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50
The pairwise energy content estimated from amino acid composition discriminates between folded and intrinsically unstructured proteins
- J. Mol. Biol
, 2005
"... Intrinsically unstructured/disordered proteins/ domains (IUPs), such as p21, 1 the N-terminal domain of p53 2 or the transactivator domain of CREB, 3 exist in a largely disordered structural state, ..."
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Cited by 114 (14 self)
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Intrinsically unstructured/disordered proteins/ domains (IUPs), such as p21, 1 the N-terminal domain of p53 2 or the transactivator domain of CREB, 3 exist in a largely disordered structural state,
A distance-dependent atomic knowledge-based potential for improved protein structure selection, Proteins 44:223–232
, 2001
"... ABSTRACT A heavy atom distance-dependent knowledge-based pairwise potential has been devel-oped. This statistical potential is first evaluated and optimized with the native structure z-scores from gapless threading. The potential is then used to recognize the native and near-native structures from b ..."
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Cited by 83 (1 self)
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ABSTRACT A heavy atom distance-dependent knowledge-based pairwise potential has been devel-oped. This statistical potential is first evaluated and optimized with the native structure z-scores from gapless threading. The potential is then used to recognize the native and near-native structures from both published decoy test sets, as well as decoys obtained from our group’s protein structure prediction program. In the gapless threading test, there is an average z-score improvement of 4 units in the optimized atomic potential over the residue-based quasichemical potential. Examination of the z-scores for individual pairwise distance shells indi-cates that the specificity for the native protein structure is greatest at pairwise distances of 3.5–6.5 Å, i.e., in the first solvation shell. On applying the current atomic potential to test sets obtained from the web, composed of native protein and decoy structures, the current generation of the potential performs better than residue-based potentials as well as the other published atomic potentials in the task of selecting native and near-native structures. This newly developed potential is also applied to structures of varying quality generated by our group’s protein structure prediction program. The current atomic potential tends to pick lower RMSD structures than do residue-based contact potentials. In particular, this atomic pairwise interaction poten-tial has better selectivity especially for near-native structures. As such, it can be used to select near-native folds generated by structure prediction algo-rithms as well as for protein structure refinement.
Testing a New Monte Carlo Algorithm for Protein Folding
- PROTEINS 31:52--66, 1998. R 1998 WILEY-LISS, INC.
, 1998
"... We demonstrate that the recently proposed pruned-enriched Rosenbluth method (PERM) (Grassberger, Phys. Rev. E 56:3682, 1997) leads to extremely efficient algorithms for the folding of simple model proteins. We test it on several models for lattice heteropolymers, and compare it to published Monte Ca ..."
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Cited by 30 (2 self)
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We demonstrate that the recently proposed pruned-enriched Rosenbluth method (PERM) (Grassberger, Phys. Rev. E 56:3682, 1997) leads to extremely efficient algorithms for the folding of simple model proteins. We test it on several models for lattice heteropolymers, and compare it to published Monte Carlo studies of the properties of particular sequences. In all cases our method is faster than the previous ones, and in several cases we find new minimal energy states. In addition to producing more reliable candidates for ground states, our method gives detailed information about the thermal spectrum and thus allows one to analyze thermodynamic aspects of the folding behavior of arbitrary sequences.
Protein design: a perspective from simple tractable models
- Design
, 1998
"... Recent progress in computational approaches to protein design builds on advances in statistical mechanical protein folding theory. Here, the number of sequences folding into a given conformation is evaluated and a simple condition for a protein model’s designability is outlined. ..."
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Cited by 25 (0 self)
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Recent progress in computational approaches to protein design builds on advances in statistical mechanical protein folding theory. Here, the number of sequences folding into a given conformation is evaluated and a simple condition for a protein model’s designability is outlined.
Developing Optimal Nonlinear Scoring Function for Protein Design
- Bioinformatics
, 2004
"... Motivation. Protein design aims to identify sequences compatible with a given protein fold but incompatible to any alternative folds. To select the correct sequences and to guide the search process, a design scoring function is critically important. Such a scoring function should be able to characte ..."
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Cited by 18 (11 self)
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Motivation. Protein design aims to identify sequences compatible with a given protein fold but incompatible to any alternative folds. To select the correct sequences and to guide the search process, a design scoring function is critically important. Such a scoring function should be able to characterize the global fitness landscape of many proteins simultaneously.
Brunak S: Using sequence motifs for enhanced neural network prediction of protein distance constraints
- In Proceedings of the Seventh International Conference on Intelligent Systems for Molecular Biology (ISMB99). La Jolla, CA: AAAI Press, Menlo Park, CA
, 1999
"... Abstract Correlations between sequence separation (in residues) and distance (in Angstrom) of any pair of amino acids in polypeptide chains are investigated. For each sequence separation we define a distance threshold. For pairs of amino acids where the distance between C α atoms is smaller than th ..."
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Cited by 17 (5 self)
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Abstract Correlations between sequence separation (in residues) and distance (in Angstrom) of any pair of amino acids in polypeptide chains are investigated. For each sequence separation we define a distance threshold. For pairs of amino acids where the distance between C α atoms is smaller than the threshold, a characteristic sequence (logo) motif, is found. The motifs change as the sequence separation increases: for small separations they consist of one peak located in between the two residues, then additional peaks at these residues appear, and finally the center peak smears out for very large separations. We also find correlations between the residues in the center of the motif. This and other statistical analyses are used to design neural networks with enhanced performance compared to earlier work. Importantly, the statistical analysis explains why neural networks perform better than simple statistical data-driven approaches such as pair probability density functions. The statistical results also explain characteristics of the network performance for increasing sequence separation. The improvement of the new network design is significant in the sequence separation range 10-30 residues. Finally, we find that the performance curve for increasing sequence separation is directly correlated to the corresponding information content. A WWW server, distanceP, is available at http://www.cbs.dtu.dk/services/distanceP/.
Protein Structure Prediction by Threading. - Why it Works and Why it Does Not
- J. Mol. Biol
, 1998
"... the quality of potentials used. These results are rationalized in terms of a threading free energy landscape. Possible ways to overcome the fundamental limitations of threading are discussed briey. # 1998 Academic Press Keywords: threading; Monte Carlo procedure; protein structure prediction *Corr ..."
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Cited by 15 (1 self)
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the quality of potentials used. These results are rationalized in terms of a threading free energy landscape. Possible ways to overcome the fundamental limitations of threading are discussed briey. # 1998 Academic Press Keywords: threading; Monte Carlo procedure; protein structure prediction *Corresponding author Introduction The problem of predicting protein conformation from sequences is of great importance and has drawn a lot of attention recently (see e.g. Moult et al., 1997; Shakhnovich, 1997a; Finkelstein, 1997; Jones, 1997; Levitt, 1997) with hundreds of papers from dozens of groups. A most desirable solution to the problem is to nd a model and an algorithm that stimulate folding of a protein pretty much in a way that mimics natural protein folding and converges to the native conformation. While some success along these lines has been documented (Kolinski & Skolnick, 1994), this approach encounters a number of serious technical difculties, making ab initio structure predict
Using genome-wide measurements for computational prediction of SH2-peptide interactions
- Nucleic Acids Res
, 2009
"... (Article begins on next page) The Harvard community has made this article openly available. Please share how this access benefits you. Your story matters. ..."
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Cited by 5 (0 self)
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(Article begins on next page) The Harvard community has made this article openly available. Please share how this access benefits you. Your story matters.
