scholarly journals Novel Algicides against Bloom-Forming Cyanobacteria from Allelochemicals: Design, Synthesis, Bioassay, and 3D-QSAR Study

Biology ◽  
2021 ◽  
Vol 10 (11) ◽  
pp. 1145
Author(s):  
Yin Luo ◽  
Yushun Yang ◽  
Wenguang Hou ◽  
Jie Fu
Keyword(s):  
Cinnamic Acid ◽  
High Efficiency ◽  
Three Dimensional ◽  
3D Qsar ◽  
Quantitative Structure Activity Relationship ◽  
Mechanism Study ◽  
Qsar Study ◽  
Design Synthesis ◽  
Qsar Analysis ◽  
Amide Derivatives

Cyanobacteria bloom caused by water eutrophication has threatened human health and become a global environmental problem. To develop green algicides with strong specificity and high efficiency, three series of ester and amide derivatives from parent allelochemicals of caffeic acid (CA), cinnamic acid (CIA), and 3-hydroxyl-2-naphthoic acid (HNA) were designed and synthesized. Their inhibitory effects on the growth of five harmful cyanobacterial species, Microcystis aeruginosa (M. aeruginosa), Microcystis wesenbergii (M. wesenbergii), Microcystis flos-aquae (M. flos-aquae), Aphanizomenon flos-aquae (Ap. flos-aquae), and Anabaena flos-aquae (An. flos-aquae), were evaluated. The results revealed that CIA esters synthesized by cinnamic acid and fatty alcohols showed the best inhibition effect, with EC50 values ranging from 0.63 to >100 µM. Moreover, some CIA esters exhibited a good selectivity in inhibiting cyanobacteria. For example, the inhibitory activity of naphthalen-2-yl cinnamate was much stronger on Ap. flos-aquae (EC50 = 0.63 µM) than other species (EC50 > 10 µM). Three-dimensional quantitative structure–activity relationship (3D-QSAR) analysis was performed and the results showed that the steric hindrance of the compounds influenced the algicidal activity. Further mechanism study found that the inhibition of CIA esters on the growth of M. aeruginosa might be related to the accumulation of malondialdehyde (MDA).

Design of Dual COX-2 and 5-LOX Inhibitors with Iron-Chelating Properties Using Structure-Based and Ligand-Based Methods

2021 ◽  
Vol 18 ◽  
Author(s):  
Jelena Bošković ◽  
Dušan Ružić ◽  
Olivera Čudina ◽  
Katarina Nikolic ◽  
Vladimir Dobričić
Keyword(s):  
Molecular Docking ◽  
External Validation ◽  
Three Dimensional ◽  
3D Qsar ◽  
Quantitative Structure Activity Relationship ◽  
Docking Studies ◽  
Qsar Analysis ◽  
In Silico Admet ◽  
Cox 2 ◽  
Lox Inhibitors

Background: Inflammation is common pathogenesis of many diseases progression, such as malignancy, cardiovascular and rheumatic diseases. The inhibition of the synthesis of inflammatory mediators by modulation of cyclooxygenase (COX) and lipoxygenase (LOX) pathways provides a challenging strategy for the development of more effective drugs. Objective: The aim of this study was to design dual COX-2 and 5-LOX inhibitors with iron-chelating properties using a combination of ligand-based (three-dimensional quantitative structure-activity relationship (3D-QSAR)) and structure-based (molecular docking) methods. Methods: The 3D-QSAR analysis was applied on a literature dataset consisting of 28 dual COX-2 and 5-LOX inhibitors in Pentacle software. The quality of developed COX-2 and 5-LOX 3D-QSAR models were evaluated by internal and external validation methods. The molecular docking analysis was performed in GOLD software, while selected ADMET properties were predicted in ADMET predictor software. Results: According to the molecular docking studies, the class of sulfohydroxamic acid analogues, previously designed by 3D-QSAR, was clustered as potential dual COX-2 and 5-LOX inhibitors with iron-chelating properties. Based on the 3D-QSAR and molecular docking, 1j, 1g, and 1l were selected as the most promising dual COX-2 and 5-LOX inhibitors. According to the in silico ADMET predictions, all compounds had an ADMET_Risk score less than 7 and a CYP_Risk score lower than 2.5. Designed compounds were not estimated as hERG inhibitors, and 1j had improved intrinsic solubility (8.704) in comparison to the dataset compounds (0.411-7.946). Conclusion: By combining 3D-QSAR and molecular docking, three compounds (1j, 1g, and 1l) are selected as the most promising designed dual COX-2 and 5-LOX inhibitors, for which good activity, as well as favourable ADMET properties and toxicity, are expected.

scholarly journals Structural investigations of CXCR2 receptor antagonists by CoMFA, CoMSIA and flexible docking studies

2012 ◽  
Vol 62 (3) ◽  
pp. 287-304 ◽  
Author(s):  
Shravan Kumar Gunda ◽  
Rohith Kumar Anugolu ◽  
Sri Ramya Tata ◽  
Saikh Mahmood
Keyword(s):  
Standard Error ◽  
Three Dimensional ◽  
3D Qsar ◽  
Homology Model ◽  
Qsar Model ◽  
Quantitative Structure Activity Relationship ◽  
Field Analysis ◽  
Structural Investigations ◽  
Qsar Analysis ◽  
Qsar Studies

= Three-dimensional quantitative structure activity relationship (3D QSAR) analysis was carried out on a et of 56 N,N’-diarylsquaramides, N,N’-diarylureas and diaminocyclobutenediones in order to understand their antagonistic activities against CXCR2. The studies included comparative molecular field analysis (CoMFA) and comparative molecular similarity indices analysis (CoMSIA). Models with good predictive abilities were generated with CoMFA q2 0.709, r2 (non-cross-validated square of correlation coefficient) = 0.951, F value = 139.903, r2 bs = 0.978 with five components, standard error of estimate = 0.144 and the CoMSIA q2 = 0.592, r2 = 0.955, F value = 122.399, r2 bs = 0.973 with six components, standard error of estimate = 0.141. In addition, a homology model of CXCR2 was used for docking based alignment of the compounds. The most active compound then served as a template for alignment of the remaining structures. Further, mapping of contours onto the active site validated each other in terms of residues involved with reference to the respective contours. This integrated molecular docking based alignment followed by 3D QSAR studies provided a further insight to support the structure-based design of CXCR2 antagonistic agents with improved activity profiles. Furthermore, in silico screening was adapted to the QSAR model in order to predict the structures of new, potentially active compounds.

MOLECULAR MODELING OF 5‐[(AMIDOBENZYL)OXY]‐ NICOTINAMIDES AS SIRTUIN 2 INHIBITORS USING ALIGNMENT- (IN)DEPENDENT 3D-QSAR ANALYSIS AND MOLECULAR DOCKING

2021 ◽  
Author(s):  
Nemanja Djokovic ◽  
◽  
Ana Postolovic ◽  
Katarina Nikolic
Keyword(s):  
Molecular Docking ◽  
Structural Similarity ◽  
3D Qsar ◽  
Quantitative Structure Activity Relationship ◽  
Study Data ◽  
Rational Drug Design ◽  
Qsar Study ◽  
Data Set ◽  
Qsar Analysis ◽  
Ligand Interactions

The group of 5‐[(amidobenzyl)oxy]‐nicotinamides represents promising group of sirtuin 2 (SIRT2) inhibitors. Despite structural similarity, representatives of this group of inhibitors displayed versatile mechanisms of inhibition which hamper rational drug design. The aim of this research was to form a 3D-QSAR (3D-Quantitative Structure-Activity Relationship) model, define the pharmacophore of this subgroup of SIRT2 inhibitors, define the mode of protein-ligand interactions and design new compounds with improved predicted activity and pharmacokinetics. For the 3D-QSAR study, data set was generated using structures and activities of 166 5‐[(amidobenzyl)oxy]‐nicotinamides. 3D-conformations of compounds were optimized, alignment-independent GRIND2 descriptors were calculated and 3D-QSAR PLS models were generated using 70% of data set. To investigate bioactive conformations of inhibitors, molecular docking was used. Molecular docking analysis identified two clusters of predicted bioactive conformations which is in alignment with experimental observations. The defined pharmacophoric features were used to design novel inhibitors with improved predicted potency and ADMET profiles.

scholarly journals 3D-QSAR and Docking Studies of a Series ofβ-Carboline Derivatives as Antitumor Agents of PLK1

2014 ◽  
Vol 2014 ◽  
pp. 1-10 ◽  
Author(s):  
Jahan B. Ghasemi ◽  
Valentin Davoudian
Keyword(s):  
Antitumor Agents ◽  
Three Dimensional ◽  
Human Tumor ◽  
3D Qsar ◽  
Qsar Model ◽  
Quantitative Structure Activity Relationship ◽  
Docking Studies ◽  
Human Tumor Cell Lines ◽  
Qsar Analysis ◽  
Leave One Out

An alignment-free, three dimensional quantitative structure-activity relationship (3D-QSAR) analysis has been performed on a series ofβ-carboline derivatives as potent antitumor agents toward HepG2 human tumor cell lines. A highly descriptive and predictive 3D-QSAR model was obtained through the calculation of alignment-independent descriptors (GRIND descriptors) using ALMOND software. For a training set of 30 compounds, PLS analyses result in a three-component model which displays a squared correlation coefficient (r2) of 0.957 and a standard deviation of the error of calculation (SDEC) of 0.116. Validation of this model was performed using leave-one-out,q2looof 0.85, and leave-multiple-out. This model gives a remarkably highr2pred(0.66) for a test set of 10 compounds. Docking studies were performed to investigate the mode of interaction betweenβ-carboline derivatives and the active site of the most probable anticancer receptor, polo-like kinase protein.

CoMFA, CoMSIA and HQSAR Analysis of 3-aryl-3-ethoxypropanoic Acid Derivatives as GPR40 Modulators

2020 ◽  
Vol 17 (1) ◽  
pp. 100-118
Author(s):  
Krishna A. Gajjar ◽  
Anuradha K. Gajjar
Keyword(s):  
Biological Activity ◽  
Structural Information ◽  
Three Dimensional ◽  
3D Qsar ◽  
Qsar Model ◽  
Quantitative Structure Activity Relationship ◽  
Docking Studies ◽  
Statistical Parameters ◽  
Qsar Study ◽  
Negative Contribution

Background: Human GPR40 receptor, also known as free fatty-acid receptor 1, is a Gprotein- coupled receptor that binds long chain free fatty acids to enhance glucose-dependent insulin secretion. In order to improve the resistance and efficacy, computational tools were applied to a series of 3-aryl-3-ethoxypropanoic acid derivatives. A relationship between the structure and biological activity of these compounds, was derived using a three-dimensional quantitative structure-activity relationship (3D-QSAR) study using CoMFA, CoMSIA and two-dimensional QSAR study using HQSAR methods. Methods: Building the 3D-QSAR models, CoMFA, CoMSIA and HQSAR were performed using Sybyl-X software. The ratio of training to test set was kept 70:30. For the generation of 3D-QSAR model three different alignments were used namely, distill, pharmacophore and docking based alignments. Molecular docking studies were carried out on designed molecules using the same software. Results: Among all the three methods used, Distill alignment was found to be reliable and predictive with good statistical results. The results obtained from CoMFA analysis q2, r2cv and r2 pred were 0.693, 0.69 and 0.992 respectively and in CoMSIA analysis q2, r2cv and r2pred were 0.668, 0.648 and 0.990. Contour maps of CoMFA (lipophilic and electrostatic), CoMSIA (lipophilic, electrostatic, hydrophobic, and donor) and HQSAR (positive & negative contribution) provided significant insights i.e. favoured and disfavoured regions or positive & negative contributing fragments with R1 and R2 substitutions, which gave hints for the modifications required to design new molecules with improved biological activity. Conclusion: 3D-QSAR techniques were applied for the first time on the series 3-aryl-3- ethoxypropanoic acids. All the models (CoMFA, CoMSIA and HQSAR) were found to be satisfactory according to the statistical parameters. Therefore such a methodology, whereby maximum structural information (from ligand and biological target) is explored, gives maximum insights into the plausible protein-ligand interactions and is more likely to provide potential lead candidates has been exemplified from this study.

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