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Structure-based modeling to assess binding and endocrine disrupting potential of polycyclic aromatic hydrocarbons in Daniorerio

Environmental contaminants, such as polycyclic aromatic hydrocarbons (PAHs), have raised concerns regarding their potential endocrine-disrupting effects on aquatic organisms, including fish. In this study, molecular docking and molecular dynamics techniques were employed to evaluate the endocrine-disrupting potential of PAHs in zebrafish, as a model organism. A virtual screening with 72 PAHs revealed a correlation between the number of PAH aromatic rings and their binding affinity to proteins involved in endocrine regulation. Furthermore, PAHs with the highest binding affinities for each protein were identified: cyclopenta[cd]pyrene for AR (-9.7 kcal/mol), benzo(g)chrysene for ERα (-11.5 kcal/mol), dibenzo(a,e)pyrene for SHBG (-8.7 kcal/mol), dibenz(a,h)anthracene for StAR (-11.2 kcal/mol), and 2,3-benzofluorene for TRα (-9.8 kcal/mol). Molecular dynamics simulations confirmed the stability of the protein-ligand complexes formed by the PAHs with the highest binding affinities throughout the simulations. Additionally, the effectiveness of the protocol used in this study was demonstrated by the receiver operating characteristic curve (ROC) analysis, which effectively distinguished decoys from true ligands. Therefore, this research provides valuable insights into the endocrine-disrupting potential of PAHs in fish, highlighting the importance of assessing their impact on aquatic ecosystems.

Antibacterial potential of Propolis: molecular docking, simulation and toxicity analysis

The issue of antibiotic resistance in pathogenic microbes is a global concern. This study was aimed to explore in silico and in vitro analysis of the antibacterial efficacy of different natural ligands against bacterial activity. The ligands included in the study were Propolis Neoflavanoide 1, Carvacrol, Cinnamaldehyde, Thymol, p-benzoquinone, and Ciprofloxacin (standard drug S*). The outcomes of molecular docking revealed that Propolis Neoflavaniode-1 showed a highly significant binding energy of - 7.1 and - 7.2 kcal/mol for the two gram-positive bacteria, as compared to the gram-negative bacteria. All ligands demonstrated acute toxicity (oral, dermal), except for Propolis Neoflavanoide 1 and S* drugs, with a confidence score range of 50-60%. Using a molecular dynamic simulation approach, we investigated Propolis Neoflavaniode-1's potential for therapeutic use in more detail. An MD simulation lasting 100 ns was performed using the Desmond Simulation software to examine the conformational stability and steady state of Propolis Neoflavaniode-1 in protein molecule complexes. Additionally, in vitro studies confirmed the antimicrobial activity of Propolis Neoflavaniode 1 by increasing the zone of inhibition against Gram-positive bacteria, p < 0.005 as compared to gram-negative bacteria. This study revealed the promising antibacterial efficacy of Propolis Neoflavaniode 1, demonstrated through robust in silico analyses, minimal toxicity, and confirmed in vitro antimicrobial activity, suggesting its potential as a viable alternative to combat antibiotic resistance.

In silico prediction of the interaction of legacy and novel per- and poly-fluoroalkyl substances (PFAS) with selected human transporters and of their possible accumulation in the human body

Per- and poly-fluorinated compounds constitute a wide group of fluorocarbon chemicals with widespread industrial applications, ranging from non-stick coating in cookware to water surfactants, from fire-fighting foams to water-repellent coatings on textiles. Presently, over 12,000 PFAS are known worldwide. In recent years, extensive research has focused on investigating the biological effects of these molecules on various organisms, including humans. Here, we conducted in silico simulations to examine the potential binding of a representative selection of PFAS to various human proteins known to be involved in chemical transportation and accumulation processes. Specifically, we targeted human serum albumin (HSA), transthyretin (TTR), thyroxine binding protein (TBG), fatty acid binding proteins (FABPs), organic anion transporters (OATs), aiming to assess the potential for bioaccumulation. Molecular docking simulations were employed for this purpose, supplemented by molecular dynamics (MD) simulations to account for protein flexibility, when necessary. Our findings indicate that so-called "legacy PFAS" such as PFOA or PFOS exhibit a higher propensity for interaction with the analysed human protein targets compared to newly formulated PFAS, characterised by higher branching and hydrophilicity, and possibly a higher accumulation in the human body.

Mechanism of 7H-Dibenzo[c,g]carbazole metabolism in cytochrome P450 1A1: Insights from computational studies

7H-Dibenzo[c,g]carbazole (DBC) is a prevalent environmental contaminant that induces tumorigenesis in several experimental animals. Recently, it has been utilized to develop high-performance solar cells and organic phosphorescent materials. It is imperative to strengthen investigations of DBC metabolism to understand its potential risks to human health. In this study, human CYP1A1 was employed as the metabolic enzyme to investigate the metabolic mechanism of DBC by molecular docking, molecular dynamics (MD) simulation, and quantum mechanical (QM) calculation. The results indicate that DBC binds to CYP1A1 in two modes (mode 1 and mode 2) mainly through nonpolar solvation energies (ΔGnonpolar). The formation of the two binding modes is attributed to the anchoring effect of the hydrogen bond formed by DBC with Asp320 (mode 1) or Ser116 (mode 2). Mode 1 is a "reactive" conformation, while mode 2 is not considered a "reactive" conformation. C5 is identified as the dominant site, and the pyrrole nitrogen cannot participate in the metabolism. DBC is metabolized mainly by a distinct electrophilic addition-rearrangement mechanism, with an energy barrier of 21.74 kcal/mol. The results provide meaningful insights into the biometabolic process of DBC and contribute to understanding its environmental effects and health risks.

Cordycepin Triphosphate as a Potential Modulator of Cellular Plasticity in Cancer via cAMP-Dependent Pathways: An In Silico Approach

Cordycepin, or 3'-deoxyadenosine, is an adenosine analog with a broad spectrum of biological activity. The key structural difference between cordycepin and adenosine lies in the absence of a hydroxyl group at the 3' position of the ribose ring. Upon administration, cordycepin can undergo an enzymatic transformation in specific tissues, forming cordycepin triphosphate. In this study, we conducted a comprehensive analysis of the structural features of cordycepin and its derivatives, contrasting them with endogenous purine-based metabolites using chemoinformatics and bioinformatics tools in addition to molecular dynamics simulations. We tested the hypothesis that cordycepin triphosphate could bind to the active site of the adenylate cyclase enzyme. The outcomes of our molecular dynamics simulations revealed scores that are comparable to, and superior to, those of adenosine triphosphate (ATP), the endogenous ligand. This interaction could reduce the production of cyclic adenosine monophosphate (cAMP) by acting as a pseudo-ATP that lacks a hydroxyl group at the 3' position, essential to carry out nucleotide cyclization. We discuss the implications in the context of the plasticity of cancer and other cells within the tumor microenvironment, such as cancer-associated fibroblast, endothelial, and immune cells. This interaction could awaken antitumor immunity by preventing phenotypic changes in the immune cells driven by sustained cAMP signaling. The last could be an unreported molecular mechanism that helps to explain more details about cordycepin's mechanism of action.

Geometry-complete perceptron networks for 3D molecular graphs

MOTIVATION

The field of geometric deep learning has recently had a profound impact on several scientific domains such as protein structure prediction and design, leading to methodological advancements within and outside of the realm of traditional machine learning. Within this spirit, in this work, we introduce GCPNet, a new chirality-aware SE(3)-equivariant graph neural network designed for representation learning of 3D biomolecular graphs. We show that GCPNet, unlike previous representation learning methods for 3D biomolecules, is widely applicable to a variety of invariant or equivariant node-level, edge-level, and graph-level tasks on biomolecular structures while being able to (1) learn important chiral properties of 3D molecules and (2) detect external force fields.

RESULTS

Across four distinct molecular-geometric tasks, we demonstrate that GCPNet's predictions (1) for protein-ligand binding affinity achieve a statistically significant correlation of 0.608, more than 5%, greater than current state-of-the-art methods; (2) for protein structure ranking achieve statistically significant target-local and dataset-global correlations of 0.616 and 0.871, respectively; (3) for Newtownian many-body systems modeling achieve a task-averaged mean squared error less than 0.01, more than 15% better than current methods; and (4) for molecular chirality recognition achieve a state-of-the-art prediction accuracy of 98.7%, better than any other machine learning method to date.

AVAILABILITY AND IMPLEMENTATION

The source code, data, and instructions to train new models or reproduce our results are freely available at https://github.com/BioinfoMachineLearning/GCPNet.

Plasma proteome profiling reveals molecular mechanisms underlying the effects of daily consumption of 'Bahia' and 'Cara Cara' orange juices

Orange juice is an important food source of bioactive compounds, mainly the flavanones hesperidin and narirutin. This study aimed to investigate the underlying molecular mechanisms of action of orange juice's health properties by analyzing changes in the plasma proteome of healthy Brazilian volunteers after consuming juices made from 'Bahia' (BOJ-source of flavanones) and 'Cara Cara' (CCOJ-source of flavanones and carotenoids) oranges cultivated in Brazil. We used an untargeted proteomic approach, with a particular emphasis on the juices' effects on blood coagulant activity. We identified 247 differentially expressed proteins, of which 170 significantly increased or decreased after BOJ consumption and 145 after CCOJ. These proteins are involved in 105 processes that can significantly regulate cell adhesion, cell signaling, cell metabolism, inflammation, or others. Bioinformatic analysis evidenced proteins with major cellular regulatory capacity (e.g., FN1 and GAPDH) and predicted transcription factors (TFs) (e.g., SP1 and CEBPA) and miRNAs (e.g., miR-1-3p and miR-615-3p) that could be involved in the regulation of differentially expressed proteins. In-silico docking analyses between flavanone metabolites and TFs evidenced the higher binding capacity of narirutin phase II metabolites with akt1 and p38, interactions that suggest how the expression of genes of differentially expressed proteins were activated or inhibited. Moreover, the study shed light on proteins of coagulation cascade that presented expression modulated by both juices, proposing the modulation of blood coagulant activity as a potential benefit of OJ (mainly CCOJ) consumption. Taken together, this study revealed that BOJ and CCOJ consumption affected plasma proteome in healthy individuals, suggesting potential molecular targets and mechanisms of OJ bioactive compounds in humans.

Ketoprofen attenuates Las/Rhl quorum-sensing (QS) systems of Pseudomonas aeruginosa: molecular and docking studies

BACKGROUND

Quorum sensing (QS) is the leading cause of persistent infections and recalcitrance to antibiotic treatment of Pseudomonas aeruginosa. Hence, QS inhibitors are promising agents for the potential treatment of P. aeruginosa infections.

METHODS AND RESULTS

Herein, the reducing effect of ketoprofen on virulence factors production including protease, hemolysin, pyocyanin, hydrogen cyanide, biofilm, and motility of P. aeruginosa strains was investigated. Furthermore, the quorum quenching activity of ketoprofen at the molecular level was examined by real-time PCR assessment. Our results showed that ketoprofen significantly attenuates virulence factors and biofilm formation in P. aeruginosa strains. Moreover, ketoprofen down-regulated the expression of lasI, lasR, rhlI, and rhlR genes, by 35-47, 22-48, 34-67, and 43-56%, respectively. As well, molecular docking simulation showed a high binding affinity of ketoprofen with QS regulatory proteins.

CONCLUSIONS

Consequently, this study confirmed the quorum quenching activity of ketoprofen, which could be employed as a useful agent for the treatment of P. aeruginosa infections.

Antibacterial activity of a novel compound isolated from Bacillus licheniformis for treating bacterial infections in fishes: An in-silico approach

Aeromonas hydrophila is a fish pathogen which is widely associated with diseases related to freshwater fishes. Vibrio parahemolyticus is a major globally emerging marine pathogen. Seven novel compounds were extracted from the ethyl acetate extract of Bacillus licheniformis, a novel marine bacterium isolated from marine actinomycetes. The compounds were identified using Gas Chromatography-Mass Spectroscopy (GC-MS). Only one bioactive compound having potent antibacterial activity was virtually screened to understand its drug-like property according to Lipinski's rule. The core proteins, 3L6E and 3RYL from the pathogens, A. hydrophila and V. parahemolyticus were targeted for drug discovery. In the present in-silico approach, Phenol,2,4-Bis(1,1-Dimethylethyl) a potent bioactive compound present in Bacillus licheniformis was used to prevent the infection due to the two pathogens. Further, using this bioactive compound, molecular docking was done to block their specific target proteins. This bioactive compound satisfied all the five rules of Lipinski. Molecular docking result revealed the best binding efficacy of Phenol,2,4-Bis(1,1-Dimethylethyl) against 3L6E and 3RYL with - 4.24 kcal/mol and - 4.82 kcal/mol, respectively. Molecular dynamics (MD) simulations were also executed to determine the binding modes as well as the stability of the protein-ligand docking complexes in the dynamic structure. The in vitro toxicity analysis of this potent bioactive compound against Artemia salina was carried out, revealing the non-toxic nature of B. licheniformis ethyl acetate extract. Thus, the bioactive compound of B. licheniformis was found to be a potent antibacterial agent against A. hydrophila and V. parahemolyticus.

UCSF ChimeraX: Tools for structure building and analysis

Advances in computational tools for atomic model building are leading to accurate models of large molecular assemblies seen in electron microscopy, often at challenging resolutions of 3-4 Å. We describe new methods in the UCSF ChimeraX molecular modeling package that take advantage of machine-learning structure predictions, provide likelihood-based fitting in maps, and compute per-residue scores to identify modeling errors. Additional model-building tools assist analysis of mutations, post-translational modifications, and interactions with ligands. We present the latest ChimeraX model-building capabilities, including several community-developed extensions. ChimeraX is available free of charge for noncommercial use at https://www.rbvi.ucsf.edu/chimerax.

Garcinia mangostana L. Pericarp Extract and Its Active Compound α-Mangostin as Potential Inhibitors of Immune Checkpoint Programmed Death Ligand-1

α-Mangostin, a major xanthone found in mangosteen (Garcinia mangostana L., Family Clusiaceae) pericarp, has been shown to exhibit anticancer effects through multiple mechanisms of action. However, its effects on immune checkpoint programmed death ligand-1 (PD-L1) have not been studied. This study investigated the effects of mangosteen pericarp extract and its active compound α-mangostin on PD-L1 by in vitro and in silico analyses. HPLC analysis showed that α-mangostin contained about 30% w/w of crude ethanol extract of mangosteen pericarp. In vitro experiments in MDA-MB-231 triple-negative breast cancer cells showed that α-mangostin and the ethanol extract significantly inhibit PD-L1 expression when treated for 72 h with 10 µM or 10 µg/mL, respectively, and partially inhibit glycosylation of PD-L1 when compared to untreated controls. In silico analysis revealed that α-mangostin effectively binds inside PD-L1 dimer pockets and that the complex was stable throughout the 100 ns simulation, suggesting that α-mangostin stabilized the dimer form that could potentially lead to degradation of PD-L1. The ADMET prediction showed that α-mangostin is lipophilic and has high plasma protein binding, suggesting its greater distribution to tissues and its ability to penetrate adipose tissue such as breast cancer. These findings suggest that α-mangostin-rich mangosteen pericarp extract could potentially be applied as a functional ingredient for cancer chemoprevention.

Network pharmacology combined with molecular docking and in vitro verification reveals the therapeutic potential of Delphinium roylei munz constituents on breast carcinoma

Delphinium roylei Munz is an indigenous medicinal plant to India where its activity against cancer has not been previously investigated, and its specific interactions of bioactive compounds with vulnerable breast cancer drug targets remain largely unknown. Therefore, in the current study, we aimed to evaluate the anti-breast cancer activity of different extracts of D. roylei against breast cancer and deciphering the molecular mechanism by Network Pharmacology combined with Molecular Docking and in vitro verification. The experimental plant was extracted with various organic solvents according to their polarity index. Phytocompounds were identified by High resolution-liquid chromatography-mass spectrometry (HR-LC/MS) technique, and SwissADME programme evaluated their physicochemical properties. Next, target(s) associated with the obtained bioactives or breast cancer-related targets were retrieved by public databases, and the Venn diagram selected the overlapping targets. The networks between overlapping targets and bioactive were visualized, constructed, and analyzed by STRING programme and Cytoscape software. Finally, we implemented a molecular docking test (MDT) using AutoDock Vina to explore key target(s) and compound(s). HR-LC/MS detected hundreds of phytocompounds, and few were accepted by Lipinski's rules after virtual screening and therefore classified as drug-like compounds (DLCs). A total of 464 potential target genes were attained for the nine quantitative phytocompounds and using Gene Cards, OMIM and DisGeNET platforms, 12063 disease targets linked to breast cancer were retrieved. With Kyoto Encyclopaedia of Genes and Genomes (KEGG) pathway enrichment, a total of 20 signalling pathways were manifested, and a hub signalling pathway (PI3K-Akt signalling pathway), a key target (Akt1), and a key compound (8-Hydroxycoumarin) were selected among the 20 signalling pathways via molecular docking studies. The molecular docking investigation revealed that among the nine phytoconstituents, 8-hydroxycoumarin showed the best binding energy (-9.2 kcal/mol) with the Akt1 breast cancer target. 8-hydroxycoumarin followed all the ADME property prediction using SwissADME, and 100 nanoseconds (ns) MD simulations of 8-hydroxycoumarin complexes with Akt1 were found to be stable. Furthermore, D. roylei extracts also showed significant antioxidant and anticancer activity through in vitro studies. Our findings indicated for the first time that D. roylei extracts could be used in the treatment of BC.

Integrated network pharmacology analysis and in vitro validation revealed the underlying mechanism of Xiyanping injection in treating coronavirus disease 2019

BACKGROUND

Coronavirus disease 2019 (COVID-19) has spread rapidly worldwide, leading to a pandemic. In China, Xiyanping injection (XYP) has been recommended as a drug for COVID-19 treatment in the Guideline on Diagnosis and Treatment of COVID-19 by the National Health Commission of the People Republic of China and National Administration of Traditional Chinese Medicine (Trial eighth Edition). However, the relevant mechanisms at the molecular-level need to be further elucidated.

METHODS

In this study, XYP related active ingredients, potential targets and COVID-19 related genes were searched in public databases. Protein-protein interaction network and module analyzes were used to screen for key targets. gene ontology and Kyoto encyclopedia of genes and genomes were performed to investigate the potentially relevant signaling pathways. Molecular docking was performed using Autodock Tools and Vina. For the validation of potential mechanism, PolyI:C was used to induce human lung epithelial cells for an inflammation model. Subsequently, CCK-8 assays, enzyme-linked immunosorbent assay, reverse transcription quantitative polymerase chain reaction and western blot were employed to determine the effect of XYP on the expression of key genes.

RESULTS

Seven effective active ingredients in XYP were searched for 123 targets in the relevant databases. Furthermore, 6446 COVID-19 disease targets were identified. Sodium 9-dehydro-17-hydro-andrographolide-19-yl sulfate was identified as the vital active compounds, and IL-6, TNF, IL-1β, CXCL8, STAT3, MAPK1, MAPK14, and MAPK8 were considered as the key targets. In addition, molecular docking revealed that the active compound and the targets showed good binding affinities. The enrichment analysis predicted that the XYP could regulate the IL-17, Toll-like receptor, PI3K-Akt and JAK-STAT signaling pathways. Consistently, further in vitro experiments demonstrated that XYP could slow down the cytokine storm in the lung tissue of COVID-19 patients by down-regulating IL-6, TNF-α, IL-1β, CXCL8, and p-STAT3.

CONCLUSION

Through effective network pharmacology analysis and molecular docking, this study suggests that XYP contains many effective compounds that may target COVID-19 related signaling pathways. Moreover, the in vitro experiment confirmed that XYP could inhibit the cytokine storm by regulating genes or proteins related to immune and inflammatory responses.

Plant Regulation Functions of Novel Phthalimide Compounds Based on AtPYL2

Novel agents contain the structure of phthalimide, which has antibacterial, insecticidal, and herbicidal activities. Recently, studies reported that these compounds can bind to plant hormone receptors and play important regulatory roles. In this study, the functions of agents were studied with in vitro and in vivo assays. The abscisic acid (ABA) receptor pyrabactin resistant-like 2 (PYL2) protein in Arabidopsis thaliana was expressed, purified, and crystallized; the analysis results of the crystal structure showed three AtPYL2 subunits in each asymmetric unit. The affinity of compounds Z1-Z11 to the AtPYL2 protein was tested by microscale thermophoresis (MST) and then verified by isothermal titration calorimetry (ITC). Furthermore, the binding pockets were found using molecular docking to verify the target relationships. Relevant in vivo assays for seed germination and a root growth assay were conducted, with the plant samples being treated with target compounds. The results show that the compounds Z3, Z5, and Z10 target AtPYL2 and that the dissociation constants for binding by MST were 3.59, 3.54, and 3.97 μmol/L, respectively, among them, and the molecular docking results showed that compounds Z3, Z5, and Z10 formed hydrophobic interactions with amino acid residues through hydrogen or halogen bonding. This highlights their potential as an ABA receptor protein agonist. On the other hand, in vivo, compounds Z3, Z5, and Z10 had different inhibitory effects on seed germination, with compound Z5 inhibiting the root growth of A. thaliana and compound Z10 affecting root growth. In conclusion, these compounds could regulate plant growth and could be further developed as new plant-regulating agents.

Buyang huanwu decoction inhibits diabetes-accelerated atherosclerosis via reduction of AMPK-Drp1-mitochondrial fission axis

ETHNOPHARMACOLOGICAL RELEVANCE

Traditional Chinese drugs, including Buyang Huanwu decoction (BYHWD), have been used in traditional practice to manage cardiovascular and cerebrovascular diseases. However, the effect and mechanisms by which this decoction alleviates diabetes-accelerated atherosclerosis are unknown and require exploration.

AIM OF THE STUDY

This study aims to investigate the pharmacological effects of BYHWD on preventing diabetes-accelerated atherosclerosis, and elucidate its underlying mechanism.

MATERIALS AND METHODS

Streptozotocin (STZ)-induced diabetic ApoE^-/- mice were treated with BYHWD. Atherosclerotic aortic lesions, endothelial function, mitochondrial morphology, and mitochondrial dynamics-related proteins were evaluated in isolated aortas. High glucose-exposed human umbilical endothelial cells (HUVECs) were treated with BYHWD and its components. AMPK siRNA transfection, Drp1 molecular docking, Drp1 enzyme activity measurement, and so on were used to explore and verify the mechanism.

RESULT

BYHWD treatment inhibited the worsening of diabetes-accelerated atherosclerosis by lessening atherosclerotic lesions in diabetic ApoE^-/- mice, by impeding endothelial dysfunction under diabetic conditions, and by inhibiting mitochondrial fragmentation by lowering protein expression levels of Drp1 and mitochondrial fission-1 protein (Fis1) in diabetic aortic endothelium. In high glucose-exposed HUVECs, BYHWD treatment also downgraded reactive oxygen species, promoted nitric oxide levels, and abated mitochondrial fission by reducing protein expression levels of Drp1 and fis1, but not mitofusin-1 and optic atrophy-1. Interestingly, we found that BYHWD's protective effect against mitochondrial fission is mediated by AMPK activation-dependent reduction of Drp1 levels. The main serum chemical components of BYHWD, ferulic acid, and calycosin-7-glucoside, can reduce the expression of Drp1 by regulating AMPK, and can inhibit the activity of GTPase of Drp1.

CONCLUSION

The above findings support the conclusion that BYHWD suppresses diabetes-accelerated atherosclerosis by reducing mitochondrial fission through modulation of the AMPK/Drp1 pathway.

Investigation of the Entry Pathway and Molecular Nature of σ1 Receptor Ligands

The σ1 receptor (σ1-R) is an enigmatic endoplasmic reticulum resident transmembrane protein implicated in a variety of central nervous system disorders and whose agonists have neuroprotective activity. In spite of σ1-R’s physio-pathological and pharmacological importance, two of the most important features required to fully understand σ1-R function, namely the receptor endogenous ligand(s) and the molecular mechanism of ligand access to the binding site, have not yet been unequivocally determined. In this work, we performed molecular dynamics (MD) simulations to help clarify the potential route of access of ligand(s) to the σ1-R binding site, on which discordant results had been reported in the literature. Further, we combined computational and experimental procedures (i.e., virtual screening (VS), electron density map fitting and fluorescence titration experiments) to provide indications about the nature of σ1-R endogenous ligand(s). Our MD simulations on human σ1-R suggested that ligands access the binding site through a cavity that opens on the protein surface in contact with the membrane, in agreement with previous experimental studies on σ1-R from Xenopus laevis. Additionally, steroids were found to be among the preferred σ1-R ligands predicted by VS, and 16,17-didehydroprogesterone was shown by fluorescence titration to bind human σ1-R, with significantly higher affinity than the prototypic σ1-R ligand pridopidine in the same essay. These results support the hypothesis that steroids are among the most important physiological σ1-R ligands.

Metformin May Alter the Metabolic Reprogramming in Cancer Cells by Disrupting the L-Arginine Metabolism: A Preliminary Computational Study

Metabolic reprogramming in cancer is considered to be one of the most important hallmarks to drive proliferation, angiogenesis, and invasion. AMP-activated protein kinase activation is one of the established mechanisms for metformin’s anti-cancer actions. However, it has been suggested that metformin may exert antitumoral effects by the modulation of other master regulators of cellular energy. Here, based on structural and physicochemical criteria, we tested the hypothesis that metformin may act as an antagonist of L-arginine metabolism and other related metabolic pathways. First, we created a database containing different L-arginine-related metabolites and biguanides. After that, comparisons of structural and physicochemical properties were performed employing different cheminformatic tools. Finally, we performed molecular docking simulations using AutoDock 4.2 to compare the affinities and binding modes of biguanides and L-arginine-related metabolites against their corresponding targets. Our results showed that biguanides, especially metformin and buformin, exhibited a moderate-to-high similarity to the metabolites belonging to the urea cycle, polyamine metabolism, and creatine biosynthesis. The predicted affinities and binding modes for biguanides displayed good concordance with those obtained for some L-arginine-related metabolites, including L-arginine and creatine. In conclusion, metabolic reprogramming in cancer cells by metformin and biguanides may be also driven by metabolic disruption of L-arginine and structurally related compounds.

Does the presence of ground state complex between a PR-10 protein and a sensitizer affect the mechanism of sensitized photo-oxidation?

The mechanisms of one-electron protein oxidation are complicated and still not well-understood. In this work, we investigated the reaction of sensitized photo-oxidation using carboxybenzophenone (CB) as a sensitizer and a PR-10 protein (MtN13) as a quencher, which is intrinsically complicated due to the complex structure of the protein and multiple possibilities of CB attack. To predict and examine the possible reactions precisely, the 3D structure of the MtN13 protein was taken into account. Our crystallographic studies revealed a specific binding of the CB molecule in the protein's hydrophobic cavity, while mass spectrometry identified the amino acid residues (Met, Tyr, Asp and Phe) creating adducts with the sensitizer, thus indicating the sites of ³CB* quenching. In addition, protein aggregation was also observed. The detailed mechanisms of CB quenching by the MtN13 molecule were elucidated by an analysis of transient products by means of time-resolved spectroscopy. The investigation of the transient and stable products formed during the protein photo-oxidation was based on the data obtained from HPLC-MS analysis of model compounds, single amino acids and dipeptides. Our proposed mechanisms of sensitized protein photo-oxidation emphasize the role of a ground state complex between the protein and the sensitizer and indicate several new and specific products arising as a result of one-electron oxidation. Based on the analysis of the transient and stable products, we have demonstrated the influence of neighboring groups, especially in the case of Tyr oxidation, where the tyrosyl radical can be formed via a direct electron transfer from Tyr to CB* or via an intramolecular electron transfer from Tyr to Met radical cation Met > S^●+ or thiyl radical CysS^● from neighboring oxidized groups.

Understanding the mode of inhibition and molecular interaction of taxifolin with human adenosine deaminase

Adenosine deaminase is a zinc⁺² dependent key enzyme of purine metabolism which irreversibly converts adenosine to inosine and form ammonia. Overexpression of adenosine deaminase has been linked to a variety of pathophysiological conditions such as atherosclerosis, hypertension, and diabetes. In the case of a cell-mediated immune response, ADA is thought to be a marker, particularly in type II diabetes. Deoxycoformycin is the most potent ADA inhibitor that has been discovered so far, but it has several drawbacks, including being toxic and having poor pharmacokinetics. Taxifolin, a flavonoid derived from plants, was discovered to be a potent inhibitor of the human ADA (hADA) enzyme in the current study. Taxifolin bound at the active site of human ADA and showed fifty percent inhibition at a concentration of 400 µM against the enzyme. To better understand the interactions between taxifolin and human ADA, docking and molecular dynamic simulations were performed. In-silico studies using autodock revealed that taxifolin bound in the active site of human ADA with a binding energy of -7.4 kcal mol ^-1 and a theoretical Ki of 3.7 uM. Comparative analysis indicated that taxifolin and deoxycoformycin share a common binding space in the active site of human ADA and inhibit its catalytic activity similarly. The work emphasises the need of employing taxifolin as a lead chemical in order to produce a more precise and effective inhibitor of the human ADA enzyme with therapeutic potential.Communicated by Ramaswamy H. Sarma.

FDI-6, a FOXM1 inhibitor, activates the aryl hydrocarbon receptor and suppresses tumorsphere formation

The aryl hydrocarbon receptor (AhR) is a ligand-activated transcription factor that is activated by environmental contaminants such as dioxins and polycyclic aromatic hydrocarbons. Following ligand binding, AhR binds to xenobiotic responsive elements and modulates the transcription of AhR target genes. Multiple studies have shown that AhR plays important roles in a range of cancer cells and is attracting attention as a therapeutic target for cancer treatment. We have previously reported that AhR agonists inhibit tumorsphere formation in an AhR-dependent manner in the MCF-7 breast cancer cell line. In the present study, we found that FDI-6, an inhibitor of the transcription factor Forkhead Box M1 (FOXM1) induced the mRNA expression of AhR target genes, nuclear translocation of AhR, and transcriptional activity of AhR. In addition, FDI-6 dose-dependently reduced the mRNA expression of FOXM1-regulated genes in AhR-expressing MCF-7 cells, although not in AhR-deficient MCF-7 cells. Furthermore, FDI-6 was found to suppress tumorsphere formation via the AhR in MCF-7 cells and HepG2 human liver cancer cell line. On the basis of the findings of this study, we show that FDI-6, a FOXM1 inhibitor, functions as an AhR agonist, and suppresses tumorsphere formation via the AhR.

Examining unsupervised ensemble learning using spectroscopy data of organic compounds

One solution to the challenge of choosing an appropriate clustering algorithm is to combine different clusterings into a single consensus clustering result, known as cluster ensemble (CE). This ensemble learning strategy can provide more robust and stable solutions across different domains and datasets. Unfortunately, not all clusterings in the ensemble contribute to the final data partition. Cluster ensemble selection (CES) aims at selecting a subset from a large library of clustering solutions to form a smaller cluster ensemble that performs as well as or better than the set of all available clustering solutions. In this paper, we investigate four CES methods for the categorization of structurally distinct organic compounds using high-dimensional IR and Raman spectroscopy data. Single quality selection (SQI) forms a subset of the ensemble by selecting the highest quality ensemble members. The Single Quality Selection (SQI) method is used with various quality indices to select subsets by including the highest quality ensemble members. The Bagging method, usually applied in supervised learning, ranks ensemble members by calculating the normalized mutual information (NMI) between ensemble members and consensus solutions generated from a randomly sampled subset of the full ensemble. The hierarchical cluster and select method (HCAS-SQI) uses the diversity matrix of ensemble members to select a diverse set of ensemble members with the highest quality. Furthermore, a combining strategy can be used to combine subsets selected using multiple quality indices (HCAS-MQI) for the refinement of clustering solutions in the ensemble. The IR + Raman hybrid ensemble library is created by merging two complementary "views" of the organic compounds. This inherently more diverse library gives the best full ensemble consensus results. Overall, the Bagging method is recommended because it provides the most robust results that are better than or comparable to the full ensemble consensus solutions.

Molecular docking and molecular dynamics approach to identify potential compounds in Huperzia squarrosa for treating Alzheimer's disease

OBJECTIVES

Alzheimer's disease (AD) is a lingering progressive neurodegenerative disorder that causes patients to lose cognitive function. The enzyme Acetylcholinesterase (AChE), Butyrylcholinesterase (BuChE), Monoamine oxidase A (MAO A), Beta-secretase cleavage enzyme (BACE 1) and N-methyl-D-aspartate (NMDA) receptors play an important role in the pathogenesis of Alzheimer's disease. Therefore, inhibiting enzymes is an effective method to treat Alzheimer disease. In this study, we evaluated in silico inhibitory effects of AChE, BuChE, MAO A, BACE 1 and NMDA enzyme of Huperzia squarrosa's compounds.

METHODS

The three-dimensional (3D) of N-methyl-D-aspartate receptor (PDB ID: 1PBQ), enzyme β-secretase 1 (PDB ID: 4X7I), enzyme monoamine oxidase A (PDB ID: 2Z5X), enzyme butyrylcholinesterase (PDB ID: 4BDS) and enzyme acetylcholinesterase (PDB ID: 1EVE) were retrieved from the Protein Data Bank RCSB. Molecular docking was done by Autodock vina software and molecular dynamics (MD) simulation of the ligand-protein complex with the least binding energy pose was perfomed by MOE. Lipinski Rule of Five is used to compare compounds with drug-like and non-drug-like properties. Pharmacokinetic parameters of potential compounds were evaluated using the pkCSM tool.

RESULTS

Based on previous publication of Huperzia squarrosa, we have collected 15 compounds. In these compounds, huperzine B, huperzinine, lycoposerramine U N-oxide, 12-epilycodine N-oxide showed strongly inhibit the five AChE, BuChE, MAO A, BACE 1 and NMDA targets for Alzheimer's treatment. Lipinski rule of five and ADMET predict have shown that four above compounds have drug-likeness properties, good absorption ability and cross the blood-brain barrier, which have the most potential to become drugs for the treatment of Alzheimer's in the future. Furthermore, MD study showed that huperzine B and huperzinine have stability of the docking pose with NMDA target.

CONCLUSIONS

In this study, we found two natural compounds in Huperzia squarrosa including Huperzine B and Huperzinine have drug-likeness properties, good absorption ability and cross the blood-brain barrier, which have potential to become drugs for the treatment of Alzheimer's in the future.

Bridging Database and Experimental Analysis to Reveal Super-hydrodynamic Conductivity Scaling Regimes in Ionic Liquids

Ion transport through electrolytes critically impacts the performance of batteries and other devices. Many frameworks used to model ion transport assume hydrodynamic mechanisms and focus on maximizing conductivity by minimizing viscosity. However, solid-state electrolytes illustrate that non-hydrodynamic ion transport can define device performance. Increasingly, selective transport mechanisms, such as hopping, are proposed for concentrated electrolytes. However, viscosity-conductivity scaling relationships in ionic liquids are often analyzed with hydrodynamic models. We report data-centric analyses of hydrodynamic transport models of viscosity-conductivity scaling in ionic liquids by merging three databases to bridge physical properties and computational descriptors. With this expansive database, we constrained scaling analyses using ion sizes defined from simulated volumes, as opposed to estimating sizes from activity coefficients. Remarkably, we find that many ionic liquids exhibit positive deviations from the Nernst-Einstein model, implying ions move faster than hydrodynamics should allow. We verify these findings using microrheology and conductivity experiments. We further show that machine learning tools can improve predictions of conductivity from molecular properties, including predictions from solely computational features. Our findings reveal that many ionic liquids exhibit super-hydrodynamic viscosity-conductivity scaling, suggesting mechanisms of correlated ion motion, which could be harnessed to enhance electrochemical device performance.

Turning around Cycles: An Approach Based on Selected Problems/Cases to Stimulate Collaborative Learning about Krebs and His Four Metabolic Cycles

Metabolism is a challenging subject for bioscience students due to the intrinsic complexity of the metabolic network, as well as that of the overlapping mechanisms of metabolic regulation. Collaborative learning based on a problem-based learning approach can help students to successfully learn and understand metabolism. In the present article, we propose a selection of exercises, problems, and cases aimed to focus students' attention on the scientific work made by Sir Hans Krebs and his collaborators to elucidate four main metabolic cycles, as well as on the study of these cycles, their regulation, and their metabolic integration. The objectives, the tools, and the implementation of this proposal are described, and the results obtained during its first implementation with volunteer students enrolled in two courses on metabolic regulation at our university are presented and discussed. These volunteer students signed a learning contract and were randomly distributed in small groups (3-4 students each). Application of this collaborative learning activity to our classrooms has been very satisfactory, as evidenced by an improvement in the volunteers' academic performance and a very positive perception by most of them, who declared to be "very satisfied" or "satisfied" with their experience and felt that they had learned more.

Methyl Eugenol Binds Recombinant Gamma-Aminobutyric Acid Receptor-Associated Protein from the Western Flower Thrips Frankliniella occidentalis

The western flower thrips (Frankliniella occidentalis) is a major pest insect in agriculture. However, few insecticides are effective for their control. The recombinant gamma-aminobutyric acid receptor-associated protein (rGABARAP) was examined as a potential target of the monoterpenoids responsible for their insecticidal activities. The insecticidal activity of anethole, linalool, and methyl eugenol (ME) was evaluated in the laboratory. The half-maximum lethal concentration (LC₅₀) of ME against second-instar nymphs of F. occidentalis was 5.5 mg/L using membrane and leaf immersion methods, while that of spinosyn A was 1.0 mg/L. The dissociation constants of ME binding to rGABARAP were 1.30 and 4.22 μmol/L, respectively, according to microscale thermophoresis (MST) and isothermal titration calorimetry (ITC) measurements. A molecular docking study showed interactions between ME and Tyr174 via π-π stacking. The MST and ITC experiments showed loss of specific binding between ME and the rGABARAP^Y174A mutant. Therefore, Tyr174 is a key amino acid residue of rGABARAP involving ME binding. The results revealed GABARAP as a potential target for the development of monoterpenoid insecticides.

QUAM-AFM: A Free Database for Molecular Identification by Atomic Force Microscopy

This paper introduces Quasar Science Resources-Autonomous University of Madrid atomic force microscopy image data set (QUAM-AFM), the largest data set of simulated atomic force microscopy (AFM) images generated from a selection of 685,513 molecules that span the most relevant bonding structures and chemical species in organic chemistry. QUAM-AFM contains, for each molecule, 24 3D image stacks, each consisting of constant-height images simulated for 10 tip-sample distances with a different combination of AFM operational parameters, resulting in a total of 165 million images with a resolution of 256 × 256 pixels. The 3D stacks are especially appropriate to tackle the goal of the chemical identification within AFM experiments by using deep learning techniques. The data provided for each molecule include, besides a set of AFM images, ball-and-stick depictions, IUPAC names, chemical formulas, atomic coordinates, and map of atom heights. In order to simplify the use of the collection as a source of information, we have developed a graphical user interface that allows the search for structures by CID number, IUPAC name, or chemical formula.

Extended quasiparticle approach to non-resonant and resonant X-ray emission spectroscopy

The initial state of X-ray emission spectroscopy (XES) and resonant inelastic X-ray emission spectroscopy (RIXS) is a highly excited eigenstate with a deep core hole after a X-ray photoelectron spectroscopy...

A computational biology approach for the identification of potential SARS-CoV-2 main protease inhibitors from natural essential oil compounds

Background: Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has fomented a climate of fear worldwide due to its rapidly spreading nature, and high mortality rate. The World Health Organization (WHO) declared it as a global pandemic on 11th March, 2020. Many endeavors have been made to find appropriate medications to restrain the SARS CoV-2 infection from spreading but there is no specific antiviral therapy to date. However, a computer-aided drug design approach can be an alternative to identify probable drug candidates within a short time. SARS-CoV-2 main protease is a proven drug target, and it plays a pivotal role in viral replication and transcription. Methods: In this study, we identified a total of 114 essential oil compounds as a feasible anti-SARS-CoV-2 agent from several online reservoirs. These compounds were screened by incorporating ADMET profiling, molecular docking, and 50 ns of molecular dynamics simulation to identify potential drug candidates against the SARS-CoV-2 main protease. The crystallized SARS-CoV-2 main protease structure was collected from the RCSB PDB database (PDB ID 6LU7). Results: According to the results of the ADMET study, none of the compounds have any side effects that could reduce their druglikeness or pharmacokinetic properties. Out of 114 compounds, we selected bisabololoxide B, eremanthin, and leptospermone as our top drug candidates based on their higher binding affinity scores, and strong interaction with the Cys 145-His 41 catalytic dyad. Finally, the molecular dynamics simulation was implemented to evaluate the structural stability of the ligand-receptor complex. MD simulations disclosed that all the hits showed conformational stability compared to the positive control α-ketoamide. Conclusions: Our study showed that the top three hits might work as potential anti-SARS-CoV-2 agents, which can pave the way for discovering new drugs, but for experimental validation, they will require more in vivo trials.

Filter Feature Selection for Unsupervised Clustering of Designer Drugs Using DFT Simulated IR Spectra Data

The rapid emergence of novel psychoactive substances (NPS) poses new challenges and requirements for forensic testing/analysis techniques. This paper aims to explore the application of unsupervised clustering of NPS compounds' infrared spectra. Two statistical measures, Pearson and Spearman, were used to quantify the spectral similarity and to generate similarity matrices for hierarchical clustering. The correspondence of spectral similarity clustering trees to the commonly used structural/pharmacological categorization was evaluated and compared to the clustering generated using 2D/3D molecular fingerprints. Hybrid model feature selections were applied using different filter-based feature ranking algorithms developed for unsupervised clustering tasks. Since Spearman tends to overestimate the spectral similarity based on the overall pattern of the full spectrum, the clustering result shows the highest degree of improvement from having the nondiscriminative features removed. The loading plots of the first two principal components of the optimal feature subsets confirmed that the most important vibrational bands contributing to the clustering of NPS compounds were selected using non-negative discriminative feature selection (NDFS) algorithms.

Histone Modification in NSCLC: Molecular Mechanisms and Therapeutic Targets

Lung cancer is the leading cause of cancer mortality in both genders, with non-small cell lung cancer (NSCLC) accounting for about 85% of all lung cancers. At the time of diagnosis, the tumour is usually locally advanced or metastatic, shaping a poor disease outcome. NSCLC includes adenocarcinoma, squamous cell carcinoma, and large cell lung carcinoma. Searching for novel therapeutic targets is mandated due to the modest effect of platinum-based therapy as well as the targeted therapies developed in the last decade. The latter is mainly due to the lack of mutation detection in around half of all NSCLC cases. New therapeutic modalities are also required to enhance the effect of immunotherapy in NSCLC. Identifying the molecular signature of NSCLC subtypes, including genetics and epigenetic variation, is crucial for selecting the appropriate therapy or combination of therapies. Epigenetic dysregulation has a key role in the tumourigenicity, tumour heterogeneity, and tumour resistance to conventional anti-cancer therapy. Epigenomic modulation is a potential therapeutic strategy in NSCLC that was suggested a long time ago and recently starting to attract further attention. Histone acetylation and deacetylation are the most frequently studied patterns of epigenetic modification. Several histone deacetylase (HDAC) inhibitors (HDIs), such as vorinostat and panobinostat, have shown promise in preclinical and clinical investigations on NSCLC. However, further research on HDIs in NSCLC is needed to assess their anti-tumour impact. Another modification, histone methylation, is one of the most well recognized patterns of histone modification. It can either promote or inhibit transcription at different gene loci, thus playing a rather complex role in lung cancer. Some histone methylation modifiers have demonstrated altered activities, suggesting their oncogenic or tumour-suppressive roles. In this review, patterns of histone modifications in NSCLC will be discussed, focusing on the molecular mechanisms of epigenetic modifications in tumour progression and metastasis, as well as in developing drug resistance. Then, we will explore the therapeutic targets emerging from studying the NSCLC epigenome, referring to the completed and ongoing clinical trials on those medications.

Elucidating doxycycline loading and release performance of imprinted hydrogels with different cross-linker concentrations: a computational and experimental study

Effective non-covalent molecular imprinting on a polymer depends on the extent of non-bonded interactions between the template and other molecules before polymerization. Here, we first determine functional monomers that can yield a doxycycline-imprinted hydrogel based on the hydrogen bond interactions at the prepolymerization step, revealed by molecular dynamics (MD) simulations, molecular docking, and simulated annealing methods. Then, acrylic acid (AA)-based doxycycline (DOX) imprinted (MIP) and non-imprinted (NIP) hydrogels are synthesized in cross-linker ethylene glycol dimethacrylate (EGDMA) ratios of 1.0, 1.5, 2.0, and 3.0 mol%. Here, molecularly imprinted polymer with 3.0 mol% EGDMA has the highest imprinting factor (1.58) and best controlled drug release performance. At this point, full-atom MD simulations of DOX–AA solutions at different EGDMA concentrations reveal that AA and EGDMA compete to interact with DOX. However, at 3.0 mol% EGDMA, AA attains numerous stable hydrogen bond interactions with the drug. This study demonstrates that the concentration of the cross-linker and functional monomer can be adjusted to increase the success of imprinting, where the interplay between these two parameters can be successfully revealed by MD simulations.

Exploring Chemical Information in PubChem

PubChem (https://pubchem.ncbi.nlm.nih.gov) is a public chemical database that serves scientific communities as well as the general public. This database collects chemical information from hundreds of data sources and organizes them into multiple data collections, including Substance, Compound, BioAssay, Protein, Gene, Pathway, and Patent. These collections are interlinked with each other, allowing users to discover related records in the various collections (e.g., drugs targeting a protein or genes modulated by a chemical). PubChem can be searched by keyword (e.g., a chemical, protein, or gene name) as well as by chemical structure. The input structure can be provided using popular line notations or drawn with the PubChem Sketcher. PubChem supports various types of structure searches, including identity search, 2‐D and 3‐D similarity searches, and substructure and superstructure searches. Results from multiple searches can be combined using Boolean operators (i.e., AND, OR, and NOT) to formulate complex queries. PubChem allows the user to quickly retrieve a list of records annotated with a particular classification or ontological term. This paper provides step‐by‐step instructions on how to explore PubChem data with examples of commonly requested tasks. © 2021. This article is a U.S. Government work and is in the public domain in the USA. Current Protocols published by Wiley Periodicals LLC.

Basic Protocol 1: Finding genes and proteins that interact with a given compound

Basic Protocol 2: Finding drug‐like compounds similar to a query compound through a two‐dimensional (2‐D) similarity search

Basic Protocol 3: Finding compounds similar to a query compound through a three‐dimensional (3‐D) similarity search

Support Protocol: Computing similarity scores between compounds

Basic Protocol 4: Getting the bioactivity data for the hit compounds from substructure search

Basic Protocol 5: Finding drugs that target a particular gene

Basic Protocol 6: Getting bioactivity data of all chemicals tested against a protein.

Basic Protocol 7: Finding compounds annotated with classifications or ontological terms

Basic Protocol 8: Finding stereoisomers and isotopomers of a compound through identity search

Potential combination therapy using twenty phytochemicals from twenty plants to prevent SARS- CoV-2 infection: An in silico Approach

Covid 19 caused by novel strain SARS- CoV-2 has become a pandemic due to its contagious nature of infection. It enters by binding with ACE2 receptor present on the outer surface of a cell by cleaving S1/S2 with proteolytic protein Furin. Further viral replication or transcription then takes place with the help of main protease 3CLpro and polymerase RdRp. This in silco study was carried out to block ACE2, Furin, 3CLpro and RdRP with various phytochemicals to prevent SARS- CoV-2 entry and replication or transcription. Twenty different phytochemicals were screened to understand the drug-likeliness obeying Lipinski’s rule 5 and further, molecular docking was performed using these phytochemicals to block their respective target proteins. All the phytochemicals follow Lipinski’s rule of five and molecular docking result shows best binding affinity of Podofilox − 7.54 kcal/mol with ACE2, Psoralidin − 8.04 kcal/mol with Furin, Ursolic acid − 8.88 kcal/mol with 3CLpro and Epiafzelechin − 8.26 kcal/mol with RdRp. Thus, blocking two human receptors ACE2 and Furin with Podofilox and Psoralidin respectively may prevent the viral entry into the cells. Also blocking viral proteins 3CLpro and RdRp with Ursolic acid and Epiafzelechin may prevent viral replication or transcription. Using this combination therapy of blocking the receptors responsible for viral entry and viral proteins responsible for replication or transcription may prevent SARS- CoV-2 infection.

Mapping Ligand-Shape Space for Protein-Ligand Systems: Distinguishing Key-in-Lock and Hand-in-Glove Proteins

Many of the recently developed methods to study the shape of molecules permit one conformation of one molecule to be compared to another conformation of the same or a different molecule: a relative shape. Other methods provide an absolute description of the shape of a conformation that does not rely on comparisons or overlays. Any absolute description of shape can be used to generate a self-organizing map (shape map) that places all molecular shapes relative to one another; in the studies reported here, the shape fingerprint and ultrafast shape recognition methods are employed to create such maps. In the shape maps, molecules that are near one another have similar shapes, and the maps for the 102 targets in the DUD-E set have been generated. By examining the distribution of actives in comparison with their physical-property-matched decoys, we show that the proteins of key-in-lock type (relatively rigid receptor and ligand) can be distinguished from those that are more of a hand-in-glove type (more flexible receptor and ligand). These are linked to known differences in protein flexibility and binding-site size.

A problem-/case-based learning approach as an useful tool for studying glycogen metabolism and its regulation

Metabolism and its regulation is one of the most complex and difficult topics for students learning biochemistry. A problem-/case-based learning (PBL) approach can be useful to help biochemistry students to fulfill the goal of acquiring an integrated view of metabolism and its regulation. The present article describes our experience enrolling volunteer students to learn glycogen metabolism making use of a design-based research methodology to develop teaching learning sequences focused on a PBL approach. Enrolled undergraduate students had better final scores than those students that did not participates. Furthermore, enrolled students were satisfied with the experience, finding it interesting, formative, and challenging.

An integrated virtual screening of compounds from Carica papaya leaves against multiple protein targets of SARS-Coronavirus-2

The pandemic of SARS-Coronavirus-2 (Coronavirus-19) has been progressing by the increasing trend of the cases as well as deaths with neither vaccine nor drug is rationally used to stop the viral spread over. This study aims to perform an integrated virtual screening of compounds that had been identified from Carica papaya leaves, which are proposed to be a herbal treatment for SARS-Coronavirus-2. The screening was initiated by evaluating the 40 compounds from Carica papaya leaves for their drug-like likeness property. The selected compounds were then secondly screened using carcinogenic and toxicity filters. Further selected compounds were thirdly screened for their pharmacokinetic profile and the screening was lastly performed by docking the third selected compounds against multiple protein targets of SARS-Coronavirus-2 employing 3-chymotrypsin-like protease (3CLpro), papain-like protease (PLpro), RNA-dependent-RNA-polymerase (RdRp), endonuclease (EndoU), S1 and S2 region of spike protein. The results show that 20 of 40 compounds, which meet the requirements of drug-like likeness, carcinogenicity-toxicity filter, and pharmacokinetic profiles, can interact with the multiple protein targets of SARS-Coronavirus-2 with the order from high to low affinity as follows: S1 > 3CLpro > EndoU > RdRp > PLpro > S2. In conclusion, Carica papaya leaves are worth to be proposed for further in vitro study against SARS-Coronavirus-2 at both molecular and cellular levels.

CMNPD: a comprehensive marine natural products database towards facilitating drug discovery from the ocean

Marine organisms are expected to be an important source of inspiration for drug discovery after terrestrial plants and microorganisms. Despite the remarkable progress in the field of marine natural products (MNPs) chemistry, there are only a few open access databases dedicated to MNPs research. To meet the growing demand for mining and sharing for MNPs-related data resources, we developed CMNPD, a comprehensive marine natural products database based on manually curated data. CMNPD currently contains more than 31 000 chemical entities with various physicochemical and pharmacokinetic properties, standardized biological activity data, systematic taxonomy and geographical distribution of source organisms, and detailed literature citations. It is an integrated platform for structure dereplication (assessment of novelty) of (marine) natural products, discovery of lead compounds, data mining of structure-activity relationships and investigation of chemical ecology. Access is available through a user-friendly web interface at https://www.cmnpd.org. We are committed to providing a free data sharing platform for not only professional MNPs researchers but also the broader scientific community to facilitate drug discovery from the ocean.

UCSF ChimeraX: Structure visualization for researchers, educators, and developers

UCSF ChimeraX is the next-generation interactive visualization program from the Resource for Biocomputing, Visualization, and Informatics (RBVI), following UCSF Chimera. ChimeraX brings (a) significant performance and graphics enhancements; (b) new implementations of Chimera's most highly used tools, many with further improvements; (c) several entirely new analysis features; (d) support for new areas such as virtual reality, light-sheet microscopy, and medical imaging data; (e) major ease-of-use advances, including toolbars with icons to perform actions with a single click, basic "undo" capabilities, and more logical and consistent commands; and (f) an app store for researchers to contribute new tools. ChimeraX includes full user documentation and is free for noncommercial use, with downloads available for Windows, Linux, and macOS from https://www.rbvi.ucsf.edu/chimerax.

Nontargeted Identification of Plasma Proteins O-, N-, and S-Transmethylated by O-Methyl Organophosphates

Organophosphates (OPs) are used worldwide as pesticides. However, acute and chronic exposure to OPs can cause serious adverse health effects. The mechanism of delayed OP toxicity is thought to involve off-target inhibition of serine proteases, although the precise molecular details remain unclear owing to the lack of an analytical method for global detection of protein targets of OPs. Here, we report the development of a mass spectrometry method to identify OP-adducted proteins from complex mixtures in a nontargeted manner. Human plasma was incubated with the OP dichlorvos that was 50% isotopically labeled and 50% unlabeled. Proteins and protein adducts were extracted, digested, and analyzed by liquid chromatography-tandem mass spectrometry (LC-MS/MS) to detect "twin ions" of peptides that were covalently modified by a chemical reaction with dichlorvos. The LC-MS/MS data were processed by a blended data analytics software (Xenophile) to detect the amino acid residue sites of proteins that were covalently modified by exposure to OPs. We discovered that OPs can transmethylate the N, S, and O side chains of His, Cys, Glu, Asp, and Lys residues. For model systems, such transmethylation reactions were confirmed by LC-MS, nuclear magnetic resonance (NMR), and rationalized using electronic structure calculations. Methylation of the ubiquitous antioxidant glutathione by dichlorvos can decrease the reducing/oxidizing equilibrium of glutathione in liver extracts, which has been implicated in diseases and pathological conditions associated with delayed OP toxicity.

PubChemQC PM6: Data Sets of 221 Million Molecules with Optimized Molecular Geometries and Electronic Properties

We report on optimized molecular geometries and electronic properties calculated by the PM6 method for 94.0% of the 91.6 million molecules cataloged in PubChem Compounds retrieved on August 29, 2016. In addition to neutral states, we also calculated those for cationic, anionic, and spin flipped electronic states of 56.2%, 49.7%, and 41.3% of the molecules, respectively. Thus, the grand total of the PM6 calculations amounted to 221 million. We compared the resulting molecular geometries with B3LYP/6-31G* optimized geometries for 2.6 million molecules. The root-mean-square deviations in bond length and bond angle were approximately 0.016 Å and 1.7°, respectively. Then, using linear regression to examine the HOMO energy levels E(HOMO) in the B3LYP and PM6 calculations, we found that E_B3LYP(HOMO) = 0.876E_PM6(HOMO) + 1.975 (eV) and calculated the coefficient of determination to be 0.803. Likewise, we examined the LUMO energy levels and found E_B3LYP(LUMO) = 1.069E_PM6(LUMO) - 0.420 (eV); the coefficient of determination was 0.842. We also generated four subdata sets, each of which was composed of molecules with molecular weights less than 500. Subdata set i contained C, H, O and N, ii contained C, H, N, O, P, and S, iii contained C, H, N, O, P, S, F, and Cl, and iv contained C, H, N, O, P, S, F, Cl, Na, K, Mg, and Ca. The data sets are available at http://pubchemqc.riken.jp/pm6_datasets.html under a Creative Commons Attribution 4.0 International license.

A Cyclodextrin-Stabilized Spermine-Tagged Drug Triplex that Targets Theophylline to the Lungs Selectively in Respiratory Emergency

Ion‐pairing a lifesaving drug such as theophylline with a targeting moiety could have a significant impact on medical emergencies such as status asthmaticus or COVID‐19 induced pneumomediastinum. However, to achieve rapid drug targeting in vivo the ion‐pair must be protected against breakdown before the entry into the target tissue. This study aims to investigate if inserting theophylline, when ion‐paired to the polyamine transporter substrate spermine, into a cyclodextrin (CD), to form a triplex, could direct the bronchodilator to the lungs selectively after intravenous administration. NMR demonstrates that upon the formation of the triplex spermine protruded from the CD cavity and this results in energy‐dependent uptake in A549 cells (1.8‐fold enhancement), which persists for more than 20 min. In vivo, the triplex produces a 2.4‐fold and 2.2‐fold increase in theophylline in the lungs 20 min after injection in rats and mice, respectively (p < 0.05). The lung targeting is selective with no increase in uptake into the brain or the heart where the side‐effects of theophylline are treatment‐limiting. Selectively doubling the concentration of theophylline in the lungs could improve the benefit‐risk ratio of this narrow therapeutic index medicine, which continues to be important in critical care.

Potent HCV NS3 Protease Inhibition by a Water-Soluble Phyllanthin Congener

NS3/4A protease of hepatitis C virus (HCV) plays an important role in viral RNA replication. A 1,4-diphenylbutanedicarboxylic acid derivative, namely, phyllanthin, extracted from the leaf of a herbal plant, Phyllanthus amarus, inhibits HCV NS3/4A protease and replication activities. However, the reduced aqueous solubility, high toxicity, and poor oral bioavailability are major impediments with phyllanthin. We herein present a design approach to generate phyllanthin congeners in order to potentiate inhibition activity against protease. The phyllanthin congeners were synthesized by chemical methods and subjected to systematic biological studies. One of the congeners, annotated as D8, is identified as a novel and potent inhibitor of the HCV-NS3/4Aprotease activity in vitro and the viral RNA replication in cell culture. Structural analysis using the computational-based docking approach demonstrated important noncovalent interactions between D8 and the catalytic residues of the viral protease. Furthermore, D8 was found to be significantly nontoxic in cell culture. More importantly, oral administration of D8 in BALB/c mice proved its better tolerability and bioavailability, as compared to native phyllanthin. Taken together, this study reveals a promising candidate for developing anti-HCV therapeutics to control HCV-induced liver diseases.

PUG-View: programmatic access to chemical annotations integrated in PubChem

PubChem is a chemical data repository that provides comprehensive information on various chemical entities. It contains a wealth of chemical information from hundreds of data sources. Programmatic access to this large amount of data provides researchers with new opportunities for data-intensive research. PubChem provides several programmatic access routes. One of these is PUG-View, which is a Representational State Transfer (REST)-style web service interface specialized for accessing annotation data contained in PubChem. The present paper describes various aspects of PUG-View, including the scope of data accessible through PUG-View, the syntax for formulating a PUG-View request URL, the difference of PUG-View from other web service interfaces in PubChem, and its limitations and usage policies.

An update on PUG-REST: RESTful interface for programmatic access to PubChem

PubChem (https://pubchem.ncbi.nlm.nih.gov) is one of the largest open chemical information resources available. It currently receives millions of unique users per month on average, serving as a key resource for many research fields such as cheminformatics, chemical biology, medicinal chemistry, and drug discovery. PubChem provides multiple programmatic access routes to its data and services. One of them is PUG-REST, a Representational State Transfer (REST)-like web service interface to PubChem. On average, PUG-REST receives more than a million requests per day from tens of thousands of unique users. The present paper provides an update on PUG-REST since our previous paper published in 2015. This includes access to new kinds of data (e.g. concise bioactivity data, table of contents headings, etc.), full implementation of synchronous fast structure search, support for assay data retrieval using accession identifiers in response to the deprecation of NCBI’s GI numbers, data exchange between PUG-REST and NCBI’s E-Utilities through the List Gateway, implementation of dynamic traffic control through throttling, and enhanced usage policies. In addition, example Perl scripts are provided, which the user can easily modify, run, or translate into another scripting language.

PerMM: A Web Tool and Database for Analysis of Passive Membrane Permeability and Translocation Pathways of Bioactive Molecules

The PerMM web server and database were developed for quantitative analysis and visualization of passive translocation of bioactive molecules across lipid membranes. The server is the first physics-based web tool that calculates membrane binding energies and permeability coefficients of diverse molecules through artificial and natural membranes (phospholipid bilayers, PAMPA-DS, blood-brain barrier, and Caco-2/MDCK cell membranes). It also visualizes the transmembrane translocation pathway as a sequence of translational and rotational positions of a permeant as it moves across the lipid bilayer, along with the corresponding changes in solvation energy. The server can be applied for prediction of permeability coefficients of compounds with diverse chemical scaffolds to facilitate selection and optimization of potential drug leads. The complementary PerMM database allows comparison of computationally and experimentally determined permeability coefficients for more than 500 compounds in different membrane systems. The website and database are freely accessible at https://permm.phar.umich.edu/ .