Systematic QSAR and iQCCR modelling of fused/non-fused aromatic hydrocarbons (FNFAHs) carcinogenicity to rodents: reducing unnecessary chemical synthesis and animal testing

Abstract

Carcinogenicity of chemicals is a highly concerned toxicological endpoint closely associated with human health. To implement 3R principles of animal studies under the background of green and sustainable chemistry, for...

Ecotoxicological risk assessment of pesticides against different aquatic and terrestrial species: using mechanistic QSTR and iQSTTR modelling approaches to fill the toxicity data gap

“…All the toxicity endpoint values were transformed to millimolar concentrations, followed by a negative logarithmic transformation, namely, pLD 50 , pEC 50 and pLC 50 that are customary in ecotoxicological QSAR/QSTR modeling. 34–38 The data generally conformed to the normal distribution that is suitable for QSTR modelling (Fig. S1†).…”

“…Here, we used the molecular weight (MW)-Alog P method to define the chemical space. 36,53–55 Fig. 5 shows the distribution scatter plots of the datasets of the four best QSTR models.…”

“…Here, we used the molecular weight (MW)-Alog P method to define the chemical space. 36,[53][54][55] Mechanistic interpretation of the descriptors in each QSTR model. In order to better understand the potential mechanisms of acute toxicity of pesticides against different species, which has been mentioned in OECD principle 5, "a QSTR should be associated with a mechanistic interpretation, if possible"; 33 we analyzed the role of descriptors in each model using variable importance plot (VIP) and loading plot (Fig.…”

Machine-Learning-Based Prediction of Plant Cuticle–Air Partition Coefficients for Organic Pollutants: Revealing Mechanisms from a Molecular Structure Perspective

“…Therefore, a decrease in log K ca could be expected for compounds with lower LLS_02 values. The descriptor SpMax2_Bh(v) was largest eigenvalue n. 2 of Burden matrix weighted by van der Waals volume, and belonged to Burden eigenvalues [ 43 ]. Burden eigenvalues were calculated from the Burden matrix Bh(w) , and the diagonal elements of the adjacency matrix are van der Waals volume.…”

Predictive binary mixture toxicity modeling of fluoroquinolones (FQs) and the projection of toxicity of hypothetical binary FQ mixtures: a combination of 2D-QSAR and machine-learning approaches

“…One of the major advantages of such QSAR models over experimentation is the ability to predict the toxicity of an innite number of combinations without physical formulation; the mixtures must fall under the domain of applicability of the developed model to get a reliable prediction. Both the QSAR and read-across have been employed in many previous studies for the toxicity predictions of individual toxicants [17][18][19] as well as chemical mixtures. [20][21][22][23] Chemical regulatory agencies such as the US-Environmental Protection Agency (US-EPA), European Chemicals Agency (ECHA), Australian Industrial Chemical Introduction Scheme (AICIS), etc.…”