Predictions of protein backbone structural parameters from first principles: Systematic comparisons of calculated N-C(.alpha.)-C' angles with high-resolution protein crystallographic results

Jiang, X.; Cao, Man; Teppen, Brian J.; Newton, Susan Q.; Schäfer, Lothar

doi:10.1021/j100026a014

Cited by 34 publications

(41 citation statements)

References 6 publications

(7 reference statements)

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“…In this paper, a database of high-resolution protein structures is described, and it is used to generate empirical distributions of observed conformations in which the effects of experimental error are minimized. Then, extending the work of Jiang et al (1995), it is shown that this database provides unambiguous experimental evidence that the N-Ca-C bond angle is highly dependent on conformation. Other bond lengths and angles also show conformation dependence, but the local geometry trends are smaller and less well determined.…”

Section: Figmentioning

confidence: 72%

Experimentally observed conformation‐dependent geometry and hidden strain in proteins

1996

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A database has been compiled documenting the peptide conformations and geometries from 70 diverse proteins refined at 1.75 A or better. Analysis of the well-ordered residues within the database shows 4, $-distributions that have more fine structure than is generally observed. Also, clear evidence is presented that the peptide covalent geometry depends on conformation, with the interpeptide N-Ca-C bond angle varying by nearly +-5 degrees from its standard value. The observed deviations from standard peptide geometry are greatest near the edges of wellpopulated regions, consistent with strain occurring in these conformations. Minimization of such hidden strain could be an important factor in thermostability of proteins. These empirical data describing how equilibrium peptide geometry varies as a function of conformation confirm and extend quantum mechanics calculations, and have predictive value that will aid both theoretical and experimental analyses of protein structure.Keywords: amino acids; conformational energetics; local geometry; peptide geometry; protein folding; protein stability; protein structure; Ramachandran plot In a landmark paper, Ramachandran and Sasisekharan (1968) reviewed concepts put forth originally by Sasisekharan (1962) to show how two main-chain torsion angles, and $, are the key variables for describing protein conformation, and how simple spatial exclusion considerations place major limitations on the conformations accessible to polypeptides (Fig. 1). They also outlined how more realistic analyses using van der Waals potentials convert the simple allowed/disallowed distinction to a continuous function of conformational energy. The general agreement of these plots with the observed conformations in proteins (compare Fig. lA,B) has provided strong evidence that local interactions within a single dipeptide are of primary importance to conformational preferences.However, s i~~f i~t deviations between the ( 6 , $-~stributions observed in proteins and calculated energetics have spurred much effort to determine more accurately the energetics of dipeptide conformations. These calculations have been made with various empirical force fields and quantum mechanics, with and without solvation terms, generating both "rigid-geometry" energy maps by assuming a fixed peptide geometry and "relaxedgeometry," or "local geometry," energy maps by allowing the covalent peptide geometry to be minimized at each point of the 4, $-map (reviewed in Brooks & Case, 1993). Although the -_ _ _ I _ Reprint requests to: P.

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Section: Figmentioning

confidence: 72%

Experimentally observed conformation‐dependent geometry and hidden strain in proteins

1996

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“…In a series of recent studies [1][2][3] we have begun to explore the possibilities of predicting peptide and protein backbone structures (bond distances and angles) from first principles. The backbone parameters of peptides, such as the N-C(α) and C(α)-C bond lengths and the N-C(α)-C angle, are characterized by an acute functional dependence on the peptide torsions φ [N-C(α)] and ψ [C(α)-C ].…”

Section: Introductionmentioning

confidence: 99%

“…Therefore, it was a discovery [1][2][3] of some potential utility that the structures of ALA calculated at the HF/4-21G level of theory [33] can be used for predicting bond distances and angles in the backbones of proteins with high accuracy. So far [1][2][3] we have focused our attention on the N-C(α)-C angle, the α-angle henceforth, because its conformational variations are particularly significant, flexing by more than 10…”

Section: Introductionmentioning

confidence: 99%

“…• was found [3] between calculated and observed parameters for the α-angles of some forty proteins, for which crystal structures with a minimum resolution of 1.5Å were selected from the Brookhaven protein data bank [37]. In addition, when more than 3000 angles involved in this comparison [3] were ordered by regions in φ/ψ-space defined by a 30…”

Section: Introductionmentioning

confidence: 99%

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Predictions of peptide and protein backbone structural parameters from first principles. IV: Systematic comparisons of calculated N—C(α)—C′ angles with peptide crystal structures

Jiang

Cao

Newton

et al. 1996

Elect J Theoret Chem

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SUMMARYFor some fifty oligopeptides for which high resolution crystal structures have been deposited in the Cambridge Crystallographic Data File, the crystallographic N-C(α)-C angles, cryst α i , were compared with values calculated on the basis of first principles. Crystal structures of cyclic and non-cyclic peptides were included in this comparison, with sizes ranging from six to sixteen residues, if they were refined to an R-factor of at least 0.08 or better. The calculated values were obtained using an algorithm which employs spline-function representations of ab initio dipeptide conformational geometry maps to predict backbone bond lengths and angles in oligopeptides and proteins as functions of the φ[N - • grid and region-average values calculated, the average rms deviation between the two sets in the most populated regions is 1.52• . As in the previous protein studies, helix compression is found in the oligopeptides. The analysis reveals that the φ/ψ-torsional dependence of N-C(α)-C in oligopeptides is similar to that previously found for proteins. We expect the computational procedure to be useful for establishing flexible geometry functions for use in empirical peptide and protein modeling and protein crystallography.KEY WORDS peptide and protein background geometries; conformationally dependent geometry trends; comparison of ab initio peptide geometries and crystal structures; standard geometry functions; ideal geometries for protein crystallography.

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“…the ' and torsion angles). This was later confirmed to occur in proteins (Jiang et al, 1995;Karplus, 1996), but remained a little known reality until it was suggested that accounting for this behaviour might resolve a controversy about how best to handle restraints in protein crystallographic refinements (Karplus et al, 2008). Shortly thereafter, an analysis was carried out that codified how backbone bond lengths and angles were observed to change with conformation in a large set of protein crystal structures solved at 1 Å resolution or better (Berkholz et al, 2009).…”

mentioning

confidence: 96%

A new default restraint library for the protein backbone inPhenix: a conformation-dependent geometry goes mainstream

Moriarty

Tronrud

Adams

et al. 2016

Acta Crystallogr D Struct Biol

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Chemical restraints are a fundamental part of crystallographic protein structure refinement. In response to mounting evidence that conventional restraints have shortcomings, it has previously been documented that using backbone restraints that depend on the protein backbone conformation helps to address these shortcomings and improves the performance of refinements [Moriartyet al.(2014),FEBS J.281, 4061–4071]. It is important that these improvements be made available to all in the protein crystallography community. Toward this end, a change in the default geometry library used byPhenixis described here. Tests are presented showing that this change will not generate increased numbers of outliers during validation, or deposition in the Protein Data Bank, during the transition period in which some validation tools still use the conventional restraint libraries.

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Predictions of protein backbone structural parameters from first principles: Systematic comparisons of calculated N-C(.alpha.)-C' angles with high-resolution protein crystallographic results

Cited by 34 publications

References 6 publications

Experimentally observed conformation‐dependent geometry and hidden strain in proteins

Experimentally observed conformation‐dependent geometry and hidden strain in proteins

Predictions of peptide and protein backbone structural parameters from first principles. IV: Systematic comparisons of calculated N—C(α)—C′ angles with peptide crystal structures

A new default restraint library for the protein backbone inPhenix: a conformation-dependent geometry goes mainstream

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