A QSAR review on melanoma toxicity

The connection Between Plasma Protein Binding and Acute Toxicity as Determined by the LD50 Value

Preclinical Research A dataset of three drug classes (acids, bases, and neutrals) with LD50 values in mice was analysed to investigate a possible connection between high plasma protein binding and acute toxicity. Initially, it was found that high plasma protein binding was associated with toxicity for acids and neutrals, but after compensating for differences in lipophilicity, plasma protein binding was found not to be associated with toxicity. The therapeutic index established by the quotient between mouse LD50 and the defined daily dose was unaffected by both lipophilicity and plasma protein binding.

QSAR of caffeines by similarity cluster prediction

A novel QSAR approach based on correlation weighting and alignment over a hypermolecule that mimics the investigated correlational space was performed on a set of 40 caffeines downloaded from the PubChem database. The best models describing log P and LD50 values of this set of caffeine derivatives were validated against the external test set and in a new predictive model by using clusters of similarity.

Comparative QSTR studies for predicting mutagenicity of nitro compounds

Mutagenicity and carcinogenicity are toxicological endpoints which pose a great concern being the major determinants of cancers and tumours. Nitroarenes possess genotoxic properties as they can form various electrophilic intermediates and adducts with biological systems. Different QSTR techniques were employed to develop models for the prediction of mutagenicity of nitroarenes using a diverse set of 197 nitro aromatic and hetero aromatic molecules. The 2D and 3D QSTR methods used for model development gave statistically significant results. The alignment for 3D methods was obtained by maximum common substructures (MCS) approach, by taking the most mutagenic molecule of the dataset as the template. All the QSTR models were developed with the same set of training and test set molecules. The 3D contours and 2D contribution maps along with molecular fingerprints provide useful information about the mutagenic potentials of the molecules. The GFA based model shows thermodynamic and topological descriptors play an important role in characterizing mutagenicity of nitroarenes. Atomic-level thermodynamic descriptor namely AlogP throws light on hydrophobic features and helps to understand the bilinear model. Topological aspects of these classes of compounds were depicted by the fragment fingerprints and Balaban indices obtained from HQSAR and GFA models, respectively. The predictive abilities of 2D and 3D QSTR models may be useful as a vibrant predictive tool to screen out mutagenic nitroarenes and design safer non-mutagenic nitro compounds.

Evaluation of electronic, lipophilic and membrane affinity effects on antiproliferative activity of 5-substituted-2-(2,4-dihydroxyphenyl)-1,3,4-thiadiazoles against various human cancer cells

The QSAR studies of 5-substituted-2-(2,4-dihydroxyphenyl)-1,3,4-thiadiazoles set of antiproliferative activity against human cancer cell lines have been performed. Electronic properties of compounds were estimated by the Hartree-Fock method at 6-31G** level. Lipophilicity and membrane affinity parameters were determined by the chromatographic methods RP-8 OPLC and IAM HPLC, respectively. Mono- and multivariable regression analyses were performed. The principle factor for determination of activity of compounds is partial charge of nitrogen (q(N3), q(N4)) and carbon (q(C5)) atoms of the 1,3,4-thiadiazole ring. Biological effect is also connected with molar refractivity (CMR) and lipophilicity of derivatives obtained by RP-8 chromatography. The analysis of the QSAR equations for individual cell lines indicates both similarities and differences of electron, steric factors and hydrophobic-hydrophilic character of the analogues of the tested set affecting the antiproliferative activity.