Proteochemometric Modeling of the Antigen-Antibody Interaction: New Fingerprints for Antigen, Antibody and Epitope-Paratope Interaction

被引:12
作者
Qiu, Tianyi [1 ]
Xiao, Han [2 ]
Zhang, Qingchen [1 ]
Qiu, Jingxuan [1 ]
Yang, Yiyan [1 ]
Wu, Dingfeng [1 ]
Cao, Zhiwei [1 ,3 ]
Zhu, Ruixin [1 ,4 ]
机构
[1] Tongji Univ, Sch Life Sci & Technol, Dept Bioinformat, Shanghai 200092, Peoples R China
[2] Univ Helsinki, Dept Comp Sci, FI-00014 Helsinki, Finland
[3] Shanghai Ctr Bioinformat Technol, Shanghai 201203, Peoples R China
[4] Liaoning Univ Tradit Chinese Med, Sch Pharm, Dalian 116600, Liaoning, Peoples R China
来源
PLOS ONE | 2015年 / 10卷 / 04期
基金
中国国家自然科学基金;
关键词
PROTEIN-BINDING SITES; CRYSTAL-STRUCTURE; SPACE; RECOGNITION; PREDICTION; INHIBITORS; INTERFACE; ALIGNMENT; PATTERNS; SURFACES;
D O I
10.1371/journal.pone.0122416
中图分类号
O [数理科学和化学]; P [天文学、地球科学]; Q [生物科学]; N [自然科学总论];
学科分类号
07 ; 0710 ; 09 ;
摘要
Despite the high specificity between antigen and antibody binding, similar epitopes can be recognized or cross-neutralized by paratopes of antibody with different binding affinities. How to accurately characterize this slight variation which may or may not change the antigen-antibody binding affinity is a key issue in this area. In this report, by combining cylinder model with shell structure model, a new fingerprint was introduced to describe both the structural and physical-chemical features of the antigen and antibody protein. Furthermore, beside the description of individual protein, the specific epitope-paratope interaction fingerprint (EPIF) was developed to reflect the bond and the environment of the antigen-antibody interface. Finally, Proteochemometric Modeling of the antigen-antibody interaction was established and evaluated on 429 antigen-antibody complexes. By using only protein descriptors, our model achieved the best performance (R-2 = 0: 91; Q(test)(2) = 0: 68) among peers. Further, together with EPIF as a new cross-term, our model (R-2 = 0: 92; Q(2) test = 0: 74) can significantly outperform peers with multiplication of ligand and protein descriptors as a cross-term (R2 <= 0.81; Q(test)(2) <= 0: 44). Results illustrated that: 1) our newly designed protein fingerprints and EPIF can better describe the antigen-antibody interaction; 2) EPIF is a better and specific cross-term in Proteochemometric Modeling for antigen-antibody interaction. The fingerprints designed in this study will provide assistance to the description of antigen-antibody binding, and in future, it may be valuable help for the high-throughput antibody screening. The algorithm is freely available on request.
引用
收藏
页数:15
相关论文
共 40 条
  • [1] The Protein Data Bank
    Berman, HM
    Westbrook, J
    Feng, Z
    Gilliland, G
    Bhat, TN
    Weissig, H
    Shindyalov, IN
    Bourne, PE
    [J]. NUCLEIC ACIDS RESEARCH, 2000, 28 (01) : 235 - 242
  • [2] Discovery of similar regions on protein surfaces
    Bock, Mary Ellen
    Garutti, Claudio
    Guerra, Concettina
    [J]. JOURNAL OF COMPUTATIONAL BIOLOGY, 2007, 14 (03) : 285 - 299
  • [3] Selection and analysis of an optimized anti-VEGF antibody: Crystal structure of an affinity-matured Fab in complex with antigen
    Chen, Y
    Wiesmann, C
    Fuh, G
    Li, B
    Christinger, HW
    McKay, P
    de Vos, AM
    Lowman, HB
    [J]. JOURNAL OF MOLECULAR BIOLOGY, 1999, 293 (04) : 865 - 881
  • [4] Broadly Neutralizing Antiviral Antibodies
    Corti, Davide
    Lanzavecchia, Antonio
    [J]. ANNUAL REVIEW OF IMMUNOLOGY, VOL 31, 2013, 31 : 705 - 742
  • [5] Delineating Antibody Recognition in Polyclonal Sera from Patterns of HIV-1 Isolate Neutralization
    Georgiev, Ivelin S.
    Doria-Rose, Nicole A.
    Zhou, Tongqing
    Do Kwon, Young
    Staupe, Ryan P.
    Moquin, Stephanie
    Chuang, Gwo-Yu
    Louder, Mark K.
    Schmidt, Stephen D.
    Altae-Tran, Han R.
    Bailer, Robert T.
    McKee, Krisha
    Nason, Martha
    O'Dell, Sijy
    Ofek, Gilad
    Pancera, Marie
    Srivatsan, Sanjay
    Shapiro, Lawrence
    Connors, Mark
    Migueles, Stephen A.
    Morris, Lynn
    Nishimura, Yoshiaki
    Martin, Malcolm A.
    Mascola, John R.
    Kwong, Peter D.
    [J]. SCIENCE, 2013, 340 (6133) : 751 - 756
  • [6] Goldsby, 2003, IMM, P57
  • [7] A new protein binding pocket similarity measure based on comparison of clouds of atoms in 3D: application to ligand prediction
    Hoffmann, Brice
    Zaslavskiy, Mikhail
    Vert, Jean-Philippe
    Stoven, Veronique
    [J]. BMC BIOINFORMATICS, 2010, 11
  • [8] Proteochemometric Modeling of the Bioactivity Spectra of HIV-1 Protease Inhibitors by Introducing Protein-Ligand Interaction Fingerprint
    Huang, Qi
    Jin, Haixiao
    Liu, Qi
    Wu, Qiong
    Kang, Hong
    Cao, Zhiwei
    Zhu, Ruixin
    [J]. PLOS ONE, 2012, 7 (07):
  • [9] Data mining of sequences and 3D structures of allergenic proteins
    Ivanciuc, O
    Schein, CH
    Braun, W
    [J]. BIOINFORMATICS, 2002, 18 (10) : 1358 - 1364
  • [10] AAindex: amino acid index database, progress report 2008
    Kawashima, Shuichi
    Pokarowski, Piotr
    Pokarowska, Maria
    Kolinski, Andrzej
    Katayama, Toshiaki
    Kanehisa, Minoru
    [J]. NUCLEIC ACIDS RESEARCH, 2008, 36 : D202 - D205