Sequence determinants of protein folding rates: positive correlation between contact energy and contact range indicates selection for fast folding

In comparison with intense investigation of the structural determinants of protein folding rates, the sequence features favoring fast folding have received little attention. Here, we investigate this subject using simple models of protein folding and a statistical analysis of the Protein Data Bank (PDB). The mean-field model by Plotkin and coworkers predicts that the folding rate is accelerated by stronger-than-average interactions at short distance along the sequence. We confirmed this prediction using the Finkelstein model of protein folding, which accounts for realistic features of polymer entropy. We then tested this prediction on the PDB. We found that native interactions are strongest at contact range l = 8. However, since short range contacts tend to be exposed and they are frequently formed in misfolded structures, selection for folding stability tends to make them less attractive, that is, stability and kinetics may have contrasting requirements. Using a recently proposed model, we predicted the relationship between contact range and contact energy based on buriedness and contact frequency. Deviations from this prediction induce a positive correlation between contact range and contact energy, that is, short range contacts are stronger than expected, for 2/3 of the proteins. This correlation increases with the absolute contact order (ACO), as expected if proteins that tend to fold slowly due to large ACO are subject to stronger selection for sequence features favoring fast folding. Our results suggest that the selective pressure for fast folding is detectable only for one third of the proteins in the PDB, in particular those with large contact order.     

Homology modeling and assigned functional annotation of an uncharacterized antitoxin protein from Streptomyces xinghaiensis

Streptomyces xinghaiensis is a Gram-positive, aerobic and non-motile bacterium. The bacterial genome is known. Therefore, it is of interest to study the uncharacterized proteins in the genome. An uncharacterized protein (gi|518540893|86 residues) in the genome was selected for a comprehensive computational sequence-structure-function analysis using available data and tools. Subcellular localization of the targeted protein with conserved residues and assigned secondary structures is documented. Sequence homology search against the protein data bank (PDB) and non-redundant GenBank proteins using BLASTp showed different homologous proteins with known antitoxin function. A homology model of the target protein was developed using a known template (PDB ID: 3CTO:A) with 62% sequence similarity in HHpred after assessment using programs PROCHECK and QMEAN6. The predicted active site using CASTp is analyzed for assigned anti-toxin function. This information finds specific utility in annotating the said uncharacterized protein in the bacterial genome.     

Structure prediction of a multi-domain EF-hand Ca2+ binding protein by PROPAINOR

PROPAINOR is a new algorithm developed for ab initio prediction of the 3D structures of proteins using knowledge-based nonparametric multivariate statistical methods. This algorithm is found to be most efficient in terms of computational simplicity and prediction accuracy for single-domain proteins as compared to other ab initio methods. In this paper, we have used the algorithm for the atomic structure prediction of a multi-domain (two-domain) calcium-binding protein, whose solution structure has been deposited in the PDB recently (PDB ID: 1JFK). We have studied the sensitivity of the predicted structure to NMR distance restraints with their incorporation as an additional input. Further, we have compared the predicted structures in both these cases with the NMR derived solution structure reported earlier. We have also validated the refined structure for proper stereochemistry and favorable packing environment with good results and elucidated the role of the central linker. Figure The predicted 3D Structure of EhCaBP with bound Ca²⁺ ions (CaBP-0). In the structure, α-helices are shown in pink and the β-strands in yellow. Ca²⁺ ions are depicted as fluorescent green balls. Some of the residues in the calcium-binding loops are depicted in space-fill representation.      

Benchmarks for flexible and rigid transcription factor-DNA docking

Background

Although structural domains in proteins (SDs) are important, half of the regions in the human proteome are currently left with no SD assignments. These unassigned regions consist not only of novel SDs, but also of intrinsically disordered (ID) regions since proteins, especially those in eukaryotes, generally contain a significant fraction of ID regions. As ID regions can be inferred from amino acid sequences, a method that combines SD and ID region assignments can determine the fractions of SDs and ID regions in any proteome.

Results

In contrast to other available ID prediction programs that merely identify likely ID regions, the DICHOT system we previously developed classifies the entire protein sequence into SDs and ID regions. Application of DICHOT to the human proteome revealed that residue-wise ID regions constitute 35%, SDs with similarity to PDB structures comprise 52%, while SDs with no similarity to PDB structures account for the remaining 13%. The last group consists of novel structural domains, termed cryptic domains, which serve as good targets of structural genomics. The DICHOT method applied to the proteomes of other model organisms indicated that eukaryotes generally have high ID contents, while prokaryotes do not. In human proteins, ID contents differ among subcellular localizations: nuclear proteins had the highest residue-wise ID fraction (47%), while mitochondrial proteins exhibited the lowest (13%). Phosphorylation and O-linked glycosylation sites were found to be located preferentially in ID regions. As O-linked glycans are attached to residues in the extracellular regions of proteins, the modification is likely to protect the ID regions from proteolytic cleavage in the extracellular environment. Alternative splicing events tend to occur more frequently in ID regions. We interpret this as evidence that natural selection is operating at the protein level in alternative splicing.

Conclusions

We classified entire regions of proteins into the two categories, SDs and ID regions and thereby obtained various kinds of complete genome-wide statistics. The results of the present study are important basic information for understanding protein structural architectures and have been made publicly available at http://spock.genes.nig.ac.jp/~genome/DICHOT.     

Aromatic claw: A new fold with high aromatic content that evades structural prediction

We determined the NMR structure of a highly aromatic (13%) protein of unknown function, Aq1974 from Aquifex aeolicus (PDB ID: 5SYQ). The unusual sequence of this protein has a tryptophan content five times the normal (six tryptophan residues of 114 or 5.2% while the average tryptophan content is 1.0%) with the tryptophans occurring in a WXW motif. It has no detectable sequence homology with known protein structures. Although its NMR spectrum suggested that the protein was rich in β‐sheet, upon resonance assignment and solution structure determination, the protein was found to be primarily α‐helical with a small two‐stranded β‐sheet with a novel fold that we have termed an Aromatic Claw. As this fold was previously unknown and the sequence unique, we submitted the sequence to CASP10 as a target for blind structural prediction. At the end of the competition, the sequence was classified a hard template based model; the structural relationship between the template and the experimental structure was small and the predictions all failed to predict the structure. CSRosetta was found to predict the secondary structure and its packing; however, it was found that there was little correlation between CSRosetta score and the RMSD between the CSRosetta structure and the NMR determined one. This work demonstrates that even in relatively small proteins, we do not yet have the capacity to accurately predict the fold for all primary sequences. The experimental discovery of new folds helps guide the improvement of structural prediction methods.     

Prospects for ab initio protein structural genomics

We present the results of a large-scale testing of the ROSETTA method for ab initio protein structure prediction. Models were generated for two independently generated lists of small proteins (up to 150 amino acid residues), and the results were evaluated using traditional rmsd based measures and a novel measure based on the structure-based comparison of the models to the structures in the PDB using DALI. For 111 of 136 all alpha and alpha/beta proteins 50 to 150 residues in length, the method produced at least one model within 7 A rmsd of the native structure in 1000 attempts. For 60 of these proteins, the closest structure match in the PDB to at least one of the ten most frequently generated conformations was found to be structurally related (four standard deviations above background) to the native protein. These results suggest that ab initio structure prediction approaches may soon be useful for generating low resolution models and identifying distantly related proteins with similar structures and perhaps functions for these classes of proteins on the genome scale.     

Functional classification of protein 3D structures from predicted local interaction sites

A new approach to the functional classification of protein 3D structures is described with application to some examples from structural genomics. This approach is based on functional site prediction with THEMATICS and POOL. THEMATICS employs calculated electrostatic potentials of the query structure. POOL is a machine learning method that utilizes THEMATICS features and has been shown to predict accurate, precise, highly localized interaction sites. Extension to the functional classification of structural genomics proteins is now described. Predicted functionally important residues are structurally aligned with those of proteins with previously characterized biochemical functions. A 3D structure match at the predicted local functional site then serves as a more reliable predictor of biochemical function than an overall structure match. Annotation is confirmed for a structural genomics protein with the ribulose phosphate binding barrel (RPBB) fold. A putative glucoamylase from Bacteroides fragilis (PDB ID 3eu8) is shown to be in fact probably not a glucoamylase. Finally a structural genomics protein from Streptomyces coelicolor annotated as an enoyl-CoA hydratase (PDB ID 3g64) is shown to be misannotated. Its predicted active site does not match the well-characterized enoyl-CoA hydratases of similar structure but rather bears closer resemblance to those of a dehalogenase with similar fold.     

Structure of glutathione S-transferase of the filarial parasite Wuchereria bancrofti: a target for drug development against adult worm

A three dimensional structural model of Glutathione-S-transferase (GST) of the lymphatic filarial parasite Wuchereria bancrofti (wb) was constructed by homology modeling. The three dimensional X-ray crystal structure of porcine -class GST with PDB ID: 2gsr-A chain protein with 42% sequential and functional homology was used as the template. The model of wbGST built by MODELLER6v2 was analyzed by the PROCHECK programs. Ramachandran plot analysis showed that 93.5% of the residues are in the core region followed by 5.4 and 1.1% residues in the allowed and generously allowed regions, respectively. None of the non-glycine residues is in disallowed regions. The PROSA II z-score and the energy graph for the final model further confirmed the quality of the modeled structure. The computationally modeled three-dimensional (3D) structure of wbGST has been submitted to the Protein Data Bank (PDB) (PDB ID: 1SFM and RCSB ID: RCSB021668). 1SFM was used for docking with GST inhibitors by Hex4.2 macromolecular docking using spherical polar Fourier correlations.Figure: A three-dimensional (3D) structure of Glutathione-S-transferase (GST) of the lymphatic filarial parasite Wuchereria bancrofti (wb) was constructed by homology modeling. This modeled 3D structure of wbGST has been submitted to the Protein Data Bank (PDB) (PDB ID: 1SFM and RCSB ID: RCSB021668).     

An accurate feature-based method for identifying DNA-binding residues on protein surfaces

Proteins that interact with DNA play vital roles in all mechanisms of gene expression and regulation. In order to understand these activities, it is crucial to analyze and identify DNA-binding residues on DNA-binding protein surfaces. Here, we proposed two novel features B-factor and packing density in combination with several conventional features to characterize the DNA-binding residues in a well-constructed representative dataset of 119 protein-DNA complexes from the Protein Data Bank (PDB). Based on the selected features, a prediction model for DNA-binding residues was constructed using support vector machine (SVM). The predictor was evaluated using a 5-fold cross validation on above dataset of 123 DNA-binding proteins. Moreover, two independent datasets of 83 DNA-bound protein structures and their corresponding DNA-free forms were compiled. The B-factor and packing density features were statistically analyzed on these 83 pairs of holo-apo proteins structures. Finally, we developed the SVM model to accurately predict DNA-binding residues on protein surface, given the DNA-free structure of a protein. Results showed here indicate that our method represents a significant improvement of previously existing approaches such as DISPLAR. The observation suggests that our method will be useful in studying protein-DNA interactions to guide consequent works such as site-directed mutagenesis and protein-DNA docking.     

Phylogenetic and modelling analysis of purple acid phosphatase 18 (SiPAP18) from Setaria italica

Purple acid phosphatases belong to metallo-phosphatase family. Intracellular phosphatases are crucial for phosphorus (P) distribution in the cell and are highly induced in phosphorus-deprived conditions in the soil. Disparate PAP isoforms exist within discrete subcellular compartments in Setaria italica and their expression in P deprived conditions fosters phosphorus amelioration. We isolated the SiPAP18 gene and developed the homology SiPAP18 protein model based on the crystal structure of the Kidney bean PvPAP (PDB ID: 2QFP) as template (sequence similarity 42.7%) using Modeller 9.12 with adequate validation. Structure model analysis shows the significance of five conserved signatures with seven metal-paired amino acid residues during P-deprivation induced phosphorus amelioration.     

Predicting the order in which contacts are broken during single molecule protein stretching experiments

We combine two methods to enable the prediction of the order in which contacts are broken under external stretching forces in single molecule experiments. These two methods are Gō-like models and elastic network models. The Gō-like models have shown remarkable success in representing many aspects of protein behavior, including the reproduction of experimental data obtained from atomic force microscopy. The simple elastic network models are often used successfully to predict the fluctuations of residues around their mean positions, comparing favorably with the experimentally measured crystallographic B-factors. The behavior of biomolecules under external forces has been demonstrated to depend principally on their elastic properties and the overall shape of their structure. We have studied in detail the muscle protein titin and green fluorescent protein and tested for ten other proteins. First, we stretch the proteins computationally by performing stochastic dynamics simulations with the Gō-like model. We obtain the force-displacement curves and unfolding scenarios of possible mechanical unfolding. We then use the elastic network model to calculate temperature factors (B-factors) and compare the slowest modes of motion for the stretched proteins and compare them with the predicted order of breaking contacts between residues in the Gō-like model. Our results show that a simple Gaussian network model is able to predict contacts that break in the next time stage of stretching. Additionally, we have found that the contact disruption is strictly correlated with the highest force exerted by the backbone on these residues. Our prediction of bond-breaking agrees well with the unfolding scenario obtained with the Gō-like model. We anticipate that this method will be a useful new tool for interpreting stretching experiments.     

Crystal structure of a consensus-designed ankyrin repeat protein: implications for stability

Consensus-designed ankyrin repeat (AR) proteins are thermodynamically very stable. The structural analysis of the designed AR protein E3_5 revealed that this stability is due to a regular fold with highly conserved structural motifs and H-bonding networks. However, the designed AR protein E3_19 exhibits a significantly lower stability than E3_5 (9.6 vs. 14.8 kcal/mol), despite 88% sequence identity. To investigate the structural correlations of this stability difference between E3_5 and E3_19, we determined the crystal structure of E3_19 at 1.9 A resolution. E3_19 as well has a regular AR domain fold with the characteristic H-bonding patterns. All structural features of the E3_5 and E3_19 molecules appear to be virtually identical (RMSD(Calpha) approximately 0.7 A). However, clear differences are observed in the surface charge distribution of the two AR proteins. E3_19 features clusters of charged residues and more exposed hydrophobic residues than E3_5. The atomic coordinates of E3_19 have been deposited in the Protein Data Bank. PDB ID: 2BKG.     

Selection and analyses of variants of a designed protein suggest importance of hydrophobicity of partially buried sidechains for protein stability at high temperatures

Computationally designed proteins of high stability provide specimen in addition to natural proteins for the study of sequence‐structure stability relationships at the very high end of protein stability spectrum. The melting temperature of E_1r26, a protein we previously designed using the A Backbone‐based Amino aCid Usage Survey (ABACUS) sequence design program, is above 110 °C, more than 50 °C higher than that of the natural thioredoxin protein whose backbone (PDB ID 1R26 ) has been used as the design target. Using an experimental selection approach, we obtained variants of E_1r26 that remain folded but are of reduced stability, including one whose unfolding temperature and denaturing guanidine concentration are similar to those of 1r26. The mutant unfolds with a certain degree of cooperativity. Its structure solved by X‐ray crystallography agrees with that of 1r26 by a root mean square deviation of 1.3 Å, adding supports to the accuracy of the ABACUS method. Analyses of intermediate mutants indicate that the substitution of two partially buried hydrophobic residues (isoleucine and leucine) by polar residues (threonine and serine, respectively) are responsible for the dramatic change in the unfolding temperature. It is suggested that the effects of mutations located in rigid secondary structure regions, but not those in loops, may be well predicted through ABACUS mutation energy analysis. The results also suggest that hydrophobic effects involving intermediately buried sidechains can be critically important for protein stability at high temperatures.     

Intrinsic disorder in the Protein Data Bank

The Protein Data Bank (PDB) is the preeminent source of protein structural information. PDB contains over 32,500 experimentally determined 3-D structures solved using X-ray crystallography or nuclear magnetic resonance spectroscopy. Intrinsically disordered regions fail to form a fixed 3-D structure under physiological conditions. In this study, we compare the amino-acid sequences of proteins whose structures are determined by X-ray crystallography with the corresponding sequences from the Swiss-Prot database. The analyzed dataset includes 16,370 structures, which represent 18,101 PDB chains and 5,434 different proteins from 910 different organisms (2,793 eukaryotic, 2,109 bacterial, 288 viral, and 244 archaeal). In this dataset, on average, each Swiss-Prot protein is represented by 7 PDB chains with 76% of the crystallized regions being represented by more than one structure. Intriguingly, the complete sequences of only approximately 7% of proteins are observed in the corresponding PDB structures, and only approximately 25% of the total dataset have >95% of their lengths observed in the corresponding PDB structures. This suggests that the vast majority of PDB proteins is shorter than their corresponding Swiss-Prot sequences and/or contain numerous residues, which are not observed in maps of electron density. To determine the prevalence of disordered regions in PDB, the residues in the Swiss-Prot sequences were grouped into four general categories, "Observed" (which correspond to structured regions), "Not observed" (regions with missing electron density, potentially disordered), "Uncharacterized," and "Ambiguous," depending on their appearance in the corresponding PDB entries. This non-redundant set of residues can be viewed as a 'fragment' or empirical domain database that contains a set of experimentally determined structured regions or domains and a set of experimentally verified disordered regions or domains. We studied the propensities and properties of residues in these four categories and analyzed their relations to the predictions of disorder using several algorithms. "Non-observed," "Ambiguous," and "Uncharacterized" regions were shown to possess the amino acid compositional biases typical of intrinsically disordered proteins. The application of four different disorder predictors (PONDR(R) VL-XT, VL3-BA, VSL1P, and IUPred) revealed that the vast majority of residues in the "Observed" dataset are ordered, and that the "Not observed" regions are mostly disordered. The "Uncharacterized" regions possess some tendency toward order, whereas the predictions for the short "Ambiguous" regions are really ambiguous. Long "Ambiguous" regions (>70 amino acid residues) are mostly predicted to be ordered, suggesting that they are likely to be "wobbly" domains. Overall, we showed that completely ordered proteins are not highly abundant in PDB and many PDB sequences have disordered regions. In fact, in the analyzed dataset approximately 10% of the PDB proteins contain regions of consecutive missing or ambiguous residues longer than 30 amino-acids and approximately 40% of the proteins possess short regions (> or =10 and < 30 amino-acid long) of missing and ambiguous residues.     

Search for glucose/galactose-binding proteins in newly discovered protein sequences using molecular modeling techniques and structural analysis

Sugar moieties serve as specificity markers in a wide variety of biochemical functions, and periplasmic glucose/galactose-binding proteins (GGBPs) serve as the primary receptors for transport and chemotaxis. Recently, complete genome sequencing projects have revealed many open reading frames for such receptors. On the basis of the homology search with the known x-ray structures (PDB ID: 3GBP/1GCA) of a periplasmic receptor protein from Salmonella typhimurium, we selected four putative proteins with amino acid identities between 30 and 48% for the prediction of three-dimensional (3D) structures of the proteins as well as their complexes with glucose and galactose. We could successfully identify the key residues involved in coordination with calcium ion spanning over two loop structures. We calculated the ligand-binding affinities and hydrogen bonding patterns of the modeled structures and compared with those of the x-ray structures. The calculation of free energies of binding of the modeled structures to glucose and galactose in the presence of water suggested that two of four putative proteins can form complexes with dissociation constants in the micromolar range (1-10 microM). Electrostatic potentials on the surfaces near the sugar and calcium-binding sites of the modeled structures were predominately negative as found in case of the x-ray structure. Taken together, our results suggest that the products of two newly discovered genes would serve as receptors for the transport of glucose and galactose.     

Inaccurate secondary structure predictions often indicate protein fold switching

Although most proteins conform to the classical one‐structure/one‐function paradigm, an increasing number of proteins with dual structures and functions have been discovered. In response to cellular stimuli, such proteins undergo structural changes sufficiently dramatic to remodel even their secondary structures and domain organization. This “fold‐switching” capability fosters protein multi‐functionality, enabling cells to establish tight control over various biochemical processes. Accurate predictions of fold‐switching proteins could both suggest underlying mechanisms for uncharacterized biological processes and reveal potential drug targets. Recently, we developed a prediction method for fold‐switching proteins using structure‐based thermodynamic calculations and discrepancies between predicted and experimentally determined protein secondary structure (Porter and Looger, Proc Natl Acad Sci U S A 2018; 115:5968–5973). Here we seek to leverage the negative information found in these secondary structure prediction discrepancies. To do this, we quantified secondary structure prediction accuracies of 192 known fold‐switching regions (FSRs) within solved protein structures found in the Protein Data Bank (PDB). We find that the secondary structure prediction accuracies for these FSRs vary widely. Inaccurate secondary structure predictions are strongly associated with fold‐switching proteins compared to equally long segments of non‐fold‐switching proteins selected at random. These inaccurate predictions are enriched in helix‐to‐strand and strand‐to‐coil discrepancies. Finally, we find that most proteins with inaccurate secondary structure predictions are underrepresented in the PDB compared with their alternatively folded cognates, suggesting that unequal representation of fold‐switching conformers within the PDB could be an important cause of inaccurate secondary structure predictions. These results demonstrate that inconsistent secondary structure predictions can serve as a useful preliminary marker of fold switching.     

Exploring the conformational space of protein loops using a mean field technique with MOLS sampling

We have recently developed a computational technique that uses mutually orthogonal Latin square sampling to explore the conformational space of oligopeptides in an exhaustive manner. In this article, we report its use to analyze the conformational spaces of 120 protein loop sequences in proteins, culled from the PDB, having the length ranging from 5 to 10 residues. The force field used did not have any information regarding the sequences or structures that flanked the loop. The results of the analyses show that the native structure of the loop, as found in the PDB falls at one of the low energy points in the conformational landscape of the sequences. Thus, a large portion of the structural determinants of the loop may be considered intrinsic to the sequence, regardless of either adjacent sequences or structures, or the interactions that the atoms of the loop make with other residues in the protein or in neighboring proteins.     

Using increment of diversity to predict mitochondrial proteins of malaria parasite: integrating pseudo-amino acid composition and structural alphabet

Due to the complexity of Plasmodium falciparum (PF) genome, predicting mitochondrial proteins of PF is more difficult than other species. In this study, using the n-peptide composition of reduced amino acid alphabet (RAAA) obtained from structural alphabet named Protein Blocks as feature parameter, the increment of diversity (ID) is firstly developed to predict mitochondrial proteins. By choosing the 1-peptide compositions on the N-terminal regions with 20 residues as the only input vector, the prediction performance achieves 86.86% accuracy with 0.69 Mathew’s correlation coefficient (MCC) by the jackknife test. Moreover, by combining with the hydropathy distribution along protein sequence and several reduced amino acid alphabets, we achieved maximum MCC 0.82 with accuracy 92% in the jackknife test by using the developed ID model. When evaluating on an independent dataset our method performs better than existing methods. The results indicate that the ID is a simple and efficient prediction method for mitochondrial proteins of malaria parasite.     

Folding of Top7 in unbiased all‐atom Monte Carlo simulations

For computational studies of protein folding, proteins with both helical and β‐sheet secondary structure elements are very challenging, as they expose subtle biases of the physical models. Here, we present reproducible folding of a 92 residue α/β protein (residues 3–94 of Top7, PDB ID: 1QYS) in computer simulations starting from random initial conformations using a transferable physical model which has been previously shown to describe the folding and thermodynamic properties of about 20 other smaller proteins of different folds. Top7 is a de novo designed protein with two α‐helices and a five stranded β‐sheet. Experimentally, it is known to be unusually stable for its size, and its folding transition distinctly deviates from the two‐state behavior commonly seen in natural single domain proteins. In our all‐atom implicit solvent parallel tempering Monte Carlo simulations, Top7 shows a rapid transition to a group of states with high native‐like secondary structure, and a much slower subsequent transition to the native state with a root mean square deviation of about 3.5 Å from the experimentally determined structure. Consistent with experiments, we find Top7 to be thermally extremely stable, although the simulations also find a large number of very stable non‐native states with high native‐like secondary structure. Proteins 2013; 81:1446–1456. © 2013 Wiley Periodicals, Inc.     

Large‐scale analysis of intrinsic disorder flavors and associated functions in the protein sequence universe

Intrinsic disorder (ID) in proteins has been extensively described for the last decade; a large‐scale classification of ID in proteins is mostly missing. Here, we provide an extensive analysis of ID in the protein universe on the UniProt database derived from sequence‐based predictions in MobiDB. Almost half the sequences contain an ID region of at least five residues. About 9% of proteins have a long ID region of over 20 residues which are more abundant in Eukaryotic organisms and most frequently cover less than 20% of the sequence. A small subset of about 67,000 (out of over 80 million) proteins is fully disordered and mostly found in Viruses. Most proteins have only one ID, with short ID evenly distributed along the sequence and long ID overrepresented in the center. The charged residue composition of Das and Pappu was used to classify ID proteins by structural propensities and corresponding functional enrichment. Swollen Coils seem to be used mainly as structural components and in biosynthesis in both Prokaryotes and Eukaryotes. In Bacteria, they are confined in the nucleoid and in Viruses provide DNA binding function. Coils & Hairpins seem to be specialized in ribosome binding and methylation activities. Globules & Tadpoles bind antigens in Eukaryotes but are involved in killing other organisms and cytolysis in Bacteria. The Undefined class is used by Bacteria to bind toxic substances and mediate transport and movement between and within organisms in Viruses. Fully disordered proteins behave similarly, but are enriched for glycine residues and extracellular structures.