title: Nucleotide's bilinear indices: novel bio-macromolecular descriptors for bioinformatics studies of nucleic acids. I. Prediction of paromomycin's affinity constant with HIV-1 Psi-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 Re(n)[b(mk)(x (m),y (m)):Re(n) x Re(n)-->Re] 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, M(m)(k) and (s)M(m)(k), respectively. That is to say, the kth non-stochastic and stochastic nucleic acid's bilinear indices are calculated using M(m)(k) and (s)M(m)(k) 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 epsilon(260) at 260 nm and pH=7.0, first (Delta E(1)) and second (Delta E(2)) single excitation energies in eV, and first (f(1)) and second (f(2)) 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 Psi-RNA have been performed and it have been obtained several linear models in order to predict 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 x 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 x 10(-4)M(-1)). The leave-one-out (LOO) press statistics, evidenced high predictive ability of both models (q(2)=0.86 and s(cv)=0.09 x 10(-4)M(-1) for non-stochastic and q(2)=0.91 and s(cv)=0.08 x 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<or=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.
authors.affiliation: Unit of Computer-Aided Molecular Biosilico Discovery and Bioinformatic Research (CAMD-BIR Unit), Faculty of Chemistry-Pharmacy, Central University of Las Villas, Santa Clara 54830, Villa Clara, Cuba. ymarrero77@yahoo.es
authors.forename: Yovani
authors.initials: Y
authors.lastname: Marrero-Ponce
authors.forename: Sadiel E
authors.initials: SE
authors.lastname: Ortega-Broche
authors.forename: Yunaimy Echeverría
authors.initials: YE
authors.lastname: Díaz
authors.forename: Ysaias J
authors.initials: YJ
authors.lastname: Alvarado
authors.forename: Nestor
authors.initials: N
authors.lastname: Cubillan
authors.forename: Gladys Casas
authors.initials: GC
authors.lastname: Cardoso
authors.forename: Francisco
authors.initials: F
authors.lastname: Torrens
authors.forename: Facundo
authors.initials: F
authors.lastname: Pérez-Giménez
mesh_terms: D001483:Base Sequence; D019295:Computational Biology; D018983:DNA Footprinting; D042003:DNA Packaging / Q000235:genetics; D004279:DNA, Viral / Q000235:genetics; D015497:HIV-1 / Q000235:genetics* / Q000378:metabolism; D008958:Models, Molecular; D008969:Molecular Sequence Data; D010303:Paromomycin / Q000378:metabolism*; D021281:Quantitative Structure-Activity Relationship; D012367:RNA, Viral / Q000235:genetics / Q000378:metabolism*; D013269:Stochastic Processes
chemical_list: D004279:DNA, Viral; D012367:RNA, Viral; D010303:Paromomycin