PubMed Health⌕ Search

PubMed · 9278711

A model of complete random molecular evolution by recurrent mutation.

Abstract

A model for random molecular evolution based on recurrent mutation is proposed. Recurrent mutation replaces completely any original base in a nucleotidic site. This occurs if more than four times the number of reproductive cycles equal to the reciprocal of the mutation rate happen; no matter the population size, the number of nucleotides a genome has, or the taxa at which it belongs. The main results are: i) the expected distribution of DNA bases in a site is an isotetranomial distribution, where Adenine (A), Guanine (G), Cytosine (C) and Thymine (T) occur with probability equal to 0.25; ii) the distribution of bases in a site is independent from the distribution of bases in other sites. Several expected consequences that can be contrasted with actual data are generated. Species or operational taxonomic units (OTUs) that evolved in big populations should present distances equal to zero and similarities equal to one. OTUs evolving in small populations should present distances equal to 3/4 and similarities equal to 1/4. Thus, random molecular evolution by recurrent mutation cannot yield a tree at all. The only possible tree is that produced by random fluctuations of distances according to their variances (stochastic tree). Some consequences of the model on the expected primary structure of proteins are also analyzed. There are sufficient generations for any DNA segment evolving apart during the last four hundred million years, to reach those expected base distributions.

Explore related subjects

Keep this discovery

Explore connections, maps & timelines

BibTeXRIS

C Y Valenzuela, J L Santos. 1996. A model of complete random molecular evolution by recurrent mutation.. https://pubmed.ncbi.nlm.nih.gov/9278711/

Cite the original work for its findings. Save a collection to share your selection of sources.

KEEP EXPLORING

Related citations

Improving disulfide connectivity prediction with sequential distance between oxidized cysteines.

SUMMARY: Predicting disulfide connectivity precisely helps towards the solution of protein structure prediction. In this study, a descriptor derived from the sequential distance between oxidized cysteines (denoted as DOC) is proposed. An approach using support vector machine (SVM) method based on weighted graph matching was further developed to predict the disulfide connectivity pattern in proteins. When DOC was applied, prediction accuracy of 63% for our SVM models could be achieved, which is significantly higher than those obtained from previous approaches. The results show that using the non-local descriptor DOC coupled with local sequence profiles significantly improves the prediction accuracy. These improvements demonstrate that DOC, with a proper scaling scheme, is an effective feature for the prediction of disulfide connectivity. The method developed in this work is available at the web server PreCys (prediction of cys-cys linkages of proteins).

Chymotrypsinogen↗

Deep UV laser-induced fluorescence detection of unlabeled drugs and proteins in microchip electrophoresis.

Deep UV fluorescence detection at 266-nm excitation wavelength has been realized for sensitive detection in microchip electrophoresis. For this purpose, an epifluorescence setup was developed enabling the coupling of a deep UV laser into a commercial fluorescence microscope. Deep UV laser excitation utilizing a frequency quadrupled pulsed laser operating at 266 nm shows an impressive performance for native fluorescence detection of various compounds in fused-silica microfluidic devices. Aromatic low molecular weight compounds such as serotonin, propranolol, a diol, and tryptophan could be detected at low-micromolar concentrations. Deep UV fluorescence detection was also successfully employed for the detection of unlabeled basic proteins. For this purpose, fused-silica chips dynamically coated with hydroxypropylmethyl cellulose were employed to suppress analyte adsorption. Utilizing fused-silica chips permanently coated with poly(vinyl alcohol), it was also possible to separate and detect egg white chicken proteins. These data show that deep UV fluorescence detection significantly widens the application range of fluorescence detection in chip-based analysis techniques.

Chymotrypsinogen↗

On-line sample enrichment for the determination of proteins by capillary zone electrophoresis with poly(vinyl alcohol)-coated bubble cell capillaries.

Field-amplified sample stacking (FASS) is used to separate basic proteins in a poly-(vinyl alcohol)-coated bubble cell capillary. To our knowledge, this is the first paper describing the on-column stacking of proteins (as cations) using FASS in bubble cell capillary. The bubble cell capillary is fabricated using a one-step method. Cetyltrimethylammonium chloride is added into the running buffer to reverse the EOF and, thus, to pump the water plug out during the sample stacking step. The effect of the water plug lengths and sample injection durations were investigated and optimized. The results obtained were compared with those for the normal capillary without bubble cell in terms of resolution and sensitivity enhancement. Under the optimal condition, this method can improve the sensitivity of the peak areas ranging from 5000- to 26 000-fold. The RSDs (n = 5) of the migration time and peak area are satisfactory (less than 0.6 and 12%, respectively). Application of the capillary electrophoresis method with bubble cell, FASS, and UV detection thereby leads to the determination of these proteins at concentrations ranging from 3 to 10 ng/mL, based on a signal-to-noise ratio of 3:1.

Chymotrypsinogen↗