Pelargonic acid's interaction with the auxin transporter PIN1: A potential mechanism behind its phytotoxic effects on plant metabolism.

Pelargonic acid (PA) is a saturated fatty acid commonly found in several organisms, that is known for its phytotoxic effect and its use as bioherbicide for sustainable weed management. Although PA is already commercialised as bioherbicide, its molecular targets and mode of action is unknown according to the Herbicide Resistance Action Committee. Therefore, the aim of this work was focusing on the way this natural active substance impacts the plant metabolism of the model species Arabidopsis thaliana.

Azelaic acid can efficiently compete for the auxin binding site TIR1, altering auxin polar transport, gravitropic response, and root growth and architecture in Arabidopsisthaliana roots.

The present study investigates the phytotoxic potential of azelaic acid (AZA) on Arabidopsis thaliana roots. Effects on root morphology, anatomy, auxin content and transport, gravitropic response and molecular docking were analysed. AZA inhibited root growth, stimulated lateral and adventitious roots, and altered the root apical meristem by reducing meristem cell number, length and width.

-cinnamaldehyde-related overproduction of benzoic acid and oxidative stress on .

Introduction: -cinnamaldehyde is a specialised metabolite that naturally occurs in plants of the Lauraceae family. This study focused on the phytotoxic effects of this compound on the morphology and metabolism of seedlings.

Material And Methods: To evaluate the phytotoxicity of -cinnamaldehyde, a dose-response curve was first performed for the root growth process in order to calculate the reference inhibitory concentrations IC50 and IC80 (-cinnamaldehyde concentrations inducing a 50% and 80% inhibition, respectively).

Similarities on the mode of action of the terpenoids citral and farnesene in Arabidopsis seedlings involve interactions with DNA binding proteins.

The sesquiterpene farnesene and the monoterpene citral are phytotoxic natural compounds characterized by a high similarity in macroscopic effects, suggesting an equal or similar mechanism of action when assayed at IC concentration. In the present study, a short-time experiment (24 and 48 h) using an imaging spectrofluorometer allowed us to monitor the in-vivo effects of the two molecules, highlighting that both terpenoids were similarly affecting all PSII parameters, even when the effects of citral were quicker in appearing than those of farnesene. The multivariate, univariate, and pathway analyses, carried out on untargeted-metabolomic data, confirmed a clear separation of the plant metabolome in response to the two treatments, whereas similarity in the affected pathways was observed.

Emerging Computational Approaches for Antimicrobial Peptide Discovery.

In the last two decades many reports have addressed the application of artificial intelligence (AI) in the search and design of antimicrobial peptides (AMPs). AI has been represented by machine learning (ML) algorithms that use sequence-based features for the discovery of new peptidic scaffolds with promising biological activity. From AI perspective, evolutionary algorithms have been also applied to the rational generation of peptide libraries aimed at the optimization/design of AMPs.

Transcriptome and binding data indicate that citral inhibits single strand DNA-binding proteins.

The mechanism of phytotoxicity of citral was probed in Arabidopsis thaliana using RNA-Seq and in silico binding analyses. Inhibition of growth by 50% by citral downregulated transcription of 9156 and 5541 genes in roots and shoots, respectively, after 1 h. Only 56 and 62 genes in roots and shoots, respectively, were upregulated.

Auxin-like effects of the natural coumarin scopoletin on Arabidopsis cell structure and morphology.

The mode of action and phytotoxic potential of scopoletin, a natural compound belonging to the group of coumarins, has been evaluated in detail. Analysis conducted by light and electron transmission microscopy showed strong cell and tissue abnormalities on treated roots, such as cell wall malformations, multi-nucleated cells, abnormal nuclei and tissue disorganization. Scopoletin compromised root development by inducing wrong microtubule assembling, mitochondrial membrane depolarization and ultimate cell death, in a way similar to auxin herbicides.

Ligand-Based Virtual Screening Using Tailored Ensembles: A Prioritization Tool for Dual A2AAdenosine Receptor Antagonists / Monoamine Oxidase B Inhibitors.

Background: Virtual Screening methodologies have emerged as efficient alternatives for the discovery of new drug candidates. At the same time, ensemble methods are nowadays frequently used to overcome the limitations of employing a single model in ligand-based drug design. However, many applications of ensemble methods to this area do not consider important aspects related to both virtual screening and the modeling process.

Topological sub-structural molecular design (TOPS-MODE): a useful tool to explore key fragments of human A3 adenosine receptor ligands.

Adenosine regulates tissue function by activating four G-protein-coupled adenosine receptors (ARs). Selective agonists and antagonists for A3 ARs have been investigated for the treatment of a variety of immune disorders, cancer, brain, and heart ischemic conditions. We herein present a QSAR study based on a Topological sub-structural molecular design (TOPS-MODE) approach, intended to predict the A3 ARs of a diverse dataset of 124 (94 training set/ 30 prediction set) adenosine derivatives.

Integrated Ugi-based assembly of functionally, skeletally, and stereochemically diverse 1,4-benzodiazepin-2-ones.

A practical, integrated and versatile U-4CR-based assembly of 1,4-benzodiazepin-2-ones exhibiting functionally, skeletally, and stereochemically diverse substitution patterns is described. By virtue of its convergence, atom economy, and bond-forming efficiency, the methodology documented herein exemplifies the reconciliation of structural complexity and experimental simplicity in the context of medicinal chemistry projects.

Classifier ensemble based on feature selection and diversity measures for predicting the affinity of A(2B) adenosine receptor antagonists.

A(2B) adenosine receptor antagonists may be beneficial in treating diseases like asthma, diabetes, diabetic retinopathy, and certain cancers. This has stimulated research for the development of potent ligands for this subtype, based on quantitative structure-affinity relationships. In this work, a new ensemble machine learning algorithm is proposed for classification and prediction of the ligand-binding affinity of A(2B) adenosine receptor antagonists.

Synthesis and cytostatic activity of purine nucleosides derivatives of allofuranose.

Several new purine nucleosides derivatives of allofuranose were prepared according to Vorbrüggen method, starting from 1,2,5,6-di-O-isopropylidene-α-D-allofuranose and using 1,2,3,5,6-pentaacetoxy-β-D-allofuranose as key intermediate. The synthesized allofuranosyl nucleosides, as well as some acetyl derivatives, were evaluated for their cytotoxicity in vitro in three human cancer cell lines (MCF-7, Hela-229 and HL-60). Among the studied compounds the 9-(2,3,5,6-tetra-O-acetyl-β-D-allofuranosyl)-2,6-dichloropurine (9) was the most potent one on the three cell lines evaluated, being its activity against HL-60 cells similar to cisplatin.

Multidimensional drug design: simultaneous analysis of binding and relative efficacy profiles of N(6)-substituted-4'-thioadenosines A3 adenosine receptor agonists.

Desirability theory (DT) is a well-known multi-criteria decision-making approach. In this work, DT is employed as a prediction model (PM) interpretation tool to extract useful information on the desired trade-offs between binding and relative efficacy of N(6)-substituted-4'-thioadenosines A3 adenosine receptor (A3AR) agonists. At the same time, it was shown the usefulness of a parallel but independent approach providing a feedback on the reliability of the combination of properties predicted as a unique desirability value.

Phase II trial of radiation dose escalation with conformal external beam radiotherapy and high-dose-rate brachytherapy combined with long-term androgen suppression in unfavorable prostate cancer: feasibility report.

Purpose: To determine the feasibility of combined long-term luteinizing hormone-releasing hormone agonist-based androgen suppressive therapy (AST) and dose escalation with high-dose-rate (HDR) brachytherapy for high-risk (HRPC) or very-high-risk prostate cancer (VHRPC).

Methods And Materials: Between January 2001 and October 2006, 134 patients (median age, 70 years) with either National Comprehensive Cancer Network criteria-defined HRPC (n = 47, 35.1%) or VHRPC (n = 87, 64.

Variable selection methods in QSAR: an overview.

Variable selection is a procedure used to select the most important features to obtain as much information as possible from a reduced amount of features. The selection stage is crucial. The subsequent design of a quantitative structure-activity relationship (QSAR) model (regression or discriminant) would lead to poor performance if little significant features are selected.

New QSAR combined strategy for the design of A1 adenosine receptor agonists.

Combined discriminant and regression analysis was carried out on a series of 167 A1 adenosine receptor agonists to identify the best linear and nonlinear models for the design of new compounds with a better biological profile. On the basis of the best linear discriminant analysis and both linear and nonlinear Multi Layer Perceptron neural networks regression, we have designed and synthesized 14 carbonucleoside analogues of adenosine. Their biological activities were predicted and experimentally measured to demonstrate the capability of our model to avoid the prediction of false positives.

Search for new antagonist ligands for adenosine receptors from QSAR point of view. How close are we?

In view of the large libraries of nucleoside analogues that are now being handled in organic synthesis, the identification of drug biological activity is advisable prior to synthesis and this can be achieved by employing predictive biological property methods. In this sense, Quantitative Structure-Activity Relationships (QSAR) or docking approaches have emerged as promising tools. Although a large number of in silico approaches have been described in the literature for the prediction of different biological activities, the use of QSAR applications to develop adenosine receptor (AR) antagonists is not common as for the case of the antibiotics and anticancer compounds for instance.

2D-autocorrelation descriptors for predicting cytotoxicity of naphthoquinone ester derivatives against oral human epidermoid carcinoma.

A QSAR study was developed, employing 2D-autocorrelation descriptors and a set of 37 naphthoquinone ester derivatives, in order to model the cytotoxicity of these compounds against oral human epidermoid carcinoma (KB). A comparison with other approaches such as the BCUT, Galvez topological charge indexes, Randić molecular profile, Geometrical, and RDF descriptors was carried out. Mathematical models were obtained by means of the multiple regression analysis (MRA) and the variables were selected using genetic algorithm.

QSAR studies using radial distribution function for predicting A1 adenosine receptors agonists.

The radial distribution function (RDF) approach has been applied to the study of the A(1) adenosine receptors agonist effect of 32 adenosine analogues. A model able to describe more than 79% of the variance in the experimental activity was developed with the use of the mentioned approach. In contrast, none of the three different approaches, including the use of 2D autocorrelations, BCUT and 3D-MORSE descriptors were able to explain more than 72% of the variance in the mentioned property with the same number of variables in the equation.

Synthesis and anti-HIV activity of novel cyclopentenyl nucleoside analogues of 8-azapurine.

Novel nucleoside analogues of structure 3-5 were synthesized starting from (+/-)-cis-2-amino-3-cyclopentenylmethanol (1). The chlorine derivative 3 inhibited both HIV-1 and HIV-2 replication in MT-4 cells with IC(50) values of 10.67 microM and of 13.

QSAR studies about cytotoxicity of benzophenazines with dual inhibition toward both topoisomerases I and II: 3D-MoRSE descriptors and statistical considerations about variable selection.

Deoxyribonucleic acid (DNA) topoisomerases are involved in diverse cellular processes, such as replication, transcription, recombination, and chromosome segregation. Searching new compounds that inhibit both topoisomerases I and II is very important due to the deficiency of the specific inhibitors to overcome multidrug resistance (MDR). A QSAR study was developed, employing the 3D-MoRSE descriptors and a set of 64 benzophenazines in order to model the inhibition of the topoisomerases I and II, expressed by the cytotoxicity of these compounds (IC(50)) versus drug-resistant human small cell lung carcinoma line cell H69/LX4.

Quantitative structure activity relationships as useful tools for the design of new adenosine receptor ligands. 1. Agonist.

In order to minimize expensive drug failures it is essential to determine the potential biological activity of new candidates as early as possible. In view of the large libraries of nucleoside analogues that are now being handled in organic synthesis, the identification of a drugs biological activity is advisable even before synthesis and this can be achieved using predictive biological activity methods. In this sense, computer aided rational drug design strategies like Quantitative Structure Activity Relationships (QSAR) or docking approaches have emerged as promising tools.

A topological function based on spectral moments for predicting affinity toward A3 adenosine receptors.

The spectral moment descriptors have been applied to the study of affinity for A(3) adenosine receptors of 32 adenosine analogues. A model, able to describe more than 95% of the variance in the experimental activity, was developed with the use of the above-mentioned approach. The fragment contributions to the activity carried out show that the sulfonamido moiety at the N(6) position and hydrogen bonding play an important role in the interaction with the receptor.

Radial distribution function descriptors: an alternative for predicting A2 A adenosine receptors agonists.

The Radial Distribution Function approach has been applied to the study of the A2 A adenosine receptors agonist effect of 29 adenosine analogues: N6- arylcarbamoyl, 2-arylalkynyl-N6 -arylcarbamoyl, and N6 -carboxamido derivatives. A model able to describe around 85% of the variance in the experimental activity was developed with the use of the mentioned approach. In contrast, no one of nine different approaches, including the use of Galvez Topological Charges indexes, BCUT, Geometrical, 2D autocorrelations, Topological, Randić Molecular profile, WHIM, 3D-MORSE and GETAWAY descriptors were able to explain more than 78% of the variance in the mentioned property with the same number of variables in the equation.

GETAWAY descriptors to predicting A(2A) adenosine receptors agonists.

The GEometry, Topology and Atom-Weights AssemblY approach has been applied to the study of the A(2A) adenosine receptors agonist effect of 29 adenosine analogues: N(6)-arylcarbamoyl, 2-arylalkynyl-N(6)-arylcarbamoyl, and N(6)-carboxamido derivatives. A model able to describe more than 77% of the variance in the experimental activity was developed with the use of the mentioned approach. In contrast, no one of four different approaches, including the use of Topological, Galvez Topological Charges indexes, Geometrical and WHIM descriptors were able to explain more than 70% of the variance in the mentioned property with the same number of variables in the equation.