Computational analysis of position-dependent disorder content in DisProt database

A bioinformatics analysis of disorder content of proteins from the DisProt database has been performed with respect to position of disordered residues.Each protein chain was divided into three parts:N-and C-terminal parts with each containing 30 amino acid(AA) residues and the middle region containing the remaining AA residues.The results show that in terminal parts,the percentage of disordered AA residues is higher than that of all AA residues(17% of disordered AA residues and 11% of all).We analyzed the percentage of disorder for each of 20 AA residues in the three parts of proteins with respect to their hydropathy and molecular weight.For each AA,the percentage of disorder in the middle part is lower than that in terminal parts which is comparable at the two termini.A new scale of AAs has been introduced according to their disorder content in the middle part of proteins:CIFWMLYHRNVTAGQDSKEP.All big hydrophobic AAs are less frequently disordered,while almost all small hydrophilic AAs are more frequently disordered.The results obtained may be useful for construction and improving predictors for protein disorder.     

Sequence complexity of disordered protein

Intrinsic disorder refers to segments or to whole proteins that fail to self-fold into fixed 3D structure, with such disorder sometimes existing in the native state. Here we report data on the relationships among intrinsic disorder, sequence complexity as measured by Shannon's entropy, and amino acid composition. Intrinsic disorder identified in protein crystal structures, and by nuclear magnetic resonance, circular dichroism, and prediction from amino acid sequence, all exhibit similar complexity distributions that are shifted to lower values compared to, but significantly overlapping with, the distribution for ordered proteins. Compared to sequences from ordered proteins, these variously characterized intrinsically disordered segments and proteins, and also a collection of low-complexity sequences, typically have obviously higher levels of protein-specific subsets of the following amino acids: R, K, E, P, and S, and lower levels of subsets of the following: C, W, Y, I, and V. The Swiss Protein database of sequences exhibits significantly higher amounts of both low-complexity and predicted-to-be-disordered segments as compared to a non-redundant set of sequences from the Protein Data Bank, providing additional data that nature is richer in disordered and low-complexity segments compared to the commonness of these features in the set of structurally characterized proteins.     

Abundance and functional roles of intrinsic disorder in the antimicrobial peptides of the NK-lysin family

NK-lysins are antimicrobial peptides (AMPs) that participate in the innate immune response and also have several pivotal roles in various biological processes. Such multifunctionality is commonly found among intrinsically disordered proteins. However, NK-lysins have never been systematically analyzed for intrinsic disorder. To fill this gap, the amino acid sequences of NK-lysins from various species were collected from UniProt and used for the comprehensive computational analysis to evaluate the propensity of these proteins for intrinsic disorder and to investigate the potential roles of disordered regions in NK-lysin functions. We analyzed abundance and peculiarities of intrinsic disorder distribution in all-known NK-lysins and showed that many NK-lysins are expected to have substantial levels of intrinsic disorder. Curiously, high level of intrinsic disorder was also found even in two proteins with known 3D-strucutres (NK-lysin from pig and human granulysin). Many of the identified disordered regions can be involved in protein–protein interactions. In fact, NK-lysins are shown to contain three to eight molecular recognition features; i.e. short structure-prone segments which are located within the long disordered regions and have a potential to undergo a disorder-to-order transition upon binding to a partner. Furthermore, these disordered regions are expected to have several sites of various posttranslational modifications. Our study shows that NK-lysins, which are AMPs with a set of prominent roles in the innate immune response, are expected to abundantly possess intrinsically disordered regions that might be related to multifunctionality of these proteins in the signal transduction pathways controlling the host response to pathogenic agents.     

Length-dependent prediction of protein intrinsic disorder

Background  

Due to the functional importance of intrinsically disordered proteins or protein regions, prediction of intrinsic protein disorder from amino acid sequence has become an area of active research as witnessed in the 6th experiment on Critical Assessment of Techniques for Protein Structure Prediction (CASP6). Since the initial work by Romero et al. (Identifying disordered regions in proteins from amino acid sequences, IEEE Int. Conf. Neural Netw., 1997), our group has developed several predictors optimized for long disordered regions (>30 residues) with prediction accuracy exceeding 85%. However, these predictors are less successful on short disordered regions (≤30 residues). A probable cause is a length-dependent amino acid compositions and sequence properties of disordered regions.     

Disorder predictors also predict backbone dynamics for a family of disordered proteins

Several algorithms have been developed that use amino acid sequences to predict whether or not a protein or a region of a protein is disordered. These algorithms make accurate predictions for disordered regions that are 30 amino acids or longer, but it is unclear whether the predictions can be directly related to the backbone dynamics of individual amino acid residues. The nuclear Overhauser effect between the amide nitrogen and hydrogen (NHNOE) provides an unambiguous measure of backbone dynamics at single residue resolution and is an excellent tool for characterizing the dynamic behavior of disordered proteins. In this report, we show that the NHNOE values for several members of a family of disordered proteins are highly correlated with the output from three popular algorithms used to predict disordered regions from amino acid sequence. This is the first test between an experimental measure of residue specific backbone dynamics and disorder predictions. The results suggest that some disorder predictors can accurately estimate the backbone dynamics of individual amino acids in a long disordered region.     

Occurrence of disordered patterns and homorepeats in eukaryotic and bacterial proteomes

Combining the motif discovery and disorder protein segment identification in PDB allows us to create the first and largest library of disordered patterns. At present the library includes 109 disordered patterns. Here we offer a comprehensive analysis of the occurrence of selected disordered patterns and 20 homorepeats of 6 residues long in 123 proteomes. 27 disordered patterns occur sparsely in all considered proteomes, but the patterns of low-complexity-homorepeats-appear more often in eukaryotic than in bacterial proteomes. A comparative analysis of the number of proteins containing homorepeats of 6 residues long and the disordered selected patterns in these proteomes has been performed. The matrices of correlation coefficients between numbers of proteins where at least once a homorepeat of six residues long for each of 20 types of amino acid residues and 109 disordered patterns from the library appears in 9 kingdoms of eukaryota and 5 phyla of bacteria have been calculated. As a rule, the correlation coefficients are higher inside the considered kingdom than between them. The largest fraction of homorepeats of 6 residues belongs to Amoebozoa proteomes (D. discoideum), 46%. Moreover, the longest uninterrupted repeats belong to S306 from D. discoideum (Amoebozoa). Homorepeats of some amino acids occur more frequently than others and the type of homorepeats varies across different proteomes, . For example, E6 appears most frequent for all considered proteomes for Chordata, Q6 for Arthropoda, S6 for Nematoda. The averaged occurrence of multiple long runs of 6 amino acids in a decreasing order for 97 eukaryotic proteomes is as follows: Q6, S6, A6, G6, N6, E6, P6, T6, D6, K6, L6, H6, R6, F6, V6, I6, Y6, C6, M6, W6, and for 26 bacterial proteomes it is A6, G6, P6, and the others occur seldom. This suggests that such short similar motifs are responsible for common functions for nonhomologous, unrelated proteins from different organisms.     

SPOT-Disorder2: Improved Protein Intrinsic Disorder Prediction by Ensembled Deep Learning

Intrinsically disordered or unstructured proteins (or regions in proteins) have been found to be important in a wide range of biological functions and implicated in many diseases. Due to the high cost and low efficiency of experimental determination of intrinsic disorder and the exponential increase of unannotated protein sequences, developing complementary computational prediction methods has been an active area of research for several decades. Here, we employed an ensemble of deep Squeeze-and-Excitation residual inception and long short-term memory (LSTM) networks for predicting protein intrinsic disorder with input from evolutionary information and predicted one-dimensional structural properties. The method, called SPOT-Disorder2, offers substantial and consistent improvement not only over our previous technique based on LSTM networks alone, but also over other state-of-the-art techniques in three independent tests with different ratios of disordered to ordered amino acid residues, and for sequences with either rich or limited evolutionary information. More importantly, semi-disordered regions predicted in SPOT-Disorder2 are more accurate in identifying molecular recognition features (MoRFs) than methods directly designed for MoRFs prediction. SPOT-Disorder2 is available as a web server and as a standalone program at https://sparks-lab.org/server/spot-disorder2/.     

TOP-IDP-scale: a new amino acid scale measuring propensity for intrinsic disorder

Intrinsically disordered proteins carry out various biological functions while lacking ordered secondary and/or tertiary structure. In order to find general intrinsic properties of amino acid residues that are responsible for the absence of ordered structure in intrinsically disordered proteins we surveyed 517 amino acid scales. Each of these scales was taken as an independent attribute for the subsequent analysis. For a given attribute value X, which is averaged over a consecutive string of amino acids, and for a given data set having both ordered and disordered segments, the conditional probabilities P(s(o) | x) and P(s(d) | x) for order and disorder, respectively, can be determined for all possible values of X. Plots of the conditional probabilities P(s(o) | x) and P(s(o) | x) versus X give a pair of curves. The area between these two curves divided by the total area of the graph gives the area ratio value (ARV), which is proportional to the degree of separation of the two probability curves and, therefore, provides a measure of the given attribute's power to discriminate between order and disorder. As ARV falls between zero and one, larger ARV corresponds to the better discrimination between order and disorder. Starting from the scale with the highest ARV, we applied a simulated annealing procedure to search for alternative scale values and have managed to increase the ARV by more than 10%. The ranking of the amino acids in this new TOP-IDP scale is as follows (from order promoting to disorder promoting): W, F, Y, I, M, L, V, N, C, T, A, G, R, D, H, Q, K, S, E, P. A web-based server has been created to apply the TOP-IDP scale to predict intrinsically disordered proteins (http://www.disprot.org/dev/disindex.php).     

Analyses of the general rule on residue pair frequencies in local amino acid sequences of soluble,ordered proteins

The amino acid sequences of soluble, ordered proteins with stable structures have evolved due to biological and physical requirements, thus distinguishing them from random sequences. Previous analyses have focused on extracting the features that frequently appear in protein substructures, such as α‐helix and β‐sheet, but the universal features of protein sequences have not been addressed. To clarify the differences between native protein sequences and random sequences, we analyzed 7368 soluble, ordered protein sequences, by inspecting the observed and expected occurrences of 400 amino acid pairs in local proximity, up to 10 residues along the sequence in comparison with their expected occurrence in random sequence. We found the trend that the hydrophobic residue pairs and the polar residue pairs are significantly decreased, whereas the pairs between a hydrophobic residue and a polar residue are increased. This trend was universally observed regardless of the secondary structure content but was not observed in protein sequences that include intrinsically disordered regions, indicating that it can be a general rule of protein foldability. The possible benefits of this rule are discussed from the viewpoints of protein aggregation and disorder, which are both caused by low‐complexity regions of hydrophobic or polar residues.     

PONDR-FIT: A meta-predictor of intrinsically disordered amino acids

Protein intrinsic disorder is becoming increasingly recognized in proteomics research. While lacking structure, many regions of disorder have been associated with biological function. There are many different experimental methods for characterizing intrinsically disordered proteins and regions; nevertheless, the prediction of intrinsic disorder from amino acid sequence remains a useful strategy especially for many large-scale proteomic investigations. Here we introduced a consensus artificial neural network (ANN) prediction method, which was developed by combining the outputs of several individual disorder predictors. By eight-fold cross-validation, this meta-predictor, called PONDR-FIT, was found to improve the prediction accuracy over a range of 3 to 20% with an average of 11% compared to the single predictors, depending on the datasets being used. Analysis of the errors shows that the worst accuracy still occurs for short disordered regions with less than ten residues, as well as for the residues close to order/disorder boundaries. Increased understanding of the underlying mechanism by which such meta-predictors give improved predictions will likely promote the further development of protein disorder predictors. Access to PONDR-FIT is available at www.disprot.org.     

Sequence patterns associated with disordered regions in proteins

The relationship between amino acid sequence and intrinsic disorder in proteins is investigated. Two databases, one of disordered proteins and the other of globular proteins, are analyzed and compared in order to extract simple sequence patterns of a few amino acids or amino acid properties that characterize disordered segments. It is found that a number of reliable, nonrandom associations exists. In particular, two types of patterns appear to be recurrent: a proline-rich pattern and a (positively or negatively) charged pattern. These results indicate that local sequence information can determine disordered regions in proteins. The derived patterns provide some insights into the physical reasons for disordered structures. They should also be helpful in improving currently available prediction methods.     

Conservation of intrinsic disorder in protein domains and families: I. A database of conserved predicted disordered regions

Many protein regions have been shown to be intrinsically disordered, lacking unique structure under physiological conditions. These intrinsically disordered regions are not only very common in proteomes, but also crucial to the function of many proteins, especially those involved in signaling, recognition, and regulation. The goal of this work was to identify the prevalence, characteristics, and functions of conserved disordered regions within protein domains and families. A database was created to store the amino acid sequences of nearly one million proteins and their domain matches from the InterPro database, a resource integrating eight different protein family and domain databases. Disorder prediction was performed on these protein sequences. Regions of sequence corresponding to domains were aligned using a multiple sequence alignment tool. From this initial information, regions of conserved predicted disorder were found within the domains. The methodology for this search consisted of finding regions of consecutive positions in the multiple sequence alignments in which a 90% or more of the sequences were predicted to be disordered. This procedure was constrained to find such regions of conserved disorder prediction that were at least 20 amino acids in length. The results of this work included 3,653 regions of conserved disorder prediction, found within 2,898 distinct InterPro entries. Most regions of conserved predicted disorder detected were short, with less than 10% of those found exceeding 30 residues in length.     

Functional anthology of intrinsic disorder. 3. Ligands, post-translational modifications, and diseases associated with intrinsically disordered proteins

Currently, the understanding of the relationships between function, amino acid sequence, and protein structure continues to represent one of the major challenges of the modern protein science. As many as 50% of eukaryotic proteins are likely to contain functionally important long disordered regions. Many proteins are wholly disordered but still possess numerous biologically important functions. However, the number of experimentally confirmed disordered proteins with known biological functions is substantially smaller than their actual number in nature. Therefore, there is a crucial need for novel bionformatics approaches that allow projection of the current knowledge from a few experimentally verified examples to much larger groups of known and potential proteins. The elaboration of a bioinformatics tool for the analysis of functional diversity of intrinsically disordered proteins and application of this data mining tool to >200 000 proteins from the Swiss-Prot database, each annotated with at least one of the 875 functional keywords, was described in the first paper of this series (Xie, H.; Vucetic, S.; Iakoucheva, L. M.; Oldfield, C. J.; Dunker, A. K.; Obradovic, Z.; Uversky, V.N. Functional anthology of intrinsic disorder. 1. Biological processes and functions of proteins with long disordered regions. J. Proteome Res. 2007, 5, 1882-1898). Using this tool, we have found that out of the 710 Swiss-Prot functional keywords associated with at least 20 proteins, 262 were strongly positively correlated with long intrinsically disordered regions, and 302 were strongly negatively correlated. Illustrative examples of functional disorder or order were found for the vast majority of keywords showing strongest positive or negative correlation with intrinsic disorder, respectively. Some 80 Swiss-Prot keywords associated with disorder- and order-driven biological processes and protein functions were described in the first paper (see above). The second paper of the series was devoted to the presentation of 87 Swiss-Prot keywords attributed to the cellular components, domains, technical terms, developmental processes, and coding sequence diversities possessing strong positive and negative correlation with long disordered regions (Vucetic, S.; Xie, H.; Iakoucheva, L. M.; Oldfield, C. J.; Dunker, A. K.; Obradovic, Z.; Uversky, V. N. Functional anthology of intrinsic disorder. 2. Cellular components, domains, technical terms, developmental processes, and coding sequence diversities correlated with long disordered regions. J. Proteome Res. 2007, 5, 1899-1916). Protein structure and functionality can be modulated by various post-translational modifications or/and as a result of binding of specific ligands. Numerous human diseases are associated with protein misfolding/misassembly/misfunctioning. This work concludes the series of papers dedicated to the functional anthology of intrinsic disorder and describes approximately 80 Swiss-Prot functional keywords that are related to ligands, post-translational modifications, and diseases possessing strong positive or negative correlation with the predicted long disordered regions in proteins.     

Comparing and combining predictors of mostly disordered proteins

Intrinsically disordered proteins and regions carry out varied and vital cellular functions. Proteins with disordered regions are especially common in eukaryotic cells, with a subset of these proteins being mostly disordered, e.g., with more disordered than ordered residues. Two distinct methods have been previously described for using amino acid sequences to predict which proteins are likely to be mostly disordered. These methods are based on the net charge-hydropathy distribution and disorder prediction score distribution. Each of these methods is reexamined, and the prediction results are compared herein. A new prediction method based on consensus is described. Application of the consensus method to whole genomes reveals that approximately 4.5% of Yersinia pestis, 5% of Escherichia coli K12, 6% of Archaeoglobus fulgidus, 8% of Methanobacterium thermoautotrophicum, 23% of Arabidopsis thaliana, and 28% of Mus musculus proteins are mostly disordered. The unexpectedly high frequency of mostly disordered proteins in eukaryotes has important implications both for large-scale, high-throughput projects and also for focused experiments aimed at determination of protein structure and function.     

Functional anthology of intrinsic disorder. 2. Cellular components, domains, technical terms, developmental processes, and coding sequence diversities correlated with long disordered regions

Biologically active proteins without stable ordered structure (i.e., intrinsically disordered proteins) are attracting increased attention. Functional repertoires of ordered and disordered proteins are very different, and the ability to differentiate whether a given function is associated with intrinsic disorder or with a well-folded protein is crucial for modern protein science. However, there is a large gap between the number of proteins experimentally confirmed to be disordered and their actual number in nature. As a result, studies of functional properties of confirmed disordered proteins, while helpful in revealing the functional diversity of protein disorder, provide only a limited view. To overcome this problem, a bioinformatics approach for comprehensive study of functional roles of protein disorder was proposed in the first paper of this series (Xie, H.; Vucetic, S.; Iakoucheva, L. M.; Oldfield, C. J.; Dunker, A. K.; Obradovic, Z.; Uversky, V. N. Functional anthology of intrinsic disorder. 1. Biological processes and functions of proteins with long disordered regions. J. Proteome Res. 2007, 5, 1882-1898). Applying this novel approach to Swiss-Prot sequences and functional keywords, we found over 238 and 302 keywords to be strongly positively or negatively correlated, respectively, with long intrinsically disordered regions. This paper describes approximately 90 Swiss-Prot keywords attributed to the cellular components, domains, technical terms, developmental processes, and coding sequence diversities possessing strong positive and negative correlation with long disordered regions.     

Sequence fingerprints distinguish erroneous from correct predictions of intrinsically disordered protein regions

More than 60 prediction methods for intrinsically disordered proteins (IDPs) have been developed over the years, many of which are accessible on the World Wide Web. Nearly, all of these predictors give balanced accuracies in the ~65%–~80% range. Since predictors are not perfect, further studies are required to uncover the role of amino acid residues in native IDP as compared to predicted IDP regions. In the present work, we make use of sequences of 100% predicted IDP regions, false positive disorder predictions, and experimentally determined IDP regions to distinguish the characteristics of native versus predicted IDP regions. A higher occurrence of asparagine is observed in sequences of native IDP regions but not in sequences of false positive predictions of IDP regions. The occurrences of certain combinations of amino acids at the pentapeptide level provide a distinguishing feature in the IDPs with respect to globular proteins. The distinguishing features presented in this paper provide insights into the sequence fingerprints of amino acid residues in experimentally determined as compared to predicted IDP regions. These observations and additional work along these lines should enable the development of improvements in the accuracy of disorder prediction algorithm.     

Physicochemical characterization and functional analysis of some snake venom toxin proteins and related non-toxin proteins of other chordates

Snake venom contains a diverse array of proteins and polypeptides. Cytotoxins and short neurotoxins are non-enzymatic polypeptide components of snake venom. The three-dimensional structure of cytotoxin and short neurotoxin resembles a three finger appearance of three-finger protein super family. Different family members of three-finger protein super family are employed in diverse biological functions. In this work we analyzed the cytotoxin, short neurotoxin and related non-toxin proteins of other chordates in terms of functional analysis, amino acid compositional (%) profile, number of amino acids, molecular weight, theoretical isoelectric point (pI), number of positively charged and negatively charged amino acid residues, instability index and grand average of hydropathy with the help of different bioinformatical tools. Among all interesting results, profile of amino acid composition (%) depicts that all sequences contain a conserved cysteine amount but differential amount of different amino acid residues which have a family specific pattern. Involvement in different biological functions is one of the driving forces which contribute the vivid amino acid composition profile of these proteins. Different biological system dependent adaptation gives the birth of enriched bio-molecules. Understanding of physicochemical properties of these proteins will help to generate medicinally important therapeutic molecules for betterment of human lives.     

Charged single alpha-helix: a versatile protein structural motif

A few highly charged natural peptide sequences were recently suggested to form stable alpha-helical structures in water. In this article we show that these sequences represent a novel structural motif called "charged single alpha-helix" (CSAH). To obtain reliable candidate CSAH motifs, we developed two conceptually different computational methods capable of scanning large databases: SCAN4CSAH is based on sequence features characteristic for salt bridge stabilized single alpha-helices, whereas FT_CHARGE applies Fourier transformation to charges along sequences. Using the consensus of the two approaches, a remarkable number of proteins were found to contain putative CSAH domains. Recombinant fragments (50-60 residues) corresponding to selected hits obtained by both methods (myosin 6, Golgi resident protein GCP60, and M4K4 protein kinase) were produced and shown by circular dichroism spectroscopy to adopt largely alpha-helical structure in water. CSAH segments differ substantially both from coiled-coil and intrinsically disordered proteins, despite the fact that current prediction methods recognize them as either or both. Analysis of the proteins containing CSAH motif revealed possible functional roles of the corresponding segments. The suggested main functional features include the formation of relatively rigid spacer/connector segments between functional domains as in caldesmon, extension of the lever arm in myosin motors and mediation of transient interactions by promoting dimerization in a range of proteins.     

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.