Simulation of formation of α-helices and β-hairpins in water-soluble proteins by the code-based physics method

One of the possible ways for a complete and final decision of the problem of the determination of three-dimensional structure of proteins from their amino acid sequence is simulation of protein three-dimensional structure formation. For the performance of this task it is suggested to use the code-based physics method developed by the author. In this article a simulation of the α-helix and β-hairpin formation in water-soluble proteins as a start of the realization of this plan is described. Results of the simulation are compared from experimental data for 14 proteins of no more than 50 amino acids and, therefore, with a small number of α-helices and β-strands (to meet limits of simulation process) and secondary structure predictions by the best current methods of protein secondary structure prediction, PSIpred, PORTER and PROFsec. The secondary structure of proteins, obtained as a result of the simulation of α-helix and β-hairpin formation by the code-based physics method, agrees completely with the experiment, while the secondary structure predicted by the PSIpred, PORTER, and PROFsec methods contains significant differences from the experimental data.     

The evolution of proteins from random amino acid sequences. I. Evidence from the lengthwise distribution of amino acids in modern protein sequences

Summary We examine in this paper one of the expected consequences of the hypothesis that modern proteins evolved from random heteropeptide sequences. Specifically, we investigate the lengthwise distributions of amino acids in a set of 1,789 protein sequences with little sequence identity using the run test statistic (r _o) of Mood (1940,Ann. Math. Stat. 11, 367–392). The probability density ofr _o for a collection of random sequences has mean=0 and variance=1 [the N(0,1) distribution] and can be used to measure the tendency of amino acids of a given type to cluster together in a sequence relative to that of a random sequence. We implement the run test using binary representations of protein sequences in which the amino acids of interest are assigned a value of 1 and all others a value of 0. We consider individual amino acids and sets of various combinations of them based upon hydrophobicity (4 sets), charge (3 sets), volume (4 sets), and secondary structure propensity (3 sets). We find that any sequence chosen randomly has a 90% or greater chance of having a lengthwise distribution of amino acids that is indistinguishable from the random expectation regardless of amino acid type. We regard this as strong support for the random-origin hypothesis. However, we do observe significant deviations from the random expectation as might be expected after billions years of evolution. Two important global trends are found: (1) Amino acids with a strong α-helix propensity show a strong tendency to cluster whereas those with β-sheet or reverse-turn propensity do not. (2) Clustered rather than evenly distributed patterns tend to be preferred by the individual amino acids and this is particularly so for methionine. Finally, we consider the problem of reconciling the random nature of protein sequences with structurally meaningful periodic “patterns” that can be detected by sliding-window, autocorrelation, and Fourier analyses. Two examples, rhodopsin and bacteriorhodopsin, show that such patterns are a natural feature of random sequences.     

Secondary structure perturbations in salt-induced protein precipitates

The secondary structure implications of precipitation induced by a chaotropic salt, KSCN, and a structure stabilizing salt, Na₂SO₄, were studied for twelve different proteins. α-helix and β-sheet content of precipitate and native structures were estimated from the analysis of amide I band Raman spectra. A statistical analysis of the estimated perturbations in the secondary structure contents indicated that the most significant event is the formation of β-sheet structures with a concomitant loss of α-helix on precipitation with KSCN. The conformational changes for each protein were also analyzed with respect to elements of primary, secondary and tertiary structure existing in the native protein; primary structure was quantified by the fractions of hydrophobic and charged amino acids, secondary structure by x-ray estimates of α-helix and β-sheet contents of native proteins and tertiary structure by the dipole moment and solvent-accessible surface area. For the KSCN precipitates, factors affecting β-sheet content included the fraction of charged amino acids in the primary sequence and the surface area. Changes in α-helix content were influenced by the initial helical content and the dipole moment. The enhanced β-sheet contents of precipitates observed in this work parallel protein structural changes occurring in other aggregative phenomena.     

Relationship of sidechain hydrophobicity and α-helical propensity on the stability of the single-stranded amphipathic α-helix

The aim of the present investigation is to determine the effect of α-helical propensity and sidechain hydrophobicity on the stability of amphipathic α-helices. Accordingly, a series of 18-residue amphipathic α-helical peptides has been synthesized as a model system where all 20 amino acid residues were substituted on the hydrophobic face of the amphipathic α-helix. In these experiments, all three parameters (sidechain hydrophobicity, α-helical propensity and helix stability) were measured on the same set of peptide analogues. For these peptide analogues that differ by only one amino acid residue, there was a 0.96 kcal/mole difference in α-helical propensity between the most (Ala) and the least (Gly) α-helical analogue, a 12.1-minute difference between the most (Phe) and the least (Asp) retentive analogue on the reversed-phase column, and a 32.3°C difference in melting temperatures between the most (Leu) and the least (Asp) stable analogue. The results show that the hydrophobicity and α-helical propensity of an amino acid sidechain are not correlated with each other, but each contributes to the stability of the amphipathic α-helix. More importantly, the combined effects of α-helical propensity and sidechain hydrophobicity at a ratio of about 2:1 had optimal correlation with α-helix stability. These results suggest that both α-helical propensity and sidechain hydrophobicity should be taken into consideration in the design of α-helical proteins with the desired stability.     

Denatured-state energy landscapes of a protein structural database reveal the energetic determinants of a framework model for folding

Position-specific denatured-state thermodynamics were determined for a database of human proteins by use of an ensemble-based model of protein structure. The results of modeling denatured protein in this manner reveal important sequence-dependent thermodynamic properties in the denatured ensembles as well as fundamental differences between the denatured and native ensembles in overall thermodynamic character. The generality and robustness of these results were validated by performing fold-recognition experiments, whereby sequences were matched with their respective folds based on amino acid propensities for the different energetic environments in the protein, as determined through cluster analysis. Correlation analysis between structure and energetic information revealed that sequence segments destined for β-sheet in the final native fold are energetically more predisposed to a broader repertoire of states than are sequence segments destined for α-helix. These results suggest that within the subensemble of mostly unstructured states, the energy landscapes are dominated by states in which parts of helices adopt structure, whereas structure formation for sequences destined for β-strand is far less probable. These results support a framework model of folding, which suggests that, in general, the denatured state has evolutionarily evolved to avoid low-energy conformations in sequences that ultimately adopt β-strand. Instead, the denatured state evolved so that sequence segments that ultimately adopt α-helix and coil will have a high intrinsic structure formation capability, thus serving as potential nucleation sites.     

Solution structure of P01, a natural scorpion peptide structurally analogous to scorpion toxins specific for apamin-sensitive potassium channel

The venom of the North African scorpion Androctonus mauretanicus mauretanicus possesses numerous highly active neurotoxins that specifically bind to various ion channels. One of these, P05, has been found to bind specifically to calcium-activated potassium channels and also to compete with apamin, a toxin extracted from bee venom. Besides the highly potent ones, several of these peptides (including that of P01) have been purified and been found to possess only a very weak, although significant, activity in competition with apamin. The amino acid sequence of P01 shows that it is shorter than P05 by two residues. This deletion occurs within an α-helix stretch (residues 5–12). This α-helix has been shown to be involved in the interaction of P05 with its receptor via two arginine residues. These two arginines are absent in the P01 sequence. Furthermore, a proline residue in position 7 of the P01 sequence may act as an α-helix breaker. We have determined the solution structure of P01 by conventional two-dimensional ¹H nuclear magnetic resonance and show that 1) the proline residue does not disturb the α-helix running from residues 5 to 12; 2) the two arginines are topologically replaced by two acidic residues, which explains the drop in activity; 3) the residual binding activity may be due to the histidine residue in position 9; and 4) the overall secondary structure is conserved, i.e., an α-helix running from residues 5 to 12, two antiparallel stretches of β-sheet (residues 15–20 and 23–27) connected by a type I′ β-turn, and three disulfide bridges connecting the α-helix to the β-sheet.     

Correlations in Protein Sequences and Property Codes

Correlation functions in large sets of non-homologous protein sequences are analysed. Finite size corrections are applied and fluctuations are estimated. As symbol sequences have to be mapped to sequences of numbers to calculate correlation functions, several property codes are tested as such mappings. We found hydrophobicity autocorrelation functions to be strongly oscillating. Another strong signal is the monotonously decaying α-helix propensity autocorrelation function. Furthermore, we detected signals corresponding to an alteration of positively and negatively charged residues at a distance of 3–4 amino acids.To look beyond the property codes gained by the methods of physical chemistry, mappings yielding a strong correlation signal are sought for using a Monte Carlo simulation. The mappings leading to strong signals are found to be related to hydrophobicity of α-helix propensity. A cluster analysis of the top scoring mappings leads to two novel property codes. These two property codes are gained from sequence data only. They turn out to be similar to known property codes for hydrophobicity or polarity.     

Analysis of protein chameleon sequence characteristics

Conversion of local structural state of a protein from an α-helix to a β-strand is usually associated with a major change in the tertiary structure. Similar changes were observed during the self assembly of amyloidogenic proteins to form fibrils, which are implicated in severe diseases conditions, e.g., Alzheimer disease. Studies have emphasized that certain protein sequence fragments known as chameleon sequences do not have a strong preference for either helical or the extended conformations. Surprisingly, the information on the local sequence neighborhood can be used to predict their secondary at a high accuracy level. Here we report a large scale-analysis of chameleon sequences to estimate their propensities to be associated with different local structural states such as α -helices, β-strands and coils. With the help of the propensity information derived from the amino acid composition, we underline their complexity, as more than one quarter of them prefers coil state over to the regular secondary structures. About half of them show preference for both α-helix and β-sheet conformations and either of these two states is favored by the rest.     

肽键的统计分析和蛋白质的二级结构

 本文对蛋白质序列的肽键进行了统计分析,计算了二肽构象参数P_α、P_β、P_c和三肽构象参数Q_α、Q_β、Q_c。在此基础上提出了由氨基酸序列预测二级结构的规则。预测的正确率达90％,优于Chou-Fasman方法。这个结果表明二肽(三肽)关联在形成蛋白质二级结构中具有明显的重要性。     

小麦多聚半乳糖醛酸酶抑制蛋白的部分结构

为了弄清小麦多聚半乳糖醛酸酶抑制蛋白 (polygalacturonase inhibitingprotein ,PGIP)的作用机制 ,并为其在基因工程中的应用提供依据 ,对其结构进行了研究 .用Edman降解法测得小麦PGIP的N端序列为Lys Pro Leu Leu Thr Lys Ile Thr Lys Gly Ala Ala Ser Thr .用CD谱研究其二级结构 ,发现小麦PGIP天然态含有 4 3 7%的 β折叠和 13 1%的α螺旋 .酸碱和温度变性引起了二级结构改变 .不完全变性阶段 ,二级结构的变化表现为α螺旋无明显变化 ,β折叠遭到破坏 ;活性完全丧失阶段 ,β折叠变化很小 ,α螺旋含量明显减少 .用NR R(非还原 还原 )双向对角线SDS PAGE鉴定出小麦PGIP含有链内二硫键 .用去糖基化法确证了小麦PGIP的糖含量为 2 2 %.小麦PGIP与双子叶植物PGIP相比 ,一级结构差异较大 ,同源性由 36 %变为 9%;二级结构相似 ,都是高 β 折叠的蛋白 ;均具有链内二硫键 ;在糖含量上也相似 .研究结果为进一步弄清小麦PGIP作用机理打下了基础 ,同时对于植物抗赤霉病基因工程具有重要意义 .     

Alpha helical structures in the leader sequence of human GLUD2 glutamate dehydrogenase responsible for mitochondrial import

Human glutamate dehydrogenase (hGDH) exists in two highly homologous isoforms with a distinct regulatory and tissue expression profile: a housekeeping hGDH1 isoprotein encoded by the GLUD1 gene and an hGDH2 isoenzyme encoded by the GLUD2 gene. There is evidence that both isoenzymes are synthesized as pro-enzymes containing a 53 amino acid long N-terminal leader peptide that is cleaved upon translocation into the mitochondria. However, this GDH signal peptide is substantially larger than that of most nuclear DNA-encoded mitochondrial proteins, the leader sequence of which typically contains 17-35 amino acids and they often form a single amphipathic α-helix. To decode the structural elements that are essential for the mitochondrial targeting of human GDHs, we performed secondary structure analyses of their leader sequence. These analyses predicted, with 82% accuracy, that both leader peptides are positively charged and that they form two to three α-helices, separated by intermediate loops. The first α-helix of hGDH2 is strongly amphipathic, displaying both a positively charged surface and a hydrophobic plane. We then constructed GLUD2-EGFP deletion mutants and used them to transfect three mammalian cell lines (HEK293, COS 7 and SHSY-5Y). Confocal laser scanning microscopy, following co-transfection with pDsRed2-Mito mitochondrial targeting vector, revealed that deletion of the entire leader sequence prevented the enzyme from entering the mitochondria, resulting in its retention in the cytoplasm. Deletion of the first strongly amphipathic α-helix only was also sufficient to prevent the mitochondrial localization of the truncated protein. Moreover, truncated leader sequences, retaining the second and/or the third putative α-helix, failed to restore the mitochondrial import of hGDH2. As such, the first N-terminal alpha helical structure is crucial for the mitochondrial import of hGDH2 and these findings may have implications in understanding the evolutionary mechanisms that led to the large mitochondrial targeting signals of human GDHs.     

Intrinsic secondary structure propensities of the amino acids,using statistical ϕ–ψ matrices: Comparison with experimental scales

Today there are several different experimental scales for the intrinsic α-helix as well as β-strand, propensities of the 20 amino acids obtained from the thermodynamic analysis of various model systems. These scales do not compare well with those extracted from statistical analysis of three-dimensional structure databases. Possible explanations for this could be the limited size of the databases used, the definitions of intrinsic propensities, or the theoretical approach. Here we report a statistical determination of α-helix and β-strand propensities derived from the analysis of a database of 279 three-dimensional structures. Contrary to what has been generally done, we have considered a particular residue as in α-helix or β-strand conformation by looking only at its dihedral angles (?–ψ matrices). Neither the identity nor the conformation of the surrounding residues in the amino acid sequence has been taken into consideration. Pseudoenergy empirical scales have been calculated from the statistical propensities. These scales agree very well with the experimental ones in relative and absolute terms. Moreover, its correlation with the average of the experimental scales for α-helix or β-strand is as good as the correlations of the individual experimental scales with the average. These results show that by using a large enough database and a proper definition for the secondary structure propensities, it is possible to obtain a scale as good as any of experimental origin. Interestingly the ?–ψ analysis of the Ramachandran plot suggests that the amino acids could have different β-strand propensities in different subregions of the β-strand area. © 1994 Wiley-Liss, Inc.     

Electronic Properties of the Amino Acid Side Chains Contribute to the Structural Preferences in Protein Folding

Abstract

A database of 118 non-redundant proteins was examined to determine the preferences of amino acids for secondary structures: α-helix, β-strand and coil conformations. To better understand how the physicochemical properties of amino acid side chains might influence protein folding, several new scales have been suggested for quantifying the electronic effects of amino acids. These include the pKa at the amino group, localized effect substituent constants (eσ), and a composite of these two scales (ε). Amino acids were also classified into 5 categories on the basis of their electronic properties: O (strong electron donor), U (weak donor), Z (ambivalent), B (weak electron acceptor), and X (strong acceptor). Certain categories of amino acid appeared to be critical for particular conformations, e.g., O and U-type residues for α-helix formation. Pairwise analysis of the database according to these categories revealed significant context effects in the structural preferences. In general, the propensity of an amino acid for a particular conformation was related to the electronic features of the side chain. Linear regression analyses revealed that the electronic properties of amino acids contributed about as much to the folding preferences as hydrophobicity, which is a well-established determinant of protein folding. A theoretical model has been proposed to explain how the electronic properties of the side chain groups might influence folding along the peptide backbone.     

Folding type-specific secondary structure propensities of amino acids,derived from α-helical, β-sheet, α/β, and α+β proteins of known structures

Folding type-specific secondary structure propensities of 20 naturally occurring amino acids have been derived from α-helical, β-sheet, α/β, and α+β proteins of known structures. These data show that each residue type of amino acids has intrinsic propensities in different regions of secondary structures for different folding types of proteins. Each of the folding types shows markedly different rank ordering, indicating folding type-specific effects on the secondary structure propensities of amino acids. Rigorous statistical tests have been made to validate the folding type-specific effects. It should be noted that α and β proteins have relatively small α-helices and β-strands forming propensities respectively compared with those of α+β and α/β proteins. This may suggest that, with more complex architectures than α and β proteins, α+β and α/β proteins require larger propensities to distinguish from interacting α-helices and β-strands. Our finding of folding type-specific secondary structure propensities suggests that sequence space accessible to each folding type may have differing features. Differing sequence space features might be constrained by topological requirement for each of the folding types. Almost all strong β-sheet forming residues are hydrophobic in character regardless of folding types, thus suggesting the hydrophobicities of side chains as a key determinant of β-sheet structures. In contrast, conformational entropy of side chains is a major determinant of the helical propensities of amino acids, although other interactions such as hydrophobicities and charged interactions cannot be neglected. These results will be helpful to protein design, class-based secondary structure prediction, and protein folding. © 1998 John Wiley & Sons, Inc. Biopoly 45: 35–49, 1998     

An amino acid packing code for α-helical structure and protein design

This work demonstrates that all packing in α-helices can be simplified to repetitive patterns of a single motif: the knob-socket. Using the precision of Voronoi Polyhedra/Delauney Tessellations to identify contacts, the knob-socket is a four-residue tetrahedral motif: a knob residue on one α-helix packs into the three-residue socket on another α-helix. The principle of the knob-socket model relates the packing between levels of protein structure: the intra-helical packing arrangements within secondary structure that permit inter-helix tertiary packing interactions. Within an α-helix, the three-residue sockets arrange residues into a uniform packing lattice. Inter-helix packing results from a definable pattern of interdigitated knob-socket motifs between two α-helices. Furthermore, the knob-socket model classifies three types of sockets: (1) free, favoring only intra-helical packing; (2) filled, favoring inter-helical interactions; and (3) non, disfavoring α-helical structure. The amino acid propensities in these three socket classes essentially represent an amino acid code for structure in α-helical packing. Using this code, we used a novel yet straightforward approach for the design of α-helical structure to validate the knob-socket model. Unique sequences for three peptides were created to produce a predicted amount of α-helical structure: mostly helical, some helical, and no helix. These three peptides were synthesized, and helical content was assessed using CD spectroscopy. The measured α-helicity of each peptide was consistent with the expected predictions. These results and analysis demonstrate that the knob-socket motif functions as the basic unit of packing and presents an intuitive tool to decipher the rules governing packing in protein structure.     

Molecular Dynamics Simulations of Peptides from the Central Domain of Smooth Muscle Caldesmon

Abstract

The central domain of smooth muscle caldesmon contains a highly charged region consisting of ten 13-residue repeats. Experimental evidence obtained from the intact protein and fragments thereof suggests that this entire region forms a single stretch of stable α-helix. We have carried out molecular dynamics simulations on peptides consisting of one, two and three repeats to examine the mechanism of α-helical stability of the central domain at the atomic level. All three peptides show high helical stability on the timescale of the MD simulations. Deviations from α-helical structure in all the simulations arise mainly from the formation of long stretches of π-helix. Interconversion between α-helical and π-helical conformations occurs through insertion of water molecules into α-helical hydrogen bonds and subsequent formation of reverse turns. The α-helical structure is stabilized by electrostatic interactions (salt bridges) between oppositely charged sidechains with i,i+4 spacings, while the π-helix is stabilized by i,i+5 salt bridge interactions. Possible i,i+3 salt bridges are of minor importance. There is a strong preference for salt bridges with a Glu residue N-terminal to a basic sidechain as compared to the opposite orientation. In the double and triple repeat peptides, strong i,i+4 salt bridges exist between the last Glu residue of one repeat and the first Lys residue of the next. This demonstrates a relationship between the repetitive nature of the central domain sequence and its ability to form very long stretches of α-helical structure.     

Secondary structure of proteins associated in thin films

The solid state secondary structure of myoglobin, RNase A, concanavalin A (Con A), poly(L -lysine), and two linear heterooligomeric peptides were examined by both far-uv CD spectroscopy¹ and by ir spectroscopy. The proteins associated from water solution on glass and mica surfaces into noncrystalline, amorphous films, as judged by transmission electron microscopy of carbon-platinum replicas of surface and cross-fractured layer. The association into the solid state induced insignificant changes in the amide CD spectra of all α-helical myoglobin, decreased the molar ellipticity of the α/β RNase A, and increased the molar ellipticity of all-β Con A with no change in the positions of the bands' maxima. High-temperature exposure of the films induced permanent changes in the conformation of all proteins, resulting in less α-helix and more β-sheet structure. The results suggest that the protein α-helices are less stable in films and that the secondary structure may rearrange into β-sheets at high temperature. Two heterooligomeric peptides and poly (L -lysine), all in solution at neutral pH with “random coil” conformation, formed films with variable degrees of their secondary structure in β-sheets or β-turns. The result corresponded to the protein-derived Chou-Fasman amino acid propensities, and depended on both temperature and solvent used. The ir and CD spectra correlations of the peptides in the solid state indicate that the CD spectrum of a “random” structure in films differs from random coil in solution. Formic acid treatment transformed the secondary structure of the protein and peptide films into a stable α-helix or β-sheet conformations. The results indicate that the proteins aggregate into a noncrystalline, glass-like state with preserved secondary structure. The solid state secondary structure may undergo further irreversible transformations induced by heat or solvent. © 1993 John Wiley & Sons, Inc.     

Conformational properties of five peptides corresponding to the entire sequence of glutathione transferase domain II

Five peptides matching the helices alpha4, alpha5, alpha6, alpha7, and alpha8, spanning the entire sequence of domain II of pG-STP1-1, have been synthesized and their conformations analyzed by far-UV CD spectroscopy. The results show that a5, a7, and a8 peptides are unstructured in water/2,2,2-trifluoroethanol (TFE) solutions. The a4-peptide also adopts random conformations in aqueous solvent. Moreover, the relative low helical content (20%), estimated for this peptide in the presence of 30% (v/v) TFE, suggests that the sequence of this protein fragment does not possess sufficient information for a strong helical propensity. On the contrary, the synthesized a6 peptide, in the presence of TFE, showed a relevant structural autonomy with a helical content (41%) which was significantly higher than that estimated, under the same conditions, for all other peptides. More in general in the presence of solvents less polar than water, the isolated a6 peptide shows the same helical conformation adopted by the corresponding alpha6-helix in the hydrophobic core of the protein. A n-capping box motif, strictly conserved at the N-terminal of the alpha6-helix of all GST and related protein including eucaryotic translation elongation factor (EF1gamma) and the yeast prion protein Ure2, plays an important role in the alpha-helix nucleation and stability of this protein fragment. The results suggest that the alpha6-helix might represent a nucleation site of GST folding and that the helical conformation of this region of the protein is an important requirement during earlier events of GST refolding.     

Automatic identification of secondary structure in globular proteins

A computer program is used to analyse automatically and objectively the atomic co-ordinates of a large number of globular proteins in order to identify the regions of α-helix, β-sheet and reverse-turn secondary structure. Several different criteria for the assignment of secondary structure are tested for accuracy, reproducibility and efficiency. The most successful criterion, which is based on patterns of peptide hydrogen bonds, inter-C^α distances and inter-C^α torsion angles, is used to find the secondary structure of all the proteins studied. The accuracy of the derived assignments is assessed by comparing them with the secondary structure reported in the literature for each protein. The reliability of the methods is assessed by comparing the secondary structures derived from the independently determined sets of co-ordinates available for some proteins.We provide the first objective and consistent compilation of α-helix, β-sheet and reverse-turn secondary structure in almost all globular proteins of known tertiary structure. These data will be invaluable for analysing the relative tendencies of different amino acids to occur in different types of secondary structure, for analysing the regularity of the secondary structure itself, and for analysing how the pieces of secondary structure fit together to form the globular tertiary structure of each protein.