Antibody informatics for drug discovery

被引:44
|
作者
Shirai, Hiroki [1 ]
Prades, Catherine [2 ]
Vita, Randi [3 ]
Marcatili, Paolo [4 ]
Popovic, Bojana [5 ]
Xu, Jianqing [5 ]
Overington, John P. [6 ]
Hirayama, Kazunori [1 ]
Soga, Shinji [1 ]
Tsunoyama, Kazuhisa [1 ]
Clark, Dominic [6 ]
Lefranc, Marie-Paule [7 ]
Ikeda, Kazuyoshi [6 ]
机构
[1] Astellas Pharma Inc, Drug Discovery Res, Mol Med Res Labs, Tsukuba, Ibaraki 3058585, Japan
[2] Ctr Rech Vitry Sur Seine, Sanofi Aventis Rech & Dev, F-94403 Vitry Sur Seine, France
[3] La Jolla Inst Allergy & Immunol, Immune Epitope Database & Anal Project, La Jolla, CA 92037 USA
[4] Tech Univ Denmark, Dept Syst Biol, Ctr Biol Sequence Anal, DK-2800 Lyngby, Denmark
[5] MedImmune Ltd, Cambridge CB21 6GH, England
[6] EMBL European Bioinformat Inst, Cambridge CB10 1SD, England
[7] Univ Montpellier 2, IMGT, Lab Immunogenet Mol LIGM, Inst Genet Humaine,UPR CNRS 1142, F-34396 Montpellier 5, France
来源
关键词
Antibody informatics; Antibody modeling; Antibody database; Antibody numbering; Drug discovery; T-CELL-RECEPTORS; VARIABLE DOMAINS; STRUCTURAL CLASSIFICATION; CANONICAL STRUCTURES; IMGT-ONTOLOGY; IMMUNOGLOBULIN; DATABASE; BINDING; REGION; PREDICTION;
D O I
10.1016/j.bbapap.2014.07.006
中图分类号
Q5 [生物化学]; Q7 [分子生物学];
学科分类号
071010 ; 081704 ;
摘要
More and more antibody therapeutics are being approved every year, mainly due to their high efficacy and antigen selectivity. However, it is still difficult to identify the antigen, and thereby the function, of an antibody if no other information is available. There are obstacles inherent to the antibody science in every project in antibody drug discovery. Recent experimental technologies allow for the rapid generation of large-scale data on antibody sequences, affinity, potency, structures, and biological functions; this should accelerate drug discovery research. Therefore, a robust bioinformatic infrastructure for these large data sets has become necessary. In this article, we first identify and discuss the typical obstacles faced during the antibody drug discovery process. We then summarize the current status of three sub-fields of antibody informatics as follows: (i) recent progress in technologies for antibody rational design using computational approaches to affinity and stability improvement, as well as ab-initio and homology-based antibody modeling; (ii) resources for antibody sequences, structures, and immune epitopes and open drug discovery resources for development of antibody drugs; and (iii) antibody numbering and IMGT. Here, we review "antibody informatics," which may integrate the above three fields so that bridging the gaps between industrial needs and academic solutions can be accelerated. This article is part of a Special Issue entitled: Recent advances in molecular engineering of antibody. (C) 2014 Elsevier B.V. All rights reserved.
引用
收藏
页码:2002 / 2015
页数:14
相关论文
共 50 条
  • [1] Informatics and drug discovery - What is next
    Cohen, FE
    ABSTRACTS OF PAPERS OF THE AMERICAN CHEMICAL SOCIETY, 1997, 213 : 394 - COMP
  • [2] Component architecture in drug discovery informatics
    Smith, PM
    CURRENT OPINION IN DRUG DISCOVERY & DEVELOPMENT, 2002, 5 (03) : 361 - 366
  • [3] Drug discovery informatics market escalates
    不详
    BIOPHARM INTERNATIONAL, 2005, 18 (06) : 20 - 20
  • [4] Discovery informatics: its evolving role in drug discovery
    Claus, BL
    Underwood, DJ
    DRUG DISCOVERY TODAY, 2002, 7 (18) : 957 - 966
  • [5] Discovery informatics: Integrating genomics and proteomics for drug discovery.
    Adams, MD
    ABSTRACTS OF PAPERS OF THE AMERICAN CHEMICAL SOCIETY, 2002, 224 : U470 - U470
  • [6] Rare Diseases: Drug Discovery and Informatics Resource
    Zhao, Mingzhu
    Wei, Dong-Qing
    INTERDISCIPLINARY SCIENCES-COMPUTATIONAL LIFE SCIENCES, 2018, 10 (01) : 195 - 204
  • [7] Evolving role of modeling and informatics in drug discovery
    Walters, W. Patrick
    ABSTRACTS OF PAPERS OF THE AMERICAN CHEMICAL SOCIETY, 2014, 247
  • [8] Chemical Informatics and the Drug Discovery Knowledge Pyramid
    Lushington, Gerald H.
    Dong, Yinghua
    Theertham, Bhargav
    COMBINATORIAL CHEMISTRY & HIGH THROUGHPUT SCREENING, 2013, 16 (10) : 764 - 776
  • [9] Informatics resources for tuberculosis - Towards drug discovery
    Sundaramurthi, Jagadish Chandrabose
    Brindha, S.
    Reddy, T. B. K.
    Hanna, Luke Elizabeth
    TUBERCULOSIS, 2012, 92 (02) : 133 - 138
  • [10] Rare Diseases: Drug Discovery and Informatics Resource
    Mingzhu Zhao
    Dong-Qing Wei
    Interdisciplinary Sciences: Computational Life Sciences, 2018, 10 : 195 - 204