Conformational Dynamics of Trialanine in Water. 2. Comparison of AMBER, CHARMM, GROMOS, and OPLS Force Fields to NMR and Infrared Experiments

Mu, Yuguang; Kosov, Daniel S.; Stock, Gerhard

doi:10.1021/jp022445a

Cited by 205 publications

(264 citation statements)

References 57 publications

(148 reference statements)

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“…According to Flory (5) and Tanford (6), unfolded proteins can be represented as statistical random coils, in which a given residue has no strong preference for any specific conformation. Confirming earlier conclusions by Tiffany and Krimm (7)(8)(9), recent evidence from a variety of spectroscopic probes (10)(11)(12)(13)(14)(15)(16)(17)(18)(19)(20)(21)(22), theoretical studies (23)(24)(25)(26)(27)(28)(29)(30)(31)(32)(33)(34), and coil library surveys (35)(36)(37)(38)(39)(40)(41)(42)(43)) consistently point to a major role for the polyproline II (PPII, ⌽ ϭ Ϫ75°, ⌿ ϭ ϩ145°) conformation in oligo-Ala (for review, see ref. 3 and related articles in the same volume), oligo-Lys, and oligo-Glu peptides (44).…”

supporting

confidence: 73%

Polyproline II propensities from GGXGG peptides reveal an anticorrelation with β-sheet scales

Shi

Kang

Liu

et al. 2005

Proc. Natl. Acad. Sci. U.S.A.

149

301

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There is growing appreciation of the functional relevance of unfolded proteins in biology. However, unfolded states of proteins have proven inaccessible to the usual techniques for high-resolution structural and energetic characterization. Unfolded states are still generally conceived of as statistical coils, based on the pioneering work of Flory [(1969 T he process by which a protein acquires its native structure is among the most complex reactions known, and challenges remain in defining the nature of the transition state(s), the structure and role of intermediates, and the properties of the starting ensemble of states (1-4). According to Flory (5) and Tanford (6), unfolded proteins can be represented as statistical random coils, in which a given residue has no strong preference for any specific conformation. Confirming earlier conclusions by Tiffany and Krimm (7-9), recent evidence from a variety of spectroscopic probes (10-22), theoretical studies (23-34), and coil library surveys (35-43) consistently point to a major role for the polyproline II (PPII, ⌽ ϭ Ϫ75°, ⌿ ϭ ϩ145°) conformation in oligo-Ala (for review, see ref. 3 and related articles in the same volume), oligo-Lys, and oligo-Glu peptides (44). We have reported that in a seven-Ala peptide model PPII converts to a ␤-like structure with increasing temperature (13). These findings raise several important questions regarding the structure of unfolded proteins: Although alanine is arguably a reasonable model for the unperturbed peptide backbone, is PPII also present in unfolded peptide chains composed of nonalanine nonproline residues? Is there an intrinsic PPII propensity for each individual side chain? If PPII is in equilibrium with ␤-structure, is there a correlation between scales of PPII propensity and analogous ␤-sheet scales? To what extent is PPII sequence and context dependent?Here, we address these questions by analyzing a series of end-blocked host pentapeptides AcGGXGGNH 2 , where X denotes 19 natural amino acids except glycine. Members of the series are found to differ in their extent of PPII conformation as determined by NMR and CD spectroscopy. Our results lead to the following conclusions: PPII is present as a dominant conformation in the majority of AcGGXGGNH 2 peptides. Different side chains show distinct propensities to adopt PPII in these unfolded molecules. Importantly, we find an inverse correlation between the determined PPII scale and the ␤-sheet-forming propensities derived from a zinc-finger model system (45) when 18 aa (except Gly and Pro) are divided into two groups: one, the nonpolar ␤-branched and bulky aromatic residues (VIWFY) and the other all of the remaining side chains. Finally, we find a correlation between our PPII scale in AcGGXGGNH 2 and a PPII scale derived from alternative model peptides such as AcPPPXPPPGYNH 2 (46). Still there are indications that the PPII scale is likely to be sequence and context dependent (47). Materials and MethodsPeptides Synthesis and Purification. Peptides were assembled on Rink Amide res...

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supporting

confidence: 73%

Polyproline II propensities from GGXGG peptides reveal an anticorrelation with β-sheet scales

Shi

Kang

Liu

et al. 2005

Proc. Natl. Acad. Sci. U.S.A.

149

301

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“…CHARMM22 and GROMOS96 variants and OPLS-AA) were previously compared 21,22 in terms of conformational sampling of blocked glycine and alanine dipeptide and noted to disagree to various degrees (particularly for glycine 21 ) with simulations employing combined QM/MM force field as well as with statistical analysis of high resolution protein crystal structures. In another study, all force fields were also shown to perform very differently with respect to a number of properties of trialanine compared to NMR and infrared observables 23 .…”

Section: Introductionmentioning

confidence: 99%

Comparison of multiple Amber force fields and development of improved protein backbone parameters

et al. 2006

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The ff94 force field that is commonly associated with the AMBER simulation package is one of the most widely used parameter sets for biomolecular simulation. After a decade of extensive use and testing, limitations in this force field, such as over stabilization of α-helices, were reported by us and other researchers. This led to a number of attempts to improve these parameters, resulting in a variety of "AMBER" force fields and significant difficulty in determining which should be used for a particular application. We show that several of these continue to suffer from inadequate balance between different secondary structure elements. In addition, the approach used in most of these studies neglected to account for the existence in AMBER of two sets of backbone φ/ψ dihedral terms. This led to parameter sets that provide unreasonable conformational preferences for glycine. We report here an effort to improve the φ/ψ dihedral terms in the ff99 energy function. Dihedral term parameters are based on fitting the energies of multiple conformations of glycine and alanine tetrapeptides from high level ab-initio quantum mechanical calculations. The new parameters for backbone dihedrals replace those in the existing ff99 force field. This parameter set, which we denote ff99SB, achieves a better balance of secondary structure elements as judged by improved distribution of backbone dihedrals for glycine and alanine with respect to PDB survey data. It also accomplishes improved agreement with published experimental data for conformational preferences of short alanine peptides, and better accord with experimental NMR relaxation data of test protein systems.

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“…The peptide is thought to exist in the PP II conformation for which our mapping predict a coupling of 3 cm −1 . In reality of course in solution a broad distribution of conformations exist and the exact weight of those is difficult to predict [76]. Therefore, verifying the map against gas phase measurements [39-42] where the conformation is well known will be more reliable.…”

Section: B Dihedral Map For Prolinementioning

confidence: 99%

Solvent and conformation dependence of amide I vibrations in peptides and proteins containing proline

Roy

Lessing

Meisl

et al. 2011

The Journal of Chemical Physics

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We present a mixed quantum-classical model for studying the amide I vibrational dynamics (predominantly CO stretching) in peptides and proteins containing proline. There are existing models developed for determining frequencies of and couplings between the secondary amide units. However, these are not applicable to proline because this amino acid has a tertiary amide unit. Therefore, a new parametrization is required for infrared-spectroscopic studies of proteins that contain proline, such as collagen, the most abundant protein in humans and animals. Here, we construct the electrostatic and dihedral maps accounting for solvent and conformation effects on frequency and coupling for the proline unit. We examine the quality and the applicability of these maps by carrying out spectral simulations of a number of peptides with proline in D 2 O and compare with experimental observations.

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Conformational Dynamics of Trialanine in Water. 2. Comparison of AMBER, CHARMM, GROMOS, and OPLS Force Fields to NMR and Infrared Experiments

Cited by 205 publications

References 57 publications

Polyproline II propensities from GGXGG peptides reveal an anticorrelation with β-sheet scales

Polyproline II propensities from GGXGG peptides reveal an anticorrelation with β-sheet scales

Comparison of multiple Amber force fields and development of improved protein backbone parameters

Solvent and conformation dependence of amide I vibrations in peptides and proteins containing proline

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