Bioinformatics and computational chemistry approaches to explore the mechanism of the anti-depressive effect of ligustilide.

Depression affects people with multiple adverse outcomes, and the side effects of antidepressants are troubling for depression sufferers. Aromatic drugs have been widely used to relieve symptoms of depression with fewer side effects. Ligustilide (LIG) is the main component of volatile oil in angelica sinensis, exhibiting an excellent anti-depressive effect. However, the mechanisms of the anti-depressive effect of LIG remain unclear. Therefore, this study aimed to explore the mechanisms of LIG exerting an anti-depressive effect. We obtained 12,969 depression-related genes and 204 LIG targets by a network pharmacology approach, which were intersected to get 150 LIG anti-depressive targets. Then, we identified core targets by MCODE, including MAPK3, EGF, MAPK14, CCND1, IL6, CASP3, IL2, MYC, TLR4, AKT1, ESR1, TP53, HIF1A, SRC, STAT3, AR, IL1B, and CREBBP. Functional enrichment analysis of core targets showed a significant association with PI3K/AKT and MAPK signaling pathways. Molecular docking showed strong affinities of LIG with AKT1, MAPK14, and ESR1. Finally, we validated the interactions between these proteins and LIG by molecular dynamics (MD) simulations. In conclusion, this study successfully predicted that LIG exerted an anti-depressive effect through multiple targets, including AKT1, MAPK14, and ESR1, and the pathways of PI3K/AKT and MAPK. The study provides a new strategy to explore the molecular mechanisms of LIG in treating depression.

Natural remedies medicine derived from flaxseed (secoisolariciresinol diglucoside, lignans, and α-linolenic acid) improve network targeting efficiency of diabetic heart conditions based on computational chemistry techniques and pharmacophore modeling.

Cytokine storms lead to cardiovascular diseases (CVDs). Natural herbal compounds are considered the primary source of active agents with the potential to prevent or treat inflammatory-related pathologies such as CVD and diabetes. Flaxseed contains phytochemicals, including secoisolariciresinol diglucoside (SDG), α-linolenic acid (ALA), and lignans, termed "SAL." Hence, we evaluated the effect of the SAL on the H9c2 cardiac cells in hyperlipidemic and hyperglycemic conditions. Here, candidate hub genes, TNF-α, IL6, SIRT1, NRF1, NPPA, and FGF7, were selected as effective genes in diabetic cardiovascular pathogenesis based on in-silico analysis and chemoinformatic. Myocardial infarction (MI) was induced using H9c2 cardiac cells in hyperlipidemic and hyperglycemic conditions. Real-time qPCR was conducted to assess the expression level of hub genes. This study indicated that SAL compounds bound to the Il-6, SIRT1, and TNF-α active sites as druggable candidate proteins based on the chemoinformatics analysis. This study displayed that the TNF-α, IL6, SIRT1, NRF1, NPPA, and FGF7 network dysfunction in MI models were ameliorated by SAL consumption. Furthermore, SAL compounds improved the function and myogenesis of H9c2 cells in hyperlipidemic and hyperglycemic conditions. Our data suggested that phytochemicals obtained from flaxseed might have proposed potential complementary treatment or preventive strategies for MI. PRACTICAL APPLICATIONS: Phytochemicals obtained from flaxseed (SAL) could reverse diabetic heart dysfunction hallmarks and provide new potential treatment approaches in cardiovascular therapy. SAL could be considered complementary and alternative medicines for treating various disorders/diseases singly or synchronizing with prescription drugs.

Investigation of fragmentation pathways of norpimarane diterpenoids by mass spectrometry combined with computational chemistry.

RATIONALE: Norpimarane diterpenes possess plentiful bioactivities and are widely distributed in herbs, such as Flickingeria fimbriata. Rapid characterization of these natural products in complicated plant extracts is of great importance, and electrospray ionization tandem mass spectrometry is a powerful tool for chemical constituent profiling. However, limited researches on their fragmentation mechanisms seriously hinder identification via mass spectrometry. METHODS: Three norpimarane diterpenes isolated from F. fimbriata via multiple types of column chromatography served as reference compounds, and collision-induced dissociation experiments were performed on them with a series of variable collision energies. Plausible fragmentation pathways were proposed based on product ions. To further validate the fragmentation mechanisms, the proton affinity and product ion energy were simulated by density functional theory at the B3LYP/6-31+G(d, p) level. RESULTS: Three main cleavage reactions induced skeleton breakage and resulted in characteristic ions, methyl (CH3 -20) migration, hydrogen arrangement and Retro-Diels-Alder reaction, among which methyl migration was firstly proposed for pimarane diterpenes. A series of common diagnostic ions were identified, such as m/z 133.1012, 121.1012, 119.0805 and 107.0855. Additionally, the constructed fragmentation mechanisms were successfully applied for fragment ion rationalization of previously reported isopimarane diterpenes. CONCLUSIONS: Fragmentation mechanisms of norpimarane diterpenes have been uncovered. Carbocation located at the C ring tends to result in methyl (CH3 -20) migration which has been rarely reported before. This characteristic dissociation reaction allows multiple diagnostic ions to be rationalized and aids in rationalizing fragmentation patterns of other diterpenes. The uncovered mechanisms also shed light on rapid identification of norpimarane diterpenes.

Screening of Severe Acute Respiratory Syndrome Coronavirus 2 RNA-Dependent RNA Polymerase Inhibitors Using Computational Approach.

The detrimental effect of coronavirus disease 2019 (COVID-19) pandemic has manifested itself as a global crisis. Currently, no specific treatment options are available for COVID-19, so therapeutic interventions to tackle the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection must be urgently established. Therefore, cohesive and multidimensional efforts are required to identify new therapies or investigate the efficacy of small molecules and existing drugs against SARS-CoV-2. Since the RNA-dependent RNA Polymerase (RdRP) of SARS-CoV-2 is a promising therapeutic target, this study addresses the identification of antiviral molecules that can specifically target SARS-CoV-2 RdRP. The computational approach of drug development was used to screen the antiviral molecules from two antiviral libraries (Life Chemicals [LC] and ASINEX) against RdRP. Here, we report six antiviral molecules (F3407-4105, F6523-2250, F6559-0746 from LC and BDG 33693278, BDG 33693315, LAS 34156196 from ASINEX), which show substantial interactions with key amino acid residues of the active site of SARS-CoV-2 RdRP and exhibit higher binding affinity (>7.5 kcalmol-1) than Galidesivir, an Food and Drug Administration-approved inhibitor of the same. Further, molecular dynamics simulation and Molecular Mechanics Poisson-Boltzmann Surface Area results confirmed that identified molecules with RdRP formed higher stable RdRP-inhibitor(s) complex than RdRP-Galidesvir complex. Our findings suggest that these molecules could be potential inhibitors of SARS-CoV-2 RdRP. However, further in vitro and preclinical experiments would be required to validate these potential inhibitors of SARS-CoV-2 protein.

Design, Synthesis, Biological Evaluation, and Computational Studies of Novel Fluorinated Candidates as PI3K Inhibitors: Targeting Fluorophilic Binding Sites.

Highly fluorinated candidates containing anticancer pharmacophores like thiosemicarbazone (5a-e) and its cyclic analogues hydrazineylidenethiazolidine (6a-e), 2-aminothiadiazole (7a-e), and 2-hydrazineylidenethiazolidin-4-one (8a-e) were synthesized, and their cytotoxic activity was assayed against 60 tumor cell lines. Compounds 6c, 7b, and 8b displayed the most potent activity with lower toxic effects on MCF-10a. In vitro phosphatidylinositol 3-kinase (PI3K) enzyme inhibition was performed. Compound 6c displayed half-maximal inhibitory concentration (IC50, µM) values of 5.8, 2.3, and 7.9; compound 7b displayed IC50 values of 19.4, 30.7, and 73.7; and compound 8b displayed IC50 values of 77.5, 53.5, and 121.3 for PI3Kα, ß, and δ, respectively. Moreover, cell cycle progression caused cell cycle arrest at the S phase for compounds 6c and 8b and at G1/S for compound 7b, while apoptosis was induced. In silico studies; molecular docking; physicochemical parameters; and absorption, distribution, metabolism, excretion, and toxicity (ADMET) analysis were performed. The results showed that compound 6c is the most potent one with a selectivity index (SI) of 39 and is considered as a latent lead for further optimization of anticancer agents.

3D-QSAR-Based Pharmacophore Modeling, Virtual Screening, and Molecular Docking Studies for Identification of Tubulin Inhibitors with Potential Anticancer Activity.

In this study, we aimed to develop a pharmacophore-based three-dimensional quantitative structure activity relationship (3D-QSAR) for a set including sixty-two cytotoxic quinolines (1-62) as anticancer agents with tubulin inhibitory activity. A total of 279 pharmacophore hypotheses were generated based on the survival score to build QSAR models. A six-point pharmacophore model (AAARRR.1061) was identified as the best model which consisted of three hydrogen bond acceptors (A) and three aromatic ring (R) features. The model showed a high correlation coefficient (R 2 = 0.865), cross-validation coefficient (Q 2 = 0.718), and F value (72.3). The best pharmacophore model was then validated by the Y-Randomization test and ROC-AUC analysis. The generated 3D contour maps were used to reveal the structure activity relationship of the compounds. The IBScreen database was screened against AAARRR.1061, and after calculating ADMET properties, 10 compounds were selected for further docking study. Molecular docking analysis showed that compound STOCK2S-23597 with the highest docking score (-10.948 kcal/mol) had hydrophobic interactions and can form four hydrogen bonds with active site residues.

Permeability prediction in the beyond-Rule-of 5 chemical space: Focus on cyclic hexapeptides.

Cyclic peptides (CPs) are gaining more and more relevance in drug discovery. Since one of their main drawbacks is poor permeability, the discovery of new orally available CP drugs requires computational tools that predict CP permeability in very early drug discovery. In this study we used a literature dataset of 62 cyclic hexapeptides to evaluate the performances of a number of in silico tools based on different computational theory to model and rationalize PAMPA and Caco-2 permeability values. In particular, we submitted the dataset to a) online calculators, b) QSPR strategies, c) a physics-based tool, d) a mixed approach and e) a kinetic method. This latter is an emergent strategy in which a few relevant conformations retrieved from a set of molecular dynamics (MD) simulations by the Markov State Model (MSM) are used to establish the compounds permeability. Both free and commercial software were used. Results were compared with a model based on experimental physicochemical descriptors. All the computational approaches but online calculators performed quite well and show that lipophilicity and not polarity is the main determinant of the investigated event. A second major outcome of the study is that the impact of flexibility on the permeability of the considered dataset cannot be unambiguously assessed. Finally, our comparative analysis, which also included not common applied strategies, allowed a sound evaluation of the pros and cons of the applied computational approaches.

A strategy combining solid-phase extraction, multiple mass defect filtering and molecular networking for rapid structural classification and annotation of natural products: characterization of chemical diversity in Citrus aurantium as a case study.

Medicinal plants are complex chemical systems containing thousands of secondary metabolites. The rapid classification and characterization of the components in medicinal plants using mass spectrometry (MS) remains an immense challenge. Herein, a novel strategy is presented for MS through the combination of solid-phase extraction (SPE), multiple mass defect filtering (MMDF) and molecular networking (MN). This strategy enables efficient classification and annotation of natural products. When combined with SPE and MMDF, the improved analytical method of MN can perform the rapid annotation of diverse natural products in Citrus aurantium according to the tandem mass spectrometry (MS/MS) fragments. In MN, MS2LDA can be initially applied to recognize substructures of natural products, according to the common fragmentation patterns and neutral losses in multiple MS/MS spectra. MolNetEnhancer was adopted here to obtain chemical classifications provided by ClassyFire. The results suggest that the integrated SPE-MMDF-MN method was capable of rapidly annotating a greater number of natural products from Citrus aurantium than the classical MN strategy alone. Moreover, SPE and MMDF enhanced the effectiveness of MN for annotating, classifying and distinguishing different types of natural products. Our workflow provides the foundation for the automated, high-throughput structural classification and annotation of secondary metabolites with various chemical structures. The developed approach can be widely applied in the analysis of constituents in natural products.

The Three Pillars of Natural Product Dereplication. Alkaloids from the Bulbs of Urceolina peruviana (C. Presl) J.F. Macbr. as a Preliminary Test Case.

The role and importance of the identification of natural products are discussed in the perspective of the study of secondary metabolites. The rapid identification of already reported compounds, or structural dereplication, is recognized as a key element in natural product chemistry. The biological taxonomy of metabolite producing organisms, the knowledge of metabolite molecular structures, and the availability of metabolite spectroscopic signatures are considered as the three pillars of structural dereplication. The role and the construction of databases is illustrated by references to the KNApSAcK, UNPD, CSEARCH, and COCONUT databases, and by the importance of calculated taxonomic and spectroscopic data as substitutes for missing or lost original ones. Two NMR-based tools, the PNMRNP database that derives from UNPD, and KnapsackSearch, a database generator that provides taxonomically focused libraries of compounds, are proposed to the community of natural product chemists. The study of the alkaloids from Urceolina peruviana, a plant from the Andes used in traditional medicine for antibacterial and anticancer actions, has given the opportunity to test different approaches to dereplication, favoring the use of publicly available data sources.

Computational screening of natural and natural-like compounds to identify novel ligands for sigma-2 receptor.

Sigma-2 (σ2) receptor is a transmembrane protein shown to be linked with neurodegenerative diseases and cancer development. Thus, it emerges as a potential biological target for the advancement of anticancer and anti-Alzheimer's agents. The current study was aimed to identify potential σ2 receptor ligands using integrated computational approaches including homology modelling, combined pharmacophore- and docking-based virtual screening, and molecular dynamics (MD) simulation. Pharmacophore-based screening was conducted against a database composed of 20,523 small natural and natural-like products. In total, 1200 structures were found to satisfy the required pharmacophore features and were then exposed to docking-based screening against the generated homology model of σ2 receptor. On the basis of the pharmacophore fit scores, docking scores, and mechanism of binding interaction, 20 potential hits were retained. Five promising candidates were selected (SR84, SR823, SR300, SR413, and SR530) on the basis of their binding score and interaction. Further, in silico ADMET profiling of these compounds showed that the selected compounds possess favourable ADME properties with low toxicity risk. The mechanism of interaction of these compounds with σ2 receptor as well as their binding stability were characterized by MD simulation.

Unravelling the Biological Activities of the Byttneria pilosa Leaves Using Experimental and Computational Approaches.

Byttneria pilosa is locally known as Harijora, and used by the native hill-tract people of Bangladesh for the treatment of rheumatalgia, snake bite, syphilis, fractured bones, elephantiasis and an antidote for poisoning. The present study was carried out to determine the possible anti-inflammatory, analgesic, neuropharmacological and anti-diarrhoeal activity of the methanol extract of B. pilosa leaves (MEBPL) through in vitro, in vivo and in silico approaches. In the anti-inflammatory study, evaluated by membrane stabilizing and protein denaturation methods, MEBPL showed a significant and dose dependent inhibition. The analgesic effect of MEBPL tested by inducing acetic acid and formalin revealed significant inhibition of pain in both tests. During the anxiolytic evaluation, the extract exhibited a significant and dose-dependent reduction of anxiety-like behaviour in mice. Similarly, mice treated with MEBPL demonstrated dose-dependent reduction in locomotion effect in the open field test and increased sedative effect in the thiopental sodium induced sleeping test. MEBPL also showed good anti-diarrheal activity in both castor oil induced diarrheal and intestinal motility tests. Besides, a previously isolated compound (beta-sitosterol) exhibited good binding affinity in docking and drug-likeliness properties in ADME/T studies. Overall, B. pilosa is a biologically active plant and could be a potential source of drug leads, which warrants further advanced study.

Discovery of Potential Chemical Probe as Inhibitors of CXCL12 Using Ligand-Based Virtual Screening and Molecular Dynamic Simulation.

CXCL12 are small pro-inflammatory chemo-attractant cytokines that bind to a specific receptor CXCR4 with a role in angiogenesis, tumor progression, metastasis, and cell survival. Globally, cancer metastasis is a major cause of morbidity and mortality. In this study, we targeted CXCL12 rather than the chemokine receptor (CXCR4) because most of the drugs failed in clinical trials due to unmanageable toxicities. Until now, no FDA approved medication has been available against CXCL12. Therefore, we aimed to find new inhibitors for CXCL12 through virtual screening followed by molecular dynamics simulation. For virtual screening, active compounds against CXCL12 were taken as potent inhibitors and utilized in the generation of a pharmacophore model, followed by validation against different datasets. Ligand based virtual screening was performed on the ChEMBL and in-house databases, which resulted in successive elimination through the steps of pharmacophore-based and score-based screenings, and finally, sixteen compounds of various interactions with significant crucial amino acid residues were selected as virtual hits. Furthermore, the binding mode of these compounds were refined through molecular dynamic simulations. Moreover, the stability of protein complexes, Root Mean Square Deviation (RMSD), Root Mean Square Fluctuation (RMSF), and radius of gyration were analyzed, which led to the identification of three potent inhibitors of CXCL12 that may be pursued in the drug discovery process against cancer metastasis.

Thyroxine binding to type III iodothyronine deiodinase.

Iodothyronine deiodinases (Dios) are important selenoproteins that control the concentration of the active thyroid hormone (TH) triiodothyronine through regioselective deiodination. The X-ray structure of a truncated monomer of Type III Dio (Dio3), which deiodinates TH inner rings through a selenocysteine (Sec) residue, revealed a thioredoxin-fold catalytic domain supplemented with an unstructured Ω-loop. Loop dynamics are driven by interactions of the conserved Trp207 with solvent in multi-microsecond molecular dynamics simulations of the Dio3 thioredoxin(Trx)-fold domain. Hydrogen bonding interactions of Glu200 with residues conserved across the Dio family anchor the loop's N-terminus to the active site Ser-Cys-Thr-Sec sequence. A key long-lived loop conformation coincides with the opening of a cryptic pocket that accommodates thyroxine (T4) through an I⋯Se halogen bond to Sec170 and the amino acid group with a polar cleft. The Dio3-T4 complex is stabilized by an I⋯O halogen bond between an outer ring iodine and Asp211, consistent with Dio3 selectivity for inner ring deiodination. Non-conservation of residues, such as Asp211, in other Dio types in the flexible portion of the loop sequence suggests a mechanism for regioselectivity through Dio type-specific loop conformations. Cys168 is proposed to attack the selenenyl iodide intermediate to regenerate Dio3 based upon structural comparison with related Trx-fold proteins.

Development, characterization and in vitro antioxidant activity of chitosan-coated alginate microcapsules entrapping Viola odorata Linn. extract.

Viola odorata Linn or sweet violet has several biological activities due to the presence of flavonoids, tannins, alaloid, glycoside, and saponins. However, susceptibility of these compounds to harsh conditions and low solubility is a great challenge for their incorporation into food products. Therefore, encapsulation can be an effective approach in this respect. In the present study, chitosan-coated microcapsules loaded with Viola extract were prepared for the first time and the effects of independent variables (sodium alginate: 1-1.5%, calcium chloride: 0.6-1.5% and extract concentrations: 5-10%) on encapsulation efficiency (EE%) were investigated. After evaluation of the model, the optimum condition for preparation of microcapsules was selected as 1.47% sodium alginate, 5.02% extract and 1.42% CaCl2 with EE% of 83.21%. The microcapsules developed at this condition had an acceptable spherical shape and the results obtained in Fourier transform-infrared spectroscopy (FTIR) indicated the presence of the extract within the microcapsules. The mean diameters of the uncoated and chitosan-coated microcapsules were 73 and 141 µm, respectively. The in vitro release in acidic medium (pH 1.5) and phosphate buffer saline (pH 7) were 43.21% and 95.39%, respectively. The prepared extract-loaded microcapsules have potential to be used in food products providing acceptable antioxidant activity.

Glycerol as Alternative Co-Solvent for Water Extraction of Polyphenols from Carménère Pomace: Hot Pressurized Liquid Extraction and Computational Chemistry Calculations.

Glycerol is a co-solvent for water extraction that has been shown to be highly effective for obtaining polyphenol extracts under atmospheric conditions. However, its efficacy under subcritical conditions has not yet been studied. We assessed different water-glycerol mixtures (15%, 32.5%, and 50%) in a hot pressurized liquid extraction system (HPLE: 10 MPa) at 90 °C, 120 °C, and 150 °C to obtain extracts of low molecular weight polyphenols from Carménère grape pomace. Under the same extraction conditions, glycerol as a co-solvent achieved significantly higher yields in polyphenols than ethanol. Optimal extraction conditions were 150 °C, with 32.5% glycerol for flavonols and 50% for flavanols, stilbenes, and phenolic acids. Considering gallic acid as a model molecule, computational chemistry calculations were applied to explain some unusual extraction outcomes. Furthermore, glycerol, methanol, ethanol, and ethylene glycol were studied to establish an incipient structure-property relationship. The high extraction yields of gallic acid obtained with water and glycerol solvent mixtures can be explained not only by the additional hydrogen bonds between glycerol and gallic acid as compared with the other alcohols, but also because the third hydroxyl group allows the formation of a three-centered hydrogen bond, which intensifies the strongest glycerol and gallic acid hydrogen bond. The above occurs both in neutral and deprotonated gallic acid. Consequently, glycerol confers to the extraction solvent a higher solvation energy of polyphenols than ethanol.

Chemistry, Biological Activities and In Silico Bioprospection of Sterols and Triterpenes from Mexican Columnar Cactaceae.

The Cactaceae family is an important source of triterpenes and sterols. The wide uses of those plants include food, gathering, medicinal, and live fences. Several studies have led to the isolation and characterization of many bioactive compounds. This review is focused on the chemistry and biological properties of sterols and triterpenes isolated mainly from some species with columnar and arborescent growth forms of Mexican Cactaceae. Regarding the biological properties of those compounds, apart from a few cases, their molecular mechanisms displayed are not still fully understand. To contribute to the above, computational chemistry tools have given a boost to traditional methods used in natural products research, allowing a more comprehensive exploration of chemistry and biological activities of isolated compounds and extracts. From this information an in silico bioprospection was carried out. The results suggest that sterols and triterpenoids present in Cactaceae have interesting substitution patterns that allow them to interact with some bio targets related to inflammation, metabolic diseases, and neurodegenerative processes. Thus, they should be considered as attractive leads for the development of drugs for the management of chronic degenerative diseases.

Transformation of hard pollen into soft matter.

Pollen's practically-indestructible shell structure has long inspired the biomimetic design of organic materials. However, there is limited understanding of how the mechanical, chemical, and adhesion properties of pollen are biologically controlled and whether strategies can be devised to manipulate pollen beyond natural performance limits. Here, we report a facile approach to transform pollen grains into soft microgel by remodeling pollen shells. Marked alterations to the pollen substructures led to environmental stimuli responsiveness, which reveal how the interplay of substructure-specific material properties dictates microgel swelling behavior. Our investigation of pollen grains from across the plant kingdom further showed that microgel formation occurs with tested pollen species from eudicot plants. Collectively, our experimental and computational results offer fundamental insights into how tuning pollen structure can cause dramatic alterations to material properties, and inspire future investigation into understanding how the material science of pollen might influence plant reproductive success.

Identification of novel inhibitors for TNFα, TNFR1 and TNFα-TNFR1 complex using pharmacophore-based approaches.

BACKGROUND: Tumor necrosis factor α (TNFα) is a multifunctional cytokine with a potent pro-inflammatory effect. It is a validated therapeutic target molecule for several disorders related to autoimmunity and inflammation. TNFα-TNF receptor-1 (TNFR1) signaling contributes to the pathological processes of these disorders. The current study is focused on finding novel small molecules that can directly bind to TNFα and/or TNFR1, preventing the interaction between TNFα or TNFR1, and regulating downstream signaling pathways. METHODS: Cheminformatics pipeline (pharmacophore modeling, virtual screening, molecular docking and in silico ADMET analysis) was used to screen for novel TNFα and TNFR1 inhibitors in the Zinc database. The pharmacophore-based models were generated to screen for the best drug like compounds in the Zinc database. RESULTS: The 39, 37 and 45 best hit molecules were mapped with the core pharmacophore features of TNFα, TNFR1, and the TNFα-TNFR1 complex respectively. They were further evaluated by molecular docking, protein-ligand interactions and in silico ADMET studies. The molecular docking analysis revealed the binding energies of TNFα, TNFR1 and the TNFα-TNFR1 complex, the basis of which was used to select the top five best binding energy compounds. Furthermore, in silico ADMET studies clearly revealed that all 15 compounds (ZINC09609430, ZINC49467549, ZINC13113075, ZINC39907639, ZINC25251930, ZINC02968981, ZINC09544246, ZINC58047088, ZINC72021182, ZINC08704414, ZINC05462670, ZINC35681945, ZINC23553920, ZINC05328058, and ZINC17206695) satisfied the Lipinski rule of five and had no toxicity. CONCLUSIONS: The new selective TNFα, TNFR1 and TNFα-TNFR1 complex inhibitors can serve as anti-inflammatory agents and are promising candidates for further research.

Timescales of developmental toxicity impacting on research and needs for intervention.

Much progress has happened in understanding developmental vulnerability to preventable environmental hazards. Along with the improved insight, the perspective has widened, and developmental toxicity now involves latent effects that can result in delayed adverse effects in adults or at old age and additional effects that can be transgenerationally transferred to future generations. Although epidemiology and toxicology to an increasing degree are exploring the adverse effects from developmental exposures in human beings, the improved documentation has resulted in little progress in protection, and few environmental chemicals are currently regulated to protect against developmental toxicity, whether it be neurotoxicity, endocrine disruption or other adverse outcome. The desire to obtain a high degree of certainty and verification of the evidence used for decision-making must be weighed against the costs and necessary duration of research, as well as the long-term costs to human health because of delayed protection of vulnerable early-life stages of human development and, possibly, future generations. Although two-generation toxicology tests may be useful for initial test purposes, other rapidly emerging tools need to be seriously considered from computational chemistry and metabolomics to CLARITY-BPA-type designs, big data and population record linkage approaches that will allow efficient generation of new insight; epigenetic mechanisms may necessitate a set of additional regulatory tests to reveal such effects. As reflected by the Prenatal Programming and Toxicity (PPTOX) VI conference, the current scientific understanding and the timescales involved require an intensified approach to protect against preventable adverse health effects that can harm the next generation and generations to come. While further research is needed, the main emphasis should be on research translation and timely public health intervention to avoid serious, irreversible and perhaps transgenerational harm.

Styryl-cinnamate hybrid inhibits glioma by alleviating translation, bioenergetics and other key cellular responses leading to apoptosis.

Gliomas are lethal and aggressive form of brain tumors with resistance to conventional radiation and cytotoxic chemotherapies; inviting continuous efforts for drug discovery and drug delivery. Interestingly, small molecule hybrids are one such pharmacophore that continues to capture interest owing to their pluripotent medicinal effects. Accordingly, we earlier reported synthesis of potent Styryl-cinnamate hybrids (analogues of Salvianolic acid F) along with its plausible mode of action (MOA). We explored iTRAQ-LC/MS-MS technique to deduce differentially expressed landscape of native & phospho-proteins in treated glioma cells. Based on this, Protein-Protein Interactome (PPI) was looked into by employing computational tools and further validated in vitro. We hereby report that the Styryl-cinnamate hybrid, an analogue of natural Salvianolic acid F, alters key regulatory proteins involved in translation, cytoskeleton development, bioenergetics, DNA repair, angiogenesis and ubiquitination. Cell cycle analysis dictates arrest at G0/G1 stage along with reduced levels of cyclin D; involved in G1 progression. We discovered that Styryl-cinnamate hybrid targets glioma by intrinsically triggering metabolite-mediated stress. Various oncological circuits alleviated by the potential drug candidate strongly supports the role of such pharmacophores as anticancer drugs. Although, further analysis of SC hybrid in treating xenografts or solid tumors is yet to be explored but their candidature has gained huge impetus through this study. This study equips us better in understanding the shift in proteomic landscape after treating glioma cells with SC hybrid. It also allows us to elicit molecular targets of this potential drug before progressing to preclinical studies.