Residual-QSAR. Implications for genotoxic carcinogenesis

Abstract

IntroductionBoth main types of carcinogenesis, genotoxic and epigenetic, were examined in the context of non-congenericity and similarity, respectively, for the structure of ligand molecules, emphasizing the role of quantitative structure-activity relationship ((Q)SAR) studies in accordance with OECD (Organization for Economic and Cooperation Development) regulations. The main purpose of this report involves electrophilic theory and the need for meaningful physicochemical parameters to describe genotoxicity by a general mechanism.Residual-QSAR MethodThe double or looping multiple linear correlation was examined by comparing the direct and residual structural information against the observed activity. A self-consistent equation of observed-computed activity was assumed to give maximum correlation efficiency for those situations in which the direct correlations gave non-significant statistical information. Alternatively, it was also suited to describe slow and apparently non-noticeable cancer phenomenology, with special application to non-congeneric molecules involved in genotoxic carcinogenesis.Application and DiscussionsThe QSAR principles were systematically applied to a given pool of molecules with genotoxic activity in rats to elucidate their carcinogenic mechanisms. Once defined, the endpoint associated with ligand-DNA interaction was used to select variables that retained the main Hansch physicochemical parameters of hydrophobicity, polarizability and stericity, computed by the custom PM3 semiempirical quantum method. The trial and test sets of working molecules were established by implementing the normal Gaussian principle of activities that applies when the applicability domain is not restrained to the congeneric compounds, as in the present study. The application of the residual, self-consistent QSAR method and the factor (or average) method yielded results characterized by extremely high and low correlations, respectively, with the latter resembling the direct activity to parameter QSARs. Nevertheless, such contrasted correlations were further incorporated into the advanced statistical minimum paths principle, which selects the minimum hierarchy from Euclidean distances between all considered QSAR models for all combinations and considered molecular sets (i.e., school and validation). This ultimately led to a mechanistic picture based on the identified alpha, beta and gamma paths connecting structural indicators (i.e., the causes) to the global endpoint, with all included causes. The molecular mechanism preserved the self-consistent feature of the residual QSAR, with each descriptor appearing twice in the course of one cycle of ligand-DNA interaction through inter-and intra-cellular stages.ConclusionsBoth basal features of the residual-QSAR principle of self-consistency and suitability for non-congeneric molecules make it appropriate for conceptually assessing the mechanistic description of genotoxic carcinogenesis. Additionally, it could be extended to enriched physicochemical structural indices by cons...

Quantitative Structure Inter-Activity Relationship (QSInAR). Cytotoxicity Study of Some Hemisynthetic and Isolated Natural Steroids and Precursors on Human Fibrosarcoma Cells HT1080

“…The cytotoxicity of congeneric (both trial and test) series was considered and modeled as being projected on three fundamental Hansch parameters such as LogP, POL and Etot; it was found that the hydrophobicity (LogP) is the main mechanism of interaction, while the polarizability (POL) has little influence on anti-tumoral mechanism—Rejecting this way the eventual generalization of Miller’s electrophilic theory of carcinogenicity to its reversible evolution though cancer cells’ apoptosis; in fact, while LogP was found to have little influence on carcinogenity [17], it appears here as having the main influence; one may conclude therefore that indeed the carcinogenity (formation of cancer cells) and the cytotoxicity (death of cancer cells) are complementary and not symmetrical with respect to QSAR analysis;…”

“…In this regard, chemoinformatics in general [15] and the recent spectral and residual variants of quantitative structure-activity relationship (QSAR) in particular [16,17], may offer a reliable in silico (or computational) analysis for establishing whether a series of compounds may indeed constitute a fruitful direction of clinical investigations. Basically, the cytotoxic molecular mechanism may be decomposed into three elementary steps: The compound effect on membrane structure, on the signal transduction pathways, and on sterical induction signal towards the cancer cells; these effects can be structurally modeled by the so called Hansch indices’ [18] such as hydrophobicity (LogP), polarizability (POL) and optimized total energy (Etot) influence on the globally observed cytotoxic activity (A), respectively.…”

Alert-QSAR. Implications for Electrophilic Theory of Chemical Carcinogenesis

“…It was recently shown [20] that direct and residual correlations should be combined; that is, for a given parameter set and an observed endpoint set, $\left({\left\{X_i\right\}}_{i=\overline{1,M}},A\right)$, the direct QSAR can be written as $A^M=a_0+\sum _{i=1}^M{b}_{0i}{X}_i$and residual analysis gives ${\mathit{ARA}}^M=a_1+b_1\left(A-A^M\right)$…”

Introducing Catastrophe-QSAR. Application on Modeling Molecular Mechanisms of Pyridinone Derivative-Type HIV Non-Nucleoside Reverse Transcriptase Inhibitors

“…The pyridinone derivatives were divided into a training set of 23 compounds and a test set of 9 compounds according to the methods of normal/Gaussian (G) and non-normal/non-Gaussian (NG) fitted activity [39–41] (Figure 1). …”