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Nucleotide's bilinear indices: Novel bio-macromolecular descriptors for bioinformatics studies of nucleic acids. I. Pbkp_rediction of paromomycin's affinity constant with HIV-1 Ψ-RNA packaging region

Abstract:

A new set of nucleotide-based bio-macromolecular descriptors are presented. This novel approach to bio-macromolecular design from a linear algebra point of view is relevant to nucleic acids quantitative structure-activity relationship (QSAR) studies. These bio-macromolecular indices are based on the calculus of bilinear maps on ℜn [bmk (over(x, -)m, over(y, -)m) : ℜn × ℜn → ℜ] in canonical basis. Nucleic acid's bilinear indices are calculated from kth power of non-stochastic and stochastic nucleotide's graph-theoretic electronic-contact matrices, Mmk and s Mmk, respectively. That is to say, the kth non-stochastic and stochastic nucleic acid's bilinear indices are calculated using Mmk and s Mmk as matrix operators of bilinear transformations. Moreover, biochemical information is codified by using different pair combinations of nucleotide-base properties as weightings (experimental molar absorption coefficient ε{lunate}260 at 260 nm and pH=7.0, first (Δ E1) and second (Δ E2) single excitation energies in eV, and first (f1) and second (f2) oscillator strength values (of the first singlet excitation energies) of the nucleotide DNA-RNA bases. As example of this approach, an interaction study of the antibiotic paromomycin with the packaging region of the HIV-1 Ψ-RNA have been performed and it have been obtained several linear models in order to pbkp_redict the interaction strength. The best linear model obtained by using non-stochastic bilinear indices explains about 91% of the variance of the experimental Log K (R=0.95 and s=0.08×10-4 M-1) as long as the best stochastic bilinear indices-based equation account for 93% of the Log K variance (R=0.97 and s=0.07×10-4 M-1). The leave-one-out (LOO) press statistics, evidenced high pbkp_redictive ability of both models (q2=0.86 and scv=0.09×10-4 M-1 for non-stochastic and q2=0.91 and scv=0.08×10-4 M-1 for stochastic bilinear indices). The nucleic acid's bilinear indices-based models compared favorably with other nucleic acid's indices-based approaches reported nowadays. These models also permit the interpretation of the driving forces of the interaction process. In this sense, developed equations involve short-reaching (k≤3), middle-reaching (4<k<9), and far-reaching (k=10 or greater) nucleotide's bilinear indices. This situation points to electronic and topologic nucleotide's backbone interactions control of the stability profile of paromomycin-RNA complexes. Consequently, the present approach represents a novel and rather promising way to theoretical-biology studies. © 2009 Elsevier Ltd. All rights reserved.