Local Propensities and Statistical Potentials of Backbone Dihedral Angles in Proteins

Betancourt, Marcos R.; Skolnick, Jeffrey

doi:10.1016/j.jmb.2004.06.091

Cited by 76 publications

(82 citation statements)

References 15 publications

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“…We focus on alanine, leucine, isoleucine, and valine homopolypeptides because in native protein structures these amino acids occur with different frequencies in helices and -stands; alanine and leucine more frequently populate helices, whereas valine and isoleucine more often occur in an extended conformation. 9 We apply a higher level of QM calculations than in previ- À4.0 À4.4 À7.7 À2.4 À0.1 À9.8 À3.6 À3.9 À7.2 À3.7 À7.9 À10.9 5 À11.9 À10.9 À18.6 À10.5 À6.3 À20.7 À13.4 À15.8 À20.1 À12.2 À18.7 À20.0 7 À20.9 À21.5 À26.7 À20.7 À15. Comparison of the results calculated at the MP2/6-31g** (MP2) level and using Amber ff99 (ff99) and ff03 (ff03) force fields.…”

Section: Discussionmentioning

confidence: 99%

“…21 Such differences in local secondary structure propensities are qualitatively similar to the differences in the statistically observed occurrence of analyzed amino acids in helices and -strands in protein structures. 9 However, these differences do not exceed 1.6 (2.4) kcal/mol at the MP2/6-31g** (MP2/cc-pVDZ) level when compared with the helix stability of pAla and become only a small fraction of the total helix stabilization energy for longer peptides.…”

Section: Differences In the Helix Stability Of Different Amino Acids mentioning

confidence: 96%

“…Most protein force fields do not contain explicit correlation terms for the backbone conformation (torsional angles) of the neighboring residues. In contrast to the isolated-pair hypothesis, there are experimental 8 and statistical data from solved protein structures, 9,10 showing that the backbone conformation of a residue in the amino acid chain is correlated with the conformation and identity of the neighboring residues. These data reflect the influence of the environment of the protein, where the correlations of local effects with solvent and nonlocal effects are nonseparable.…”

Section: Introductionmentioning

confidence: 95%

“…In native protein structures, alanine and leucine more frequently populate helices, whereas valine and isoleucine occur more often in an extended conformation. 9 Since these observations are in folded proteins, it is not apparent whether they reflect intrinsic amino acid preferences or reflect both nonlocal interactions (between separate secondary protein fragments that are local in space but not in sequence) and solvation effects. QM calculations of helix versus extended structure relative energies performed for isolated short peptides in the gas phase can determine to what extent the relative stability originates from the local interactions.…”

Section: Stability Of the Helix Versus Extended Conformations In Reprmentioning

confidence: 99%

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Origin of intrinsic 3₁₀‐helix versus strand stability in homopolypeptides and its implications for the accuracy of the Amber force field

Jagielska

Skolnick

2007

J Comput Chem

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Current all-atom force fields often fail to recognize the native structure of a protein as the lowest free energy minimum. One possible cause could be the mathematical form of the potential based on the assumption that the conformation of a residue is independent of its neighbors. Here, using quantum mechanical (QM) methods (MP2/6-31g**//HF/6-31g** and MP2/cc-pVDZ//cc-pVDZ//HF/cc-pVDZ), the intrinsic correctness of the gas phase terms (without solvation) of the Amber ff03 and ff99 potentials are examined by testing their ability to reproduce the relative 3 10 -helix versus extended structure stabilities in the gas phase for 1-7-residue alanine, valine, leucine, and isoleucine homopolypeptides. The 3 10 -helix versus extended state stability strongly depends on chain length and less on the amino acid identity. The helical conformation becomes lower in energy than the extended conformation for all tested peptides longer than two residues, and its stability increases with the increase of chain length. The ff03 potential better describes the 3 10 -helix versus extended state energy than ff99 and also reproduces the curvature of the relative helix-extended state energies. Therefore, the mathematical form of the Amber potential is sufficient to describe the local effect of 3 10 -helix versus extended structure stabilization in the gas phase. However, the energy curves are shifted and the backbone geometries differ compared with the QM results. This may cause significant geometric discrepancies between native and predicted structures. Therefore, extant molecular mechanics force fields, such as Amber, need refinement of their parameters to correctly describe helix-extended state energetics and geometry of major conformations.

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Section: Discussionmentioning

confidence: 99%

Section: Differences In the Helix Stability Of Different Amino Acids mentioning

confidence: 96%

Section: Introductionmentioning

confidence: 95%

Section: Stability Of the Helix Versus Extended Conformations In Reprmentioning

confidence: 99%

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Origin of intrinsic 3₁₀‐helix versus strand stability in homopolypeptides and its implications for the accuracy of the Amber force field

Jagielska

Skolnick

2007

J Comput Chem

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“…The simplest observable 1,2 that one can use to characterize a structure is the presence of a contact between two specific residues. This procedure has been generalized to include more and more complex observables 3,6,7,[9][10][11][12][13][14][15] , making the KBPs more and more accurate. , a scoring function derived using an elegant Bayesian analysis, the composite scoring function QMEAN6 35,36 and the potential RF_CB_SRS_OD introduced by Rykunov and Fiser 18 are particularly successfull, even when tested on CASP targets 18,28 .…”

mentioning

confidence: 99%

A simple and efficient statistical potential for scoring ensembles of protein structures

Cossio

Granata

Laio

et al. 2012

Sci Rep

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In protein structure prediction it is essential to score quickly and reliably large sets of models by selecting the ones that are closest to the native state. We here present a novel statistical potential constructed by Bayesian analysis measuring a few structural observables on a set of 500 experimental protein structures. Even though employing much less parameters than current state-of-the-art methods, our potential is capable of discriminating with an unprecedented reliability the native state in large sets of misfolded models of the same protein. We also introduce the new idea that thermal fluctuations cannot be neglected for scoring models that are very similar to each other. In these cases, the best structure can be recognized only by comparing the probability distributions of our potential over short finite temperature molecular dynamics simulations starting from the competing models. 1-4 are energy functions derived from databases of known protein conformations that empirically aim to capture the most relevant aspects of the physical chemistry of protein structure and function. They are derived by measuring the probability of an observable in an ensemble of experimental structures relative to a reference state 2,6,[16][17][18] . The conversion of the probability into an energy function is normally done employing Boltzmann's law 3 . Theory of conditional probabilities 5,6 , linear and quadratic programming 7 and information theory 8 have been invoked to justify the approach. The simplest observable 1,2 that one can use to characterize a structure is the presence of a contact between two specific residues. This procedure has been generalized to include more and more complex observables 3,6,7,[9][10][11][12][13][14][15] , making the KBPs more and more accurate. , a scoring function derived using an elegant Bayesian analysis, the composite scoring function QMEAN6 35,36 and the potential RF_CB_SRS_OD introduced by Rykunov and Fiser 18 are particularly successfull, even when tested on CASP targets 18,28 . However, even the best performing KBP is not capable of distinguishing the folded state in all the decoy sets, indicating that improvements are still possible. Moreover, the state-of-the-art KBPs exploit many complex observables, such as the distance between pair of residues or atoms, which significantly boosts the number of parameters. The weights of the various terms (which may include correlated observables, such as value of the torsions and the presence of secondary structure elements) are optimized on the decoy sets in order to obtain the best performance 10,35 . This may affect the robustness of the potentials and the possibility to use them for different purposes other than fold recognition.We here introduce a statistical potential that we call BACH (Bayesian Analysis Conformation Hunt). Its definition relies on a few binary structural observables, such as the presence of short range contacts between pair of residues, in the spirit of the original works 1,2 on KBPs. As a consequence, the energy functio...

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Discovery of a Pseudo β Barrel: Synthesis and Formation by Tiling of Ferrocene Cyclopeptides

Chowdhury¹,

Sanders²,

Schatte³

et al. 2006

Angewandte Chemie

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Local Propensities and Statistical Potentials of Backbone Dihedral Angles in Proteins

Cited by 76 publications

References 15 publications

Origin of intrinsic 3₁₀‐helix versus strand stability in homopolypeptides and its implications for the accuracy of the Amber force field

Origin of intrinsic 3₁₀‐helix versus strand stability in homopolypeptides and its implications for the accuracy of the Amber force field

A simple and efficient statistical potential for scoring ensembles of protein structures

Discovery of a Pseudo β Barrel: Synthesis and Formation by Tiling of Ferrocene Cyclopeptides

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Local Propensities and Statistical Potentials of Backbone Dihedral Angles in Proteins

Cited by 76 publications

References 15 publications

Origin of intrinsic 310‐helix versus strand stability in homopolypeptides and its implications for the accuracy of the Amber force field

Origin of intrinsic 310‐helix versus strand stability in homopolypeptides and its implications for the accuracy of the Amber force field

A simple and efficient statistical potential for scoring ensembles of protein structures

Discovery of a Pseudo β Barrel: Synthesis and Formation by Tiling of Ferrocene Cyclopeptides

Contact Info

Product

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Origin of intrinsic 3₁₀‐helix versus strand stability in homopolypeptides and its implications for the accuracy of the Amber force field

Origin of intrinsic 3₁₀‐helix versus strand stability in homopolypeptides and its implications for the accuracy of the Amber force field