Simulation of protein evolution by random fixation of allowed codons

Summary Computer simulation of protein evolution is based on a simple model consisting of random fixation of allowed codons (RFAC). Random replacement of single nucleotides occurs in a DNA sequence. If this results in any of the synonomous codons for allowed amino acids the mutation is fixed, if not, there is no change in the DNA and the cycle is repeated. Multiple fixations at the same nucleotide site, back mutations, degenerate fixations and coincidental identity of amino acids all occur. RFAC simulation begins with a single DNA sequence and follows a phylogeny based on the fossil record. The rate of fixation at the level of DNA is constant. The model upon which RFAC simulation is based is the same as the neutral theory of molecular evolution. The simulation is therefore a test of this theory. The results of simulated and real evolution are compared for fibrinopeptides A in mammals and cytochromes C and hemoglobin and chains in vertebrates. In each case the allowed variation at each site has been set equal to that observed, twice that observed and all protein amino acids. Rates of fixation vary from 2.4 × 10^–10 to 10^–5 accepted nucleotide fixations per codon per year. There is some, although never excellent, agreement between real and simulated evolution, the better fits are obtained in the cases of fibrinopeptides A and cytochromes C. The major source of discrepancy between real evolution and simulation is irregularities in the rates of real evolution. RFAC simulation is compared with the random evolutionary hit (REH) model, augmented maximum parsimony and the accepted point mutations (PAM) approach.     

Metallothionein protein evolution: a miniassay

Metallothionein (MT) evolution is one of the most obscure yet fascinating aspects of the study of these atypical metal-binding peptides. The different members of the extremely heterogeneous MT protein superfamily probably evolved through a web of duplication, functional differentiation, and/or convergence events leading to the current scenario, which is particularly hard to interpret in terms of molecular evolution. Difficulties in drawing straight evolutionary relationships are reflected in the lack of definite MT classification criteria. Presently, MTs are categorized either according to a pure taxonomic clustering or depending on their metal binding preferences and specificities. Extremely well documented MT revisions were recently published. But beyond classic approaches, this review of MT protein evolution will bring together new aspects that have seldom been discussed before. Hence, the emergence of life on our planet, since metal ion utilization is accepted to be at the root of the emergence of living organisms, and global trends that underlie structural and functional MT diversification, will be presented. Major efforts are currently being devoted to identifying rules for function-constrained MT evolution that may be applied to different groups of organisms.     

Neutral evolution of multiple quantitative characters: a genealogical approach

The G matrix measures the components of phenotypic variation that are genetically heritable. The structure of G, that is, its principal components and their associated variances, determines, in part, the direction and speed of multivariate trait evolution. In this article we present a framework and results that give the structure of G under the assumption of neutrality. We suggest that a neutral expectation of the structure of G is important because it gives a null expectation for the structure of G from which the unique consequences of selection can be determined. We demonstrate how the processes of mutation, recombination, and drift shape the structure of G. Furthermore, we demonstrate how shared common ancestry between segregating alleles shapes the structure of G. Our results show that shared common ancestry, which manifests itself in the form of a gene genealogy, causes the structure of G to be nonuniform in that the variances associated with the principal components of G decline at an approximately exponential rate. Furthermore we show that the extent of the nonuniformity in the structure of G is enhanced with declines in mutation rates, recombination rates, and numbers of loci and is dependent on the pattern and modality of mutation.     

Biological invasions and phenotypic evolution: a quantitative genetic perspective

Among the many different components of global environmental change, biological invasions represent the one with the most long-term ecological and evolutionary consequences, as effects are irreversible. Although the ecological impact of invasive species has been under great scrutiny, its evolutionary aspects and consequences have remained less explored. Once established, an important part of the success of an invasive species will depend on the presence of genetic variation in populations at the geographic boundaries upon which natural selection can act. This information is integrated in G, the matrix of additive genetic variances and covariances for a suite of traits. The G-matrix shows the restrictions and potentialities of adaptive evolution and, together with natural selection determine the direction and rate of phenotypic evolution. Here I propose that a geographic analysis of G in populations of the introduced and native range becomes essential to understand critical evolutionary issues associated with invasion success.     

A modular domain of NifU,a nitrogen fixation cluster protein,is highly conserved in evolution

HnifU, a gene exhibiting similarity tonifU genes of nitrogen fixation gene clusters, was identified in the course of expressed sequence tag (EST) generation from a human fetal heart cDNA library. Northern blot of human tissues and polymerase chain reaction (PCR) using human genomic DNA verified that the hnifU gene represented a human gene rather than a microbial contaminant of the cDNA library. Conceptual translation of the hnifU cDNA yielded a protein product bearing 77% and 70% amino acid identity to NifU-like hypothetical proteins fromHaemophilus influenzae andSaccharomyces cerevisiae, respectively, and 40–44% identity to the N-terminal regions of NifU proteins from several diazatrophs (i.e., nitrogen-fixing organisms). Pairwise determination of amino acid identities between the NifU-like proteins of nondiazatrophs showed that these NifU-like proteins exhibited higher sequence identity to each other (63–77%) than to the diazatrophic NifU proteins (40–48%). Further, the NifU-like proteins of non-nitrogenfixing organisms were similar only to the N-terminal region of diazatrophic NifU proteins and therefore identified a novel modular domain in these NifU proteins. These findings support the hypothesis that NifU is indeed a modular protein. The high degree of sequence similarity between NifU-like proteins from species as divergent as humans andH. influenzae suggests that these proteins perform some basic cellular function and may be among the most highly conserved proteins. Correspondence to: C.-C. Liew     

The evolution of dinitrogen fixation

It is argued that nitrogenase originated monophyletically in obligate anaerobes similar to Clostridia. The enzyme system was later inherited, without much change, by photosynthetic bacteria, by prokaryotic plants (blue-greens) and by aerobic bacteria. The hydrogenase function of the enzyme complex preceded the nitrogenase function, and was useful in hydrogen fermentations. The consumption of ATP served to assure disposal of electrons in the form of hydrogen gas. The present need of the enzyme system, whether acting as a hydrogenase or as a nitrogenase, for ATP may be a relic from the period when the biosphere was still reducing.     

A survey of carbon fixation pathways through a quantitative lens

While the reductive pentose phosphate cycle is responsible for the fixation of most of the carbon in the biosphere, it has several natural substitutes. In fact, due to the characterization of three new carbon fixation pathways in the last decade, the diversity of known metabolic solutions for autotrophic growth has doubled. In this review, the different pathways are analysed and compared according to various criteria, trying to connect each of the different metabolic alternatives to suitable environments or metabolic goals. The different roles of carbon fixation are discussed; in addition to sustaining autotrophic growth it can also be used for energy conservation and as an electron sink for the recycling of reduced electron carriers. Our main focus in this review is on thermodynamic and kinetic aspects, including thermodynamically challenging reactions, the ATP requirement of each pathway, energetic constraints on carbon fixation, and factors that are expected to limit the rate of the pathways. Finally, possible metabolic structures of yet unknown carbon fixation pathways are suggested and discussed.     

CIRSE: a solvation energy estimator compatible with flexible protein docking and design applications

We present the Coordinate Internal Representation of Solvation Energy (CIRSE) for computing the solvation energy of protein configurations in terms of pairwise interactions between their atoms with analytic derivatives. Currently, CIRSE is trained to a Poisson/surface-area benchmark, but CIRSE is not meant to fit this benchmark exclusively. CIRSE predicts the overall solvation energy of protein structures from 331 NMR ensembles with 0.951+/-0.047 correlation and predicts relative solvation energy changes between members of individual ensembles with an accuracy of 15.8+/-9.6 kcal/mol. The energy of individual atoms in any of CIRSE's 17 types is predicted with at least 0.98 correlation. We apply the model in energy minimization, rotamer optimization, protein design, and protein docking applications. The CIRSE model shows some propensity to accumulate errors in energy minimization as well as rotamer optimization, but these errors are consistent enough that CIRSE correctly identifies the relative solvation energies of designed sequences as well as putative docked complexes. We analyze the errors accumulated by the CIRSE model during each type of simulation and suggest means of improving the model to be generally useful for all-atom simulations.     

Constrained evolution of a quantitative character by pleiotropic mutation

The long-term response to directional selection and its selection limit are derived for a quantitative character that is controlled by pleiotropic mutations with direct deleterious effect on fitness. Directional selection is assumed to be weaker than the selection acting directly on mutations via deleterious effects (purging selection), which renders all mutations to eventual elimination. The analysis embedding this restrictive assumption indicates that the evolutionary response of the character starting from an equilibrium state, in which mutation and purging selection balance but no directional selection is operating, decreases monotonically with time at an exponential rate. And the fading rate of responses is mostly determined by the direct deleterious effect. Contrary to the expectation by the standard selection limit theory based on fixation of extant genetic variation, the present model predicts that the selection limit depends on the intensity of directional selection, the limit being proportional to the ratio of the directional selection intensity to the direct deleterious effect. A slightly larger genetic variance is maintained at the selection limit than would be without directional selection.     

Insulin internalization and intracellular protein degradation: a quantitative correlation

We have recently demonstrated that internalization of insulin is essential for insulin's action upon intracellular proteolysis (Draznin and Trowbridge 1982). In this study we have investigated the quantitative relationship between the rate of insulin internalization and its ability to inhibit intracellular proteolysis. We have used the acidification technique to separate surface bound 125I-insulin (sur) from internalized ligand (In). The In/Sur ratio plotted as a function of time permits the calculation of the rate of insulin internalization (K-e) (Draznin, Trowbridge and Ferguson 1984). Insulin in a dose dependent manner increased the rate of C14-glucose incorporation into glycogen and inhibited the rate of degradation of intracellular proteins prelabelled in vivo with C14-valine. When insulin internalization was blocked by phenylarsine oxide (10(-5) M), the amount of surface bound ligand and its effect on glucose incorporation into glycogen were unaffected whereas insulin's effect on intracellular proteolysis was markedly diminished. There was a direct and significant correlation between K-e and insulin induced inhibition of intracellular proteolysis (r = .72, P less than .05). The correlation between the amount of internalized insulin and intracellular proteolysis was also significant (r = .84, P less than .01).     

Functional evolution within a protein superfamily

The ability to predict and characterize distributions of reactivities over families and even superfamilies of proteins opens the door to an array of analyses regarding functional evolution. In this article, insights into functional evolution in the Kazal inhibitor superfamily are gained by analyzing and comparing predicted association free energy distributions against six serine proteinases, over a number of groups of inhibitors: all possible Kazal inhibitors, natural avian ovomucoid first and third domains, and sets of Kazal inhibitors with statistically weighted combinations of residues. The results indicate that, despite the great hypervariability of residues in the 10 proteinase-binding positions, avian ovomucoid third domains evolved to inhibit enzymes similar to the six enzymes selected, whereas the orthologous first domains are not inhibitors of these enzymes on purpose. Hypervariability arises because of similarity in energetic contribution from multiple residue types; conservation is in terms of functionality, with "good" residues, which make positive or less deleterious contributions to the binding, selected more frequently, and yielding overall the same distributional characteristics. Further analysis of the distributions indicates that while nature did optimize inhibitor strength, the objective may not have been the strongest possible inhibitor against one enzyme but rather an inhibitor that is relatively strong against a number of enzymes.     

Profiling protein tyrosine phosphorylation: a quantitative 45-plex peptide-based immunoassay

Cellular homeostasis and responses to stimuli are mediated by complex signaling network events dominated by changes in protein phosphorylation states. Understanding information flow in the network is essential for correlating signaling changes to cell physiology. Tyrosine phosphorylation constitutes only a small portion of all protein phosphorylation, but its importance is manifested by the significant role it plays in diseases such as cancer. A peptide-based immunoassay microarray, designed to provide site specificity, quantification, broad coverage, and accessibility, is described that profiles 45 tyrosine phosphorylation sites across 34 proteins. Epidermal growth factor-stimulated A431 cells in the absence and presence of kinase inhibitors analyzed by microarrays showed biologically validated tyrosine phosphorylation changes and unanticipated activation of other targets. The approach is scalable for increasing the breadth of content as well as for interrogating other types of protein posttranslational modifications. ( Journal of Biomolecular Screening 2008:626-637).