Insights into protein structure and function from disorder-complexity space

The food and pharmaceutical additive benzoic acid induces amyloid fibrillation of an intrinsically disordered protein

Benzoic acid (BA) is a microbe-inhibiting flavoring agent used extensively as an additive in foods, pharmaceuticals, and hygiene and cosmetic products. The level of BA in foodstuffs prescribed by world bodies and governmental agencies is assumed to be safe so as to prevent adverse health effects. The safety level of BA is however controversial, and whether different conditions of its use would be generally regarded as safe (GRAS) has been rarely determined. In the quest of how food additives affect the structure and conformation of proteins, this study evaluates the interaction of BA with an intrinsically disordered protein (IDP) at pH 4.2 that matches the pH conditions applicable for the commercial use of benzoate preservatives, and examines its structural transformation by NMR, fluorescence, and high-resolution microscopy. The interaction with BA transforms the protein to a denatured aggregated mesophase that undergoes reconfiguration to yield rigid amyloid fibrils. Significantly, fibrils are observed even with 0.1 mM BA while the recommended level of its use as a preservative is in the 0.4-8 mM range. The discussion refrains from safety comments with no projection of the BA level that could be GRAS.

A three-state mechanism for trifluoroethanol denaturation of an intrinsically disordered protein (IDP)

Relating the amino acid composition and sequence to chain folding and binding preferences of intrinsically disordered proteins (IDPs) has emerged as a huge challenge. While globular proteins have respective 3D structures that are unique to their individual functions, IDPs violate this structure-function paradigm because rather than having a well-defined structure an ensemble of rapidly interconverting disordered structures characterize an IDP. This work measures 2,2,2-trifluoroethanol (TFE)-induced equilibrium transitions of an IDP called AtPP16-1 (Arabidopsis thaliana phloem protein type 16-1) by using fluorescence, circular dichroism, infrared and nuclear magnetic resonance (NMR) methods at pH 4, 298 K. Low TFE reversibly removes the tertiary structure to produce an ensemble of obligate intermediate ($\mathrm{I}$) retaining the native-state ($\mathrm{N}$) secondary structure. The intermediate $\mathrm{I}$ is preceded by a non-obligate tryptophan-specific intermediate ${\mathrm{I}}_{\mathrm{w}}$ whose population is detectable for AtPP16-1 specifically. Accumulation of such non-obligate intermediates is discriminated according to the sequence composition of the protein. In all cases, however, a tertiary structure-unfolded general obligate intermediate $\mathrm{I}$ is indispensable. The $\mathrm{I}$ ensemble has higher helical propensity conducive to the acquisition of an exceedingly large level of α-helices by a reversible denaturation transition of $\mathrm{I}$ to the denatured state $\mathrm{D}$ as the TFE level is increased. Strikingly, it is the same $\mathrm{N}\rightleftharpoons \mathrm{I}\rightleftharpoons \mathrm{D}$ scheme typifying the TFE transitions of globular proteins. The high-energy state $\mathrm{I}$ characterized by increased helical propensity is called a universal intermediate encountered in both genera of globular and disordered proteins. Neither $\mathrm{I}$ nor $\mathrm{D}$ strictly show molten globule (MG)-like properties, dismissing the belief that TFE promotes MGs.

Negative Thermal Expansion and Disorder-to-Order Collapse of an Intrinsically Disordered Protein under Marginally Denaturing Conditions

Recent work with intrinsically disordered proteins (IDPs) has projected a myriad of their survival instincts based mainly on the total charge content, the abundance of polar residues, and the paucity of hydrophobic amino acids. This work uses a plant IDP AtPP16-1 (Arabidopsis thaliana phloem protein class 16-1), whose solution NMR structure was determined by us recently, to show legitimate negative thermal expansion (NTE) of the native state. The thermal expansion continues to be negative even as the tertiary structure is perturbed by ultralow levels of urea up to 0.4 M. The NTE of these subdenatured states is called apparent NTE because they are prone to undergo conformational changes with temperature. Hydrodynamic shrinkage of the NTE IDP is also observed by dynamic light scattering (DLS) and NMR-measured global rotational correlation time (τ_c). The protein with denatured tertiary structure but otherwise preserved native-state secondary structure collapses to a dynamically rigid state. The data are mainly based on thermal coefficients of chemical shift and nuclear relaxation measured by heteronuclear NMR. The hydrodynamic shrinkage and collapse under marginally varying solvent compositions that may arise from unstable tertiary structure and dynamic disorder of chain segments across the backbone could be a generic property of IDPs.

Evaluation of protein secondary structure from FTIR spectra improved after partial deuteration

FTIR spectroscopy has become a major tool to determine protein secondary structure. One of the identified obstacle for reaching better predictions is the strong overlap of bands assigned to different secondary structures. Yet, while for instance disordered structures and α-helical structures absorb almost at the same wavenumber, the absorbance bands are differentially shifted upon deuteration, in part because exchange is much faster for disordered structures. We recorded the FTIR spectra of 85 proteins at different stages of hydrogen/deuterium exchange process using protein microarrays and infrared imaging for high throughput measurements. Several methods were used to relate spectral shape to secondary structure content. While in absolute terms, β-sheet is always better predicted than α-helix content, results consistently indicate an improvement of secondary structure predictions essentially for the α-helix and the category called “Others” (grouping random, turns, bends, etc.) after 15 min of exchange. On the contrary, the β-sheet fraction is better predicted in non-deuterated conditions. Using partial least square regression, the error of prediction for the α-helix content is reduced after 15-min deuteration. Further deuteration degrades the prediction. Error on the prediction for the “Others” structures also decreases after 15-min deuteration. Cross-validation or a single 25-protein test set result in the same overall conclusions.

A convenient protein library for spectroscopic calibrations

While several Raman, CD or FTIR spectral libraries are available for well-characterized proteins of known structure, proteins themselves are usually very difficult to acquire, preventing a convenient calibration of new instruments and new recording methods. The problem is particularly critical in the field of FTIR spectroscopy where numerous new methods are becoming available on the market.

The present papers reports the construction of a protein library (cSP92) including commercially available products, that are well characterized experimentally for their purity and solubility in conditions compatible with the recording of FTIR spectra and whose high-resolution structure is available.

Overall, 92 proteins were selected. These proteins cover well the CATH space at the level of classes and architectures. In terms of secondary structure content, an analysis of their high-resolution structure by DSSP shows that the mean content in the different secondary structures present in cSP92 is very similar to the mean content found in the PDB.

The 92-protein set is analyzed in details for the distribution of helix length, number of strands in β- sheets, length of β-strands and amino acid content, all features that may be important for the interpretation of FTIR spectra.

Sequence specificity despite intrinsic disorder: How a disease-associated Val/Met polymorphism rearranges tertiary interactions in a long disordered protein

The role of electrostatic interactions and mutations that change charge states in intrinsically disordered proteins (IDPs) is well-established, but many disease-associated mutations in IDPs are charge-neutral. The Val66Met single nucleotide polymorphism (SNP) in precursor brain-derived neurotrophic factor (BDNF) is one of the earliest SNPs to be associated with neuropsychiatric disorders, and the underlying molecular mechanism is unknown. Here we report on over 250 μs of fully-atomistic, explicit solvent, temperature replica-exchange molecular dynamics (MD) simulations of the 91 residue BDNF prodomain, for both the V66 and M66 sequence. The simulations were able to correctly reproduce the location of both local and non-local secondary structure changes due to the Val66Met mutation, when compared with NMR spectroscopy. We find that the change in local structure is mediated via entropic and sequence specific effects. We developed a hierarchical sequence-based framework for analysis and conceptualization, which first identifies “blobs” of 4-15 residues representing local globular regions or linkers. We use this framework within a novel test for enrichment of higher-order (tertiary) structure in disordered proteins; the size and shape of each blob is extracted from MD simulation of the real protein (RP), and used to parameterize a self-avoiding heterogenous polymer (SAHP). The SAHP version of the BDNF prodomain suggested a protein segmented into three regions, with a central long, highly disordered polyampholyte linker separating two globular regions. This effective segmentation was also observed in full simulations of the RP, but the Val66Met substitution significantly increased interactions across the linker, as well as the number of participating residues. The Val66Met substitution replaces β-bridging between V66 and V94 (on either side of the linker) with specific side-chain interactions between M66 and M95. The protein backbone in the vicinity of M95 is then free to form β-bridges with residues 31-41 near the N-terminus, which condenses the protein. A significant role for Met/Met interactions is consistent with previously-observed non-local effects of the Val66Met SNP, as well as established interactions between the Met66 sequence and a Met-rich receptor that initiates neuronal growth cone retraction.

Intrinsically disordered proteins are proteins that have no well-defined structure in at least one functional form. Mutations in one amino acid may still affect their function significantly, especially in subtle ways with cumulative adverse effects on health. Here we report on molecular dynamics simulations of a protein that is critical for neuronal health throughout adulthood (brain-derived neurotrophic factor). We investigate the effects of a mutation carried by 30% of human population, which has been widely studied for its association with aging-related and stress-related disorders, reduced volume of the hippocampus, and variations in episodic memory. We identify a molecular mechanism in which the mutation may change the global conformations of the protein and its ability to bind to receptors.

Highly disordered histone H1-DNA model complexes and their condensates

Disordered proteins play an essential role in a wide variety of biological processes, and are often posttranslationally modified. One such protein is histone H1; its highly disordered C-terminal tail (CH1) condenses internucleosomal linker DNA in chromatin in a way that is still poorly understood. Moreover, CH1 is phosphorylated in a cell cycle-dependent manner that correlates with changes in the chromatin condensation level. Here we present a model system that recapitulates key aspects of the in vivo process, and also allows a detailed structural and biophysical analysis of the stages before and after condensation. CH1 remains disordered in the DNA-bound state, despite its nanomolar affinity. Phase-separated droplets (coacervates) form, containing higher-order assemblies of CH1/DNA complexes. Phosphorylation at three serine residues, spaced along the length of the tail, has little effect on the local properties of the condensate. However, it dramatically alters higher-order structure in the coacervate and reduces partitioning to the coacervate phase. These observations show that disordered proteins can bind tightly to DNA without a disorder-to-order transition. Importantly, they also provide mechanistic insights into how higher-order structures can be exquisitely sensitive to perturbation by posttranslational modifications, thus broadening the repertoire of mechanisms that might regulate chromatin and other macromolecular assemblies.

Translational Control by Prion-like Proteins

Prion-like proteins overlap with intrinsically disordered and low-complexity sequence families. These proteins are widespread, especially among mRNA-binding proteins. A salient feature of these proteins is the ability to form protein assemblies with distinct biophysical and functional properties. While prion-like proteins are involved in myriad of cellular processes, we propose potential roles for protein assemblies in regulated protein synthesis. Since proteins are the ultimate functional output of gene expression, when, where, and how much of a particular protein is made dictates the functional state of a cell. Recent finding suggests that the prion-like proteins offer unique advantages in translation regulation and also raises questions regarding formation and regulation of protein assemblies.

Unravelling the relationship between protein sequence and low-complexity regions entropies: Interactome implications

Low-complexity regions are sub-sequences of biased composition in a protein sequence. The influence of these regions over protein evolution, specific functions and highly interactive capacities is well known. Although protein sequence entropy has been largely studied, its relationship with low-complexity regions and the subsequent effects on protein function remains unclear. In this work we propose a theoretical and empirical model integrating the sequence entropy with local complexity parameters. Our results indicate that the protein sequence entropy is related with the protein length, the entropies inside and outside the low-complexity regions as well as their number and average size. We found a small but significant increment in the sequence entropy of hubs proteins. In agreement with our theoretical model, this increment is highly dependent of the balance between the increment of protein length and average size of the low-complexity regions. Finally, our models and proteins analysis provide evidence supporting that modifications in the average size is more relevant in hubs proteins than changes in the number of low-complexity regions.

DisMeta: a meta server for construct design and optimization

Intrinsically disordered or unstructured regions in proteins are both common and biologically important, particularly in regulation, signaling, and modulating intermolecular recognition processes. From a practical point of view, however, such disordered regions often can pose significant challenges for crystallization. Disordered regions are also detrimental to NMR spectral quality, complicating the analysis of resonance assignments and three-dimensional protein structures by NMR methods. The DisMeta Server has been used by Northeastern Structural Genomics (NESG) consortium as a primary tool for construct design and optimization in preparing samples for both NMR and crystallization studies. It is a meta-server that generates a consensus analysis of eight different sequence-based disorder predictors to identify regions that are likely to be disordered. DisMeta also identifies predicted secretion signal peptides, transmembrane segments, and low-complexity regions. Identification of disordered regions, by either experimental or computational methods, is an important step in the NESG structure production pipeline, allowing the rational design of protein constructs that have improved expression and solubility, improved crystallization, and better quality NMR spectra.

The subsequence composition of polypeptides

The quantitative underpinning of the information content of biosequences represents an elusive goal and yet also an obvious prerequisite to the quantitative modeling and study of biological function and evolution. Several past studies have addressed the question of what distinguishes biosequences from random strings, the latter being clearly unpalatable to the living cell. Such studies typically analyze the organization of biosequences in terms of their constituent characters or substrings and have, in particular, consistently exposed a tenacious lack of compressibility on behalf of biosequences. This article attempts, perhaps for the first time, an assessement of the structure and randomness of polypeptides in terms on newly introduced parameters that relate to the vocabulary of their (suitably constrained) subsequences rather than their substrings. It is shown that such parameters grasp structural/functional information, and are related to each other under a specific set of rules that span biochemically diverse polypeptides. Measures on subsequences separate few amino acid strings from their random permutations, but show that the random permutations of most polypeptides amass along specific linear loci.

Parameterization of disorder predictors for large-scale applications requiring high specificity by using an extended benchmark dataset

BACKGROUND

Algorithms designed to predict protein disorder play an important role in structural and functional genomics, as disordered regions have been reported to participate in important cellular processes. Consequently, several methods with different underlying principles for disorder prediction have been independently developed by various groups. For assessing their usability in automated workflows, we are interested in identifying parameter settings and threshold selections, under which the performance of these predictors becomes directly comparable.

RESULTS

First, we derived a new benchmark set that accounts for different flavours of disorder complemented with a similar amount of order annotation derived for the same protein set. We show that, using the recommended default parameters, the programs tested are producing a wide range of predictions at different levels of specificity and sensitivity. We identify settings, in which the different predictors have the same false positive rate. We assess conditions when sets of predictors can be run together to derive consensus or complementary predictions. This is useful in the framework of proteome-wide applications where high specificity is required such as in our in-house sequence analysis pipeline and the ANNIE webserver.

CONCLUSIONS

This work identifies parameter settings and thresholds for a selection of disorder predictors to produce comparable results at a desired level of specificity over a newly derived benchmark dataset that accounts equally for ordered and disordered regions of different lengths.

Potential implications of availability of short amino acid sequences in proteins: an old and new approach to protein decoding and design

Three-dimensional structure of a protein molecule is primarily determined by its amino acid sequence, and thus the elucidation of general rules embedded in amino acid sequences is of great importance in protein science and engineering. To extract valuable information from sequences, we propose an analytical method in which a protein sequence is considered to be constructed by serial superimpositions of short amino acid sequences of n amino acid sets, especially triplets (3-aa sets). Using the comprehensive nonredundant protein database, we first examined "availability" of all possible combinatorial sets of 8,000 triplet species. Availability score was mathematically defined as an indicator for the relative "preference" or "avoidance" for a given short constituent sequence to be used in protein chain. Availability scores of real proteins were clearly biased against those of randomly generated proteins. We found many triplet species that occurred in the database more than expected or less than expected. Such bias was extended to longer sets, and we found that some species of pentats (5-aa sets) that occurred reasonably frequently in the randomly generated protein population did not occur at all in any real proteins known today. Availability score was dependent on species, potentially serving as a phylogenetic indicator. Furthermore, we suggest possibilities of various biotechnological applications of characteristic short sequences such as human-specific and pathogen-specific short sequences obtained from availability analysis. Availability score was also dependent on secondary structures, potentially serving as a structural indicator. Availability analysis on triplets may be combined with a comprehensive data collection on the varphi and psi peptide-bond angles of the amino acid at the center of each triplet, i.e., a collection of Ramachandran plots for each triplet. These triplet characters, together with other physicochemical data, will provide us with basic information between protein sequence and structure, by which structure prediction and engineering may be greatly facilitated. Availability analysis may also be useful in identifying word processing units in amino acid sequences based on an analogy to natural languages. Together with other approaches, availability analysis will elucidate general rules hidden in the primary sequences and eventually contributes to rebuilding the paradigm of protein science.

Quantitative characterization of intrinsic disorder in polyglutamine: insights from analysis based on polymer theories

Intrinsically disordered proteins (IDPs) are unfolded under physiological conditions. Here we ask if archetypal IDPs in aqueous milieus are best described as swollen disordered coils in a good solvent or collapsed disordered globules in a poor solvent. To answer this question, we analyzed data from molecular simulations for a 20-residue polyglutamine peptide and concluded, in accord with experimental results, that water is a poor solvent for this system. The relevance of monomeric polyglutamine is twofold: It is an archetypal IDP sequence and its aggregation is associated with nine neurodegenerative diseases. The main advance in this work lies in our ability to make accurate assessments of solvent quality from analysis of simulations for a single, rather than multiple chain lengths. We achieved this through the proper design of simulations and analysis of order parameters that are used to describe conformational equilibria in polymer physics theories. Despite the preference for collapsed structures, we find that polyglutamine is disordered because a heterogeneous ensemble of conformations of equivalent compactness is populated at equilibrium. It is surprising that water is a poor solvent for polar polyglutamine and the question is: why? Our preliminary analysis suggests that intrabackbone interactions provide at least part of the driving force for the collapse of polyglutamine in water. We also show that dynamics for conversion between distinct conformations resemble structural relaxation in disordered, glassy systems, i.e., the energy landscape for monomeric polyglutamine is rugged. We end by discussing generalizations of our methods to quantitative studies of conformational equilibria of other low-complexity IDP sequences.

Intrinsic disorder and functional proteomics

The recent advances in the prediction of intrinsically disordered proteins and the use of protein disorder prediction in the fields of molecular biology and bioinformatics are reviewed here, especially with regard to protein function. First, a close look is taken at intrinsically disordered proteins and then at the methods used for their experimental characterization. Next, the major statistical properties of disordered regions are summarized, and prediction models developed thus far are described, including their numerous applications in functional proteomics. The future of the prediction of protein disorder and the future uses of such predictions in functional proteomics comprise the last section of this article.

DisProt: the Database of Disordered Proteins

The Database of Protein Disorder (DisProt) links structure and function information for intrinsically disordered proteins (IDPs). Intrinsically disordered proteins do not form a fixed three-dimensional structure under physiological conditions, either in their entireties or in segments or regions. We define IDP as a protein that contains at least one experimentally determined disordered region. Although lacking fixed structure, IDPs and regions carry out important biological functions, being typically involved in regulation, signaling and control. Such functions can involve high-specificity low-affinity interactions, the multiple binding of one protein to many partners and the multiple binding of many proteins to one partner. These three features are all enabled and enhanced by protein intrinsic disorder. One of the major hindrances in the study of IDPs has been the lack of organized information. DisProt was developed to enable IDP research by collecting and organizing knowledge regarding the experimental characterization and the functional associations of IDPs. In addition to being a unique source of biological information, DisProt opens doors for a plethora of bioinformatics studies. DisProt is openly available at .