Ld/Mm+ Simulation of Some Aristolochic and Humic Acids Species Coupled in Periodic Box with Water.

BACKGROUND: This study is one of the dynamics molecular docking that presents the interactions between a molecular model of the mixture of humic acid structure and 18 aristolochic acid structures, from the PubChem database in a water box that simulates the environment reactions. OBJECTIVE: The major objective was to identify what happens in this procedure (LD/MM+) with the coupled species. METHODS: LD/MM+ SIMULATION (Langevin dynamics simulation). RESULTS: The R-Squared statistic indicates that the model, as fitted by MLR, explains 90.9437% of the variability in volume. CONCLUSION: The interactions of these acids, the types of forces, and the way that these molecules can get closer to each other, in terms of total energy density, while identifying the specificities vis-àvis of water-aromaticity or water-reactivity behaviors were observed.

Potential carcinogenicity predicted by computational toxicity evaluation of thiophosphate pesticides using QSTR/QSCarciAR model.

This study presents in silico prediction of toxic activities and carcinogenicity, represented by the potential carcinogenicity DSSTox/DBS, based on vector regression with a new Kernel activity, and correlating the predicted toxicity values through a QSAR model, namely: QSTR/QSCarciAR (quantitative structure toxicity relationship/quantitative structure carcinogenicity-activity relationship) described by 2D, 3D descriptors and biological descriptors. The results showed a connection between carcinogenicity (compared to the structure of a compound) and toxicity, as a basis for future studies on this subject, but each prediction is based on structurally similar compounds and the reactivation of the substructures of these compounds.

Molecular docking study to evaluate the carcinogenic potential and mammalian toxicity of thiophosphonate pesticides by cluster and discriminant analysis.

In this paper, the carcinogenic potential and mammalian toxicity on rodents, based on the quantitative relationship models between structure and biological activity (QSAR), were evaluated. The carcinogenicity and acute toxicity were evaluated by docking molecular physicochemical descriptors, on a series of 33 thiophosphonates. These properties, mainly hydrophobicity, electronic distribution, hydrogen bonding characteristics, molecule size and flexibility, and the presence of various pharmacophoric features, influence the behavior of molecule in a living organism, including bioavailability, transport properties, affinity to proteins, reactivity, toxicity, metabolic stability and many others. The model was validated using linear regression methods: principal component analysis (PCA), partial least squares (PLS) and multiple linear regression (MLR); non-linear regression methods: cluster analysis (CA) and discriminant analysis (DA); and neural network analysis: probabilistic neural network (PNN), identifying the best predictor.

Quantitative structure-activity/ecotoxicity relationships (QSAR/QEcoSAR) of a series of phosphonates.

In this paper the structure-toxicity relationship studies were performed for a series of 60 phosphonates. The toxicity of the compounds was determined by two ways: by quantifying the measured toxicity values, Mlog(1/MRIC50) collected by literature, for rodents species; second by using EcoSAR software version 1.11, for calculating the toxicity for fish species, considered as dependent variables and they were related to structural features obtained by molecular and quantum mechanics calculations. The QSAR/QEcoSAR was validated by multiple linear regression (MLR), although the purpose of this work was not to validate the model proposed, but rather to test the influence of structural parameters of the proposed model QSAR/QEcoSAR. The obtained models showed that the toxicity of phosphonates was influenced by steric and molecular geometry which cause inhibition of cholinesterase activity.