structures indicate that conformational motion of residues outside the binding pocket contributes significantly to the discrimination of the 4 classes., (Copyright © 2019 Elsevier Inc. All rights reserved.)

Tyrosinase enzyme plays a crucial role in melanin biosynthesis and enzymatic browning process of vegetables and fruits. Hence, tyrosinase inhibitors are important in the fields of medicine, cosmetics and agriculture. In this study, novel N-(2-morpholinoethyl)cinnamamide derivatives bearing different substituents on phenyl ring were designed, synthesized and evaluated for their tyrosinase diphenolase inhibitory activity. The compounds were found to be better tyrosinase inhibitors (IC 50 s were in micro molar range) than cinnamic acid. (E)-3-(3-chlorophenyl)-N-(2-morpholinoethyl)acrylamide (B6) exhibited the highest inhibition with IC 50 value of 15.2 ± 0.6 μM which was comparable to that of kojic acid. The inhibition kinetic analysis of B6 indicated that the compound was a mixed-type tyrosinase inhibitor. In silico ADME prediction indicated that B6 might show more skin penetration than kojic acid. Molecular docking analysis confirmed that the active inhibitors well accommodated in the mushroom tyrosinase active site and it was also revealed that B6 formed the most stable drug-receptor complex with the target protein. Therefore, cinnamamide B6 could be introduced as a potent tyrosinase inhibitor that might be a promising lead in cosmetics, medicine and food industry., (Copyright © 2019 Elsevier B.V. All rights reserved.)

The enzyme phenylalanine ammonia lyase (PAL) is of special importance for the treatment of phenylketonuria patients. The aim of this study was to find a stable recombinant PAL with suitable kinetic properties among all natural PAL producing species using in silico and experimental approaches. To find such a stable PAL among 481 natural isoforms, 48,000 of 3-D models were predicted using the Modeller 9.10 program and evaluated by Ramachandran plot. Correlation analysis between Ramachandran plot and the energy of different thermodynamic components indicated that this plot could be an appropriate tool to predict protein stability. Hence, PAL6 from Lotus japonicus (LjPAL6) was selected as a stable isoform. Molecular dynamic (MD) simulation for 50 ns and docking has been conducted for LjPAL6-phenylalanine complex. The best PAL-phenylalanine frame was selected by re-docking with l-phenylalanine (L-Phe) and root-mean-square deviation (RMSD) value. MD simulation showed that the complex has a good stability, depicted by the low RMSD value, binding free energy and hydrogen bindings. Docking results showed that LjPAL6 has a high affinity toward l-Phe according to the low level of binding free energy. By overexpressing Ljpal6 in E. coli BL21, a total of 33.5 mg/l of protein was obtained, which has been increased to 83.7 mg/l via the optimization of LjPAL6 production using response surface methodology. The optimal pH and temperature were 8.5 and 50 °C, respectively. LjPAL6 showed a specific activity of 42 nkat/mg protein, with K m , K cat and K cat /K m values of 0.483 mM, 7 S -1 and 14.5 S -1  mM -1 for l-phe, respectively. In conclusion, finding models with the most reasonable stereo-chemical quality and lowest numbers of steric clashes would result in easier folding. Hence, in silico analyses of bulk data from natural origin will lead one to find an optimal model for in vitro studies and drug design., (Copyright © 2018 Elsevier Inc. All rights reserved.)

Background: Prediction of proteins' secondary structure is one of the major steps in the generation of homology models. These models provide structural information which is used to design suitable ligands for potential medicinal targets. However, selecting a proper tool between multiple Secondary Structure Prediction (SSP) options is challenging. The current study is an insight into currently favored methods and tools, within various contexts., Objective: A systematic review was performed for a comprehensive access to recent (2013-2016) studies which used or recommended protein SSP tools., Methods: Three databases, Web of Science, PubMed and Scopus were systematically searched and 99 out of the 209 studies were finally found eligible to extract data., Results: Four categories of applications for 59 retrieved SSP tools were: (I) prediction of structural features of a given sequence, (II) evaluation of a method, (III) providing input for a new SSP method and (IV) integrating an SSP tool as a component for a program. PSIPRED was found to be the most popular tool in all four categories. JPred and tools utilizing PHD (Profile network from HeiDelberg) method occupied second and third places of popularity in categories I and II. JPred was only found in the two first categories, while PHD was present in three fields., Conclusion: This study provides a comprehensive insight into the recent usage of SSP tools which could be helpful for selecting a proper tool., (Copyright© Bentham Science Publishers; For any queries, please email at epub@benthamscience.net.)

Organophosphate compounds bioremediation by use of organophosphorus degradation enzymes such as DFPase is a developing interest in industry and medicine. The most important problem with the bio-catalytic enzymes is their instability on high temperatures. This work carried out to find suitable locations for introducing disulfide bridges in DFPase enzyme. We employed some computational approaches to design the disulfide bridges and evaluate their roles in the enzyme structural thermostability. According to the in silico results, mutant 6 (V24C, C76) increased the enzyme thermostability relative to wild-type., (Copyright © 2018 Elsevier Ltd. All rights reserved.)

Proteins are often monitored by combining a fluorescent polypeptide tag with the target protein. However, due to the high molecular weight and immunogenicity of such tags, they are not suitable choices for combining with fusion proteins such as immunotoxins. In this study, we designed a polypeptide sequence with a dual role (it acts as both a linker and a fluorescent probe) to use with fusion proteins. Two common fluorescent tag sequences based on tetracysteine were compared to a commonly used rigid linker as well as our proposed dual-purpose sequence. Computational investigations showed that the dual-purpose sequence was structurally stable and may be a good choice to use as both a linker and a fluorescence marker between two moieties in a fusion protein.

Phytotherapy is a source of finding new remedies for migraine. Traditional chamomile oil (chamomile extraction in sesame oil) is a formulation in Persian medicine (PM) for pain relief in migraine. An oleogel preparation of reformulated traditional chamomile oil was prepared and then standardized based on chamazulene (as a marker in essential oil) and apigenin via gas chromatography (GC) and high-performance liquid chromatography (HPLC) methods, respectively. A crossover double-blind clinical trial was performed with 100 patients. Each patient took two tubes of drug and two tubes of placebo during the study. Visual analog scale (VAS) questionnaires were filled in by the patients and scores were given, ranging from 0 to 10 (based on the severity of pain) during 24 h. Other complications like nausea, vomiting, photophobia, and phonophobia were also monitored. There was 4.48 ± 0.01 μl/ml of chamazulene and 0.233 mg/g of apigenin in the preparation (by correcting the amount with extraction ratio). Thirty-eight patients in the drug-placebo and 34 patients in the placebo-drug groups (a total number of 72 patients as per protocol) completed the process in the randomized controlled trial (RCT). Adapted results from the questionnaires showed that pain, nausea, vomiting, photophobia, and phonophobia significantly (p < 0.001) decreased by using chamomile oleogel on the patients after 30 min. Results supported the efficacy of chamomile oleogel as a pain relief in migraine without aura.

Diaryl urea derivatives have exhibited a broad spectrum of biochemical effects and pharmaceutical applications. Several diaryl urea derivatives such as sorafenib, regorafenib, linifanib, and tivozanib and lenvatinib are in clinical trial or clinical use. Therefore, development of small molecules within the diaryl urea scaffold with the ability of binding to variety of enzymes and receptors in the biological system are an interesting topic for researchers. Sorafenib as a diaryl urea derivative is a well-known anticancer agent. Corresponding to available information about biological activities of quinoxaline moieties, based on sorafenib scaffold, several structures were designed by replacement of pyridyl carboxamide group of sorafenib with quinoxalindione moiety. A total of 14 novel compounds in 7 synthetic steps were synthesized. Briefly, the amino group of p-aminophenol was first protected followed by O-arylation of 4-acetamidophenol with 5-chloro-2-nitroaniline to provide 5-(4-acetamidophenoxy)-2-nitroaniline. Reduction of the nitro group of 5-(4-acetamidophenoxy)-2-nitroaniline and cyclization of diamine N-(4-(3,4-diaminophenoxy) phenyl) acetamides with oxalic acid afforded compound N-(4-((2,3-dioxo-1,2,3,4-tetrahydroquinoxalin-6-yl)oxy)phenyl) acetamides which on deacetylation gave compounds 6-(4-aminophenoxy) quinoxaline-2,3 (1H, 4H)-diones. Then resultant compounds, 6-(4-aminophenoxy) quinoxaline-2,3 (1H, 4H)-diones were reacted by appropriate isocyanates/ carbamates to give the target compounds 1-(4-((2,3-dioxo-1,2,3,4-tetrahydroquinoxalin-6-yl)oxy)phenyl)-3-phenylureas. The structures of compounds confirmed by proton nuclear magnetic resonance ( 1 H NMR), mass spectrum and Fourier transform infrared (FT-IR).

Background: The plant Nardostachys jatamansi from Valerianaceae family is a well known antidepressant plant and has historically been used in traditional medicine. As N. jatamansi contains many different compounds, to identify its mechanisms of action, we need a network-based study. Network-based studies are becoming an increasingly important tool in understanding the mechanisms of actions of drugs. Systems pharmacology (SP) and bioinformatics are two emerging tools that use computation to develop an understanding of drug actions in molecular and cellular levels. SP can provide mechanistic understanding of protein-protein (drug-target) interaction involved in a common biological pathway. The present study was undertaken to identify unknown targets and mechanisms of antidepressant activity of N. jatamansi according to a systems pharmacology approach., Method: First of all a list of all the targets (receptors and metabolites) involved in depression process were provided based on KEGG database. The 3D structures of protein targets were collected as PDB files and their active sites coordinates were found. In the next step the structures of known compounds of N. jatamansi were collected. For identifying the protein-lagand interactions, a docking process was run in AutoDock and an output was received. To complete our study, the similarity between antidepressant conventional drugs and N. jatamansi compounds was analyzed. A SP map figured by Cytoscape Software, shows the relations between herbal compounds, molecular targets and depression., Results: According to the docking results, we can suggest several important targets that we have no drugs for, or several natural compounds that play an important role in depression process. According to the similarity results we can suggest several molecules for extraction or synthesis that need more researches for their therapeutic effects. This study shows that how N. jatamansi can effect on depression by multiple molecular targeting with multiple compounds., (Copyright© Bentham Science Publishers; For any queries, please email at epub@benthamscience.org.)

In this study a series of diarylurea derivatives containing quinoxalindione group were biologically evaluated for their cytotoxic activities using MTT assay against MCF-7 and HepG2 cell lines. Antibacterial activities of these compounds were also evaluated by Microplate Alamar Blue Assay (MABA) against three Gram-negative ( Escherichia coli , Pseudomonas aeruginosa and Salmonella typhi ), three Gram-positive ( Staphylococcus aureus , Bacillus subtilis and Listeria monocitogenes ) and one yeast-like fungus (Candida albicans) strain. Furthermore, molecular docking was carried out to study the binding pattern of the compounds to the active site of B-RAF kinase (PDB code: 1UWH). Molecular dynamics simulation was performed on the best ligand (16e) to investigate the ligand binding dynamics in the physiological environment. Cytotoxic evaluation revealed the most prominent cytotoxicity for 6 compounds with IC 50 values of 10-18 μM against two mentioned cell lines. None of the synthesized compounds showed significant antimicrobial activity. The obtained results of the molecular docking study showed that all compounds fitted in the binding site of enzyme with binding energy range of -11.22 to -12.69 kcal/mol vs sorafenib binding energy -11.74 kcal/mol as the lead compound. Molecular dynamic simulation indicated that the binding of ligand (16e) was stable in the active site of B-RAF during the simulation.

Background: Cabazitaxel (CTX) is a second- generation taxane derivative, a class of potent anticancer drugs with very low water solubility. CTX is used in patients with resistant prostate cancer unresponsive to the first generation taxane, docetaxel. Currently marketed formulations of CTX contain high concentrations of surfactant and ethanol, which cause severe hypersensitivity reactions in patients., Methods: In order to increase its solubility, two hemiester analogs; CTX-succinate and CTX-glutarate were synthesized and characterized. To improve the solubility of hemiesters even more, dextran as a biocompatible polymer was also conjugated to hemiester analogs. MTT assay was performed on MCF-7 cell line to evaluate the cytotoxicity effect of hemiesters and conjugates., Results: Based on the results, hemiester analogs increased water solubility of the drug up to about 3 and 8 fold. Conjugation to dextran enhanced the CTX solubility to more than 1500 fold. These conjugates released the conjugated CTX in less than 24 hours in a pH dependent manner and showed proper hemocompatibility characteristics. The hemiesters had approximately similar cytotoxicity in comparison with CTX and the dextran conjugates showed higher cytotoxicity effect on MCF-7 cell line., (Copyright© Bentham Science Publishers; For any queries, please email at epub@benthamscience.org.)

With the growing number of labor-intensive data in the pharmaceutical industries and public domain for protein-ligand complexes, a significant challenge is still remaining in managing and leveraging this vast information. Here, a standalone application is presented for analysis, organization, and illustration of structural data and molecular interactions for exploiting 3D-structures into simple 1D fingerprints. The utility of the approach was shown in unraveling a feasible solution for post-processing of docking results in parallel with providing fruitful analysis for users in order to investigate molecular interactions. Remarkably, all interaction possibilities including (hydrogen bond, water-bridged, electrostatic, and hydrophobic as well as π- π and cation-π interactions) are supported both in the form of fingerprints and compelling reports. These investigations are mainly considered based on right orientation, location, and geometry of the interacting pairs rather than the acquisition of the energy terms. The reasonable efficiency of our application in different models was comparable to recent methods It is clearly presented that FLIP provides a faster way to generate usable fingerprints for ligand and protein binding modes. FLIP is free for academic use and is available at: http://zistrayan.com/development/download/flip/package.zip., (Copyright © 2017 Elsevier Inc. All rights reserved.)

Herbal oils have been widely used in Iran as medicinal compounds dating back to thousands of years in Iran. Chamomile oil is widely used as an example of traditional oil. We remade chamomile oils and tried to modify it with current knowledge and facilities. Six types of oil (traditional and modified) were prepared. Microbial limit tests and physicochemical tests were performed on them. Also, principal component analysis, hierarchical cluster analysis, and partial least squares discriminant analysis were done on the spectral data of attenuated total reflectance-infrared in order to obtain insight based on classification pattern of the samples. The results show that we can use modified versions of the chamomile oils (modified Clevenger-type apparatus method and microwave method) with the same content of traditional ones and with less microbial contaminations and better physicochemical properties.

Hydrosol beverages in Persian nutrition culture and ethnomedicine are the side products of essential oil industry that are used as delicious drinks or safe remedies. To investigate indications and chemical composition of hydrosol beverages for hyperlipidemia and cardiovascular conditions, Fars province was selected as the field of study. Ethnomedical data were gathered by questionnaires. The constituents of hydrosols were extracted with liquid/liquid extraction and analyzed by gas chromatography-mass spectrometry. Statistical analysis were used to cluster their constituents and find the relevance of their composition. A literature survey was also performed on plants used to prepare them. Thymol was the major or second major component of these beverages, except for wormwood and olive leaf hydrosols. Based on clustering methods, although some similarities could be found, composition of barberry, will fumitory, dill, and aloe hydrosols have more differences than others. These studies may help in developing some functional beverages or new therapeutics.

A great challenge in medicinal chemistry is to develop different methods for structural design based on the pattern of the previously synthesized compounds. In this study two different QSAR methods were established and compared for a series of piperidine acetylcholinesterase inhibitors. In one novel approach, PC-LS-SVM and PLS-LS-SVM was used for modeling 3D interaction descriptors, and in the other method the same nonlinear techniques were used to build QSAR equations based on field descriptors. Different validation methods were used to evaluate the models and the results revealed the more applicability and predictive ability of the model generated by field descriptors (Q 2 LOO-CV =1, R 2 ext =0.97). External validation criteria revealed that both methods can be used in generating reasonable QSAR models. It was concluded that due to ability of interaction descriptors in prediction of binding mode, using this approach can be implemented in future 3D-QSAR softwares., (Copyright © 2017 Elsevier Ltd. All rights reserved.)

Dichloroacetate (DCA) is a simple and small anticancer drug that arouses the activity of the enzyme pyruvate dehydrogenase (PDH) through inhibition of the enzyme pyruvate dehydrogenase kinases (PDK1-4). DCA can selectively promote mitochondria-regulated apoptosis, depolarizing the hyperpolarized inner mitochondrial membrane potential to normal levels, inhibit tumor growth and reduce proliferation by shifting the glucose metabolism in cancer cells from anaerobic to aerobic glycolysis. In this study, a series of DCA analogues were applied to quantitative structure-activity relationship (QSAR) analysis. A collection of chemometrics methods such as multiple linear regression (MLR), factor analysis-based multiple linear regression (FA-MLR), principal component regression (PCR), and partial least squared combined with genetic algorithm for variable selection (GA-PLS) were applied to make relations between structural characteristics and cytotoxic activities of a variety of DCA analogues. The best multiple linear regression equation was obtained from genetic algorithms partial least squares, which predict 90% of variances. Based on the resulted model, an in silico -screening study was also conducted and new potent lead compounds based on new structural patterns were designed. Molecular docking as well as protein ligand interaction fingerprints (PLIF) studies of these compounds were also investigated and encouraging results were acquired. There was a good correlation between QSAR and docking results.

The IL-1β plays a major role in inflammatory disorders and IL-1β production inhibitors can be used in the treatment of inflammatory and related diseases. In this study, quantitative relationships between the structures of 46 pyridazine derivatives (inhibitors of IL-1β production) and their activities were investigated by Multiple Linear Regression (MLR) technique Stepwise Regression Method (ES-SWR). The genetic algorithm (GA) has been proposed for improvement of the performance of the MLR modeling by choosing the most relevant descriptors. The results show that eight descriptors are able to describe about 83.70% of the variance in the experimental activity of the molecules in the training set. The physical meaning of the selected descriptors is discussed in detail. Power predictions of the QSAR models developed were evaluated using cross-validation, and validation through an external prediction set. The results showed satisfactory goodness-of-fit, robustness and perfect external predictive performance. The applicability domain was used to define the area of reliable predictions. Furthermore, the in silico screening technique was applied in order to predict the structure and potency of new compounds of this type using the proposed QSAR model.