Preference of Amino acids in Different Protein Structural Classes: A Database Analysis

被引:0
|
作者
Ismail, Wazim Mohammed [1 ,2 ]
Chowdhury, Shibasish [1 ]
机构
[1] Birla Inst Technol & Sci, Biol Sci Grp, Pilani 333031, Rajasthan, India
[2] IBM India Private Ltd, Bangalore 560071, Karnataka, India
关键词
SECONDARY STRUCTURE; ALPHA-HELICES; BETA-SHEET; PROPENSITIES; RECOGNITION; PREDICTION; DEPENDENCE;
D O I
暂无
中图分类号
R318 [生物医学工程];
学科分类号
0831 ;
摘要
Understanding sequence-structure relationship is the key step in protein modeling and de novo protein design. Although almost 55,000 protein structures are solved and stored in protein data bank, elucidating sequence-structure relationship is still a challenging task. To understand sequence-structure relationship better, a statistical analysis of amino acid residues in four major structural classes of protein viz. alpha proteins, ss proteins, alpha/ss proteins and alpha+ss proteins is performed. We use non-homologous proteins from (< 30% identity) October 2008 release Brookhaven Protein Data Bank (PDB) with resolution better than 2.5 angstrom. Interestingly, in comparison to the helical protein, the helical propensities of hydrophobic residues in mix proteins (containing both alpha helix and ss sheet) are increased significantly. On the other hand, the helical propensities of hydrophilic residues are reduced in mixed proteins. A reverse trend is observed in strand propensity. The difference in helical propensity of hydrophobic and hydrophilic residues in different fold may be due to differential folding mechanism. The size of protein may also play a crucial role. A position specific analysis of helices is also done in all alpha and alpha/ss proteins. The detailed analysis of helix dissection reveals that, the presence of ss sheet influences the individual preference of amino acids in different positions within helix. This result indicates that the preference of amino acid in different positions (N terminus, C terminus and middle) within a helix are influenced by long range interactions with other structural elements.
引用
收藏
页数:5
相关论文
共 50 条
  • [31] Protein-RNA interactions: structural characteristics and hotspot amino acids
    Krueger, Dennis M.
    Neubacher, Saskia
    Grossmann, Tom N.
    RNA, 2018, 24 (11) : 1457 - 1465
  • [32] Protein-RNA interactions: Structural analysis and functional classes
    Ellis, Jonathan J.
    Broom, Mark
    Jones, Susan
    PROTEINS-STRUCTURE FUNCTION AND BIOINFORMATICS, 2007, 66 (04) : 903 - 911
  • [33] PREDICTION OF PROTEIN STRUCTURAL CLASSES
    CHOU, KC
    ZHANG, CT
    CRITICAL REVIEWS IN BIOCHEMISTRY AND MOLECULAR BIOLOGY, 1995, 30 (04) : 275 - 349
  • [34] CORRELATION-ANALYSIS OF AMINO-ACID USAGE IN PROTEIN CLASSES
    KARLIN, S
    BUCHER, P
    PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA, 1992, 89 (24) : 12165 - 12169
  • [35] Finding the frequency of occurrence of amino acids in different types of protein β-structures
    Osorio, Natalia
    Almeida, Paulo F.
    Cardenas, Jaime
    Elms, Alex
    BIOPHYSICAL JOURNAL, 2024, 123 (03) : 201A - 201A
  • [36] CHARACTERISTICS OF DIFFERENT AMINO ACIDS AS PROTEIN PRECURSORS IN MOUSE BRAIN - ADVANTAGES OF CERTAIN CARXYL-LABELED AMINO ACIDS
    BANKER, G
    COTMAN, CW
    ARCHIVES OF BIOCHEMISTRY AND BIOPHYSICS, 1971, 142 (02) : 565 - &
  • [37] Comparative analysis of amino acids and amino-acid derivatives in protein crystallization
    Ito, Len
    Shiraki, Kentaro
    Yamaguchi, Hiroshi
    ACTA CRYSTALLOGRAPHICA SECTION F-STRUCTURAL BIOLOGY COMMUNICATIONS, 2010, 66 : 744 - 749
  • [38] Distribution of dipeptides in different protein structural classes: an effort to find new similarities
    Mahin Ghadimi
    Emran Heshmati
    Khosrow Khalifeh
    European Biophysics Journal, 2018, 47 : 31 - 38
  • [39] Distribution of dipeptides in different protein structural classes: an effort to find new similarities
    Ghadimi, Mahin
    Heshmati, Emran
    Khalifeh, Khosrow
    EUROPEAN BIOPHYSICS JOURNAL WITH BIOPHYSICS LETTERS, 2018, 47 (01): : 31 - 38
  • [40] BIOPEP database of sensory peptides and amino acids
    Iwaniak, Anna
    Minkiewicz, Piotr
    Darewicz, Malgorzata
    Sieniawski, Krzysztof
    Starowicz, Piotr
    FOOD RESEARCH INTERNATIONAL, 2016, 85 : 155 - 161