Literature DB >> 10878855

Beta-and gamma-turns in proteins revisited: a new set of amino acid turn-type dependent positional preferences and potentials.

K Guruprasad1, S Rajkumar.   

Abstract

The number of beta-turns in a representative set of 426 protein three-dimensional crystal structures selected from the recent Protein Data Bank has nearly doubled and the number of gamma-turns in a representative set of 320 proteins has increased over seven times since the previous analysis. Beta-turns (7153) and gamma-turns (911) extracted from these proteins were used to derive a revised set of type-dependent amino acid positional preferences and potentials. Compared with previous results, the preference for proline, methionine and tryptophan has increased and the preference for glutamine, valine, glutamic acid and alanine has decreased for beta-turns. Certain new amino acid preferences were observed for both turn types and individual amino acids showed turn-type dependent positional preferences. The rationale for new amino acid preferences are discussed in the light of hydrogen bonds and other interactions involving the turns. Where main-chain hydrogen bonds of the type NH(i + 3) --> CO(i) were not observed for some beta-turns, other main-chain hydrogen bonds or solvent interactions were observed that possibly stabilize such beta-turns. A number of unexpected isolated beta-turns with proline at i + 2 position were also observed. The NH(i + 2) --> CO(i) hydrogen bond was observed for almost all gamma-turns. Nearly 20% classic gamma-turns and 43% inverse gamma-turns are isolated turns.

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Year:  2000        PMID: 10878855

Source DB:  PubMed          Journal:  J Biosci        ISSN: 0250-5991            Impact factor:   1.826


  39 in total

1.  A neural-network based method for prediction of gamma-turns in proteins from multiple sequence alignment.

Authors:  Harpreet Kaur; G P S Raghava
Journal:  Protein Sci       Date:  2003-05       Impact factor: 6.725

2.  Prediction of beta-turns in proteins from multiple alignment using neural network.

Authors:  Harpreet Kaur; Gajendra Pal Singh Raghava
Journal:  Protein Sci       Date:  2003-03       Impact factor: 6.725

3.  ProRegIn: a regularity index for the selection of native-like tertiary structures of proteins.

Authors:  Lipi Thukral; Sandhya R Shenoy; Kumkum Bhushan; B Jayaram
Journal:  J Biosci       Date:  2007-01       Impact factor: 1.826

Review 4.  Roles of beta-turns in protein folding: from peptide models to protein engineering.

Authors:  Anna Marie C Marcelino; Lila M Gierasch
Journal:  Biopolymers       Date:  2008-05       Impact factor: 2.505

5.  Amino acid contribution to protein solubility: Asp, Glu, and Ser contribute more favorably than the other hydrophilic amino acids in RNase Sa.

Authors:  Saul R Trevino; J Martin Scholtz; C Nick Pace
Journal:  J Mol Biol       Date:  2006-10-13       Impact factor: 5.469

6.  Increasing protein conformational stability by optimizing beta-turn sequence.

Authors:  Saul R Trevino; Stephanie Schaefer; J Martin Scholtz; C Nick Pace
Journal:  J Mol Biol       Date:  2007-08-09       Impact factor: 5.469

7.  Molecular Dynamics Simulations of 441 Two-Residue Peptides in Aqueous Solution: Conformational Preferences and Neighboring Residue Effects with the Amber ff99SB-ildn-NMR Force Field.

Authors:  Shuxiang Li; Casey T Andrews; Tamara Frembgen-Kesner; Mark S Miller; Stephen L Siemonsma; Timothy D Collingsworth; Isaac T Rockafellow; Nguyet Anh Ngo; Brady A Campbell; Reid F Brown; Chengxuan Guo; Michael Schrodt; Yu-Tsan Liu; Adrian H Elcock
Journal:  J Chem Theory Comput       Date:  2015-03-10       Impact factor: 6.006

8.  Predicting beta-turns and their types using predicted backbone dihedral angles and secondary structures.

Authors:  Petros Kountouris; Jonathan D Hirst
Journal:  BMC Bioinformatics       Date:  2010-07-31       Impact factor: 3.169

9.  NetTurnP--neural network prediction of beta-turns by use of evolutionary information and predicted protein sequence features.

Authors:  Bent Petersen; Claus Lundegaard; Thomas Nordahl Petersen
Journal:  PLoS One       Date:  2010-11-30       Impact factor: 3.240

10.  Prediction of beta-turns at over 80% accuracy based on an ensemble of predicted secondary structures and multiple alignments.

Authors:  Ce Zheng; Lukasz Kurgan
Journal:  BMC Bioinformatics       Date:  2008-10-10       Impact factor: 3.169

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