Analytical determination of receptor-ligand dissociation constants of two populations of receptors from displacement curves.

The determination of receptor-ligand dissociation constants from displacement data has been restricted until recently to the condition of receptor saturation, in which the concentration of receptor is negligible as compared to the displaced ligand and the displacing ligand used. This restriction has lately been removed since an accurate method has been developed for the determination of the dissociation constants for all experimental conditions for a system that includes a single type of binding site. In many cases, however, there are two types of receptor binding sites that exhibit different affinities toward the ligand. The present study provides an analytic solution for the problem of determination of the two dissociation constants as well as the proportion of the two receptor types. The formal derivation of the equations is described, along with analysis of a displacement simulation. The sensitivity of the method to the ratio between the two dissociation constants is also investigated. The application of the method is demonstrated for the analysis of the binding of beta-adrenergic receptors to the agonist isoproterenol as monitored by the displacement of the beta-antagonist 125I-labeled cyanopindolol.

Chemical kinetics of induced gene expression: activation of transcription by noncooperative binding of multiple regulatory molecules.

A chemical kinetics model is described for the regulation of gene expression by the progressive binding of regulatory molecules to specific binding sites on DNA. Chemical rate equations are formulated and solved for the accumulation of regulatory molecules on DNA, the change in the level of induced mRNA, and the change in the level of the encoded protein in the activated tissue. Some special cases are examined, including that of an activation threshold created by a requirement for the binding of a minimum number of regulatory molecules prior to gene activation. Experimental data for several hormone-activated genetic systems are analyzed in the frame of the proposed model, and kinetic parameters are predicted. The model accounts for a number of experimental characteristics of hormone-inducible genetic systems, including the existence of a lag in the time course of mRNA accumulation, the sigmoidal curve of induced mRNA kinetics, the effect of hormone on mRNA stabilization, and the induction parameters observed when hormone analogues are used. The model also provides an explanation for the phenotypes of genetic variants with altered inducibility as changes in the molecular kinetic parameters of gene activity.

Nucleotide distribution and the recognition of coding regions in DNA sequences: an information theory approach.

A method for the recognition of coding-regions along DNA sequences is described. The method is based on the observation, made in several cases, that nucleotide distribution at the third position of the codon is more biased (less random) than that in the other two positions. It is suggested that since nucleotide distribution at the third position is only weakly influenced by the amino acid distribution in the coded protein, there must be some constraints at the DNA level which bias the nucleotide distribution at the third position. The distinction between DNA-level constraints and protein-level constraints is discussed in the frame of Information Theory, and the analysis of the Mitochondrial gene coding for subunit-1 of the yeast cytochrome oxidase is presented.

A Markov analysis of DNA sequences.

We present a model by which we look at the DNA sequence as a Markov process. It has been suggested by several workers that some basic biological or chemical features of nucleic acids stand behind the frequencies of dinucleotides (doublets) in these chains. Comparing patterns of doublet frequencies in DNA of different organisms was shown to be a fruitful approach to some phylogenetic questions (Russel & Subak-Sharpe, 1977). Grantham (1978) formulated mRNA sequence indices, some of which involve certain doublet frequencies. He suggested that using these indices may provide indications of the molecular constraints existing during gene evolution. Nussinov (1981) has shown that a set of dinucleotide preference rules holds consistently for eukaryotes, and suggested a strong correlation between these rules and degenerate codon usage. Gruenbaum, Cedar & Razin (1982) found that methylation in eukaryotic DNA occurs exclusively at C-G sites. Important biological information thus seems to be contained in the doublet frequencies. One of the basic questions to be asked (the "correlation question") is to what extent are the 64 trinucleotide (triplet) frequencies measured in a sequence determined by the 16 doublet frequencies in the same sequence. The DNA is described here as a Markov process, with the nucleotides being outcomes of a sequence generator. Answering the correlation question mentioned above means finding the order of the Markov process. The difficulty is that natural sequences are of finite length, and statistical noise is quite strong. We show that even for a 16000 nucleotide long sequence (like that of the human mitochondrial genome) the finite length effect cannot be neglected. Using the Markov chain model, the correlation between doublet and triplet frequencies can, however, be determined even for finite sequences, taking proper account of the finite length. Two natural DNA sequences, the human mitochondrial genome and the SV40 DNA, are analysed as examples of the method.