Exploring blood-brain barrier passage using atomic weighted vector and machine learning.

Context: This study investigates the potential of leveraging molecular properties, as determined by MD-LOVIs software and machine learning techniques, to predict the ability of compounds to cross the blood-brain barrier (BBB). Accurate prediction of BBB permeation is critical for the development of central nervous system (CNS) drugs. The study applies various machine learning models, including both classification and regression techniques, to predict BBB passage and molecular activity.

QSPR predicting the vapor pressure of pesticides into high/low volatility classes.

In this work, the vapor pressure of pesticides is employed as an indicator of their volatility potential. Quantitative Structure-Property Relationship models are established to predict the classification of compounds according to their volatility, into the high and low binary classes separated by the 1-mPa limit. A large dataset of 1005 structurally diverse pesticides with known experimental vapor pressure data at 20 °C is compiled from the publicly available Pesticide Properties DataBase (PPDB) and used for model development.

Excito-repellent and Pesticide-Likeness Properties of Essential Oils on (Fabricius) (Nitidulidae) and (L.) (Silvanidae).

(Fabricius) (Nitidulidae) and (L.) (Silvanidae) are insect pests that cause severe damage in important walnut growing regions in the northwest of Argentina. The current management approaches for these pests involve the use of unsafe phosphorus pesticides whose overuse have led to farmworker poisoning, pest resistance issues, and environmental contamination.

Resonance structure contributions, flexibility, and frontier molecular orbitals (HOMO-LUMO) of pelargonidin, cyanidin, and delphinidin throughout the conformational space: application to antioxidant and antimutagenic activities.

This research refers to the study and understanding of the conformational space of the positive-charged anthocyanidin structures in relation with the known chemical reactivities and bioactivities of these compounds. Therefore, the planar (P) and nonplanar (Z) conformers of the three hydroxylated anthocyanidins pelargonidin, cyanidin, and delphinidin were analyzed throughout the conformational space at the B3LYP/6-311 ++ G** level of theory. The outcome displayed eleven new conformers for pelargonidin, fifty-four for cyanidin, and thirty-one for delphinidin.

Dietary anthocyanins balance immune signs in osteoarthritis and obesity - update of human studies and clinical trials.

Anthocyanins are known to change ligand-receptor bindings, cell membrane permeability, and intracellular signaling pathways. The beneficial effects of dietary anthocyanins have been chronologically demonstrated in interventional and observational studies, including fourteen human chondrocyte studies and related cell culture assays, nineteen human clinical trials in osteoarthritis patients, seven obesity assays, nineteen assays in preadipocytes and related cells, and twenty-two clinical trials in overweight/obese subjects, which are critically discussed in this update. Strawberries, cherries, berries, pomegranate, tropical fruits, rosehip, purple rice, purple corn, red beans, and black soybean, together with cyanidin, delphinidin, malvidin, peonidin, some 3--glycosides, metabolites, and acylated anthocyanins from a potato cultivar have shown the best outcomes.

In Silico Antiprotozoal Evaluation of 1,4-Naphthoquinone Derivatives against Chagas and Leishmaniasis Diseases Using QSAR, Molecular Docking, and ADME Approaches.

Chagas and leishmaniasis are two neglected diseases considered as public health problems worldwide, for which there is no effective, low-cost, and low-toxicity treatment for the host. Naphthoquinones are ligands with redox properties involved in oxidative biological processes with a wide variety of activities, including antiparasitic. In this work, in silico methods of quantitative structure-activity relationship (QSAR), molecular docking, and calculation of ADME (absorption, distribution, metabolism, and excretion) properties were used to evaluate naphthoquinone derivatives with unknown antiprotozoal activity.

Predicting zebrafish (Danio rerio) embryo developmental toxicity through a non-conformational QSAR approach.

For many years, the frequent use of synthetic chemicals in the manufacture of veterinary drugs and plague control products has raised negative effects on human health and other non-target organisms, promoting the need to employ a practical and suitable methodology for early risk identification of several thousand commercial compounds. The zebrafish (Danio rerio) embryo has been emerged as one sustainable animal model for measuring developmental toxicity, an endpoint that is included in the regulatory procedures to approve chemicals, avoiding conventional and costly toxicity assays based on animal testing. In this context, the Quantitative Structure-Activity Relationships (QSAR) theory is applied to develop a predictive model based on a well-defined zebrafish embryo developmental toxicity database reported by the ToxCast™ Phase I chemical library of the Environmental Protection Agency (U.

Ensemble learning application to discover new trypanothione synthetase inhibitors.

Trypanosomatid-caused diseases are among the neglected infectious diseases with the highest disease burden, affecting about 27 million people worldwide and, in particular, socio-economically vulnerable populations. Trypanothione synthetase (TryS) is considered one of the most attractive drug targets within the thiol-polyamine metabolism of typanosomatids, being unique, essential and druggable. Here, we have compiled a dataset of 401 T.

QSAR models for insecticidal properties of plant essential oils on the housefly ( L.).

The fumigant and topical activities exhibited by 27 plant-derived essentials oils (EOs) on adult housefly are predicted through the Quantitative Structure-Activity Relationship (QSAR) theory. These molecular structure based calculations are performed on 253 structurally diverse compounds from the EOs, where the number of constituents in each essential oil mixture varies between 2 to 24. A large number of 86,048 non-conformational mixture descriptors are derived as linear combinations of the molecular descriptors of the EO components.

Antiprotozoal QSAR modelling for trypanosomiasis (Chagas disease) based on thiosemicarbazone and thiazole derivatives.

Chagas disease, caused by the protozoan parasite Trypanosoma cruzi, remains a neglected endemic infection that affects around 8 million people worldwide and causes 12,000 premature deaths per year. Traditional chemotherapy is limited to the nitro-antiparasitic drugs Benznidazole and Nifurtimox, which present serious side effects and low long-term efficacy. Several research efforts have been made over the last decade to find new chemical structures with better effectiveness and tolerance than standard anti-Chagas drugs.

Foodinformatic prediction of the retention time of pesticide residues detected in fruits and vegetables using UHPLC/ESI Q-Orbitrap.

The present work describes the development of an in silico model to predict the retention time (t) of a large Compound DataBase (CDB) of pesticides detected in fruits and vegetables. The model utilizes ultrahigh-performance liquid chromatography electrospray ionization quadrupole-Orbitrap (UHPLC/ESI Q-Orbitrap) mass spectrometry (MS) data. The available CDB was properly curated, and the pesticides were represented by conformation-independent molecular descriptors.

QSAR models for the fumigant activity prediction of essential oils.

The Quantitative Structure-Activity Relationships (QSAR) theory, which allows predicting the insecticidal activity of chemical compounds through calculations from the molecular structure, is applied on 23 essential oils composed of 402 structurally diverse compounds at different chemical compositions. A large number of 114,871 conformation-independent molecular descriptors are computed through different types of freely available open-source programs. Mixture descriptors are calculated based on molecular descriptors of the essential oil components and their composition.

The Use of the Index of Ideality of Correlation to Build Up Models for Bioconcentration Factor.

We establish a QSPR analysis for the bioconcentration factor of 851 heterogeneous structural compounds. Linear models are proposed via two different approaches: i. the optimal descriptor method implemented in CORAL, and ii.

A non-conformational QSAR study for plant-derived larvicides against Zika Aedes aegypti L. vector.

A set of 263 plant-derived compounds with larvicidal activity against Aedes aegypti L. (Diptera: Culicidae) vector is collected from the literature, and is studied by means of a non-conformational quantitative structure-activity relationships (QSAR) approach. The balanced subsets method (BSM) is employed to split the complete dataset into training, validation and test sets.

QSPR studies on water solubility, octanol-water partition coefficient and vapour pressure of pesticides.

The assessment of the environmental fate and (eco)toxicological effects of pesticide compounds is of crucial importance. The present review is focused on Quantitative Structure-Property Relationships (QSPR) applications on three environmentally relevant physicochemical properties of pesticides, which can be used for assessing their environmental partition and transport, as well as exposure potential namely water solubility, octanol-water partition coefficient and vapour pressure. This article revises various interesting QSPR applications with special emphasis on studies developed during the 2009-2019 period.

QSAR studies of the antioxidant activity of anthocyanins.

Through experimental information available from antioxidant assays of seventeen anthocyanins, and six common anthocyanidins, quantitative structure-activity relationships (QSAR) have been established in the present work. The antioxidant bioactivity has been predicted in three different lipid environments: emulsified and bulk oil (methyl linoleate) (in vitro tests) at concentrations of 50 and 250 μM, and 50 μM of the inhibitor, respectively, and in human LDL (low-density lipoprotein; "bad cholesterol") (ex vivo test) at concentrations of 2.5, 10, and 25 μM of the inhibitor.

Foodinformatics: Quantitative Structure-Property Relationship Modeling of Volatile Organic Compounds in Peppers.

The aim of this work was the foodinformatic (chemoinformatic) modeling of volatile organic compounds (VOCs) of different samples of peppers based on a quantitative structure-property relationship (QSPR) for the retention indices of 273 identified compounds. The experimental retention indices were measured by means of comprehensive two-dimensional gas chromatography combined with quadrupole-mass spectrometry (GC × GC/qMS) using the BPX5 and BP20 column coupled system. All the VOCs were represented by means of both conformation-independent molecular descriptors and molecular fingerprints calculated in the Dragon and PaDEL-Descriptor software.

Conformation-independent quantitative structure-property relationships study on water solubility of pesticides.

Water solubility is a key physicochemical parameter in pesticide control and regulation, although sometimes its experimental determination is not an easy task. In this study, we present Quantitative Structure-Property Relationships (QSPRs) for predicting the water solubility at 20 °C of 1211 approved heterogeneous pesticide compounds, collected from the online Pesticides Properties Data Base (PPDB). Validated and generally applicable Multivariable Linear Regression (MLR) models were established, including molecular descriptors carrying constitutional and topological aspects of the analyzed compounds.

QSAR Study of Biologically Active Essential Oils against Beetles Infesting the Walnut in Catamarca, Argentina.

Essential oils from six species of aromatic plants collected in the Catamarca Province of Argentina were evaluated for their chemical composition and repellent and insecticidal activities against beetles of the genus Carpophilus (Coleoptera: Nitidulidae) and Oryzaephilus (Coleoptera: Silvanidae) that infest the local walnut production. Experimental data were analyzed using generalized estimating equations, with normal distribution and the identity link function. From the spectral information from the tested essential oils, we worked their molecular modeling as mixtures by developing mixture descriptors ( D) that combined the molecular descriptor of each component in the mixture ( d ) and its relative concentration ( x ), i.

Linear Regression QSAR Models for Polo-Like Kinase-1 Inhibitors.

A structurally diverse dataset of 530 polo-like kinase-1 (PLK1) inhibitors is compiled from the ChEMBL database and studied by means of a conformation-independent quantitative structure-activity relationship (QSAR) approach. A large number (26,761) of molecular descriptors are explored with the main intention of capturing the most relevant structural characteristics affecting the bioactivity. The structural descriptors are derived with different freeware, such as PaDEL, Mold², and QuBiLs-MAS; such descriptor software complements each other and improves the QSAR results.

Quantitative structure-activity relationship (QSAR) analysis of plant-derived compounds with larvicidal activity against Zika Aedes aegypti (Diptera: Culicidae) vector using freely available descriptors.

Background: We have developed a quantitative structure-activity relationship (QSAR) model for predicting the larvicidal activity of 60 plant-derived molecules against Aedes aegypti L. (Diptera: Culicidae), a vector of several diseases such as dengue, yellow fever, chikungunya and Zika. The balanced subsets method (BSM) based on k-means cluster analysis (k-MCA) was employed to split the data set.

The conformation-independent QSPR approach for predicting the oxidation rate constant of water micropollutants.

In advanced water treatment processes, the degradation efficiency of contaminants depends on the reactivity of the hydroxyl radical toward a target micropollutant. The present study predicts the hydroxyl radical rate constant in water (k ) for 118 emerging micropollutants, by means of quantitative structure-property relationships (QSPR). The conformation-independent QSPR approach is employed, together with a large number of 15,251 molecular descriptors derived with the PaDEL, Epi Suite, and Mold2 freewares.

The quantitative structure-insecticidal activity relationships from plant derived compounds against chikungunya and zika Aedes aegypti (Diptera:Culicidae) vector.

The insecticidal activity of a series of 62 plant derived molecules against the chikungunya, dengue and zika vector, the Aedes aegypti (Diptera:Culicidae) mosquito, is subjected to a Quantitative Structure-Activity Relationships (QSAR) analysis. The Replacement Method (RM) variable subset selection technique based on Multivariable Linear Regression (MLR) proves to be successful for exploring 4885 molecular descriptors calculated with Dragon 6. The predictive capability of the obtained models is confirmed through an external test set of compounds, Leave-One-Out (LOO) cross-validation and Y-Randomization.