In-depth analysis of amino acid and nucleotide sequences of Hsp60: How conserved is this protein?

Chaperonin Hsp60, as a protein found in all organisms, is of great interest in medicine, since it is present in many tissues and can be used both as a drug and as an object of targeted therapy. Hence, Hsp60 deserves a fundamental comparative analysis to assess its evolutionary characteristics. It was found that the percent identity of Hsp60 amino acid sequences both within and between phyla was not high enough to identify Hsp60s as highly conserved proteins. However, their ATP binding sites are largely conserved. The amino acid composition of Hsp60s remained relatively constant. At the same time, the analysis of the nucleotide sequences showed that GC content in the Hsp60 genes was comparable to or greater than the genomic values, which may indicate a high resistance to mutations due to tight control of the nucleotide composition by DNA repair systems. Natural selection plays a dominant role in the evolution of Hsp60 genes. The degree of mutational pressure affecting the Hsp60 genes is quite low, and its direction does not depend on taxonomy. Interestingly, for the Hsp60 genes from Chordata, Arthropoda, and Proteobacteria the exact direction of mutational pressure could not be determined. However, upon further division into classes, it was found that the direction of the mutational pressure for Hsp60 genes from Fish differs from that for other chordates. The direction of the mutational pressure affects the synonymous codon usage bias. The number of high and low represented codons increases with increasing GC content, which can improve codon usage. Special server has been created for bioinformatics analysis of Hsp60: http://oka.protres.ru:4202/.

ComSin: database of protein structures in bound (complex) and unbound (single) states in relation to their intrinsic disorder.

Most of the proteins in a cell assemble into complexes to carry out their function. In this work, we have created a new database (named ComSin) of protein structures in bound (complex) and unbound (single) states to provide a researcher with exhaustive information on structures of the same or homologous proteins in bound and unbound states. From the complete Protein Data Bank (PDB), we selected 24 910 pairs of protein structures in bound and unbound states, and identified regions of intrinsic disorder. For 2448 pairs, the proteins in bound and unbound states are identical, while 7129 pairs have sequence identity 90% or larger. The developed server enables one to search for proteins in bound and unbound states with several options including sequence similarity between the corresponding proteins in bound and unbound states, and validation of interaction interfaces of protein complexes. Besides that, through our web server, one can obtain necessary information for studying disorder-to-order and order-to-disorder transitions upon complex formation, and analyze structural differences between proteins in bound and unbound states. The database is available at http://antares.protres.ru/comsin/.

FoldAmyloid: a method of prediction of amyloidogenic regions from protein sequence.

MOTIVATION: Amyloidogenic regions in polypeptide chains are very important because such regions are responsible for amyloid formation and aggregation. It is useful to be able to predict positions of amyloidogenic regions in protein chains. RESULTS: Two characteristics (expected probability of hydrogen bonds formation and expected packing density of residues) have been introduced by us to detect amyloidogenic regions in a protein sequence. We demonstrate that regions with high expected probability of the formation of backbone-backbone hydrogen bonds as well as regions with high expected packing density are mostly responsible for the formation of amyloid fibrils. Our method (FoldAmyloid) has been tested on a dataset of 407 peptides (144 amyloidogenic and 263 non-amyloidogenic peptides) and has shown good performance in predicting a peptide status: amyloidogenic or non-amyloidogenic. The prediction based on the expected packing density classified correctly 75% of amyloidogenic peptides and 74% of non-amyloidogenic ones. Two variants (averaging by donors and by acceptors) of prediction based on the probability of formation of backbone-backbone hydrogen bonds gave a comparable efficiency. With a hybrid-scale constructed by merging the above three scales, our method is correct for 80% of amyloidogenic peptides and for 72% of non-amyloidogenic ones. Prediction of amyloidogenic regions in proteins where positions of amyloidogenic regions are known from experimental data has also been done. In the proteins, our method correctly finds 10 out of 11 amyloidogenic regions. AVAILABILITY: The FoldAmyloid server is available at http://antares.protres.ru/fold-amyloid/.

The Ising model for prediction of disordered residues from protein sequence alone.

Intrinsically disordered regions serve as molecular recognition elements, which play an important role in the control of many cellular processes and signaling pathways. It is useful to be able to predict positions of disordered residues and disordered regions in protein chains using protein sequence alone. A new method (IsUnstruct) based on the Ising model for prediction of disordered residues from protein sequence alone has been developed. According to this model, each residue can be in one of two states: ordered or disordered. The model is an approximation of the Ising model in which the interaction term between neighbors has been replaced by a penalty for changing between states (the energy of border). The IsUnstruct has been compared with other available methods and found to perform well. The method correctly finds 77% of disordered residues as well as 87% of ordered residues in the CASP8 database, and 72% of disordered residues as well as 85% of ordered residues in the DisProt database.

Library of disordered patterns in 3D protein structures.

Intrinsically disordered regions serve as molecular recognition elements, which play an important role in the control of many cellular processes and signaling pathways. It is useful to be able to predict positions of disordered regions in protein chains. The statistical analysis of disordered residues was done considering 34,464 unique protein chains taken from the PDB database. In this database, 4.95% of residues are disordered (i.e. invisible in X-ray structures). The statistics were obtained separately for the N- and C-termini as well as for the central part of the protein chain. It has been shown that frequencies of occurrence of disordered residues of 20 types at the termini of protein chains differ from the ones in the middle part of the protein chain. Our systematic analysis of disordered regions in PDB revealed 109 disordered patterns of different lengths. Each of them has disordered occurrences in at least five protein chains with identity less than 20%. The vast majority of all occurrences of each disordered pattern are disordered. This allows one to use the library of disordered patterns for predicting the status of a residue of a given protein to be ordered or disordered. We analyzed the occurrence of the selected patterns in three eukaryotic and three bacterial proteomes.

Different packing of external residues can explain differences in the thermostability of proteins from thermophilic and mesophilic organisms.

MOTIVATION: Understanding the basis of protein stability in thermophilic organisms raises a general question: what structural properties of proteins are responsible for the higher thermostability of proteins from thermophilic organisms compared to proteins from mesophilic organisms? RESULTS: A unique database of 373 structurally well-aligned protein pairs from thermophilic and mesophilic organisms is constructed. Comparison of proteins from thermophilic and mesophilic organisms has shown that the external, water-accessible residues of the first group are more closely packed than those of the second. Packing of interior parts of proteins (residues inaccessible to water molecules) is the same in both cases. The analysis of amino acid composition of external residues of proteins from thermophilic organisms revealed an increased fraction of such amino acids as Lys, Arg and Glu, and a decreased fraction of Ala, Asp, Asn, Gln, Thr, Ser and His. Our theoretical investigation of folding/unfolding behavior confirms the experimental observations that the interactions that differ in thermophilic and mesophilic proteins form only after the passing of the transition state during folding. Thus, different packing of external residues can explain differences in thermostability of proteins from thermophilic and mesophilic organisms. AVAILABILITY: The database of 373 structurally well-aligned protein pairs is available at http://phys.protres.ru/resources/termo_meso_base.html. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Prediction of number and position of domain boundaries in multi-domain proteins by use of amino acid sequence alone.

Prediction of protein domain boundaries is an important step for the prediction of three-dimensional structure. The simple method PDP has been elaborated for prediction of the number and position of domain boundaries in multi-domain proteins by use of amino acid sequence alone. The method uses an optimized scale based on the statistics of appearance of amino acid residues at domain boundaries. Our method demonstrates promising results in comparison to other methods that do not use homologous sequences. From the database of proteins that are targets from CASP6 (Critical Assessment of Techniques for Protein Structure Prediction) our program correctly assigned the number of domains for approximately 80% of one domain proteins and approximately 50% for two-domain proteins. Our method offers three main advantages: it is very simple, it is fast, and it uses a minimal number of parameters in comparison with other methods.

FoldUnfold: web server for the prediction of disordered regions in protein chain.

UNLABELLED: Identification of disordered regions in polypeptide chains is very important because such regions are essential for protein function. A new parameter, namely mean packing density of residues has been introduced to detect disordered regions in a protein sequence. We have demonstrated that regions with weak expected packing density would be responsible for the appearance of disordered regions. Our method (FoldUnfold) has been tested on datasets of globular proteins (559 proteins) and long disordered protein segments (129 proteins) and showed improved performance over some other widely used methods, such as DISOPRED, PONDR VL3H, IUPred and GlobPlot. AVAILABILITY: The FoldUnfold server is available for users at http://skuld.protres.ru/~mlobanov/ogu/ogu.cgi. There is a link to our server through the web site of DisProt (http://www.disprot.org/predictors.php).

Is it possible to predict amyloidogenic regions from sequence alone?

Identification of potentially amyloidogenic regions in polypeptide chains is very important because the amyloid fibril formation can be induced in most normal proteins. In our work we suggest a new method to detect amyloidogenic regions in protein sequence. It is based on the assumption that packing is tight inside an amyloid and therefore regions which could potentially pack well would have a tendency to form amyloids. This means that the regions with strong expected packing of residues would be responsible for the amyloid formation. We use this property to identify potentially amyloidogenic regions in proteins basing on their amino acid sequences only. Our predictions are consistent with known disease-related amyloidogenic regions for 8 of 11 amyloid-forming proteins and peptides in which the positions of amyloidogenic regions have been revealed experimentally. Predictions of the regions which are responsible for the formation of amyloid fibrils in proteins unrelated to disease have been also done.

Non-random distribution of homo-repeats: links with biological functions and human diseases.

The biological function of multiple repetitions of single amino acids, or homo-repeats, is largely unknown, but their occurrence in proteins has been associated with more than 20 hereditary diseases. Analysing 122 bacterial and eukaryotic genomes, we observed that the number of proteins containing homo-repeats is significantly larger than expected from theoretical estimates. Analysis of statistical significance indicates that the minimal size of homo-repeats varies with amino acid type and proteome. In an attempt to characterize proteins harbouring long homo-repeats, we found that those containing polar or small amino acids S, P, H, E, D, K, Q and N are enriched in structural disorder as well as protein- and RNA-interactions. We observed that E, S, Q, G, L, P, D, A and H homo-repeats are strongly linked with occurrence in human diseases. Moreover, S, E, P, A, Q, D and T homo-repeats are significantly enriched in neuronal proteins associated with autism and other disorders. We release a webserver for further exploration of homo-repeats occurrence in human pathology at http://bioinfo.protres.ru/hradis/.

Comparison of X-ray and NMR structures: is there a systematic difference in residue contacts between X-ray- and NMR-resolved protein structures?

We have compared structures of 78 proteins determined by both NMR and X-ray methods. It is shown that X-ray and NMR structures of the same protein have more differences than various X-ray structures obtained for the protein, and even more than various NMR structures of the protein. X-ray and NMR structures of 18 of these 78 proteins have obvious large-scale structural differences that seem to reflect a difference of crystal and solution structures. The other 60 pairs of structures have only small-scale differences comparable with differences between various X-ray or various NMR structures of a protein; we have analyzed these structures more attentively. One of the main differences between NMR and X-ray structures concerns the number of contacts per residue: (1) NMR structures presented in PDB have more contacts than X-ray structures at distances below 3.0 A and 4.5-6.5 A, and fewer contacts at distances of 3.0-4.5 A and 6.5-8.0 A; (2) this difference in the number of contacts is greater for internal residues than for external ones, and it is larger for beta-containing proteins than for all-alpha proteins. Another significant difference is that the main-chain hydrogen bonds identified in X-ray and NMR structures often differ. Their correlation is 69% only. However, analogous difference is found for refined and rerefined NMR structures, allowing us to suggest that the observed difference in interresidue contacts of X-ray and NMR structures of the same proteins is due mainly to a difference in mathematical treatment of experimental results.

To be folded or to be unfolded?

The lack of ordered structure in "natively unfolded" proteins raises a general question: Are there intrinsic properties of amino acid residues that are responsible for the absence of fixed structure at physiological conditions? In this article, we demonstrate that the competence of a protein to be folded or to be unfolded may be determined by the property of amino acid residues to form a sufficient number of contacts in a globular state. The expected average number of contacts per residue calculated from the amino acid sequence alone (using the average number of contacts for 20 amino acid residues in globular proteins) can be used as one of the simple indicators of natively unfolded proteins. The prediction accuracy for the sets of 80 folded and 90 natively unfolded proteins reaches 89% if the expected average number of contacts is used as a parameter and 83% in the case of hydrophobicity. An optimal set of artificial parameters for 20 amino acid residues obtained by Monte Carlo algorithm to maximally separate the sets of 90 natively unfolded and 80 folded proteins demonstrates the upper limit for prediction accuracy, which is 95%.

An N-terminal, 830 residues intrinsically disordered region of the cytoskeleton-regulatory protein supervillin contains Myosin II- and F-actin-binding sites.

Supervillin, the largest member of the villin/gelsolin family, is a cytoskeleton regulating, peripheral membrane protein. Supervillin increases cell motility and promotes invasive activity in tumors. Major cytoskeletal interactors, including filamentous actin and myosin II, bind within the unique supervillin amino terminus, amino acids 1-830. The structural features of this key region of the supervillin polypeptide are unknown. Here, we utilize circular dichroism and bioinformatics sequence analysis to demonstrate that the N-terminal part of supervillin forms an extended intrinsically disordered region (IDR). Our combined data indicate that the N-terminus of human and bovine supervillin sequences (positions 1-830) represents an IDR, which is the largest IDR known to date in the villin/gelsolin family. Moreover, this result suggests a potentially novel mechanism of regulation of myosin II and F-actin via the intrinsically disordered N-terminal region of hub protein supervillin.

Disordered patterns in clustered Protein Data Bank and in eukaryotic and bacterial proteomes.

We have constructed the clustered Protein Data Bank and obtained clusters of chains of different identity inside each cluster, http://bioinfo.protres.ru/st_pdb/. We have compiled the largest database of disordered patterns (141) from the clustered PDB where identity between chains inside of a cluster is larger or equal to 75% (version of 28 June 2010) by using simple rules of selection. The results of these analyses would help to further our understanding of the physicochemical and structural determinants of intrinsically disordered regions that serve as molecular recognition elements. We have analyzed the occurrence of the selected patterns in 97 eukaryotic and in 26 bacterial proteomes. The disordered patterns appear more often in eukaryotic than in bacterial proteomes. The matrix of correlation coefficients between numbers of proteins where a disordered pattern from the library of 141 disordered patterns appears at least once in 9 kingdoms of eukaryota and 5 phyla of bacteria have been calculated. As a rule, the correlation coefficients are higher inside of the considered kingdom than between them. The patterns with the frequent occurrence in proteomes have low complexity (PPPPP, GGGGG, EEEED, HHHH, KKKKK, SSTSS, QQQQQP), and the type of patterns vary across different proteomes, http://bioinfo.protres.ru/fp/search_new_pattern.html.

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.