Dmitry N. Ivankov

Contact order revisited: influence of protein size on the folding rate.

Guided by the recent success of empirical model predicting the folding rates of small two‐state folding proteins from the relative contact order (CO) of their native structures, by a theoretical model of protein folding that predicts that logarithm of the folding rate decreases with the protein chain length L as L2/3, and by the finding that the folding rates of multistate folding proteins strongly correlate with their sizes and have very bad correlation with CO, we reexamined the dependence of folding rate on CO and L in attempt to find a structural parameter that determines folding rates for the totality of proteins. We show that the Abs_CO = CO × L, is able to predict rather accurately folding rates for both two‐state and multistate folding proteins, as well as short peptides, and that this Abs_CO scales with the protein chain length as L0.70 ± 0.07 for the totality of studied single‐domain proteins and peptides.

Chain length is the main determinant of the folding rate for proteins with three-state folding kinetics.

We demonstrate that chain length is the main determinant of the folding rate for proteins with the three‐state folding kinetics. The logarithm of their folding rate in water (kf) strongly anticorrelates with their chain length L (the correlation coefficient being −0.80). At the same time, the chain length has no correlation with the folding rate for two‐state folding proteins (the correlation coefficient is −0.07). Another significant difference of these two groups of proteins is a strong anticorrelation between the folding rate and Bakers “relative contact order” for the two‐state folders and the complete absence of such correlation for the three‐state folders. Proteins 2003;51:162–166.

Folding nuclei in proteins.

When a protein folds or unfolds, it passes through many half‐folded microstates. Only a few of them can accumulate and be seen experimentally, and this happens only when the folding (or unfolding) occurs far from the point of thermodynamic equilibrium between the native and denatured states. The universal features of folding, though, are observed just close to the equilibrium point. Here the ‘two‐state’ transition proceeds without any accumulation of metastable intermediates, and only the transition state (‘folding nucleus’) is outlined by its key influence on the folding–unfolding kinetics. Our aim is to review recent experimental and theoretical studies of the folding nuclei.

Local fitness landscape of the green fluorescent protein.

Fitness landscapes depict how genotypes manifest at the phenotypic level and form the basis of our understanding of many areas of biology, yet their properties remain elusive. Previous studies have analysed specific genes, often using their function as a proxy for fitness, experimentally assessing the effect on function of single mutations and their combinations in a specific sequence or in different sequences. However, systematic high-throughput studies of the local fitness landscape of an entire protein have not yet been reported. Here we visualize an extensive region of the local fitness landscape of the green fluorescent protein from Aequorea victoria (avGFP) by measuring the native function (fluorescence) of tens of thousands of derivative genotypes of avGFP. We show that the fitness landscape of avGFP is narrow, with 3/4 of the derivatives with a single mutation showing reduced fluorescence and half of the derivatives with four mutations being completely non-fluorescent. The narrowness is enhanced by epistasis, which was detected in up to 30% of genotypes with multiple mutations and mostly occurred through the cumulative effect of slightly deleterious mutations causing a threshold-like decrease in protein stability and a concomitant loss of fluorescence. A model of orthologous sequence divergence spanning hundreds of millions of years predicted the extent of epistasis in our data, indicating congruence between the fitness landscape properties at the local and global scales. The characterization of the local fitness landscape of avGFP has important implications for several fields including molecular evolution, population genetics and protein design.

KineticDB: a database of protein folding kinetics

We propose here KineticDB, a systematically compiled database of protein folding kinetics, which contains about 90 unique proteins. The main goal of the KineticDB is to provide users with a diverse set of protein folding rates determined experimentally. The search for determinants of protein folding is still in progress, aimed at obtaining a new understanding of the folding process. Comparison with experimental protein folding rates has been the main tool for validation of both theoretical models and empirical relationships during the last 10 years. It is, therefore, necessary to provide a researcher with as much data as possible in a simple and easy-to-use way. At present, the KineticDB contains the results of folding kinetics measurements of single-domain proteins and separate protein domains as well as short peptides without disulfide bonds. It includes data on about 90 unique proteins and many mutants that have been systematically accumulated over the last 10 years and is the largest collection of protein folding kinetic data presented as a database. The KineticDB is available at http://kineticdb.protres.ru/db/index.pl.

Coupling between Properties of the Protein Shape and the Rate of Protein Folding

There are several important questions on the coupling between properties of the protein shape and the rate of protein folding. We have studied a series of structural descriptors intended for describing protein shapes (the radius of gyration, the radius of cross-section, and the coefficient of compactness) and their possible connection with folding behavior, either rates of folding or the emergence of folding intermediates, and compared them with classical descriptors, protein chain length and contact order. It has been found that when a descriptor is normalized to eliminate the influence of the protein size (the radius of gyration normalized to the radius of gyration of a ball of equal volume, the coefficient of compactness defined as the ratio of the accessible surface area of a protein to that of an ideal ball of equal volume, and relative contact order) it completely looses its ability to predict folding rates. On the other hand, when a descriptor correlates well with protein size (the radius of cross-section and absolute contact order in our consideration) then it correlates well with the logarithm of folding rates and separates reasonably well two-state folders from multi-state ones. The critical control for the performance of new descriptors demonstrated that the radius of cross-section has a somewhat higher predictive power (the correlation coefficient is −0.74) than size alone (the correlation coefficient is −0.65). So, we have shown that the numerical descriptors of the overall shape-geometry of protein structures are one of the important determinants of the protein-folding rate and mechanism.

Golden triangle for folding rates of globular proteins

The ability of protein chains to spontaneously form their spatial structures is a long-standing puzzle in molecular biology. Experimentally measured rates of spontaneous folding of single-domain globular proteins range from microseconds to hours: the difference (11 orders of magnitude) is akin to the difference between the life span of a mosquito and the age of the universe. Here, we show that physical theory with biological constraints outlines a “golden triangle” limiting the possible range of folding rates for single-domain globular proteins of various size and stability, and that the experimentally measured folding rates fall within this narrow triangle built without any adjustable parameters, filling it almost completely. In addition, the golden triangle predicts the maximal size of protein domains that fold under solely thermodynamic (rather than kinetic) control. It also predicts the maximal allowed size of the “foldable” protein domains, and the size of domains found in known protein structures is in a good agreement with this limit.

More compact protein globules exhibit slower folding rates

We have demonstrated that, among proteins of the same size, α/β proteins have on the average a greater number of contacts per residue due to their more compact (more “spherical”) structure, rather than due to tighter packing. We have examined the relationship between the average number of contacts per residue and folding rates in globular proteins according to general protein structural class (all‐α, all‐β, α/β, α+β). Our analysis demonstrates that α/β proteins have both the greatest number of contacts and the slowest folding rates in comparison to proteins from the other structural classes. Because α/β proteins are also known to be the oldest proteins, it can be suggested that proteins have evolved to pack more quickly and into looser structures. Proteins 2008.

Unexpected Diversity of Signal Peptides in Prokaryotes

ABSTRACT Signal peptides are a cornerstone mechanism for cellular protein localization, yet until now experimental determination of signal peptides has come from only a narrow taxonomic sampling. As a result, the dominant view is that Sec-cleaved signal peptides in prokaryotes are defined by a canonical AxA motif. Although other residues are permitted in the motif, alanine is by far the most common. Here we broadly examine proteomics data to reveal the signal peptide sequences for 32 bacterial and archaeal organisms from nine phyla and demonstrate that this alanine preference is not universal. Discoveries include fundamentally distinct signal peptide motifs from Alphaproteobacteria, Spirochaetes, Thermotogae and Euryarchaeota. In these novel motifs, alanine is no longer the dominant residue but has been replaced in a different way for each taxon. Surprisingly, divergent motifs correlate with a proteome-wide reduction in alanine. Computational analyses of ~1,500 genomes reveal numerous major evolutionary clades which have replaced the canonical signal peptide sequence with novel motifs. IMPORTANCE This article replaces a widely held general model with a more detailed model describing phylogenetically correlated variation in motifs for Sec secretion. This article replaces a widely held general model with a more detailed model describing phylogenetically correlated variation in motifs for Sec secretion.

How many signal peptides are there in bacteria

Over the last 5 years proteogenomics (using mass spectroscopy to identify proteins predicted from genomic sequences) has emerged as a promising approach to the high-throughput identification of protein N-termini, which remains a problem in genome annotation. Comparison of the experimentally determined N-termini with those predicted by sequence analysis tools allows identification of the signal peptides and therefore conclusions on the cytoplasmic or extracytoplasmic (periplasmic or extracellular) localization of the respective proteins. We present here the results of a proteogenomic study of the signal peptides in Escherichia coli K-12 and compare its results with the available experimental data and predictions by such software tools as SignalP and Phobius. A single proteogenomics experiment recovered more than a third of all signal peptides that had been experimentally determined during the past three decades and confirmed at least 31 additional signal peptides, mostly in the known exported proteins, which had been previously predicted but not validated. The filtering of putative signal peptides for the peptide length and the presence of an eight-residue hydrophobic patch and a typical signal peptidase cleavage site proved sufficient to eliminate the false-positive hits. Surprisingly, the results of this proteogenomics study, as well as a re-analysis of the E. coli genome with the latest version of SignalP program, show that the fraction of proteins containing signal peptides is only about 10%, or half of previous estimates.