Question

Dissociation and reassociation kinetics of dna

Answer 1

Answer:

Explanation:

Dissociation:

The first order rate constants for the dissociation of daunorubicin, doxorubicin, and 1-; 1,4-; 1,5-; and 1,8-; N,N-diethylaminoethylamino-substituted anthraquinones from calf thymus DNA were determined using stopped-flow spectrophotometry. Sodium dodecyl sulphate was used to disrupt the equilibrium. In all cases there was an increase in the rate constant with temperature. The dissociation rate constants at 20 degrees, 25 degrees and 37 degrees, were in the order 1-; much greater than 1,8-; greater than 1,4-; greater than daunorubicin and doxorubicin greater than 1,5-disubstituted anthraquinone. The 1,5-disubstituted anthraquinone (VII) thus shows the slowest rate of dissociation from DNA; the DNA complex dissociating more slowly than the DNA complexes of the anthracyclines, daunorubicin and doxorubicin. The result is consistent with the data from computer graphics modelling studies [39] which show that DNA-breathing (transient base pair unstacking) has to occur to allow the docking of the 1,5-disubstituted anthraquinone (VII) into the receptor site. Hence once the 1,5-disubstituted anthraquinone molecule has intercalated into DNA, DNA-breathing is required before dissociation can take place. This is not necessary with the other compounds (though the 1,4-disubstituted anthraquinone (V) can bind in this manner as well). So the very slow dissociation of the DNA/1,5-disubstituted anthraquinone complex relative to that of the DNA complexes of the other compounds examined here, supports the proposed mode of binding.

Reassociation :

DNA reassociation kinetics, also known as Cot curves, were recently used by Gans and co-workers to estimate the

number of bacterial species present in soil samples. By reanalysing the mathematical model we show that rather than the

number of species, Simpson and Shannon diversity indices are encoded in the experimental data. Our main tool to

establish this result are the so-called Re´nyi diversities, closely related to Hill numbers, illustrating the power of these

concepts in interpreting ecological data. We argue that the huge diversity encountered in microbial ecology can be

quantified more informatively by diversity indices than by number of species.