Computational Resources for Predicting Protein-Protein Interactions

被引:10
|
作者
Tanwar, Himani [1 ]
Doss, C. George Priya [1 ]
机构
[1] VIT Univ, Sch Biosci & Technol, Vellore, Tamil Nadu, India
关键词
MOLECULAR INTERACTION DATABASE; INTERACTION NETWORKS; HIGH-THROUGHPUT; VISUALIZATION; TOOLS; INTERFACES; ALGORITHM; BIOLAYOUT; SUMMARIES; PROGRAM;
D O I
10.1016/bs.apcsb.2017.07.006
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
Proteins are the essential building blocks and functional components of a cell. They account for the vital functions of an organism. Proteins interact with each other and form protein interaction networks. These protein interactions play a major role in all the biological processes and pathways. The previous methods of predicting protein interactions were experimental which focused on a small set of proteins or a particular protein. However, these experimental approaches are low-throughput as they are time-consuming and require a significant amount of human effort. This led to the development of computational techniques that uses high-throughput experimental data for analyzing protein-protein interactions. The main purpose of this review is to provide an overview on the computational advancements and tools for the prediction of protein interactions. The major databases for the deposition of these interactions are also described. The advantages, as well as the specific limitations of these tools, are highlighted which will shed light on the computational aspects that can help the biologist and researchers in their research.
引用
收藏
页码:251 / 275
页数:25
相关论文
共 50 条
  • [31] Computational modeling of dynamic behavior of protein-protein interactions
    Perisic, OZ
    Haliloglu, T
    Lu, H
    BIOPHYSICAL JOURNAL, 2004, 86 (01) : 267A - 267A
  • [32] A computational framework for modeling functional protein-protein interactions
    Pal, Abantika
    Pal, Debnath
    Mitra, Pralay
    PROTEINS-STRUCTURE FUNCTION AND BIOINFORMATICS, 2021, 89 (10) : 1353 - 1364
  • [33] Computational Drug Design Targeting Protein-Protein Interactions
    Bienstock, Rachelle J.
    CURRENT PHARMACEUTICAL DESIGN, 2012, 18 (09) : 1240 - 1254
  • [34] Computational Approaches for the Prediction of Protein-Protein Interactions: A Survey
    Theofilatos, Konstantinos A.
    Dimitrakopoulos, Christos M.
    Tsakalidis, Athanasios K.
    Likothanassis, Spyridon D.
    Papadimitriou, Stergios T.
    Mavroudi, Seferina P.
    CURRENT BIOINFORMATICS, 2011, 6 (04) : 398 - 414
  • [35] Predicting disease genes using protein-protein interactions
    Oti, M.
    Snel, B.
    Huynen, M. A.
    Brunner, H. G.
    JOURNAL OF MEDICAL GENETICS, 2006, 43 (08) : 691 - 698
  • [36] Predicting protein-protein interactions using signature products
    Martin, S
    Roe, D
    Faulon, JL
    BIOINFORMATICS, 2005, 21 (02) : 218 - 226
  • [37] Predicting protein-protein interactions by a supervised learning classifier
    Huang, Y
    Frishman, D
    Muchnik, I
    COMPUTATIONAL BIOLOGY AND CHEMISTRY, 2004, 28 (04) : 291 - 301
  • [38] Computational Prediction of Protein-Protein Interaction Networks: Algorithms and Resources
    Zahiri, Javad
    Bozorgmehr, Joseph Hannon
    Masoudi-Nejad, Ali
    CURRENT GENOMICS, 2013, 14 (06) : 397 - 414
  • [39] Machine learning solutions for predicting protein-protein interactions
    Casadio, Rita
    Martelli, Pier Luigi
    Savojardo, Castrense
    WILEY INTERDISCIPLINARY REVIEWS-COMPUTATIONAL MOLECULAR SCIENCE, 2022, 12 (06)
  • [40] Predicting Protein-Protein Interactions based on ensemble classifiers
    Zhou, Zheng-Rong
    Song, Xiao-Feng
    Wang, Ming-Hao
    Tien Tzu Hsueh Pao/Acta Electronica Sinica, 2010, 38 (06): : 1464 - 1467