scholarly journals Flavonoid Glycosides with a Triazole Moiety for Marine Antifouling Applications: Synthesis and Biological Activity Evaluation

Marine Drugs ◽  
2020 ◽  
Vol 19 (1) ◽  
pp. 5
Author(s):  
Daniela Pereira ◽  
Catarina Gonçalves ◽  
Beatriz T. Martins ◽  
Andreia Palmeira ◽  
Vitor Vasconcelos ◽  
...  
Keyword(s):  
Qsar Model ◽  
Quantitative Structure Activity Relationship ◽  
Artemia Salina ◽  
Flavonoid Glycosides ◽  
Antifouling Activity ◽  
Antifouling Coatings ◽  
Marine Industry ◽  
Low Toxicity ◽  
Polymethoxylated Flavones ◽  
First Time

Over the last decades, antifouling coatings containing biocidal compounds as active ingredients were used to prevent biofouling, and eco-friendly alternatives are needed. Previous research from our group showed that polymethoxylated chalcones and glycosylated flavones obtained by synthesis displayed antifouling activity with low toxicity. In this work, ten new polymethoxylated flavones and chalcones were synthesized for the first time, including eight with a triazole moiety. Eight known flavones and chalcones were also synthesized and tested in order to construct a quantitative structure-activity relationship (QSAR) model for these compounds. Three different antifouling profiles were found: three compounds (1b, 11a and 11b) exhibited anti-settlement activity against a macrofouling species (Mytilus galloprovincialis), two compounds (6a and 6b) exhibited inhibitory activity against the biofilm-forming marine bacteria Roseobacter litoralis and one compound (7b) exhibited activity against both mussel larvae and microalgae Navicula sp. Hydrogen bonding acceptor ability of the molecule was the most significant descriptor contributing positively to the mussel larvae anti-settlement activity and, in fact, the triazolyl glycosylated chalcone 7b was the most potent compound against this species. The most promising compounds were not toxic to Artemia salina, highlighting the importance of pursuing the development of new synthetic antifouling agents as an ecofriendly and sustainable alternative for the marine industry.

scholarly journals From Natural Xanthones to Synthetic C-1 Aminated 3,4-Dioxygenated Xanthones as Optimized Antifouling Agents

Marine Drugs ◽  
2021 ◽  
Vol 19 (11) ◽  
pp. 638
Author(s):  
Diana I. S. P. Resende ◽  
Joana R. Almeida ◽  
Sandra Pereira ◽  
Alexandre Campos ◽  
Agostinho Lemos ◽  
...  
Keyword(s):  
Larval Settlement ◽  
Marine Species ◽  
Artemia Salina ◽  
Bacterial Strains ◽  
Antifouling Activity ◽  
Cellular Processes ◽  
Marine Biofouling ◽  
The Us ◽  
Low Toxicity ◽  
First Time

Biofouling, which occurs when certain marine species attach and accumulate in artificial submerged structures, represents a serious economic and environmental issue worldwide. The discovery of new non-toxic and eco-friendly antifouling systems to control or prevent biofouling is, therefore, a practical and urgent need. In this work, the antifouling activity of a series of 24 xanthones, with chemical similarities to natural products, was exploited. Nine (1, 2, 4, 6, 8, 16, 19, 21, and 23) of the tested xanthones presented highly significant anti-settlement responses at 50 μM against the settlement of mussel Mytilus galloprovincialis larvae and low toxicity to this macrofouling species. Xanthones 21 and 23 emerged as the most effective larval settlement inhibitors (EC50 = 7.28 and 3.57 µM, respectively). Additionally, xanthone 23 exhibited a therapeutic ratio (LC50/EC50) > 15, as required by the US Navy program attesting its suitability as natural antifouling agents. From the nine tested xanthones, none of the compounds were found to significantly inhibit the growth of the marine biofilm-forming bacterial strains tested. Xanthones 4, 6, 8, 16, 19, 21, and 23 were found to be non-toxic to the marine non-target species Artemia salina (<10% mortality at 50 μM). Insights on the antifouling mode of action of the hit xanthones 21 and 23 suggest that these two compounds affected similar molecular targets and cellular processes in mussel larvae, including that related to mussel adhesion capacity. This work exposes for the first time the relevance of C-1 aminated xanthones with a 3,4-dioxygenated pattern of substitution as new non-toxic products to prevent marine biofouling.

scholarly journals Structure-Antifouling Activity Relationship and Molecular Targets of Bio-Inspired(thio)xanthones

Biomolecules ◽  
2020 ◽  
Vol 10 (8) ◽  
pp. 1126 ◽  
Author(s):  
Joana R. Almeida ◽  
Andreia Palmeira ◽  
Alexandre Campos ◽  
Isabel Cunha ◽  
Micaela Freitas ◽  
...  
Keyword(s):  
Acetylcholinesterase Activity ◽  
Qsar Model ◽  
Artemia Salina ◽  
Activity Relationship ◽  
Predictive Capacity ◽  
Antifouling Activity ◽  
In Silico Studies ◽  
Mussel Adhesive

The development of alternative ecological and effective antifouling technologies is still challenging. Synthesis of nature-inspired compounds has been exploited, given the potential to assure commercial supplies of potential ecofriendly antifouling agents. In this direction, the antifouling activity of a series of nineteen synthetic small molecules, with chemical similarities with natural products, were exploited in this work. Six (4, 5, 7, 10, 15 and 17) of the tested xanthones showed in vivo activity toward the settlement of Mytilus galloprovincialis larvae (EC50: 3.53–28.60 µM) and low toxicity to this macrofouling species (LC50 > 500 µM and LC50/EC50: 17.42–141.64), and two of them (7 and 10) showed no general marine ecotoxicity (<10% of Artemia salina mortality) after 48 h of exposure. Regarding the mechanism of action in mussel larvae, the best performance compounds 4 and 5 might be acting by the inhibition of acetylcholinesterase activity (in vitro and in silico studies), while 7 and 10 showed specific targets (proteomic studies) directly related with the mussel adhesive structure (byssal threads), given by the alterations in the expression of Mytilus collagen proteins (PreCols) and proximal thread proteins (TMPs). A quantitative structure-activity relationship (QSAR) model was built with predictive capacity to enable speeding the design of new potential active compounds.

scholarly journals Quantitative Structure–Activity Relationships for the Flavonoid-Mediated Inhibition of P-Glycoprotein in KB/MDR1 Cells

Molecules ◽  
2019 ◽  
Vol 24 (9) ◽  
pp. 1661 ◽  
Author(s):  
Mengmeng Xia ◽  
Yajing Fang ◽  
Weiwei Cao ◽  
Fuqiang Liang ◽  
Siyi Pan ◽  
...  
Keyword(s):  
Inhibitory Activity ◽  
Qsar Model ◽  
Quantitative Structure Activity Relationship ◽  
Quantitative Structure ◽  
Glycoprotein P ◽  
Chemotherapy Drugs ◽  
Structure Activity ◽  
P Glycoprotein ◽  
Daily Diet ◽  
Low Toxicity

P-glycoprotein (P-gp) serves as a therapeutic target for the development of inhibitors to overcome multidrug resistance (MDR) in cancer cells. In order to enhance the uptake of chemotherapy drugs, larger amounts of P-gp inhibitors are required. Besides several chemically synthesized P-gp inhibitors, flavonoids as P-gp inhibitors are being investigated, with their advantages including abundance in our daily diet and a low toxicity. The cytotoxicity of daunorubicin (as a substrate of P-gp) to KB/MDR1 cells and the parental KB cells was measured in the presence or absence of flavonoids. A two-dimensional quantitative structure–activity relationship (2D-QSAR) model was built with a high cross-validation coefficient (Q2) value of 0.829. Descriptors including vsurf_DW23, E_sol, Dipole and vsurf_G were determined to be related to the inhibitory activity of flavonoids. The lack of 2,3-double bond, 3′-OH, 4′-OH and the increased number of methoxylated substitutions were shown to be beneficial for the inhibition of P-gp. These results are important for the screening of flavonoids for inhibitory activity on P-gp.

Interpretable SMILES-based QSAR model of inhibitory activity of sirtuins 1 and 2

2020 ◽  
Vol 23 ◽  
Author(s):  
Apilak Worachartcheewan ◽  
Alla P. Toropova ◽  
Andrey A. Toropov ◽  
Reny Pratiwi ◽  
Virapong Prachayasittikul ◽  
...  
Keyword(s):  
Histone Deacetylases ◽  
Rational Design ◽  
Qsar Model ◽  
Quantitative Structure Activity Relationship ◽  
Sirtuin 1 ◽  
Data Set ◽  
Functional Roles ◽  
Molecular Features ◽  
Oecd Principles ◽  
Qsar Models

Background: Sirtuin 1 (Sirt1) and sirtuin 2 (Sirt2) are NAD+ -dependent histone deacetylases which play important functional roles in removal of the acetyl group of acetyl-lysine substrates. Considering the dysregulation of Sirt1 and Sirt2 as etiological causes of diseases, Sirt1 and Sirt2 are lucrative target proteins for treatment, thus there has been great interest in the development of Sirt1 and Sirt2 inhibitors. Objective: This study compiled the bioactivity data of Sirt1 and Sirt2 for the construction of quantitative structure-activity relationship (QSAR) models in accordance with the OECD principles. Method: Simplified molecular input line entry system (SMILES)-based molecular descriptors were used to characterize the molecular features of inhibitors while the Monte Carlo method of the CORAL software was employed for multivariate analysis. The data set was subjected to 3 random splits in which each split separated the data into 4 subsets consisting of training, invisible training, calibration and external sets. Results: Statistical indices for the evaluation of QSAR models suggested good statistical quality for models of Sirt1 and Sirt2 inhibitors. Furthermore, mechanistic interpretation of molecular substructures that are responsible for modulating the bioactivity (i.e. promoters of increase or decrease of bioactivity) was extracted via the analysis of correlation weights. It exhibited molecular features involved Sirt1 and Sirt2 inhibitors. Conclusion: It is anticipated that QSAR models presented herein can be useful as guidelines in the rational design of potential Sirt1 and Sirt2 inhibitors for the treatment of Sirtuin-related diseases.

scholarly journals Identification of Anti-SARS-CoV-2 Compounds from Food Using QSAR-Based Virtual Screening, Molecular Docking, and Molecular Dynamics Simulation Analysis

2021 ◽  
Vol 14 (4) ◽  
pp. 357
Author(s):  
Magdi E. A. Zaki ◽  
Sami A. Al-Hussain ◽  
Vijay H. Masand ◽  
Siddhartha Akasapu ◽  
Sumit O. Bajaj ◽  
...  
Keyword(s):  
Molecular Dynamics ◽  
Molecular Docking ◽  
Virtual Screening ◽  
Simulation Analysis ◽  
Qsar Model ◽  
Quantitative Structure Activity Relationship ◽  
Dynamics Simulation ◽  
Multilinear Regression ◽  
Qsar Analysis ◽  
Main Protease

Due to the genetic similarity between SARS-CoV-2 and SARS-CoV, the present work endeavored to derive a balanced Quantitative Structure−Activity Relationship (QSAR) model, molecular docking, and molecular dynamics (MD) simulation studies to identify novel molecules having inhibitory potential against the main protease (Mpro) of SARS-CoV-2. The QSAR analysis developed on multivariate GA–MLR (Genetic Algorithm–Multilinear Regression) model with acceptable statistical performance (R2 = 0.898, Q2loo = 0.859, etc.). QSAR analysis attributed the good correlation with different types of atoms like non-ring Carbons and Nitrogens, amide Nitrogen, sp2-hybridized Carbons, etc. Thus, the QSAR model has a good balance of qualitative and quantitative requirements (balanced QSAR model) and satisfies the Organisation for Economic Co-operation and Development (OECD) guidelines. After that, a QSAR-based virtual screening of 26,467 food compounds and 360 heterocyclic variants of molecule 1 (benzotriazole–indole hybrid molecule) helped to identify promising hits. Furthermore, the molecular docking and molecular dynamics (MD) simulations of Mpro with molecule 1 recognized the structural motifs with significant stability. Molecular docking and QSAR provided consensus and complementary results. The validated analyses are capable of optimizing a drug/lead candidate for better inhibitory activity against the main protease of SARS-CoV-2.

Antimicrobial Screening, in Silico Studies and QSAR of Chalcone-based 1,4-disubstituted 1,2,3-triazole Hybrids

Drug Research ◽  
2020 ◽  
Author(s):  
Pinki Yadav ◽  
Kashmiri Lal ◽  
Ashwani Kumar
Keyword(s):  
Topoisomerase Ii ◽  
Antimicrobial Properties ◽  
Qsar Model ◽  
Quantitative Structure Activity Relationship ◽  
Binding Modes ◽  
E Coli ◽  
Structure Activity ◽  
In Silico Studies ◽  
Microbial Strains

AbstractThe in vitro antimicrobial properties of some chalcones (1a–1c ) and chalcone tethred 1,4-disubstituted 1,2,3-triazoles (2a–2u) towards different microbial strains viz. Staphylococcus aureus, Bacillus subtilis, Escherichia coli, Pseudomonas aeruginosa, Aspergillus niger and Candida albicans are reported. Compounds 2g and 2u exhibited better potency than the standard Fluconazole with MIC values of 0.0063 µmol/mL and 0.0068 µmol/mL, respectively. Furthermore, molecular docking was performed to investigate the binding modes of two potent compounds 2q and 2g with E. coli topoisomerase II DNA gyrase B and C. albicans lanosterol 14α-demethylase, respectively. Based on these results, a statistically significant quantitative structure activity relationship (QSAR) model was successfully summarized for antibacterial activity against B. subtilis.

scholarly journals Development of a Hierarchical Support Vector Regression-Based In Silico Model for Caco-2 Permeability

Pharmaceutics ◽  
2021 ◽  
Vol 13 (2) ◽  
pp. 174 ◽  
Author(s):  
Giang Huong Ta ◽  
Cin-Syong Jhang ◽  
Ching-Feng Weng ◽  
Max K. Leong
Keyword(s):  
Drug Discovery ◽  
Support Vector Regression ◽  
Human Colon ◽  
Qsar Model ◽  
Quantitative Structure Activity Relationship ◽  
Support Vector ◽  
Human Colon Carcinoma Cell ◽  
Drug Discovery And Development ◽  
Training Samples ◽  
Experimental Values

Drug absorption is one of the critical factors that should be taken into account in the process of drug discovery and development. The human colon carcinoma cell layer (Caco-2) model has been frequently used as a surrogate to preliminarily investigate the intestinal absorption. In this study, a quantitative structure–activity relationship (QSAR) model was generated using the innovative machine learning-based hierarchical support vector regression (HSVR) scheme to depict the exceedingly confounding passive diffusion and transporter-mediated active transport. The HSVR model displayed good agreement with the experimental values of the training samples, test samples, and outlier samples. The predictivity of HSVR was further validated by a mock test and verified by various stringent statistical criteria. Consequently, this HSVR model can be employed to forecast the Caco-2 permeability to assist drug discovery and development.

Flavon- and Flavonolglycosides from Achillea pannonica Scheele

2001 ◽  
Vol 56 (7-8) ◽  
pp. 521-525 ◽  
Author(s):  
Denata Kasaj ◽  
Liselotte Krenn ◽  
Sonja Prinz ◽  
Antje Hüfner ◽  
Shi Shan Yuc ◽  
...  
Keyword(s):  
Methanolic Extract ◽  
2D Nmr ◽  
Flavonoid Glycosides ◽  
Spectroscopic Methods ◽  
Esi Ms ◽  
Aerial Parts ◽  
Nmr Techniques ◽  
Chemotaxonomic Study ◽  
First Time ◽  
C Nmr

The detailed investigation of a methanolic extract of aerial parts of Achillea pannonica SCHEELE. within a chemotaxonomic study led to the isolation of 6 flavonoid glycosides. Besides rutin, apigenin-7-O-glucopyranoside, luteolin-7-O-glucopyranoside, apigenin-7-O-rutinoside and acacetin-7-O-rutinoside, an unusual flavondiglucoside was isolated. Its structure was established by UV, 1HNMR and 13C NMR spectroscopic methods including 2D-NMR techniques and ESI-MS as luteolin-7,4′-O-β-diglucoside. This substance is reported for the first time in the genus Achillea. Chemotaxonomic aspects are discussed briefly

scholarly journals Development of a new quantitative structure–activity relationship model for predicting Ames mutagenicity of food flavor chemicals using StarDrop™ auto-Modeller™

2021 ◽  
Vol 43 (1) ◽  
Author(s):  
Toshio Kasamatsu ◽  
Airi Kitazawa ◽  
Sumie Tajima ◽  
Masahiro Kaneko ◽  
Kei-ichi Sugiyama ◽  
...  
Keyword(s):  
Molecular Weight ◽  
Ames Test ◽  
Qsar Model ◽  
Quantitative Structure Activity Relationship ◽  
Structure Activity Relationship ◽  
Activity Relationship ◽  
Low Molecular Weight ◽  
Quantitative Structure ◽  
Industrial Chemicals ◽  
Structure Activity

Abstract Background Food flavors are relatively low molecular weight chemicals with unique odor-related functional groups that may also be associated with mutagenicity. These chemicals are often difficult to test for mutagenicity by the Ames test because of their low production and peculiar odor. Therefore, application of the quantitative structure–activity relationship (QSAR) approach is being considered. We used the StarDrop™ Auto-Modeller™ to develop a new QSAR model. Results In the first step, we developed a new robust Ames database of 406 food flavor chemicals consisting of existing Ames flavor chemical data and newly acquired Ames test data. Ames results for some existing flavor chemicals have been revised by expert reviews. We also collected 428 Ames test datasets for industrial chemicals from other databases that are structurally similar to flavor chemicals. A total of 834 chemicals’ Ames test datasets were used to develop the new QSAR models. We repeated the development and verification of prototypes by selecting appropriate modeling methods and descriptors and developed a local QSAR model. A new QSAR model “StarDrop NIHS 834_67” showed excellent performance (sensitivity: 79.5%, specificity: 96.4%, accuracy: 94.6%) for predicting Ames mutagenicity of 406 food flavors and was better than other commercial QSAR tools. Conclusions A local QSAR model, StarDrop NIHS 834_67, was customized to predict the Ames mutagenicity of food flavor chemicals and other low molecular weight chemicals. The model can be used to assess the mutagenicity of food flavors without actual testing.

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