A region-resolved proteomic map of the human brain enabled by high-throughput proteomics.

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).

Illuminating phenotypic drug responses of sarcoma cells to kinase inhibitors by phosphoproteomics.

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.

EDTox: an R Shiny application to predict the endocrine disruption potential of compounds.

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.

4H-benzochromene derivatives as novel tyrosinase inhibitors and radical scavengers: synthesis, biological evaluation, and molecular docking analysis.

A series of ethyl 2-amino-4H-benzo[h]chromene-3-carboxylate derivatives, having phenyl ring with diverse substituents at C4 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 C4-phenyl ring, was the most potent tyrosinase inhibitor (IC50 = 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 EC50s 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.

Evaluation of the effect of topical chamomile (Matricaria chamomilla L.) oleogel as pain relief in migraine without aura: a randomized, double-blind, placebo-controlled, crossover study.

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.

Insilico analysis of three different tag polypeptides with dual roles in scFv antibodies.

Single chain fragment variable (scFv) antibodies are composed of variable heavy (VH) and variable light (VL) domains that are joined by a polypeptide linker. Typically, [(Gly4Ser) n] sequence is used as a linker to retain the integrity of the antigen-binding domain. Due to its low immunogenicity, this sequence cannot be used as a tag for scFv detection and purification. Several evidences have shown that the addition of an N or C-terminal tag for scFv detection and purification will result in the decreased expression and binding capacity of this antibody fragment. In this study, we substituted the traditional linker (GGGGS) with His-tag, C-myc or E-tag sequences through molecular modeling. Stability and integrity of all models were assessed by molecular dynamic (MD) simulation. Based on MD simulation analysis, the model containing E-tag sequence as a linker indicated more stability compared to other molecules. The results suggest that E-tag not only can be substituted for the traditional linker, also eliminates the necessity of using additional tag for scFv detection and purification.

Synthesis and biological evaluation of 5-benzylidenerhodanine-3-acetic acid derivatives as AChE and 15-LOX inhibitors.

A series of 5-benzylidenerhodanine-3-acetamides bearing morpholino-, 4-arylpiperazinyl-, or 4-benzylpiperidinyl- moieties were synthesized and their inhibitory activities against acetylcholinesterase (AChE) were evaluated. Alteration of amide part and substitution on the benzylidene moiety resulted in change of anti-AChE activity. The most active compound was the 1-benzylpiperidinyl derivative containing 4-(dimethylamino)benzylidene scaffold. Notably, the intermediate compounds, namely 5-arylidene-rhodanine-3-acetic acids (3), showed mild inhibitory activity against 15-lipoxygenase (15-LOX), while the final compound 4 showed no activity against 15-LOX.

Correlation of Myeloid-Derived Suppressor Cell Expansion with Upregulated Transposable Elements in Severe COVID-19 Unveiled in Single-Cell RNA Sequencing Reanalysis.

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.

A combination of virtual screening, molecular dynamics simulation, MM/PBSA, ADMET, and DFT calculations to identify a potential DPP4 inhibitor.

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.

Decrypting lysine deacetylase inhibitor action and protein modifications by dose-resolved proteomics.

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.

Decrypting the molecular basis of cellular drug phenotypes by dose-resolved expression proteomics.

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.

Synthesis of some new 3-coumaranone and coumarin derivatives as dual inhibitors of acetyl- and butyrylcholinesterase.

A novel series of coumarin and 3-coumaranone derivatives encompassing the phenacyl pyridinium moiety were synthesized and evaluated for their acetylcholinesterase (AChE) and butyrylcholinesterase (BuChE) inhibitory activity using Ellman's method. All compounds presented inhibitory activity against both AChE and BuChE in the micromolar range. The molecular docking simulations revealed that all compounds were dual binding site inhibitors of AChE. A kinetic study was performed and the mechanism of enzyme inhibition was proved to be of mixed type. All compounds were tested for their antioxidant activity and no significant activity was observed.

5,6-Dimethoxybenzofuran-3-one derivatives: a novel series of dual Acetylcholinesterase/Butyrylcholinesterase inhibitors bearing benzyl pyridinium moiety.

BACKGROUND: Several studies have been focused on design and synthesis of multi-target anti Alzheimer compounds. Utilizing of the dual Acetylcholinesterase/Butyrylcholinesterase inhibitors has gained more interest to treat the Alzheimer's disease. As a part of a research program to find a novel drug for treating Alzheimer disease, we have previously reported 6-alkoxybenzofuranone derivatives as potent acetylcholinesterase inhibitors. In continuation of our work, we would like to report the synthesis of 5,6-dimethoxy benzofuranone derivatives bearing a benzyl pyridinium moiety as dual Acetylcholinesterase/Butyrylcholinesterase inhibitors. METHODS: The synthesis of target compounds was carried out using a conventional method. Bayer-Villiger oxidation of 3,4-dimethoxybenzaldehyde furnished 3,4-dimethoxyphenol. The reaction of 3,4-dimethoxyphenol with chloroacetonitrile followed by treatment with HCl solution and then ring closure yielded the 5,6-dimethoxy benzofuranone. Condensation of the later compound with pyridine-4-carboxaldehyde and subsequent reaction with different benzyl halides afforded target compounds. The biological activity was measured using standard Ellman's method. Docking studies were performed to get better insight into interaction of compounds with receptor. RESULTS: The in vitro anti acetylcholinesterase/butyrylcholinesterase activity of compounds revealed that, all of the target compounds have good inhibitory activity against both Acetylcholinesterase/Butyrylcholinesterase enzymes in which compound 5b (IC50 = 52 ± 6.38nM) was the most active compound against acetylcholinesterase. The same binding mode and interactions were observed for the reference drug donepezil and compound 5b in docking study. CONCLUSIONS: In this study, we presented a new series of benzofuranone-based derivatives having pyridinium moiety as potent dual acting Acetylcholinesterase/Butyrylcholinesterase inhibitors.

Structure-Selectivity Relationship Prediction of Tau Imaging Tracers Using Machine Learning-Assisted QSAR Models and Interaction Fingerprint Map.

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 Aß structures confirmed that these two compounds favor different binding sites of tau; however, the preferential binding site in Aß 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.

Structure-based virtual screening, molecular docking, molecular dynamics simulation and MM/PBSA calculations towards identification of steroidal and non-steroidal selective glucocorticoid receptor modulators.

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.

Getting Ready for Large-Scale Proteomics in Crop Plants.

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.

Novel coumarin derivatives bearing N-benzyl pyridinium moiety: potent and dual binding site acetylcholinesterase inhibitors.

A novel series of coumarin derivatives linked to benzyl pyridinium group were synthesized and biologically evaluated as inhibitors of both acetylcholinesterase (AChE) and butyrylcholinesterase (BuChE). The enzyme inhibitory activity of synthesized compounds was measured using colorimetric Ellman's method. It was revealed that compounds 3e, 3h, 3l, 3r and 3s have shown higher activity compared with donepezil hydrochloride as standard drug. Most of the compounds in these series had nanomolar range IC(50) in which compound 3r (IC(50) = 0.11 nM) was the most active compound against acetylcholinesterase enzyme.

Synthesis and SAR study of 4,5-diaryl-1H-imidazole-2(3H)-thione derivatives, as potent 15-lipoxygenase inhibitors.

A series of 4,5-diaryl-1H-imidazole-2(3H)-thione was synthesized and their inhibitory potency against soybean 15-lipoxygenase and free radical scavenging activities were determined. Compound 11 showed the best IC(50) for 15-LOX inhibition (IC(50) = 4.7 µM) and free radical scavenging activity (IC(50) = 14 µM). Methylation of SH at C(2) position of imidazole has dramatically decreased the 15-LOX inhibition and radical scavenging activity as it can be observed in the inactive compound 14 (IC(50) >250 µM). Structure activity similarity (SAS) showed that the most important chemical modification in this series was methylation of SH group and Docking studies revealed a proper orientation for SH group towards Fe core of the 15-LOX active site. Therefore it was concluded that iron chelating could be a possible mechanism for enzyme inhibition in this series of compounds.

A highly potential cleavable linker for tumor targeting antibody-chemokines.

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.

PyProtModel: An easy to use GUI for comparative protein modeling.

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.