Frequencies of hydrophobic and hydrophilic runs and alternations in proteins of known structure

Distribution and solvent exposure of Hsp70 chaperone binding sites across the Escherichia coli proteome

Many proteins must interact with molecular chaperones to achieve their native state in the cell. Yet, how chaperone binding-site characteristics affect the folding process is poorly understood. The ubiquitous Hsp70 chaperone system prevents client-protein aggregation by holding unfolded conformations and by unfolding misfolded states. Hsp70 binding sites of client proteins comprise a nonpolar core surrounded by positively charged residues. However, a detailed analysis of Hsp70 binding sites on a proteome-wide scale is still lacking. Further, it is not known whether proteins undergo some degree of folding while chaperone bound. Here, we begin to address the above questions by identifying Hsp70 binding sites in 2258 Escherichia coli (E. coli) proteins. We find that most proteins bear at least one Hsp70 binding site and that the number of Hsp70 binding sites is directly proportional to protein size. Aggregation propensity upon release from the ribosome correlates with number of Hsp70 binding sites only in the case of large proteins. Interestingly, Hsp70 binding sites are more solvent-exposed than other nonpolar sites, in protein native states. Our findings show that the majority of E. coli proteins are systematically enabled to interact with Hsp70 even if this interaction only takes place during a fraction of the protein lifetime. In addition, our data suggest that some conformational sampling may take place within Hsp70-bound states, due to the solvent exposure of some chaperone binding sites in native proteins. In all, we propose that Hsp70-chaperone-binding traits have evolved to favor Hsp70-assisted protein folding devoid of aggregation.

Comparison of ATP-binding pockets and discovery of homologous recombination inhibitors

The ATP binding sites of many enzymes are structurally related, which complicates their development as therapeutic targets. In this work, we explore a diverse set of ATPases and compare their ATP binding pockets using different strategies, including direct and indirect structural methods, in search of pockets attractive for drug discovery. We pursue different direct and indirect structural strategies, as well as ligandability assessments to help guide target selection. The analyses indicate human RAD51, an enzyme crucial in homologous recombination, as a promising, tractable target. Inhibition of RAD51 has shown promise in the treatment of certain cancers but more potent inhibitors are needed. Thus, we design compounds computationally against the ATP binding pocket of RAD51 with consideration of multiple criteria, including predicted specificity, drug-likeness, and toxicity. The molecules designed are evaluated experimentally using molecular and cell-based assays. Our results provide two novel hit compounds against RAD51 and illustrate a computational pipeline to design new inhibitors against ATPases.

Identification of the Primary Factors Determining theSpecificity of Human VKORC1 Recognition by Thioredoxin-Fold Proteins

Redox (reduction-oxidation) reactions control many important biological processes in all organisms, both prokaryotes and eukaryotes. This reaction is usually accomplished by canonical disulphide-based pathways involving a donor enzyme that reduces the oxidised cysteine residues of a target protein, resulting in the cleavage of its disulphide bonds. Focusing on human vitamin K epoxide reductase (hVKORC1) as a target and on four redoxins (protein disulphide isomerase (PDI), endoplasmic reticulum oxidoreductase (ERp18), thioredoxin-related transmembrane protein 1 (Tmx1) and thioredoxin-related transmembrane protein 4 (Tmx4)) as the most probable reducers of VKORC1, a comparative in-silico analysis that concentrates on the similarity and divergence of redoxins in their sequence, secondary and tertiary structure, dynamics, intraprotein interactions and composition of the surface exposed to the target is provided. Similarly, hVKORC1 is analysed in its native state, where two pairs of cysteine residues are covalently linked, forming two disulphide bridges, as a target for Trx-fold proteins. Such analysis is used to derive the putative recognition/binding sites on each isolated protein, and PDI is suggested as the most probable hVKORC1 partner. By probing the alternative orientation of PDI with respect to hVKORC1, the functionally related noncovalent complex formed by hVKORC1 and PDI was found, which is proposed to be a first precursor to probe thiol-disulphide exchange reactions between PDI and hVKORC1.

Methods for Proteogenomics Data Analysis, Challenges, and Scalability Bottlenecks: A Survey

Big Data Proteogenomics lies at the intersection of high-throughput Mass Spectrometry (MS) based proteomics and Next Generation Sequencing based genomics. The combined and integrated analysis of these two high-throughput technologies can help discover novel proteins using genomic, and transcriptomic data. Due to the biological significance of integrated analysis, the recent past has seen an influx of proteogenomic tools that perform various tasks, including mapping proteins to the genomic data, searching experimental MS spectra against a six-frame translation genome database, and automating the process of annotating genome sequences. To date, most of such tools have not focused on scalability issues that are inherent in proteogenomic data analysis where the size of the database is much larger than a typical protein database. These state-of-the-art tools can take more than half a month to process a small-scale dataset of one million spectra against a genome of 3 GB. In this article, we provide an up-to-date review of tools that can analyze proteogenomic datasets, providing a critical analysis of the techniques' relative merits and potential pitfalls. We also point out potential bottlenecks and recommendations that can be incorporated in the future design of these workflows to ensure scalability with the increasing size of proteogenomic data. Lastly, we make a case of how high-performance computing (HPC) solutions may be the best bet to ensure the scalability of future big data proteogenomic data analysis.

Exploring the candidates for a new protein folding - cross-α amyloid - in available protein databases

Amyloid fibrils are formed from the assembly of soluble proteins and are responsible for many diseases. They are known to have a cross-β structure, where the fibril runs perpendicular to the β-sheets. A new type of tertiary structure formed by the aggregation of peptides in their α-helical form, in naturally occurring as well as synthetic peptides, termed cross-α amyloid has been reported recently. We have studied the interactions responsible for the formation of these cross-α amyloids and proposed a model to determine the peptides that could form these structures. Eight such peptides obtained using the model have been shown to form a cross-α structure using molecular dynamics simulations. The formation of a cross-α structure from eight copies of a randomly chosen peptide and its stability over a microsecond simulation have been demonstrated. A software named Cross-Alpha-Det has been developed that can determine whether a protein can form a cross-α structure from its secondary structure.

Properties of protein unfolded states suggest broad selection for expanded conformational ensembles

Much attention is being paid to conformational biases in the ensembles of intrinsically disordered proteins. However, it is currently unknown whether or how conformational biases within the disordered ensembles of foldable proteins affect function in vivo. Recently, we demonstrated that water can be a good solvent for unfolded polypeptide chains, even those with a hydrophobic and charged sequence composition typical of folded proteins. These results run counter to the generally accepted model that protein folding begins with hydrophobicity-driven chain collapse. Here we investigate what other features, beyond amino acid composition, govern chain collapse. We found that local clustering of hydrophobic and/or charged residues leads to significant collapse of the unfolded ensemble of pertactin, a secreted autotransporter virulence protein from Bordetella pertussis, as measured by small angle X-ray scattering (SAXS). Sequence patterns that lead to collapse also correlate with increased intermolecular polypeptide chain association and aggregation. Crucially, sequence patterns that support an expanded conformational ensemble enhance pertactin secretion to the bacterial cell surface. Similar sequence pattern features are enriched across the large and diverse family of autotransporter virulence proteins, suggesting sequence patterns that favor an expanded conformational ensemble are under selection for efficient autotransporter protein secretion, a necessary prerequisite for virulence. More broadly, we found that sequence patterns that lead to more expanded conformational ensembles are enriched across water-soluble proteins in general, suggesting protein sequences are under selection to regulate collapse and minimize protein aggregation, in addition to their roles in stabilizing folded protein structures.

Water as a Good Solvent for Unfolded Proteins: Folding and Collapse are Fundamentally Different

The argument that the hydrophobic effect is the primary effect driving the folding of globular proteins is nearly universally accepted (including by the authors). But does this view also imply that water is a "poor" solvent for the unfolded states of these same proteins? Here we argue that the answer is "no," that is, folding to a well-packed, extensively hydrogen-bonded native structure differs fundamentally from the nonspecific chain collapse that defines a poor solvent. Thus, the observation that a protein folds in water does not necessitate that water is a poor solvent for its unfolded state. Indeed, chain-solvent interactions that are marginally more favorable than nonspecific intrachain interactions are beneficial to protein function because they destabilize deleterious misfolded conformations and inter-chain interactions.

Proteomic Atomics Reveals a Distinctive Uracil-5-Methyltransferase

Carbon (C), hydrogen (H), nitrogen (N), oxygen (O), and sulfur (S) atoms intrigue as they are the foundation for amino acid (AA) composition and the folding and functions of proteins and thus define and control the survival of a cell, the smallest unit of life. Here, we calculated the proteomic atom distribution in >1500 randomly selected species across the entire current phylogenetic tree and identified uracil-5-methyltransferase (U5MTase) of the protozoan parasite Plasmodium falciparum (Pf, strain Pf3D7), with a distinct atom and AA distribution pattern. We determined its apicoplast location and in silico 3D protein structure to refocus attention exclusively on U5MTase with tremendous potential for therapeutic intervention in malaria. Around 300 million clinical cases of malaria occur each year in tropical and subtropical regions of the world, resulting in over one million deaths annually, placing malaria among the most serious infectious diseases. Genomic and proteomic research of the clades of parasites containing Pf is progressing slowly and the functions of most of the ∼5300 genes are still unknown. We applied a 'bottom-up' comparative proteomic atomics analysis across the phylogenetic tree to visualize a protein molecule on its actual basis - i. e., its atomic level. We identified a protruding Pf3D7-specific U5MTase, determined its 3D protein structure, and identified potential inhibitory drug molecules through in silico drug screening that might serve as possible remedies for the treatment of malaria. Besides, this atomic-based proteome map provides a unique approach for the identification of parasite-specific proteins that could be considered as novel therapeutic targets.

Commonly used FRET fluorophores promote collapse of an otherwise disordered protein

The dimensions that unfolded proteins, including intrinsically disordered proteins (IDPs), adopt in the absence of denaturant remain controversial. We developed an analysis procedure for small-angle X-ray scattering (SAXS) profiles and used it to demonstrate that even relatively hydrophobic IDPs remain nearly as expanded in water as they are in high denaturant concentrations. In contrast, as demonstrated here, most fluorescence resonance energy transfer (FRET) measurements have indicated that relatively hydrophobic IDPs contract significantly in the absence of denaturant. We use two independent approaches to further explore this controversy. First, using SAXS we show that fluorophores employed in FRET can contribute to the observed discrepancy. Specifically, we find that addition of Alexa-488 to a normally expanded IDP causes contraction by an additional 15%, a value in reasonable accord with the contraction reported in FRET-based studies. Second, using our simulations and analysis procedure to accurately extract both the radius of gyration (R_g) and end-to-end distance (R_ee) from SAXS profiles, we tested the recent suggestion that FRET and SAXS results can be reconciled if the R_g and R_ee are "uncoupled" (i.e., no longer simply proportional), in contrast to the case for random walk homopolymers. We find, however, that even for unfolded proteins, these two measures of unfolded state dimensions remain proportional. Together, these results suggest that improved analysis procedures and a correction for significant, fluorophore-driven interactions are sufficient to reconcile prior SAXS and FRET studies, thus providing a unified picture of the nature of unfolded polypeptide chains in the absence of denaturant.

Increased sequence hydrophobicity reduces conformational specificity: A mutational case study of the Arc repressor protein

The amino-acid sequences of soluble, globular proteins must have hydrophobic residues to form a stable core, but excess sequence hydrophobicity can lead to loss of native state conformational specificity and aggregation. Previous studies of polar-to-hydrophobic mutations in the β-sheet of the Arc repressor dimer showed that a single substitution at position 11 (N11L) leads to population of an alternate dimeric fold in which the β-sheet is replaced by helix. Two additional hydrophobic mutations at positions 9 and 13 (Q9V and R13V) lead to population of a differently folded octamer along with both dimeric folds. Here we conduct a comprehensive study of the sequence determinants of this progressive loss of fold specificity. We find that the alternate dimer-fold specifically results from the N11L substitution and is not promoted by other hydrophobic substitutions in the β-sheet. We also find that three highly hydrophobic substitutions at positions 9, 11, and 13 are necessary and sufficient for oligomer formation, but the oligomer size depends on the identity of the hydrophobic residue in question. The hydrophobic substitutions increase thermal stability, illustrating how increased hydrophobicity can increase folding stability even as it degrades conformational specificity. The oligomeric variants are predicted to be aggregation-prone but may be hindered from doing so by proline residues that flank the β-sheet region. Loss of conformational specificity due to increased hydrophobicity can manifest itself at any level of structure, depending upon the specific mutations and the context in which they occur.

The Relation between α-Helical Conformation and Amyloidogenicity

Amyloid fibrils are stable aggregates of misfolded proteins and polypeptides that are insoluble and resistant to protease activity. Abnormal formation of amyloid fibrils in vivo may lead to neurodegenerative disorders and other systemic amyloidosis, such as Alzheimer's, Parkinson's, and atherosclerosis. Because of their clinical importance, amyloids are under intense scientific research. It is believed that short polypeptide segments within proteins are responsible for the transformation of correctly folded proteins into parts of larger amyloid fibrils and that this transition is modulated by environmental factors, such as pH, salt concentration, interaction with the cell membrane, and interaction with metal ions. Most studies on amyloids focus on the amyloidogenic sequences. The focus of this study is on the structure of the amyloidogenic α-helical segments because the α-helical secondary structure has been recognized to be a key player in different stages of the amyloidogenesis process. We have previously shown that the α-helical conformation may be expressed by two parameters (θ and ρ) that form orthogonal coordinates based on the Ramachandran dihedrals (φ and ψ) and provide an illuminating interpretation of the α-helical conformation. By performing statistical analysis on α-helical conformations found in the Protein Data Bank, an apparent relation between α-helical conformation, as expressed by θ and ρ, and amyloidogenicity is revealed. Remarkably, random amino acid sequences, whose helical structures were obtained from the most probable dihedral angles, revealed the same dependency of amyloidogenicity, suggesting the importance of α-helical structure as opposed to sequence.

Peptide binding landscapes: Specificity and homophilicity across sequence space in a lattice model

Peptide aggregation frequently involves sequences with strong homophilic binding character, i.e., sequences that self-assemble with like species in a crowded cellular environment, in the face of a multitude of other peptides or proteins as potential heterophilic binding partners. What kinds of sequences display a strong tendency towards homophilic binding and self-assembly, and what are the origins of this behavior? Here, we consider how sequence specificity in oligomerization processes plays out in a simple two-dimensional (2D) lattice statistical-thermodynamic peptide model that permits exhaustive examination of the entire sequence and configurational landscapes. We find that sequences with strong self-specificities have either alternating hydrophobic and hydrophilic residues or short patches of hydrophobic residues, both which minimize intramolecular hydrophobic interactions in part due to the constraints of the 2D lattice. We also find that these specificities are highly sensitive to entropic and free energetic features of the unbound conformational state, such that direct binding interaction energies alone do not capture the complete behavior. These results suggest that the ability of particular peptide sequences to self-assemble and aggregate in a many-protein environment reflects a precise balance of direct binding interactions and behavior in the unbound (monomeric) state.

The Purine Bias of Coding Sequences is Determined by Physicochemical Constraints on Proteins

For this report, we analyzed protein secondary structures in relation to the statistics of three nucleotide codon positions. The purpose of this investigation was to find which properties of the ribosome, tRNA or protein level, could explain the purine bias (Rrr) as it is observed in coding DNA. We found that the Rrr pattern is the consequence of a regularity (the codon structure) resulting from physicochemical constraints on proteins and thermodynamic constraints on ribosomal machinery. The physicochemical constraints on proteins mainly come from the hydropathy and molecular weight (MW) of secondary structures as well as the energy cost of amino acid synthesis. These constraints appear through a network of statistical correlations, such as (i) the cost of amino acid synthesis, which is in favor of a higher level of guanine in the first codon position, (ii) the constructive contribution of hydropathy alternation in proteins, (iii) the spatial organization of secondary structure in proteins according to solvent accessibility, (iv) the spatial organization of secondary structure according to amino acid hydropathy, (v) the statistical correlation of MW with protein secondary structures and their overall hydropathy, (vi) the statistical correlation of thymine in the second codon position with hydropathy and the energy cost of amino acid synthesis, and (vii) the statistical correlation of adenine in the second codon position with amino acid complexity and the MW of secondary protein structures. Amino acid physicochemical properties and functional constraints on proteins constitute a code that is translated into a purine bias within the coding DNA via tRNAs. In that sense, the Rrr pattern within coding DNA is the effect of information transfer on nucleotide composition from protein to DNA by selection according to the codon positions. Thus, coding DNA structure and ribosomal machinery co-evolved to minimize the energy cost of protein coding given the functional constraints on proteins.

Amyloid peptides derived from CsgA and FapC modify the viscoelastic properties of biofilm model matrices

The bacterial biofilm is a complex environment of cells, which secrete a matrix made of various components, mainly polysaccharides and proteins. An understanding of the precise role of these components in the stability and dynamics of biofilm architecture would be a great advantage for the improvement of anti-biofilm strategies. Here, artificial biofilm matrices made of polysaccharides and auto-assembled peptides were designed, and the influence of bacterial amyloid proteins on the mechanical properties of the biofilm matrix was studied. The model polysaccharides methylcellulose and alginate and peptides derived from the amyloid proteins curli and FapC found in biofilms of Enterobacteriaceae and Pseudomonas, respectively, were used. Rheological measurements showed that the amyloid peptides do not prevent the gelation of the polysaccharides but influence deformation of the matrices under shear stress and modify the gel elastic response. Hence the secretion of amyloids could be for the biofilm a way of adapting to environmental changes.

On the foldability of tryptophan-containing tetra- and pentapeptides: an exhaustive molecular dynamics study

Short peptides serve as minimal model systems to decipher the determinants of foldability due to their simplicity arising from their smaller size, their ability to echo protein-like structural characteristics, and their direct implication in force field validation. Here, we describe an effort to identify small peptides that can still form stable structures in aqueous solutions. We followed the in silico folding of a selected set of 8640 tryptophan-containing tetra- and pentapeptides through 15 210 molecular dynamics simulations amounting to a total of 272.46 μs using explicit representation of the solute and full treatment of the electrostatics. The evaluation and sorting of peptides is achieved through scoring functions, which include terms based on interatomic vector distances, atomic fluctuations, and rmsd matrices between successive frames of a trajectory. Highly scored peptides are studied further via successive simulation rounds of increasing simulation length and using different empirical force fields. Our method suggested only a handful of peptides with strong foldability prognosis. The discrepancies between the predictions of the various force fields for such short sequences are also extensively discussed. We conclude that the vast majority of such short peptides do not adopt significantly stable structures in water solutions, at least based on our computational predictions. The present work can be utilized in the rational design and engineering of bioactive peptides with desired molecular properties.

A polymetamorphic protein

Arc repressor is a homodimeric protein with a ribbon-helix-helix fold. A single polar-to-hydrophobic substitution (N11L) at a solvent-exposed position leads to population of an alternate dimeric fold in which 3₁₀ helices replace a β-sheet. Here we find that the variant Q9V/N11L/R13V (S-VLV), with two additional polar-to-hydrophobic surface mutations in the same β-sheet, forms a highly stable, reversibly folded octamer with approximately half the α-helical content of wild-type Arc. At low protein concentration and low ionic strength, S-VLV also populates both dimeric topologies previously observed for N11L, as judged by NMR chemical shift comparisons. Thus, accumulation of simple hydrophobic mutations in Arc progressively reduces fold specificity, leading first to a sequence with two folds and then to a manifold bridge sequence with at least three different topologies. Residues 9-14 of S-VLV form a highly hydrophobic stretch that is predicted to be amyloidogenic, but we do not observe aggregates of higher order than octamer. Increases in sequence hydrophobicity can promote amyloid aggregation but also exert broader and more complex effects on fold specificity. Altered native folds, changes in fold coupled to oligomerization, toxic pre-amyloid oligomers, and amyloid fibrils may represent a near continuum of accessible alternatives in protein structure space.

The role of tryptophan in protein fibrillogenesis: relevance of Trp7 and Trp14 to the amyloidogenic properties of myoglobin

In order to understand the role of tryptophan in the mechanisms of fibrils formation, the ability of a series of analogs of the residue 7-18 span of myoglobin to form amyloid-like fibrils was investigated. Alternatively one or both tryptophans were substituted with alanine and leucine, to determine the contribution of hydrophobicity and aromaticity. The scale of aggregation propensity of the peptides determined indicates that tryptophan is crucial for the amyloidogenic process. Since the rare tryptophan residue is generally engaged in structural roles in proteins, or when exposed serves as binding sites, we surmise that its exposure in the amyloidogenic fragments allows for intermolecular clustering with residues from other molecules leading to the formation of amyloid aggregates.

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.

Sequence periodicity and secondary structure propensity in model proteins

We explore the question of whether local effects (originating from the amino acids intrinsic secondary structure propensities) or nonlocal effects (reflecting the sequence of amino acids as a whole) play a larger role in determining the fold of globular proteins. Earlier circular dichroism studies have shown that the pattern of polar, non polar amino acids (nonlocal effect) dominates over the amino acid intrinsic propensity (local effect) in determining the secondary structure of oligomeric peptides. In this article, we present a coarse grained computational model that allows us to quantitatively estimate the role of local and nonlocal factors in determining both the secondary and tertiary structure of small, globular proteins. The amino acid intrinsic secondary structure propensity is modeled by a dihedral potential term. This dihedral potential is parametrized to match with experimental measurements of secondary structure propensity. Similarly, the magnitude of the attraction between hydrophobic residues is parametrized to match the experimental transfer free energies of hydrophobic amino acids. Under these parametrization conditions, we systematically explore the degree of frustration a given polar, non polar pattern can tolerate when the secondary structure intrinsic propensities are in opposition to it. When the parameters are in the biophysically relevant range, we observe that the fold of small, globular proteins is determined by the pattern of polar, non polar amino acids regardless of their instrinsic secondary structure propensities. Our simulations shed new light on previous observations that tertiary interactions are more influential in determining protein structure than secondary structure propensity. The fact that this can be inferred using a simple polymer model that lacks most of the biochemical details points to the fundamental importance of binary patterning in governing folding.

Amyloidogenic sequences in native protein structures

Numerous short peptides have been shown to form beta-sheet amyloid aggregates in vitro. Proteins that contain such sequences are likely to be problematic for a cell, due to their potential to aggregate into toxic structures. We investigated the structures of 30 proteins containing 45 sequences known to form amyloid, to see how the proteins cope with the presence of these potentially toxic sequences, studying secondary structure, hydrogen-bonding, solvent accessible surface area and hydrophobicity. We identified two mechanisms by which proteins avoid aggregation: Firstly, amyloidogenic sequences are often found within helices, despite their inherent preference to form beta structure. Helices may offer a selective advantage, since in order to form amyloid the sequence will presumably have to first unfold and then refold into a beta structure. Secondly, amyloidogenic sequences that are found in beta structure are usually buried within the protein. Surface exposed amyloidogenic sequences are not tolerated in strands, presumably because they lead to protein aggregation via assembly of the amyloidogenic regions. The use of alpha-helices, where amyloidogenic sequences are forced into helix, despite their intrinsic preference for beta structure, is thus a widespread mechanism to avoid protein aggregation.

Folding by numbers: primary sequence statistics and their use in studying protein folding

The exponential growth over the past several decades in the quantity of both primary sequence data available and the number of protein structures determined has provided a wealth of information describing the relationship between protein primary sequence and tertiary structure. This growing repository of data has served as a prime source for statistical analysis, where underlying relationships between patterns of amino acids and protein structure can be uncovered. Here, we survey the main statistical approaches that have been used for identifying patterns within protein sequences, and discuss sequence pattern research as it relates to both secondary and tertiary protein structure. Limitations to statistical analyses are discussed, and a context for their role within the field of protein folding is given. We conclude by describing a novel statistical study of residue patterning in β-strands, which finds that hydrophobic (i,i+2) pairing in β-strands occurs more often than expected at locations near strand termini. Interpretations involving β-sheet nucleation and growth are discussed.

The effect of sequence on the conformational stability of a model heteropolymer in explicit water

We investigate the properties of a two-dimensional lattice heteropolymer model for a protein in which water is explicitly represented. The model protein distinguishes between hydrophobic and polar monomers through the effect of the hydrophobic monomers on the entropy and enthalpy of the hydrogen bonding of solvation shell water molecules. As experimentally observed, model heteropolymer sequences fold into stable native states characterized by a hydrophobic core to avoid unfavorable interactions with the solvent. These native states undergo cold, pressure, and thermal denaturation into distinct configurations for each type of unfolding transition. However, the heteropolymer sequence is an important element, since not all sequences will fold into stable native states at positive pressures. Simulation of a large collection of sequences indicates that these fall into two general groups, those exhibiting highly stable native structures and those that do not. Statistical analysis of important patterns in sequences shows a strong tendency for observing long blocks of hydrophobic or polar monomers in the most stable sequences. Statistical analysis also shows that alternation of hydrophobic and polar monomers appears infrequently among the most stable sequences. These observations are not absolute design rules and, in practice, these are not sufficient to rationally design very stable heteropolymers. We also study the effect of mutations on improving the stability of the model proteins, and demonstrate that it is possible to obtain a very stable heteropolymer from directed evolution of an initially unstable heteropolymer.

The distribution of residues in a polypeptide sequence is a determinant of aggregation optimized by evolution

It has been shown that the propensity of a protein to form amyloid-like fibrils can be predicted with high accuracy from the knowledge of its amino acid sequence. It has also been suggested, however, that some regions of the sequences are more important than others in determining the aggregation process. Here, we have addressed this issue by constructing a set of "sequence scrambled" variants of the first 29 residues of horse heart apomyoglobin (apoMb(1-29)), in which the sequence was modified while maintaining the same amino acid composition. The clustering of the most amyloidogenic residues in one region of the sequence was found to cause a marked increase of the elongation rate (k(agg)) and a remarkable shortening of the lag phase (t(lag)) of the fibril growth, as determined by far-UV circular dichroism and thioflavin T fluorescence. We also show that taking explicitly into consideration the presence of aggregation-promoting regions in the predictive methods results in a quantitative agreement between the theoretical and observed k(agg) and t(lag) values of the apoMb(1-29) variants. These results, together with a comparison between homologous segments from the family of globins, indicate the existence of a negative selection against the clustering of highly amyloidogenic residues in one or few regions of polypeptide sequences.

Signatures of hydrophobic collapse in extended proteins captured with force spectroscopy

We unfold and extend single proteins at a high force and then linearly relax the force to probe their collapse mechanisms. We observe a large variability in the extent of their recoil. Although chain entropy makes a small contribution, we show that the observed variability results from hydrophobic interactions with randomly varying magnitude from protein to protein. This collapse mechanism is common to highly extended proteins, including nonfolding elastomeric proteins like PEVK from titin. Our observations explain the puzzling differences between the folding behavior of highly extended proteins, from those folding after chemical or thermal denaturation. Probing the collapse of highly extended proteins with force spectroscopy allows separation of the different driving forces in protein folding.

Entropic criteria for protein folding derived from recurrences: six residues patch as the basic protein word

Some research has suggested that patches of six constitute an important amino acid window length in proteins for conveying information. We present database evidence that supports this conjecture, as well as additional recurrence-based data that characterization and quantification of these words affect the folding/aggregation features of proteins. Other indirect evidence is presented and discussed.

High polar content of long buried blocks of sequence in protein domains suggests selection against amyloidogenic non-polar sequences

Native protein structures achieve stability in part by burying hydrophobic side-chains. About 75% of all amino acid residues buried in protein interiors are non-polar. Buried residues are not uniformly distributed in protein sequences, but sometimes cluster as contiguous polypeptide stretches that run through the interior of protein domain structures. Such regions have an intrinsically high local sequence density of non-polar residues, creating a potential problem: local non-polar sequences also promote protein misfolding and aggregation into non-native structures such as the amyloid fibrils in Alzheimer's disease. Here we show that long buried blocks of sequence in protein domains of known structure have, on average, a lower content of non-polar amino acids (about 70%) than do isolated buried residues (about 80%). This trend is observed both in small and in large protein domains and is independent of secondary structure. Long, completely non-polar buried stretches containing many large side-chains are particularly avoided. Aspartate residues that are incorporated in long buried stretches were found to make fewer polar interactions than those in short stretches, hinting that they may be destabilizing to the native state. We suggest that evolutionary pressure is acting on non-native properties, causing buried polar residues to be placed at positions where they would break up aggregation-prone non-polar sequences, perhaps even at some cost to native state stability.