Comprehensive review and empirical analysis of hallmarks of DNA-, RNA- and protein-binding residues in protein chains

被引:81
作者
Zhang, Jian [1 ]
Ma, Zhiqiang [2 ]
Kurgan, Lukasz [3 ]
机构
[1] Xinyang Normal Univ, Sch Comp & Informat Technol, Xinyang, Peoples R China
[2] Northeast Normal Univ, Coll Humanities & Sci, Changchun, Jilin, Peoples R China
[3] Virginia Commonwealth Univ, Comp Sci, Richmond, VA USA
关键词
protein-RNA interactions; protein-DNA interactions; protein-nucleic acid interactions; protein-protein interactions; DNA-binding residues; RNA-binding residues; STRUCTURALLY CONSERVED RESIDUES; STRUCTURE-BASED PREDICTION; AROMATIC-AMINO-ACIDS; EVOLUTIONARY CONSERVATION; SECONDARY STRUCTURE; INTERACTION SITES; WEB SERVER; HOT-SPOTS; SEQUENCE; RECOGNITION;
D O I
10.1093/bib/bbx168
中图分类号
Q5 [生物化学];
学科分类号
071010 ; 081704 ;
摘要
Proteins interact with a variety of molecules including proteins and nucleic acids. We review a comprehensive collection of over 50 studies that analyze and/or predict these interactions. While majority of these studies address either solely protein-DNA or protein-RNA binding, only a few have a wider scope that covers both protein-protein and protein-nucleic acid binding. Our analysis reveals that binding residues are typically characterized with three hallmarks: relative solvent accessibility (RSA), evolutionary conservation and propensity of amino acids (AAs) for binding. Motivated by drawbacks of the prior studies, we perform a large-scale analysis to quantify and contrast the three hallmarks for residues that bind DNA-, RNA-, protein- and (for the first time) multi-ligand-binding residues that interact with DNA and proteins, and with RNA and proteins. Results generated on a well-annotated data set of over 23 000 proteins show that conservation of binding residues is higher for nucleic acid-than protein-binding residues. Multi-ligand-binding residues are more conserved and have higher RSA than single-ligand-binding residues. We empirically show that each hallmark discriminates between binding and non-binding residues, even predicted RSA, and that combining them improves discriminatory power for each of the five types of interactions. Linear scoring functions that combine these hallmarks offer good predictive performance of residue-level propensity for binding and provide intuitive interpretation of predictions. Better understanding of these residue-level interactions will facilitate development of methods that accurately predict binding in the exponentially growing databases of protein sequences.
引用
收藏
页码:1250 / 1268
页数:19
相关论文
共 113 条
  • [1] PSSM-based prediction of DNA binding sites in proteins
    Ahmad, S
    Sarai, A
    [J]. BMC BIOINFORMATICS, 2005, 6 (1)
  • [2] Protein-DNA interactions: structural, thermodynamic and clustering patterns of conserved residues in DNA-binding proteins
    Ahmad, Shandar
    Keskin, Ozlem
    Sarai, Akinori
    Nussinov, Ruth
    [J]. NUCLEIC ACIDS RESEARCH, 2008, 36 (18) : 5922 - 5932
  • [3] Apweiler R, 2004, NUCLEIC ACIDS RES, V32, pD115, DOI [10.1093/nar/gkw1099, 10.1093/nar/gkh131]
  • [4] Asadabadi Ebrahim Barzegari, 2013, Avicenna Journal of Medical Biotechnology, V5, P148
  • [5] Dissecting protein-RNA recognition sites
    Bahadur, Ranjit Prasad
    Zacharias, Martin
    Janin, Joel
    [J]. NUCLEIC ACIDS RESEARCH, 2008, 36 (08) : 2705 - 2716
  • [6] Role of aromatic amino acids in protein-nucleic acid recognition
    Baker, Christopher M.
    Grant, Guy H.
    [J]. BIOPOLYMERS, 2007, 85 (5-6) : 456 - 470
  • [7] PRince: a web server for structural and physicochemical analysis of Protein-RNA interface
    Barik, Amita
    Mishra, Abhishek
    Bahadur, Ranjit Prasad
    [J]. NUCLEIC ACIDS RESEARCH, 2012, 40 (W1) : W440 - W444
  • [8] UniProt: a hub for protein information
    Bateman, Alex
    Martin, Maria Jesus
    O'Donovan, Claire
    Magrane, Michele
    Apweiler, Rolf
    Alpi, Emanuele
    Antunes, Ricardo
    Arganiska, Joanna
    Bely, Benoit
    Bingley, Mark
    Bonilla, Carlos
    Britto, Ramona
    Bursteinas, Borisas
    Chavali, Gayatri
    Cibrian-Uhalte, Elena
    Da Silva, Alan
    De Giorgi, Maurizio
    Dogan, Tunca
    Fazzini, Francesco
    Gane, Paul
    Cas-tro, Leyla Garcia
    Garmiri, Penelope
    Hatton-Ellis, Emma
    Hieta, Reija
    Huntley, Rachael
    Legge, Duncan
    Liu, Wudong
    Luo, Jie
    MacDougall, Alistair
    Mutowo, Prudence
    Nightin-gale, Andrew
    Orchard, Sandra
    Pichler, Klemens
    Poggioli, Diego
    Pundir, Sangya
    Pureza, Luis
    Qi, Guoying
    Rosanoff, Steven
    Saidi, Rabie
    Sawford, Tony
    Shypitsyna, Aleksandra
    Turner, Edward
    Volynkin, Vladimir
    Wardell, Tony
    Watkins, Xavier
    Zellner, Hermann
    Cowley, Andrew
    Figueira, Luis
    Li, Weizhong
    McWilliam, Hamish
    [J]. NUCLEIC ACIDS RESEARCH, 2015, 43 (D1) : D204 - D212
  • [9] Deciphering the shape and deformation of secondary structures through local conformation analysis
    Baussand, Julie
    Camproux, Anne-Claude
    [J]. BMC STRUCTURAL BIOLOGY, 2011, 11
  • [10] The Protein Data Bank at 40: Reflecting on the Past to Prepare for the Future
    Berman, Helen M.
    Kleywegt, Gerard J.
    Nakamura, Haruki
    Markley, John L.
    [J]. STRUCTURE, 2012, 20 (03) : 391 - 396