Coil Library Research Articles

Disorder and order in unfolded and disordered peptides and proteins: A view derived from tripeptide conformational analysis. I. Tripeptides with long and predominantly hydrophobic side chains

We performed a conformational analysis of the central residues of three tripeptides glycyl-L-isoleucyl-glycine (GIG), glycyl-L-tyrosyl-glycine (GYG) and glycyl-L-arginyl-glycine (GRG) in aqueous solution, based on a global analysis of amide I' band profiles and NMR J-coupling constants. The results are compared with recently reported distributions of GVG, GFG and GEG. For GIG and GYG, we found that even though the polyproline II (pPII) fraction is below 0.5, it is still the most populated conformation, whereas GVG and GFG show both a larger β-strand fraction. For GRG, we observed a clear dominance of pPII over β-strand, reminiscent of observations for GEG and GKG. This finding indicates that terminal charges on otherwise hydrophobic residue side chains stabilize pPII over β-strand conformations. For all peptides investigated we found that a variety of compact and turn-like conformations constitute nearly 20 percent of their conformational distributions. Attempts to analyze our data with a simple two-state pPII-->/<--β model therefore do not yield any satisfactory reproduction of experimental results. A comparison of the obtained GxG ensembles with conformational distributions of GxG segments in truncated coil libraries (helices and sheets omitted) revealed a much larger fraction of type II β(i+2) and type III β like conformations for the latter. Thus, a comparison of conformational distributions of unfolded peptide segments in solution and in coil libraries reveal interesting information on how the interplay between intrinsic propensities of amino acid residues and non-local interactions in polypeptide chains determine the conformations of loop segments in proteins.

How do Nearest-Neighbor Interactions Effect the Conformational Distributions in Peptides?

For structural predictions of intrinsically disordered proteins (IDPs), knowledge about intrinsic propensities of amino acids must be complimented by information on nearest-neighbor interactions. To explore the influence of nearest-neighbors on conformational distributions of amino acid residues, we preformed a joint vibrational and 2D-NMR study of selected GxyG host-guest peptides: GDyG, GSyG, GxLG, GxVG, where x/y={A,K,LV}. The choice of D and S (L/V) for the x (y) position was motivated by their documented ability to drastically change the distribution of alanine in xAy tripeptide sequences in truncated coil libraries. Five J-coupling constants and amide I’ profiles of the respective IR, polarized Raman and Vibrational Circular Dichroism spectra were analyzed using a superposition of 2D-Gaussian functions in Ramachandran space representing sub-ensembles of pPII-, β-strand-, helical-, and turn-like conformations. Our analysis of the amide I' profiles exploits excitonic coupling between the local amide I′ modes in the tetra-peptides. Our results reveal that D and S particularly alter the conformation of their downstream neighbor. In a recent study, these amino acids were shown to have an unusually high preference for type I’/IIβ and asx-turns. A direct comparison of the ensemble obtained for serine in GSAG, GSLG and GSG reveals that A and L cause the asx-turn population to be mitigated in favor of more extended pPII/ β structures. Upon insertion of these ‘turn-forming’ residues, alanine's conformational ensemble is modestly changed (shift from pPII to β), while the position of pPII and particularly of β is shifted to lower ψ-values. DFT calculations indeed show that the forced reduction in ψ for A increases the H-bond distance for serine in the asx-turn conformation. Taken together, our results indicate that Dx and Sx-motifs might act as conformational randomizers in proteins, attenuating intrinsic propensities of neighboring residues.

The intrinsic conformational features of amino acids from a protein coil library and their applications in force field development

The local conformational (φ, ψ, χ) preferences of amino acid residues remain an active research area, which are important for the development of protein force fields. In this perspective article, we first summarize spectroscopic studies of alanine-based short peptides in aqueous solution. While most studies indicate a preference for the P(II) conformation in the unfolded state over α and β conformations, significant variations are also observed. A statistical analysis from various coil libraries of high-resolution protein structures is then summarized, which gives a more coherent view of the local conformational features. The φ, ψ, χ distributions of the 20 amino acids have been obtained from a protein coil library, considering both backbone and side-chain conformational preferences. The intrinsic side-chain χ(1) rotamer preference and χ(1)-dependent Ramachandran plot can be generally understood by combining the interaction of the side-chain Cγ/Oγ atom with two neighboring backbone peptide groups. Current all-atom force fields such as AMBER ff99sb-ILDN, ff03 and OPLS-AA/L do not reproduce these distributions well. A method has been developed by combining the φ, ψ plot of alanine with the influence of side-chain χ(1) rotamers to derive the local conformational features of various amino acids. It has been further applied to improve the OPLS-AA force field. The modified force field (OPLS-AA/C) reproduces experimental (3)J coupling constants for various short peptides quite well. It also better reproduces the temperature-dependence of the helix-coil transition for alanine-based peptides. The new force field can fold a series of peptides and proteins with various secondary structures to their experimental structures. MD simulations of several globular proteins using the improved force field give significantly less deviation (RMSD) to experimental structures. The results indicate that the local conformational features from coil libraries are valuable for the development of balanced protein force fields.

Predicting most probable conformations of a given peptide sequence in the random coil state

In this work, we present a computational scheme for finding high probability conformations of peptides. The scheme calculates the probability of a given conformation of the given peptide sequence using the probability distribution of torsion states. Dependence of the states of a residue on the states of its first neighbors along the chain is considered. Prior probabilities of torsion states are obtained from a coil library. Posterior probabilities are calculated by the matrix multiplication Rotational Isomeric States Model of polymer theory. The conformation of a peptide with highest probability is determined by using a hidden Markov model Viterbi algorithm. First, the probability distribution of the torsion states of the residues is obtained. Using the highest probability torsion state, one can generate, step by step, states with lower probabilities. To validate the method, the highest probability state of residues in a given sequence is calculated and compared with probabilities obtained from the Coil Databank. Predictions based on the method are 32% better than predictions based on the most probable states of residues. The ensemble of "n" high probability conformations of a given protein is also determined using the Viterbi algorithm with multistep backtracking.

Water-Mediated Conformations of the Alanine Dipeptide as Revealed by Distributed Umbrella Sampling Simulations, Quantum Mechanics Based Calculations, and Experimental Data

An exhaustive umbrella sampling simulation of the alanine dipeptide in solution is reported. The presence of stable Y conformations in solution is assessed by both quantum calculations and experimental data from X-ray and NMR protein-solved structures available in the protein coil library. The agreement between experimental and simulation Ramachandran plots of the dipeptide in solution is excellent. A suitable explanation of the stabilization of the Y conformation mediated by water for the alanine dipeptide is discussed on the basis of Car-Parrinello MD calculations of the dipeptide in water.

Negative Design in Protein Coils

The classic folding paradigm, established by Anfinsen and others, has been interpreted to mean that under folding conditions, the native fold is selected from an astronomical number of conceivable alternatives by the constellation of favorable interactions among its amino acid sidechains. This plausible idea is entirely consistent with the characteristic close-packing seen in protein crystal structures, where it is apparent that residues distant in sequence are brought together in space, presumably providing both topological specificity and structural stability. Accordingly, organizing interactions are believed to persist into the native state. This supposition is the basis for knowledge-based potentials, Go models, and the like. Contrary to this view, we present evidence from simulations coupled with an analysis of the protein coil library (http://www.roselab.jhu.edu/coil/) that the overall fold is established prior to eventual sidechain close-packing. In this process, chain organization depends not only on selecting favorable interactions but also on rejecting unfavorable ones. Eliminating those interactions that result in steric clashes or unsatisfied hydrogen bonds winnows fold space substantially. Accordingly, such interactions play a crucial role in determining the native state, but given their mode of action, they are not visible in solved structures (like the dog that didn't bark in the night∗). ∗Gregory ( Scotland Yard detective): “Is there any other point to which you would wish to draw my attention?” Holmes: “To the curious incident of the dog in the night-time.” Gregory: “The dog did nothing in the night-time.” Holmes: “That was the curious incident.”

Sidechain conformational dependence of hydrogen exchange in model peptides

Peptide hydrogens that are exposed to solvent in protein X-ray structures exhibit a billion-fold range in hydroxide-catalyzed exchange rates, and these rates have previously been shown to be predictable by continuum dielectric methods to within a factor of 7, based on single protein conformations. When using a protein coil library to model the Boltzmann-weighted conformational distribution for the various N-acetyl-[X-Ala]-N-methylamides and N-acetyl-[Ala-Y]-N-methylamides, the acidity of the central amide in the individual conformers of each peptide spans nearly a million-fold range. Nevertheless, population averaging of these conformer acidities predicts the standard sidechain-dependent hydrogen exchange correction factors for nonpolar model peptides to within a factor of 30% (10 0.11) with a correlation coefficient r = 0.91. Comparison with the analogous continuum dielectric calculations for the other N-acetyl-[X-Y]-N-methylamides indicates that deviations from the isolated residue hypothesis of classical polymer theory predict appreciable errors in the exchange rates for conformationally disordered peptides when the standard sidechain-dependent hydrogen exchange rate correction factors are assumed to be independently additive. Although electronic polarizability generally dominates the dielectric shielding for the ∼ 10 ps lifetime of peptide ionization, evidence is presented for modest contributions from rapid intrarotamer conformational reorganization of Asn and Gln sidechains.

Influence of Side Chain Conformations on Local Conformational Features of Amino Acids and Implication for Force Field Development

Statistical analysis of coil regions in protein structures has been used to obtain the local backbone phi, psi preferences of amino acids, which agree well with the NMR experiments of unfolded peptides and proteins. We analyzed the conformational features of amino acid residues in a restricted coil library of 4220 high-resolution protein crystal structures. In addition to Gly, Ala, and Pro, the phi, psi distribution (Ramachandran plot) of each amino acid is analyzed with respect to three side chain conformers: g+ (chi(1) approximately -60 degrees), g- (chi(1) approximately 60 degrees), and t (chi(1) approximately 180 degrees). The statistical study indicates that the effect of side chain conformations on phi, psi distributions is even greater than the effect of amino acid types. On the basis of the chi(1), phi, psi conformational preferences, the amino acids in addition to Gly, Pro, and Ala can be divided into five types: (1) ordinary amino acids, (2) Ser, (3) Asp and Asn, (4) Val and Ile, and (5) Thr, each with distinguished chi(1) rotamers. The alpha-helix, beta-sheet, and type-I beta-turn preferences of the different rotamers of various amino acid types can be captured by their intrinsic phi, psi preferences from our coil library. Molecular dynamics simulations of dipeptide Ac-X-NHMe and tetrapeptide Ac-A-X-A-NHMe models give nearly the same side chain rotamer distributions. However, for many amino acids, both OPLS-AA/L and AMBER-FF03 force fields give very different chi(1) rotamer distributions from the coil library. This may partially explain why dipeptide models sometimes cannot reproduce those of protein structures well. The current coil library analysis may be valuable in improving the force field for protein simulations.

Physical-chemical determinants of coil conformations in globular proteins

We present a method with the potential to generate a library of coil segments from first principles. Proteins are built from alpha-helices and/or beta-strands interconnected by these coil segments. Here, we investigate the conformational determinants of short coil segments, with particular emphasis on chain turns. Toward this goal, we extracted a comprehensive set of two-, three-, and four-residue turns from X-ray-elucidated proteins and classified them by conformation. A remarkably small number of unique conformers account for most of this experimentally determined set, whereas remaining members span a large number of rare conformers, many occurring only once in the entire protein database. Factors determining conformation were identified via Metropolis Monte Carlo simulations devised to test the effectiveness of various energy terms. Simulated structures were validated by comparison to experimental counterparts. After filtering rare conformers, we found that 98% of the remaining experimentally determined turn population could be reproduced by applying a hydrogen bond energy term to an exhaustively generated ensemble of clash-free conformers in which no backbone polar group lacks a hydrogen-bond partner. Further, at least 90% of longer coil segments, ranging from 5- to 20 residues, were found to be structural composites of these shorter primitives. These results are pertinent to protein structure prediction, where approaches can be divided into either empirical or ab initio methods. Empirical methods use database-derived information; ab initio methods rely on physical-chemical principles exclusively. Replacing the database-derived coil library with one generated from first principles would transform any empirically based method into its corresponding ab initio homologue.

Backbone Statistical Potential from Local Sequence-Structure Interactions in Protein Loops

Native proteins have been optimized by evolution simultaneously for structure and sequence. Structural databases reflect this interdependency. In this paper, we present a new statistical potential for a reduced backbone representation that has both structure and sequence characteristics as variables. We use information from structural data available in the Protein Coil Library, selected on the basis of resolution and refinement factor. In these structures, the nonlocal interactions are randomly distributed and, thus, average out in statistics, so structural propensities due to local backbone-based interactions can be studied separately. We collect data in the form of local sequence-specific phi-psi backbone dihedral pairs. From these data, we construct dihedral probability density functions (DPDFs) that quantify any adjacent phi-psi pair distribution in the context of all possible combinations of local residue types. We use a probabilistic analysis to deduce how the correlations encoded in the various DPDFs as well as in residue frequencies propagate along the sequence and can be cumulated in a statistical potential capable of efficiently scoring a loop by its backbone conformation and sequence only. Our potential is able to identify with high accuracy the native structure of a loop with a given sequence among possible alternative conformations from sets of well-constructed decoys. Conversely, the potential can also be used for sequence prediction problems and is shown to score the native sequence of a given loop structure among the most fit of the possible sequence combinations. Applications for both structure prediction and sequence design are discussed.

Intrinsic Propensities of Amino Acid Residues in GxG Peptides Inferred from Amide I′ Band Profiles and NMR Scalar Coupling Constants

A reliable intrinsic propensity scale of amino acid residues is indispensable for an assessment of how local conformational distributions in the unfolded state can affect the folding of peptides and proteins. Short host-guest peptides, such as GxG tripeptides, are suitable tools for probing such propensities. To explore the conformational distributions sampled by the central amino acid residue in these motifs, we combined vibrational (IR, Raman, and VCD) with NMR spectroscopy. The data were analyzed in terms of a superposition of two-dimensional Gaussian distribution functions in the Ramachandran space pertaining to subensembles of polyproline II, beta-strand, right- and left-handed helical, and gamma-turn-like conformations. The intrinsic propensities of eight amino acid residues (x = A, V, F, L, S, E, K, and M) in GxG peptides were determined as mole fractions of these subensembles. Our results show that alanine adopts primarily (approximately 80%) a PPII-like conformation, while valine and phenylalanine were found to sample PPII and beta-strand-like conformations equally. The centers of the respective beta-strand distributions generally do not coincide with canonical values of dihedral angles of residues in parallel or antiparallel beta-strands. In fact, the distributions for most residues found in the beta-region significantly overlap the PPII-region. A comparison with earlier reported results for trivaline reveals that the terminal valines increase the beta-strand propensity of the central valine residue even further. Of the remaining investigated amino acids, methionine preferred PPII the most (0.64), and E, S, L, and K exhibit moderate (0.56-0.45) PPII propensities. Residues V, F, S, E, and L sample, to a significant extent, a region between the canonical PPII and (antiparallel) beta-strand conformations. This region coincides with the sampling reported for L and V using theoretical predictions (Tran et al. Biochemistry 2005, 44, 11369). The distributions of all investigated residues differ from coil library and computationally predicted distributions in that they do not exhibit a substantial sampling of helical conformations. We conclude that this sampling of helical conformations arises from the context dependence, for example, neighboring residues, in proteins and longer peptides, some of which is long-range.

Conformational energies and entropies of peptides, and the peptide–protein binding problem

A novel statistical thermodynamic approach is applied to free-peptide segments in order to classify them according to their conformational energies, entropies and heat capacities. Our approach employs the rotational isomeric state (RIS) model in which the states are described by the Ramachandran map of backbone torsion angles. The statistical weight matrices for the pairwise-dependent states are derived from the torsion angle probabilities of the consecutive dipeptides in a coil library. The partition function is determined for a given sequence via RIS multiplication of the pre-determined matrices. The conformational partition function, Helmholtz free energy, energy, entropy and heat capacity are obtained. The model is applied to randomly produced peptides and also to known peptide inhibitors to analyze their thermodynamic properties. Peptides with low energy, low entropy and low-heat capacity are determined to be essential for a peptide to be a good candidate inhibitor. Free energy changes in peptide binding are also discussed.

Distribution of Conformations Sampled by the Central Amino Acid Residue in Tripeptides Inferred From Amide I Band Profiles and NMR Scalar Coupling Constants

The conformational preference of individual amino acid residues in the unfolded state of peptides and proteins is the subject of a continuous debate. Research has mostly been focused on alanine, owing to its abundance in proteins and its relevance for the understanding of helix <----> coil transitions. In the current study, we have analyzed the amide I band profiles of the IR, isotropic and anisotropic Raman, and VCD profiles of trialanine in terms of a conformational model which, for the first time, explicitly considers the entire ensemble of possible conformations rather than representative structures. The distribution function utilized for a satisfactory simulation of the amide I band profiles was found to also reproduce a set of five J coupling constants reported by Graf et al. (Graf, J.; et al. J. Am. Chem. Soc. 2007, 129, 1179). The results of our analysis reveal a PPII fraction of approximately 0.84 for the central alanine residue, which strongly corroborates the notion that alanine has a very high PPII propensity, exceeding the values obtained from restricted coil libraries. We performed a similar analysis for trivaline and found that the dominant fraction of its central residue is a beta-strand. The fraction of the respective distribution is 0.68. The remaining fraction contains contributions from helical and PPII conformations. The results of our analysis enable us to decide on the suitability of force fields used for MD simulations of short alanine-containing peptides. The paper establishes vibrational spectroscopy as a suitable method to explore the energy landscape of amino acid residues.

Distribution of Conformations Sampled by the Central Amino Acid Residue in GXG Peptides Inferred from Amide 1′ Band Profiles and NMR Scalar Coupling Constants

The conformational propensity of amino acids in the unfolded state of peptides and proteins is the subject of ongoing deliberation. Recent research has mostly focused on alanine, owing to its abundance in proteins and its relevance for the understanding of helix coil transitions. We have analyzed the amide I' band profiles of the IR, isotropic and anisotropic Raman, and VCD profiles of a series of GXG peptides, X representing a subset of the naturally occurring amino acids, in terms of a conformational model which explicitly considers the entire ensemble of possible conformations rather than representative structures. The distribution function utilized for satisfactory simulations of the amide I' band profiles was found to also reproduce a set of seven J-coupling constants reported by Graf et al1. The results of our analysis reveal a PPII fraction of 0.91 for the central alanine residue in GAG, which strongly corroborates the notion that alanine has a very high PPII propensity. We performed a similar analysis for X=E, F, S, V, K, L and M. Preliminary indication is that E, F, K and L exhibit a substantial PPII propensity, whereas S, V and M exhibit a less pronounced PPII propensity with an increased propensity for β-strand. We also used distributions from coil libraries and MD simulations to model amide I band profiles and J-coupling constants for alanine and valine. We found most of them to be inconsistent with our experimental data. Thus, these results clearly demonstrate that caution must be taken in using coil libraries and MD simulations to describe the unfolded state of peptides and proteins, and that experimental data are a prerequisite for quantitative evaluation of amino acid residues.

The intrinsic conformational propensities of the 20 naturally occurring amino acids and reflection of these propensities in proteins

Here, we compare the distributions of main chain (Phi,Psi) angles (i.e., Ramachandran maps) of the 20 naturally occurring amino acids in three contexts: (i) molecular dynamics (MD) simulations of Gly-Gly-X-Gly-Gly pentapeptides in water at 298 K with exhaustive sampling, where X = the amino acid in question; (ii) 188 independent protein simulations in water at 298 K from our Dynameomics Project; and (iii) static crystal and NMR structures from the Protein Data Bank. The GGXGG peptide series is often used as a model of the unstructured denatured state of proteins. The sampling in the peptide MD simulations is neither random nor uniform. Instead, individual amino acids show preferences for particular conformations, but the peptide is dynamic, and interconversion between conformers is facile. For a given amino acid, the (Phi,Psi) distributions in the protein simulations and the Protein Data Bank are very similar and often distinct from those in the peptide simulations. Comparison between the peptide and protein simulations shows that packing constraints, solvation, and the tendency for particular amino acids to be used for specific structural motifs can overwhelm the "intrinsic propensities" of amino acids for particular (Phi,Psi) conformations. We also compare our helical propensities with experimental consensus values using the host-guest method, which appear to be determined largely by context and not necessarily the intrinsic conformational propensities of the guest residues. These simulations represent an improved coil library free from contextual effects to better model intrinsic conformational propensities and provide a detailed view of conformations making up the "random coil" state.

Structures, basins, and energies: A deconstruction of the Protein Coil Library

Globular proteins adopt complex folds, composed of organized assemblies of alpha-helix and beta-sheet together with irregular regions that interconnect these scaffold elements. Here, we seek to parse the irregular regions into their structural constituents and to rationalize their formative energetics. Toward this end, we dissected the Protein Coil Library, a structural database of protein segments that are neither alpha-helix nor beta-strand, extracted from high-resolution protein structures. The backbone dihedral angles of residues from coil library segments are distributed indiscriminately across the phi,psi map, but when contoured, seven distinct basins emerge clearly. The structures and energetics associated with the two least-studied basins are the primary focus of this article. Specifically, the structural motifs associated with these basins were characterized in detail and then assessed in simple simulations designed to capture their energetic determinants. It is found that conformational constraints imposed by excluded volume and hydrogen bonding are sufficient to reproduce the observed ,psi distributions of these motifs; no additional energy terms are required. These three motifs in conjunction with alpha-helices, strands of beta-sheet, canonical beta-turns, and polyproline II conformers comprise approximately 90% of all protein structure.

A Hamiltonian Replica Exchange Approach and Its Application to the Study of Side-Chain Type and Neighbor Effects on Peptide Backbone Conformations.

We presented a Hamiltonian replica exchange approach and applied it to investigate the effects of various factors on the conformational equilibrium of peptide backbone. In different replicas, biasing potentials of varying strengths are applied to all backbone (φ,ψ) torsional angle pairs to overcome sampling barriers. A general form of constructing biasing potentials based on a reference free energy surface is employed to minimize sampling in physically irrelevant parts of the conformational space. An extension of the weighted histogram analysis formulation allows for conformational free energy surfaces to be computed using all replicas, including those with biased Hamiltonians. This approach can significantly reduce the statistical uncertainties in computed free energies. For the peptide systems considered, it allows for effects of the order of 0.5-1 kJ/mol to be quantified using explicit solvent simulations. We applied this approach to capped peptides of 2-5 peptide units containing Ala, Phe, or Val in explicit water solvent and focused on how the conformational equilibrium of a single pair of backbone angles are influenced by changing the residue types of the same and neighboring residues as well as conformations of neighboring residues. For the effects of changing side-chain types of the same residue, our results consistently showed increased preference of β for Phe and Val relative to Ala. As for neighbor effects, our results not only indicated that they can be as large as the effects of changing the side-chain type of the same residue but also led to several new insights. We found that for the N-terminal neighbors, their conformations seem to have large effects. Relative to the β conformer of an N-terminal neighbor, its α conformer stabilizes the β conformer of its next Ala disregarding the residue type of the neighbor. For C-terminal neighbors, their chemical identities seem to play more important roles. Val as the C-terminal neighbor significantly increases the PII propensity of its previous Ala disregarding its own conformational state. These results are in good accordance with reported statistics of protein coil structure libraries, proving the persistent presence of such effects in short peptides as well as in proteins. We also observed other side-chain identity and neighbor effects which have been consistently reproduced in our simulations of different small peptide systems but not displayed by coil library statistics.

Conformations of Alanine-Based Peptides in Water Probed by FTIR, Raman, Vibrational Circular Dichroism, Electronic Circular Dichroism, and NMR Spectroscopy

We have used a combination of FTIR, VCD, ECD, Raman, and NMR spectroscopies to probe the solution conformations sampled by H-(AAKA)-OH by utilizing an excitonic coupling model and constraints imposed by the 3JCalphaHNH coupling constants of the central residues to simulate the amide I' profile of the IR, isotropic Raman, anisotropic Raman, and VCD spectra in terms of a mixture of three conformations, i.e., polyproline II, beta-strand and right-handed helical. The representative coordinates of the three conformations were obtained from published coil libraries. Alanine was found to exhibit PPII fractions of 0.60 or greater, mixed with smaller fractions of helices and beta-strand conformations. Lysine showed no clear conformational propensity in that it samples polyproline II, beta-strand, and helical conformations with comparable probability. This is at variance with results obtained earlier for ionized polylysine, which suggest a high polyproline II propensity. We reanalyzed previously investigated tetra- and trialanine by combining published vibrational spectroscopy data with 3JCalphaHNH coupling constants and obtained again blends dominated by PPII with smaller admixtures of beta-strand and right-handed helical conformations. The polyproline II propensity of alanine was found to be higher in tetraalanine than in trialanine. For all peptides investigated, our results rule out a substantial population of turn-like conformations. Our results are in excellent agreement with MD simulations on short alanine peptides by Gnanakaran and Garcia [(2003) J. Phys. Chem. B 107, 12555-12557] but at variance with multiple MD simulations particularly for the alanine dipeptide.

Intrinsic backbone preferences are fully present in blocked amino acids.

The preferences of amino acid residues for ,psi backbone angles vary strikingly among the amino acids, as shown by the backbone angle found from the (3)J(H(alpha),H(N)) coupling constant for short peptides in water. New data for the (3)J(H(alpha),H(N)) values of blocked amino acids (dipeptides) are given here. Dipeptides exhibit the full range of coupling constants shown by longer peptides such as GGXGG and dipeptides present the simplest system for analyzing backbone preferences. The dipeptide coupling constants are surprisingly close to values computed from the coil library (conformations of residues not in helices and not in sheets). Published coupling constants for GGXGG peptides agree closely with dipeptide values for all nonpolar residues and for some polar residues but not for X = D, N, T, and Y, which are probably affected by polar side chain-backbone interactions in GGXGG peptides. Thus, intrinsic backbone preferences are already determined at the dipeptide level and remain almost unchanged in GGXGG peptides and are strikingly similar in the coil library of conformations from protein structures. The simplest explanation for the backbone preferences is that backbone conformations are strongly affected by electrostatic dipole-dipole interactions in the peptide backbone and by screening of these interactions with water, which depends on nearby side chains. Strong backbone electrostatic interactions occur in dipeptides. This is shown by calculations both of backbone electrostatic energy for different conformers of the alanine dipeptide in the gas phase and by electrostatic solvation free energies of amino acid dipeptides.

Hydrogen‐bonded turns in proteins: The case for a recount

Beta-turns are sites at which proteins change their overall chain direction, and they occur with high frequency in globular proteins. The Protein Data Bank has many instances of conformations that resemble beta-turns but lack the characteristic N-H(i) --> O=C(i - 3) hydrogen bond of an authentic beta-turn. Here, we identify potential hydrogen-bonded beta-turns in the coil library, a Web-accessible database utility comprised of all residues not in repetitive secondary structure, neither alpha-helix nor beta-sheet (http://www.roselab.jhu.edu/coil). In particular, candidate turns were identified as four-residue segments satisfying highly relaxed geometric criteria but lacking a strictly defined hydrogen bond. Such candidates were then subjected to a minimization protocol to determine whether slight changes in torsion angles are sufficient to shift the conformation into reference-quality geometry without deviating significantly from the original structure. This approach of applying constrained minimization to known structures reveals a substantial population of previously unidentified, stringently defined, hydrogen-bonded beta-turns. In particular, 33% of coil library residues were classified as beta-turns prior to minimization. After minimization, 45% of such residues could be classified as beta-turns, with another 8% in 3(10) helixes (which closely resemble type III beta-turns). Of the remaining coil library residues, 37% have backbone dihedral angles in left-handed polyproline II structure.