Ab initio modeling of small, medium, and large loops in proteins

Galaktionov, S. G.; Nikiforovich, Gregory V.; Marshall, Garland R.

doi:10.1002/1097-0282(2001)60:2<153::aid-bip1010>3.0.co;2-6

Cited by 43 publications

(34 citation statements)

References 30 publications

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“…It can help to probe and sample the flexibility of loops. It can be useful too in ab initio loop prediction [34,35], recently shown to be important for some docking methods for protein-protein [36] and protein-DNA interaction [37]. …”

Section: Discussionmentioning

confidence: 99%

Use of a structural alphabet for analysis of short loops connecting repetitive structures

2004

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Background: Because loops connect regular secondary structures, analysis of the former depends directly on the definition of the latter. The numerous assignment methods, however, can offer different definitions. In a previous study, we defined a structural alphabet composed of 16 average protein fragments, which we called Protein Blocks (PBs). They allow an accurate description of every region of 3D protein backbones and have been used in local structure prediction. In the present study, we use this structural alphabet to analyze and predict the loops connecting two repetitive structures.

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Section: Discussionmentioning

confidence: 99%

Use of a structural alphabet for analysis of short loops connecting repetitive structures

2004

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“…The scoring schemes that have been used vary widely. At one extreme are methods in which energetics play little or no role, and scoring is accomplished by statistics-based functions (e.g., based on loop sequence 2 and stem matching, 2,5 or contact map representations 10 ). Fiser et al 9 used a mixture of molecular mechanics force-field terms and statistically derived terms for scoring, whereas Xiang et al 8 used a scoring function that included steric interactions, hydrophobicity, torsional energy, and hydrogen bonding, but ignored many electrostatic effects.…”

Section: Overview Of Methodologymentioning

confidence: 99%

A hierarchical approach to all‐atom protein loop prediction

et al. 2004

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The application of all-atom force fields (and explicit or implicit solvent models) to protein homology-modeling tasks such as side-chain and loop prediction remains challenging both because of the expense of the individual energy calculations and because of the difficulty of sampling the rugged all-atom energy surface. Here we address this challenge for the problem of loop prediction through the development of numerous new algorithms, with an emphasis on multiscale and hierarchical techniques. As a first step in evaluating the performance of our loop prediction algorithm, we have applied it to the problem of reconstructing loops in native structures; we also explicitly include crystal packing to provide a fair comparison with crystal structures. In brief, large numbers of loops are generated by using a dihedral angle-based buildup procedure followed by iterative cycles of clustering, side-chain optimization, and complete energy minimization of selected loop structures. We evaluate this method by using the largest test set yet used for validation of a loop prediction method, with a total of 833 loops ranging from 4 to 12 residues in length. Average/median backbone rootmean-square deviations (RMSDs) to the native structures (superimposing the body of the protein, not the loop itself) are 0.42/0.24 Å for 5 residue loops, 1.00/0.44 Å for 8 residue loops, and 2.47/1.83 Å for 11 residue loops. Median RMSDs are substantially lower than the averages because of a small number of outliers; the causes of these failures are examined in some detail, and many can be attributed to errors in assignment of protonation states of titratable residues, omission of ligands from the simulation, and, in a few cases, probable errors in the experimentally determined structures. When these obvious problems in the data sets are filtered out, average RMSDs to the native structures improve to 0.43 Å for 5 residue loops, 0.84 Å for 8 residue loops, and 1.63 Å for 11 residue loops. In the vast majority of cases, the method locates energy minima that are lower than or equal to that of the minimized native loop, thus indicating that sampling rarely limits prediction accuracy. The overall results are, to our knowledge, the best reported to date, and we attribute this success to the combination of an accurate all-atom energy function, efficient methods for loop buildup and side-chain optimization, and, especially for the longer loops, the hierarchical refinement protocol.

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“…and less typical structural motifs (e.g., loops, ␤-bulges) of a single peptide chain are more and more in the focus of computational studies. [1][2][3][4][5][6][7][8][9][10] Properties associated with the above molecular conformers are commonly classified either by structure or stability characteristics. Stability is an energetic concept measurable by the computed total energy, often transformed to some relative energy with respect to a reference state.…”

Section: Stability Measures Of Systems With Covalently Bonded Peptidementioning

confidence: 99%

Stability issues of covalently and noncovalently bonded peptide subunits

et al. 2004

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Abstract:The present study focuses on important questions associated with modeling of peptide and protein stability.Computing at different levels of theory (RHF, B3LYP) for a representative ensemble of conformers of di-and tripeptides of alanine, we found that the Gibbs Free Energy values correlate significantly with the total electronic energy of the molecules (0.922 Յ R 2 ). For noncovalently attached but interacting peptide subunits, such as [For-NH 2 ] 2 or [For-L-Ala-NH 2 ] 2 , we have found, as expected, that the basis set superimposition error (BSSE) is large in magnitude for small basis set but significantly smaller when larger basis sets [e.g., B3LYP/6-311ϩϩG(d,p)] are used. Stability of the two hydrogen bonds of antiparallel ␤-pleated sheets were quantitatively determined as a function of the molecular structure, S10 and S14, computed as 4.0 Ϯ 0.5 and 8.1 Ϯ 1.1 kcal/mol, respectively. Finally, a suitable thermoneutral isodesmic reaction was introduced to scale both covalently and noncovalently attached peptide units onto a common stability scale. We found that a suitable isodesmic reaction can result in the total electronic energy as well as the Gibbs free energy of a molecule, from its "noninteracting" fragments, as accurate as a few tenths of a kcal per mol. The latter observation seems to hold for peptides regardless of their length (1 Յ n Յ 8) or the level of theory applied.

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Ab initio modeling of small, medium, and large loops in proteins

Cited by 43 publications

References 30 publications

Use of a structural alphabet for analysis of short loops connecting repetitive structures

Use of a structural alphabet for analysis of short loops connecting repetitive structures

A hierarchical approach to all‐atom protein loop prediction

Stability issues of covalently and noncovalently bonded peptide subunits

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