Hydrophobicity and structural classes in proteins.

The bulk hydrophobic character for the 20 natural amino acid residues, has been obtained from a database of 60 protein structures, grouped in the four structural classes alpha alpha, beta beta, alpha + beta and alpha/beta. The hydrophobicity coefficients thus obtained are compared with Ponnuswamy's original values using scales normalized to average = 0.0 and standard deviation = 1.0. Even though most of the amino acid residues do not change their hydropathic character in the different structural classes, their behaviour suggests the convenience that averaging methods should only consider proteins of the same structural class and that this information should be included in the secondary structure methods.     

The folding type of a protein is relevant to the amino acid composition

The folding types of 135 proteins, the three-dimensional structures of which are known, were analyzed in terms of the amino acid composition. The amino acid composition of a protein was expressed as a point in a multidimensional space spanned with 20 axes, on which the corresponding contents of 20 amino acids in the protein were represented. The distribution pattern of proteins in this composition space was examined in relation to five folding types, alpha, beta, alpha/beta, alpha + beta, and irregular type. The results show that amino acid compositions of the alpha, beta, and alpha/beta types are located in different regions in the composition space, thus allowing distinct separation of proteins depending on the folding types. The points representing proteins of the alpha + beta and irregular types, however, are widely scattered in the space, and the existing regions overlap with those of the other folding types. A simple method of utilizing the "distance" in the space was found to be convenient for classification of proteins into the five folding types. The assignment of the folding type with this method gave an accuracy of 70% in the coincidence with the experimental data.     

A correlation-coefficient method to predicting protein-structural classes from amino acid compositions.

A protein is usually classified into one of the following four structural classes: all alpha, all beta, (alpha + beta) and alpha/beta. In this paper, based on the maximum correlation-coefficient principle, a new formulation is proposed for predicting the structural class of a protein according to its amino acid composition. Calculations have been made for a development set of proteins from which the amino acid compositions for the standard structural classes were derived, and an independent set of proteins which are outside the development set. The former can test the self consistency of a method and the latter can test its extrapolating effectiveness. In both cases, the results showed that the new method gave a considerably higher rate of correct prediction than any of the previous methods, implying that a significant improvement has been achieved by implementing the maximum-correlation-coefficient principle in the new method.     

How good is prediction of protein structural class by the component-coupled method?

Proteins of known structures are usually classified into four structural classes: all-alpha, all-beta, alpha+beta, and alpha/beta type of proteins. A number of methods to predicting the structural class of a protein based on its amino acid composition have been developed during the past few years. Recently, a component-coupled method was developed for predicting protein structural class according to amino acid composition. This method is based on the least Mahalanobis distance principle, and yields much better predicted results in comparison with the previous methods. However, the success rates reported for structural class prediction by different investigators are contradictory. The highest reported accuracies by this method are near 100%, but the lowest one is only about 60%. The goal of this study is to resolve this paradox and to determine the possible upper limit of prediction rate for structural classes. In this paper, based on the normality assumption and the Bayes decision rule for minimum error, a new method is proposed for predicting the structural class of a protein according to its amino acid composition. The detailed theoretical analysis indicates that if the four protein folding classes are governed by the normal distributions, the present method will yield the optimum predictive result in a statistical sense. A non-redundant data set of 1,189 protein domains is used to evaluate the performance of the new method. Our results demonstrate that 60% correctness is the upper limit for a 4-type class prediction from amino acid composition alone for an unknown query protein. The apparent relatively high accuracy level (more than 90%) attained in the previous studies was due to the preselection of test sets, which may not be adequately representative of all unrelated proteins.     

Sequence of a full-length cDNA for rat lung beta-galactoside-binding protein: primary and secondary structure of the lectin

A full-length cDNA for rat lung beta-galactoside lectin (subunit Mr approximately 14,000, lectin 14K) was cloned and the nucleotide sequence determined. The deduced amino acid sequence agrees with the amino acid composition and direct amino acid sequence analysis of purified rat lung lectin peptides. We found that the amino-terminal alanine is blocked with an acetyl group. Comparison of the amino acid sequence with other proteins shows a high degree of homology only with other vertebrate lectin sequences, supporting the suggestion that these lectins may constitute a unique class of vertebrate proteins. The amino acid composition and sequence of lectin peptides, the sequence of lectin cDNA, and isoelectric focusing of purified lectin indicate that rat lung lectin 14K is composed predominantly of a single protein. In addition, rat uterus lectin 14K was found to be the same protein as that present in lung. We characterized the secondary and tertiary structure of rat lung lectin 14K by circular dichroism, by analytical ultracentrifugation, and by computer analysis of its primary structure. Results of these experiments suggest that lectin 14K is primarily a hydrophilic protein with an asymmetric, elongated structure consisting of approximately equal amounts of alpha helix, beta sheet, beta turn, and random coil. We found that Cys-2 and Cys-130 react most rapidly with iodoacetamide; one or both of these residues may be primarily responsible for the thiol requirement of lectin activity.     

A weighting method for predicting protein structural class from amino acid composition.

A protein is generally classified into one of the following four structural classes: all alpha, all beta, alpha+beta and alpha/beta. In this paper, based on the weighting to the 20 constituent amino acids, a new method is proposed for predicting the structural class of a protein according to its amino acid composition. The 20 weighting parameters, which reflect the different properties of the 20 constituent amino acids, have been obtained from a training set of proteins through the linear-programming approach. The rate of correct prediction for a training set of proteins by means of the new method was 100%, whereas the highest rate of previous methods was 82.8%. Furthermore, the results showed that the more numerous training proteins, the more effective the new method.     

Predicting protein structure from long-range contacts

Short-range and long-range contacts are important in forming protein structure. The proteins can be grouped into four different structural classes according to the content and topology of alpha-helices and beta-strands, and there are all-alpha, all-beta, alpha/beta and alpha+beta proteins. However, there is much difference in statistical property for those classes of proteins. In this paper, we will discuss protein structure in the view of the relative number of long-range (short-range) contacts for each residue. We find the percentage of residues having a large number of long-range contacts in protein is small in all-alpha class of proteins, and large in all-beta class of proteins. However, the percentage of residues is almost the same in alpha/beta and alpha+beta classes of proteins. We calculate the percentage of residues having the number of long-range contacts greater than or equal to (>/=) N(L)=5, and 7 for 428 proteins. The average percentage is 13.3%, 54.8%, 41.4% and 37.0% for all-alpha, all-beta, alpha/beta and alpha+beta classes of proteins with N(L)=5, respectively. With N(L) increasing, the percentage decreases, especially for all-alpha class of proteins. In the meantime, the percentage of residues having the number of short-range contacts greater than or equal to N(S) (>/=N(S)) in protein samples is large for all-alpha class of proteins, and small for all-beta class of proteins, especially for large N(S). We also investigate the ability of amino residues in forming a large number of long-range and short-range contacts. Cys, Val, Ile, Tyr, Trp and Phe can form a large number of long-range contacts easily, and Glu, Lys, Asp, Gln, Arg and Asn can form a large number of long-range contacts, but with difficulty. We also discuss the relative ability in forming short-range contacts for 20 amino residues. Comparison with Fauchere-Pliska hydrophobicity scale and the percentage of residues having large number of long-range contacts is also made. This investigation can provide some insights into the protein structure.     

Accessible surfaces of beta proteins increase with increasing protein molecular mass more rapidly than those of other proteins

Here we present a systematic analysis of accessible surface areas and hydrogen bonds of 2554 globular proteins from four structural classes (all-α, all-β, α/β and α+β proteins) that is aimed to learn in which structural class the accessible surface area increases with increasing protein molecular mass more rapidly than in other classes, and what structural peculiarities are responsible for this effect. The beta structural class of proteins was found to be the leader, with the following possible explanations of this fact. First, in beta structural proteins, the fraction of residues not included in the regular secondary structure is the largest, and second, the accessible surface area of packaged elements of the beta-structure increases more rapidly with increasing molecular mass in comparison with the alpha-structure. Moreover, in the beta structure, the probability of formation of backbone hydrogen bonds is higher than that in the alpha helix for all residues of α+β proteins (the average probability is 0.73±0.01 for the beta-structure and 0.60±0.01 for the alpha-structure without proline) and α/β proteins, except for asparagine, aspartic acid, glycine, threonine, and serine (0.70±0.01 for the beta-structure and 0.60±0.01 for the alpha-structure without the proline residue). There is a linear relationship between the number of hydrogen bonds and the number of amino acid residues in the protein (Number of hydrogen bonds=0.678·number of residues-3.350).     

Influence of medium- and long-range interactions in different folding types of globular proteins

Recognition of protein fold from amino acid sequence is a challenging task. The structure and stability of proteins from different fold are mainly dictated by inter-residue interactions. In our earlier work, we have successfully used the medium- and long-range contacts for predicting the protein folding rates, discriminating globular and membrane proteins and for distinguishing protein structural classes. In this work, we analyze the role of inter-residue interactions in commonly occurring folds of globular proteins in order to understand their folding mechanisms. In the medium-range contacts, the globin fold and four-helical bundle proteins have more contacts than that of DNA-RNA fold although they all belong to all-alpha class. In long-range contacts, only the ribonuclease fold prefers 4-10 range and the other folding types prefer the range 21-30 in alpha/beta class proteins. Further, the preferred residues and residue pairs influenced by these different folds are discussed. The information about the preference of medium- and long-range contacts exhibited by the 20 amino acid residues can be effectively used to predict the folding type of each protein.     

An optimization approach to predicting protein structural class from amino acid composition.

Proteins are generally classified into four structural classes: all-alpha proteins, all-beta proteins, alpha + beta proteins, and alpha/beta proteins. In this article, a protein is expressed as a vector of 20-dimensional space, in which its 20 components are defined by the composition of its 20 amino acids. Based on this, a new method, the so-called maximum component coefficient method, is proposed for predicting the structural class of a protein according to its amino acid composition. In comparison with the existing methods, the new method yields a higher general accuracy of prediction. Especially for the all-alpha proteins, the rate of correct prediction obtained by the new method is much higher than that by any of the existing methods. For instance, for the 19 all-alpha proteins investigated previously by P.Y. Chou, the rate of correct prediction by means of his method was 84.2%, but the correct rate when predicted with the new method would be 100%! Furthermore, the new method is characterized by an explicable physical picture. This is reflected by the process in which the vector representing a protein to be predicted is decomposed into four component vectors, each of which corresponds to one of the norms of the four protein structural classes.     

Entropy capacity determines protein folding

Search and study of the general principles that govern kinetics and thermodynamics of protein folding generate a new insight into the factors controlling this process. Here, based on the known experimental data and using theoretical modeling of protein folding, we demonstrate that there exists an optimal relationship between the average conformational entropy and the average energy of contacts per residue-that is, an entropy capacity-for fast protein folding. Statistical analysis of conformational entropy and number of contacts per residue for 5829 protein structures from four general structural classes (all-alpha, all-beta, alpha/beta, alpha+beta) demonstrates that each class of proteins has its own class-specific average number of contacts (class alpha/beta has the largest number of contacts) and average conformational entropy per residue (class all-alpha has the largest number of rotatable angles phi, psi, and chi per residue). These class-specific features determine the folding rates: alpha proteins are the fastest folding proteins, then follow beta and alpha+beta proteins, and finally alpha/beta proteins are the slowest ones. Our result is in agreement with the experimental folding rates for 60 proteins. This suggests that structural and sequence properties are important determinants of protein folding rates.     

More compact protein globules exhibit slower folding rates

We have demonstrated that, among proteins of the same size, alpha/beta 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-alpha, all-beta, alpha/beta, alpha+beta). Our analysis demonstrates that alpha/beta proteins have both the greatest number of contacts and the slowest folding rates in comparison to proteins from the other structural classes. Because alpha/beta 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.     

The primary structure and the functional domains of an elongation factor-1 alpha from Mucor racemosus

We have determined the complete nucleotide sequence for TEF-1, one of three genes coding for elongation factor (EF)-1 alpha in Mucor racemosus. The deduced EF-1 alpha protein contains 458 amino acids encoded by two exons. The presence of an intervening sequence located near the 3' end of the gene was predicted by the nucleotide sequence data and confirmed by alkaline S1 nuclease mapping. The amino acid sequence of EF-1 alpha was compared to the published amino acid sequences of EF-1 alpha proteins from Saccharomyces cerevisiae and Artemia salina. These proteins shared nearly 85% homology. A similar comparison to the functionally analogous EF-Tu from Escherichia coli revealed several regions of amino acid homology suggesting that the functional domains are conserved in elongation factors from these diverse organisms. Secondary structure predictions indicated that alpha helix and beta sheet conformations associated with the functional domains in EF-Tu are present in the same relative location in EF-1 alpha from M. racemosus. Through this comparative structural analysis we have predicted the general location of functional domains in EF-1 alpha which interact with GTP and tRNA.     

Optimal relationship between average conformational entropy and average energy of interactions between residues for fast protein folding

Based on the known experimental data and using the theoretical modeling of protein folding, we demonstrate that there exists an optimal relationship between the average conformational entropy and the average energy of contacts per residue, that is an entropy capacity, for fast protein folding. Statistical analysis of conformational entropy and the number of contacts per residue for 5829 protein structures from four general structural classes (all-alpha, all-beta, +/-/beta, alpha+beta) demonstrates that each class of proteins has its own class-specific average number of contacts and average conformational entropy per residue. These class-specific features determine the folding rates: a proteins are the fastest folding proteins, then follow beta and alpha+beta proteins, and finally alpha/beta proteins are the slowest ones.     

Selective constraints, amino acid composition, and the rate of protein evolution

What are the major forces governing protein evolution? A common view is that proteins with strong structural and functional requirements evolve more slowly than proteins with weak constraints, because a stringent negative selection pressure limits the number of substitutions. In contrast, Graur claimed that the substitution rate of a protein is mainly determined by its amino acid composition and the changeabilities of amino acids. In this paper, however, we found that the relative changeabilities of amino acids in mammalian proteins are different for transmembranal and nontransmembranal segments, which have very distinct structural requirements. This indicates that the changeability of a given residue is influenced by the structural and functional context. We also reexamined the relationship between substitution rate and amino acid composition. Indeed, the two kinds of segments exhibit contrasting amino acid compositions: transmembranal regions are made up mainly of hydrophobic residues (a total frequency of approximately 60%) and are very poor in polar amino acids (<5%), whereas nontransmembranal segments have frequencies of 30% and 22%, respectively. Interestingly, we found that within a given integral membrane protein, nontransmembranal segments accumulate, on average, twice as many substitutions as transmembranal regions. However, regression analyses showed that the variability in amino acid frequencies among proteins cannot explain more than 30% of the variability in substitution rate for the transmembranal and nontransmembranal data sets. Furthermore, transmembranal and nontransmembranal segments evolving at the same rate in different proteins have different compositions, and the compositions of slowly evolving and rapidly evolving segments of the same type are similar. From these observations, we conclude that the rate of protein evolution is only weakly affected by amino acid composition but is mostly determined by the strength of functional requirements or selective constraints.     

Crystal structure of the phosphoenolpyruvate-binding enzyme I-domain from the Thermoanaerobacter tengcongensis PEP: sugar phosphotransferase system (PTS)

Enzyme I (EI), the first component of the phosphoenolpyruvate (PEP):sugar phosphotransferase system (PTS), consists of an N-terminal protein-binding domain (EIN) and a C-terminal PEP-binding domain (EIC). EI transfers phosphate from PEP by double displacement via a histidine residue on EIN to the general phosphoryl carrier protein HPr. Here, we report the 1.82A crystal structure of the homodimeric EIC domain from Thermoanaerobacter tengcongensis, a saccharolytic eubacterium that grows optimally at 75 degrees C. EIC folds into a (betaalpha)(8) barrel with three large helical insertions between beta2/alpha2, beta3/alpha3 and beta6/alpha6. The large amphipathic dimer interface buries 3750A(2) of accessible surface area per monomer. A comparison with pyruvate phosphate dikinase (PPDK) reveals that the active-site residues in the empty PEP-binding site of EIC and in the liganded PEP-binding site of PPDK have almost identical conformations, pointing to a rigid structure of the active site. In silico models of EIC in complex with the Z and E-isomers of chloro-PEP provide a rational explanation for their difference as substrates and inhibitors of EI. The EIC domain exhibits 54% amino acid sequence identity with Escherichia coli and 60% with Bacillus subtilis EIC, has the same amino acid composition but contains additional salt-bridges and a more complex salt-bridge network than the homology model of E.coli EIC. The easy crystallization of EIC suggests that T.tengcongensis can serve as source for stable homologs of mesophilic proteins that are too labile for crystallization.     

The genes encoding the two carboxyltransferase subunits of Escherichia coli acetyl-CoA carboxylase.

We report characterization of the component proteins and molecular cloning of the genes encoding the two subunits of the carboxyltransferase component of the Escherichia coli acetyl-CoA carboxylase. Peptide mapping of the purified enzyme component indicates that the carboxyltransferase component is a complex of two nonidentical subunits, a 35-kDa alpha subunit and a 33-kDa beta subunit. The alpha subunit gene encodes a protein of 319 residues and is located immediately downstream of the polC gene (min 4.3 of the E. coli genetic map). The deduced amino acid composition, molecular mass, and amino acid sequence match those determined for the purified alpha subunit. Six sequenced internal peptides also match the deduced sequence. The amino-terminal sequence of the beta subunit was found within a previously identified open reading frame of unknown function called dedB and usg (min 50 of the E. coli genetic map) which encodes a protein of 304 residues. Comparative peptide mapping also indicates that the dedB/usg gene encodes the beta subunit. Moreover, the deduced molecular mass and amino acid composition of the dedB/usg-encoded protein closely match those determined for the beta subunit. The deduced amino acid sequences of alpha and beta subunits show marked sequence similarities to the COOH-terminal half and the NH2-terminal halves, respectively, of the rat propionyl-CoA carboxylase, a biotin-dependent carboxylase that catalyzes a similar carboxyltransferase reaction reaction. Several conserved regions which may function as CoA-binding sites are noted.     

The carboxy-terminal domain of Gs alpha is necessary for anchorage of the activated form in the plasma membrane

GTP-binding proteins which participate in signal transduction share a common heterotrimeric structure of the alpha beta gamma-type. In the activated state, the alpha subunit dissociates from the beta gamma complex but remains anchored in the membrane. The alpha subunits of several GTP-binding proteins, such as Go and Gi, are myristoylated at the amino terminus (Buss, J. E., S. M. Mumby, P. J. Casey, A. G. Gilman, and B. M. Sefton. 1987. Proc. Natl. Acad. Sci. USA. 84:7493-7497). This hydrophobic modification is crucial for their membrane attachment. The absence of fatty acid on the alpha subunit of Gs (Gs alpha), the protein involved in adenylate cyclase activation, suggests a different mode of anchorage. To characterize the anchoring domain of Gs alpha, we used a reconstitution model in which posttranslational addition of in vitro-translated Gs alpha to cyc- membranes (obtained from a mutant of S49 cell line which does not express Gs alpha) restores the coupling between the beta-adrenergic receptor and adenylate cyclase. The consequence of deletions generated by proteolytic removal of amino acid sequences or introduced by genetic removal of coding sequences was determined by analyzing membrane association of the proteolyzed or mutated alpha chains. Proteolytic removal of a 9-kD amino-terminal domain or genetic deletion of 28 amino-terminal amino acids did not modify the anchorage of Gs alpha whereas proteolytic removal of a 1-kD carboxyterminal domain abolished membrane interaction. Thus, in contrast to the myristoylated alpha subunits which are tethered through their amino terminus, the carboxy-terminal residues of Gs alpha are required for association of this protein with the membrane.     

The major structural proteins of cod (Gadus morhua) eggshells and protein crosslinking during teleost egg hardening

The highly hydrophobic protein aggregate which constitutes the fish eggshell has for the first time been quantitatively solubilized. This study shows that the nonactivated eggshell from cod is composed primarily of only three protein monomers, designated alpha (74 kDa) beta (54 kDa) and gamma (47 kDa). Protein extraction studies of the eggshells before and after egg activation demonstrate that egg hardening is accompanied by a 10-fold decline in total protein solubility, which is due to nonextraction of the alpha, beta, and gamma chains. When present during the egg activation process monodansylcadaverine (MDC-a fluorescent lysine analog) inhibits eggshell hardening and at the same time becomes covalently incorporated into the eggshell. This MDC incorporation is calcium-dependent and suggests the induction of a perivitelline transglutaminase activity after egg activation. (Transglutaminases catalyze the formation of an amide bond (isopeptide bond) between the gamma-carbonyl group of glutamine and the epsilon-amino group of lysine with release of ammonia. Crosslinks between proteins are generated when the two amino acid residues are located on different proteins.) Protein solubilization studies and NaDodSO4 gel analysis of the eggshell proteins from eggs subjected to 5 mM MDC during egg activation, reveal that when eggshell hardening is blocked by MDC, the three main eggshell proteins remain extractable even after egg activation. Simultaneously we observed a covalent incorporation of MDC into the gamma protein.