Coil Library Research Articles

Randomizing of Oligopeptide Conformations by Nearest Neighbor Interactions between Amino Acid Residues.

Flory’s random coil model assumes that conformational fluctuations of amino acid residues in unfolded poly(oligo)peptides and proteins are uncorrelated (isolated pair hypothesis, IPH). This implies that conformational energies, entropies and solvation free energies are all additive. Nearly 25 years ago, analyses of coil libraries cast some doubt on this notion, in that they revealed that aromatic, but also β-branched side chains, could change the 3J(HNHCα) coupling of their neighbors. Since then, multiple bioinformatical, computational and experimental studies have revealed that conformational propensities of amino acids in unfolded peptides and proteins depend on their nearest neighbors. We used recently reported and newly obtained Ramachandran plots of tetra- and pentapeptides with non-terminal homo- and heterosequences of amino acid residues to quantitatively determine nearest neighbor coupling between them with a Ising type model. Results reveal that, depending on the choice of amino acid residue pairs, nearest neighbor interactions either stabilize or destabilize pairs of polyproline II and β-strand conformations. This leads to a redistribution of population between these conformations and a reduction in conformational entropy. Interactions between residues in polyproline II and turn(helix)-forming conformations seem to be cooperative in most cases, but the respective interaction parameters are subject to large statistical errors.

Analyses of experiment based ramachandran plots of tri-, tetra- and pentapeptides reveal residue dependent interactions between neighbors

Flory's canonical random coil model is based on the assumption that conformational fluctuations of amino acid residues in unfolded poly(oligo)peptides and proteins are uncorrelated (isolated pair hypothesis, IPH). It implies that conformational energies, entropies, and solvation free energies are all additive. Nearly 25 years ago, analyses of coil libraries casted some doubt on this notion in that they revealed that aromatic residues could change the 3J(HNHCα) coupling of their neighbors. Since then multiple lines of bioinformatical, computational and lately also experimental evidence indicate that the conformational propensities of amino acids in unfolded peptides and proteins depend on their nearest neighbors and possibly even on the nature of the second neighbor.

Intrinsic Conformational Preferences of the Charged Amino Acids in Disordered Proteins

Conformational equilibria in the unfolded states of proteins have many important biological roles, from regulating how some proteins fold and maintain structural stability, to describing the macromolecular details of intrinsically disordered proteins (IDPs), a protein class that does not adopt physiologically stable structures and instead utilizes unfolded states to facilitate their functions. Recently, to better understand the structural properties of IDPs, we analyzed both the sequence dependence to the mean hydrodynamic size of IDPs in water, as well as the impact of heat on the coil dimensions, showing that the sequence dependence and thermodynamic energies associated with intrinsic biases for the polyproline II (PPII) backbone conformation could be obtained. This result is important because PPII is used biologically for protein–protein and protein–nucleic acid interactions and thus has a role in molecular recognition. Experiments that evaluate how the hydrodynamic size changes with compositional changes in the IDP revealed amino acid-specific preferences for PPII that were in excellent quantitative agreement with calorimetry-measured values from small unfolded peptides and also those inferred by a survey of the protein coil library. Here, a set of charge-substitution experiments were used to measure the intrinsic preferences of the charged amino acids (i.e., lysine, arginine, glutamic acid, and aspartic acid) for the PPII backbone conformation, the results of which provide insight into how long-range charge-charge interactions and short-range effects, such as hydration and sterics, can modulate the structural and dynamical properties of IDPs, an increasingly important protein class in cell function.

Structural and Energetic Characterization of the Denatured State from the Perspectives of Peptides, the Coil Library, and Intrinsically Disordered Proteins.

The α and polyproline II (PPII) basins are the two most populated regions of the Ramachandran map when constructed from the protein coil library, a widely used denatured state model built from the segments of irregular structure found in the Protein Data Bank. This indicates the α and PPII conformations are dominant components of the ensembles of denatured structures that exist in solution for biological proteins, an observation supported in part by structural studies of short, and thus unfolded, peptides. Although intrinsic conformational propensities have been determined experimentally for the common amino acids in short peptides, and estimated from surveys of the protein coil library, the ability of these intrinsic conformational propensities to quantitatively reproduce structural behavior in intrinsically disordered proteins (IDPs), an increasingly important class of proteins in cell function, has thus far proven elusive to establish. Recently, we demonstrated that the sequence dependence of the mean hydrodynamic size of IDPs in water and the impact of heat on the coil dimensions, provide access to both the sequence dependence and thermodynamic energies that are associated with biases for the α and PPII backbone conformations. Here, we compare results from peptide-based studies of intrinsic conformational propensities and surveys of the protein coil library to those of the sequence-based analysis of heat effects on IDP hydrodynamic size, showing that a common structural and thermodynamic description of the protein denatured state is obtained.

Systematic Differences between Current Molecular Dynamics Force Fields To Represent Local Properties of Intrinsically Disordered Proteins.

The prevalence of intrinsically disordered proteins (IDPs) and protein regions in structural biology has prompted the recent development of molecular dynamics (MD) force fields for the more realistic representations of such systems. Using experimental nuclear magnetic resonance backbone scalar 3J-coupling constants of the intrinsically disordered proteins α-synuclein and amyloid-β in their native aqueous environment as a metric, we compare the performance of four recent MD force fields, namely, AMBER ff14SB, CHARMM C36m, AMBER ff99SB-disp, and AMBER ff99SBnmr2, by partitioning the polypeptides into an overlapping series of heptapeptides for which a cumulative total of 276 μs MD simulations were performed. The results show substantial differences between the different force fields at the individual residue level. Except for ff99SBnmr2, the force fields systematically underestimate the scalar 3J(HN,Hα)-couplings due to an underrepresentation of β-conformations and an overrepresentation of either α- or PPII conformations. The study demonstrates that the incorporation of coil library information in modern MD force fields, as shown here for ff99SBnmr2, provides substantially improved performance and more realistic sampling of the local backbone dihedral angles of IDPs as reflected by the good accuracy of the computed scalar 3J(HN,Hα)-couplings with less than 0.5 Hz error. Such force fields will enable a better understanding of how structural dynamics and thermodynamics influence the IDP function. Although the methodology based on heptapeptides used here does not allow the assessment of potential intramolecular long-range interactions, its computational affordability permits well-converged simulations that can be easily parallelized. This should make the quantitative validation of intrinsic disorder observed in MD simulations of polypeptides with experimental scalar J-couplings widely applicable.

Heat Effects on Coil Hydrodynamic Size Reveal the Energetics of Denatured State Conformational Bias

Conformational equilibria in the protein denatured state has key roles regulating folding, stability, and function. Yet detailed information on the denatured state has proven elusive because of the low solubility of unfolded protein and the difficulty in deciphering the character of individual conformations from the ensemble average. To better understand the structural preferences of the denatured state, we have analyzed both the sequence dependence to the mean hydrodynamic size of disordered proteins in water and the impact of heat on the coil dimensions, showing that the sequence dependence and thermodynamic energies associated with intrinsic biases for the α and PPII backbone conformations can be obtained. These results are important for two reasons. First, survey of the protein coil library reveals that the α and PPII basins of the Ramachandran map are the dominant structural features of the protein denatured state. Our results demonstrate how to measure the temperature dependence to the α and PPII populations. Second, it has long been known that the dimensions of denatured proteins in 6 M guanidinium chloride are successfully predicted by the random coil model, irrespective of numerous experiments showing they can maintain residual structures. Hence, the protein hydrodynamic size is thought to give poor structural detail. Our results show that this is not the case for unfolded proteins in water. Rather, surprisingly, the hydrodynamic size of the unfolded state is found to be an effective reporter on the extent of the biases for the α and PPII backbone conformations.

Balanced Amino-Acid-Specific Molecular Dynamics Force Field for the Realistic Simulation of Both Folded and Disordered Proteins.

Molecular dynamics (MD) simulations provide a unique atomic-level description of the structure and dynamics of proteins, which is essential for the mechanistic understanding of protein interactions and function in living organisms. However, traditional MD force fields that are optimized for folded proteins often generate overly compact structures and incorrect characteristics of intrinsically disordered proteins (IDPs) and protein regions (IDRs), thereby limiting the quantitative insights that can be gained from MD simulations. We introduce the residue-specific protein force field, ff99SBnmr2, which is derived from ff99SBnmr1 by balancing the backbone dihedral angle potentials in a residue-specific manner to quantitatively reproduce dihedral angle distributions from an experimental coil library. The new force field substantially improves the backbone conformational ensembles of disordered proteins, protein regions, and peptides while keeping well-defined protein structures stable and accurate. This balanced new force field should enable a myriad of applications that require quantitative descriptions of IDPs, IDRs, loop dynamics, and folding/unfolding equilibria in the presence and absence of interaction partners.

Impact of Heat on Coil Hydrodynamic Size Yields the Energetics of Denatured State Conformational Bias.

Conformational equilibria in the protein denatured state have key roles regulating folding, stability, and function. The extent of conformational bias in the protein denatured state under folding conditions, however, has thus far provenelusive to quantify, particularly with regard to its sequence dependence and energetic character. To better understand the structural preferences of the denatured state, we analyzed both the sequence dependence to the mean hydrodynamic size of disordered proteins in water and the impact of heat on the coil dimensions, showing that the sequence dependence and thermodynamic energies associated with intrinsic biases for the α and polyproline II (PPII) backbone conformations can be obtained. Experiments that evaluate how the hydrodynamic size changes with compositional changes in the protein reveal amino acid specific preferences for PPII that are in good quantitative agreement with calorimetry-measured values from unfolded peptides and those inferred by survey of the protein coil library. At temperatures above 25 °C, the denatured state follows the predictions of a PPII-dominant ensemble. Heat effects oncoil hydrodynamic size indicate the α bias is comparable to the PPII bias at cold temperatures. Though historically thought to give poor resolution tostructural details, the hydrodynamic size of the unfolded state is found to be an effective reporter on the extent of the biases for the α and PPII backbone conformations.

Developments and Applications of Coil-Library-Based Residue-Specific Force Fields for Molecular Dynamics Simulations of Peptides and Proteins.

Molecular dynamics (MD) simulation has become a powerful tool for studying the structures and functional mechanisms of biomolecules, and its reliability crucially depends on the accuracy of underlying force fields. This perspective describes our recent efforts to develop more accurate protein force fields by improving the description of intrinsic conformational preferences of amino acid residues using residue-specific dihedral-angle-related parameters. Both backbone and side-chain conformational distributions and their coupling were optimized to fit those from a protein coil library. The resulting force fields RSFF1 and RSFF2 have been found to be more accurate than popular protein force fields, in reproducing experimental structural data of various peptides and proteins. They have also been successfully used in studying folding mechanisms and refinement of structure models. Further methodology developments related to intrinsically disordered proteins (RSFF2+) and a more universal implementation (RSFF2C) based on CMAP potentials are also described.

Experimentally Derived and Computationally Optimized Backbone Conformational Statistics for Blocked Amino Acids.

Experimentally derived, amino acid specific backbone dihedral angle distributions are invaluable for modeling data-driven conformational equilibria of proteins and for enabling quantitative assessments of the accuracies of molecular mechanics force fields. The protein coil library that is extracted from analysis of high-resolution structures of proteins has served as a useful proxy for quantifying intrinsic and context-dependent conformational distributions of amino acids. However, data that go into coil libraries will have hidden biases, and ad hoc procedures must be used to remove these biases. Here, we combine high-resolution biased information from protein structural databases with unbiased low-resolution information from spectroscopic measurements of blocked amino acids to obtain experimentally derived and computationally optimized coil-library landscapes for each of the 20 naturally occurring amino acids. Quantitative descriptions of conformational distributions require parsing of data into conformational basins with defined envelopes, centers, and statistical weights. We develop and deploy a numerical method to extract conformational basins. The weights of conformational basins are optimized to reproduce quantitative inferences drawn from spectroscopic experiments for blocked amino acids. The optimized distributions serve as touchstones for assessments of intrinsic conformational preferences and for quantitative comparisons of molecular mechanics force fields.

Universal Implementation of a Residue-Specific Force Field Based on CMAP Potentials and Free Energy Decomposition

The coupling between neighboring backbone ϕ and ψ dihedral angles (torsions) has been well appreciated in protein force field development, as in correction map (CMAP) potentials. However, although preferences of backbone torsions are significantly affected by side-chain conformation, there has been no easy way to optimize this coupling. Herein, we prove that the three-dimensional (3D) free energy hypersurface of joint (ϕ, ψ, χ1) torsions can be decomposed into three separated 2D surfaces. Thus, each of the 2D torsional surfaces can be efficiently and automatically optimized using a CMAP potential. This strategy is then used to reparameterize an AMBER force field such that the resulting χ1-dependent backbone conformational preference can agree excellently with the reference protein coil library statistics. In various validation simulations (including the folding of seven peptides/proteins, backbone dynamics of three folded proteins, and two intrinsically disordered peptides), the new RSFF2C (residue-specific force field with CMAP potentials) force field gives similar or better performance compared with RSFF2. This strategy can be used to implement our RSFF force fields into a variety of molecular dynamics packages easily.

Prediction of nearest neighbor effects on backbone torsion angles and NMR scalar coupling constants in disordered proteins.

Using fine-tuned hydrogen bonding criteria, a library of coiled peptide fragments has been generated from a large set of high-resolution protein X-ray structures. This library is shown to be an improved representation of ϕ/ψ torsion angles seen in intrinsically disordered proteins (IDPs). The ϕ/ψ torsion angle distribution of the library, on average, provides good agreement with experimentally observed chemical shifts and 3 JHN-Hα coupling constants for a set of five disordered proteins. Inspection of the coil library confirms that nearest-neighbor effects significantly impact the ϕ/ψ distribution of residues in the coil state. Importantly, 3 JHN-Hα coupling constants derived from the nearest-neighbor modulated backbone ϕ distribution in the coil library show improved agreement to experimental values, thereby providing a better way to predict 3 JHN-Hα coupling constants for IDPs, and for identifying locations that deviate from fully random behavior.

Construction and comparison of the statistical coil states of unfolded and intrinsically disordered proteins from nearest-neighbor corrected conformational propensities of short peptides.

Assessing the influence of nearest neighbors on the conformational ensemble of amino acid residues in unfolded and intrinsically disordered proteins and peptides is pivotal for a thorough understanding of the statistical coil state of unfolded proteins as well as of the energetics of the folding process. Research aimed at exploring nearest neighbor interactions has mostly focused on the analysis of restricted coil libraries that reflect conformational distributions in loops connecting more regular secondary structure segments. Recently, however, Toal et al. reported an experimentally based structural analysis of selected xy-pairs in GxyG tetrapeptides, which revealed quantitative information about conformational changes induced by nearest-neighbor interactions (Eur. J. Chem., 2015, 21, 5173-5192). Here, we perform analyses of Ramachandran plots of xy-pairs in GxyG and in coil libraries (Ting et al., PLOS CompBiol, 2010, 6, e1000763) using Hellinger distances as a quantitative measure of dissimilarities between Ramachandran distributions. Our analysis reveals that nearest-neighbor effects inferred from the above coil library are much less pronounced than corresponding structural changes observed for GxyG peptides. To determine whether nearest-neighbor induced conformational changes observed for GxyG can be utilized for the analysis of unfolded proteins, we analyzed sets of 3J(HHHα) coupling constants of three different unfolded proteins, namely the 130-residue fragment of the Staphylococcus aureus fibronectin-binding protein (FnBPc), denatured hen lysozyme, and the htau40 protein. For the first two proteins we found statistically meaningful correlations between predicted nearest-neighbor induced changes of 3J(HHHα) and experimentally observed deviations from corresponding coupling constants of GxG peptides in water, which we used as reference system with minimal nearest-neighbor interactions. This observation is in line with the NMR based understanding of these proteins being predominantly statistical coils. For htau40, however, which is known to exhibit residual structure and large deviations form statistical coil expectations, these correlations are weak or absent. Our results thus underscore the importance of nearest-neighbor interactions for a complete physical description of an ideal statistical coil state of a protein.

MERA: a webserver for evaluating backbone torsion angle distributions in dynamic and disordered proteins from NMR data.

MERA (Maximum Entropy Ramachandran map Analysis from NMR data) is a new webserver that generates residue-by-residue Ramachandran map distributions for disordered proteins or disordered regions in proteins on the basis of experimental NMR parameters. As input data, the program currently utilizes up to 12 different parameters. These include three different types of short-range NOEs, three types of backbone chemical shifts ((15)N, (13)C(α), and (13)C'), six types of J couplings ((3)JHNHα, (3)JC'C', (3)JC'Hα, (1)JHαCα, (2)JCαN and (1)JCαN), as well as the (15)N-relaxation derived J(0) spectral density. The Ramachandran map distributions are reported in terms of populations of their 15°×15° voxels, and an adjustable maximum entropy weight factor is available to ensure that the obtained distributions will not deviate more from a newly derived coil library distribution than required to account for the experimental data. MERA output includes the agreement between each input parameter and its distribution-derived value. As an application, we demonstrate performance of the program for several residues in the intrinsically disordered protein α-synuclein, as well as for several static and dynamic residues in the folded protein GB3.

Molecular Dynamics Simulations of 441 Two-Residue Peptides in Aqueous Solution: Conformational Preferences and Neighboring Residue Effects with the Amber ff99SB-ildn-NMR Force Field.

Understanding the intrinsic conformational preferences of amino acids and the extent to which they are modulated by neighboring residues is a key issue for developing predictive models of protein folding and stability. Here we present the results of 441 independent explicit-solvent MD simulations of all possible two-residue peptides that contain the 20 standard amino acids with histidine modeled in both its neutral and protonated states. (3)J(HNHα) coupling constants and δ(Hα) chemical shifts calculated from the MD simulations correlate quite well with recently published experimental measurements for a corresponding set of two-residue peptides. Neighboring residue effects (NREs) on the average (3)J(HNHα) and δ(Hα) values of adjacent residues are also reasonably well reproduced, with the large NREs exerted experimentally by aromatic residues, in particular, being accurately captured. NREs on the secondary structure preferences of adjacent amino acids have been computed and compared with corresponding effects observed in a coil library and the average β-turn preferences of all amino acid types have been determined. Finally, the intrinsic conformational preferences of histidine, and its NREs on the conformational preferences of adjacent residues, are both shown to be strongly affected by the protonation state of the imidazole ring.

Conformational Entropies of Unfolded Peptides: The Source of a Realistic Estimation of the Entropy of Unfolded Peptides and Proteins

All theories of protein folding agree in suggesting that the folded state is promoted by a gain in enthalpy, whereas the unfolded state is favored by entropy. The entropy of the latter and thus the entropic loss associated with protein folding is generally estimated by utilizing the rather random conformational distributions of the so-called random coil model which assumes that all amino acid residues sample the entire sterically allowed region of the Ramachandran space. However, recent spectroscopic studies as well as analyses of coil libraries have revealed residue specific and generally less pronounced conformational sampling than suggested by the random coil model. These findings imply that unfolded peptides and proteins carry less entropy than expected. We used experimentally obtained Ramachandran plots of amino acid residues in GxG and GxyG host guest systems (x,y,: selected amino acid residues) in water to calculate the Boltzmann entropy of individual residues in the absence and presence of nearest neighbor interactions. Our results suggest that entropic chains of polypeptides exhibit conformational entropies which at room temperature contribute 3-5 kJ/mol less to the Gibbs/Helmholtz free energy. This suggest that classical random coil distributions lead to a substantial overestimation of conformational entropies. Thermodynamic data inferred from the temperature dependence of 1H 3J(HNHα) coupling constants and UVCD spectra of the investigated peptides allowed an estimation of the temperature dependence of the conformational entropies and a comparison with changes of the enthalpies and entropies of solvation.

Residue-specific force field based on protein coil library. RSFF2: modification of AMBER ff99SB.

Recently, we developed a residue-specific force field (RSFF1) based on conformational free-energy distributions of the 20 amino acid residues from a protein coil library. Most parameters in RSFF1 were adopted from the OPLS-AA/L force field, but some van der Waals and torsional parameters that effectively affect local conformational preferences were introduced specifically for individual residues to fit the coil library distributions. Here a similar strategy has been applied to modify the Amber ff99SB force field, and a new force field named RSFF2 is developed. It can successfully fold α-helical structures such as polyalanine peptides, Trp-cage miniprotein, and villin headpiece subdomain and β-sheet structures such as Trpzip-2, GB1 β-hairpins, and the WW domain, simultaneously. The properties of various popular force fields in balancing between α-helix and β-sheet are analyzed based on their descriptions of local conformational features of various residues, and the analysis reveals the importance of accurate local free-energy distributions. Unlike the RSFF1, which overestimates the stability of both α-helix and β-sheet, RSFF2 gives melting curves of α-helical peptides and Trp-cage in good agreement with experimental data. Fitting to the two-state model, RSFF2 gives folding enthalpies and entropies in reasonably good agreement with available experimental results.

A maximum entropy approach to the study of residue-specific backbone angle distributions in α-synuclein, an intrinsically disordered protein.

α-Synuclein is an intrinsically disordered protein of 140 residues that switches to an α-helical conformation upon binding phospholipid membranes. We characterize its residue-specific backbone structure in free solution with a novel maximum entropy procedure that integrates an extensive set of NMR data. These data include intraresidue and sequential H(N) − H(α) and H(N) − H(N) NOEs, values for (3) JHNHα, (1) JHαCα, (2) JCαN, and (1) JCαN, as well as chemical shifts of (15)N, (13)C(α), and (13)C' nuclei, which are sensitive to backbone torsion angles. Distributions of these torsion angles were identified that yield best agreement to the experimental data, while using an entropy term to minimize the deviation from statistical distributions seen in a large protein coil library. Results indicate that although at the individual residue level considerable deviations from the coil library distribution are seen, on average the fitted distributions agree fairly well with this library, yielding a moderate population (20-30%) of the PPII region and a somewhat higher population of the potentially aggregation-prone β region (20-40%) than seen in the database. A generally lower population of the αR region (10-20%) is found. Analysis of (1)H − (1)H NOE data required consideration of the considerable backbone diffusion anisotropy of a disordered protein.

Residue-specific force field based on the protein coil library. RSFF1: modification of OPLS-AA/L.

Traditional protein force fields use one set of parameters for most of the 20 amino acids (AAs), allowing transferability of the parameters. However, a significant shortcoming is the difficulty to fit the Ramachandran plots of all AA residues simultaneously, affecting the accuracy of the force field. In this Feature Article, we report a new strategy for protein force field parametrization. Backbone and side-chain conformational distributions of all 20 AA residues obtained from protein coil library were used as the target data. The dihedral angle (torsion) potentials and some local nonbonded (1-4/1-5/1-6) interactions in OPLS-AA/L force field were modified such that the target data can be excellently reproduced by molecular dynamics simulations of dipeptides (blocked AAs) in explicit water, resulting in a new force field with AA-specific parameters, RSFF1. An efficient free energy decomposition approach was developed to separate the corrections on ϕ and ψ from the two-dimensional Ramachandran plots. RSFF1 is shown to reproduce the experimental NMR (3)J-coupling constants of AA dipeptides better than other force fields. It has a good balance between α-helical and β-sheet secondary structures. It can successfully fold a set of α-helix proteins (Trp-cage and Homeodomain) and β-hairpins (Trpzip-2, GB1 hairpin), which cannot be consistently stabilized by other state-of-the-art force fields. Interestingly, the RSFF1 force field systematically overestimates the melting temperature (and the stability of native state) of these peptides/proteins. It has a potential application in the simulation of protein folding and protein structure refinement.

Nearest Neighbor Interactions Attenuate Intrinsic Amino Acid Conformational Preferences: A Combined Vibrational and NMR Study

Contrary to the isolated pair hypothesis, a pivotal ingredient of the random coil model, conformational distributions of amino acid residues in unfolded proteins cannot be considered as isolated from their nearest neighbors. To enable structural predictions of unfolded proteins or peptides (IDPs) knowledge about intrinsic propensities of amino acid residues must be complemented by information on nearest-neighbor interactions. To explore this influence, we preformed a joint vibrational and 2D-NMR spectroscopy study of selected “GxyG” host-guest peptides in aqueous solution: GDyG, GSyG, GxLG, GxVG, where x/y={A,K,LV}. The choice of D and S (L and V) for the x (y) position was motivated by their documented ability to drastically change the distribution of alanine in xAy tripeptides of truncated coil libraries. The observed spectral information were analyzed in terms of superpositions of 2D-Gaussian functions in the Ramachandran space, representing sub-ensembles of pPII-, β-strand-, helical-, and turn-like conformations. Results reveal that “turn forming residues” and hydrophobic residues have very strong effects on the conformation of their nearest neighbors. A direct comparison of the conformational distribution for S and D in GSAG ,GSLG, and GDAG with corresponding distributions in GxG peptiess reveals that hydrophobic neighbors cause drastic reductions of turn propensities. As a neighbor, K eliminates the asx turn propensity of D. In addition, insertion of these 'turn forming' residues (S, and D) causes conformational redistributions of L, A, and K from pPII to more extended β strand-like conformations while at the same time increasing the overall turn content. Concomitantly, the positions of pPII and particularly of β distributions are shifted to lower ψ values. Taken together, our results indicate that Dx and Sx motifs might act as conformational randomizers in proteins, attenuating intrinsic propensities of neighboring residues.