Recent Advances in Computational Methods for Identifying Anticancer Peptides

被引:6
作者
Feng, Pengmian [1 ]
Wang, Zhenyi [2 ]
机构
[1] North China Univ Sci & Technol, Sch Publ Hlth, Tangshan 063000, Peoples R China
[2] North China Univ Sci & Technol, Sch Life Sci, Ctr Genom & Computat Biol, Tangshan 063000, Peoples R China
关键词
Anticancer peptides; disease; cancer; drug target; machine learning methods; sequence encoding scheme; AMINO-ACID-COMPOSITION; MODEL QUALITY ASSESSMENT; S-NITROSYLATION SITES; FEATURE-SELECTION; GENERAL-FORM; SUBCELLULAR-LOCALIZATION; THERAPEUTIC PEPTIDES; PSEUDO; PROTEINS; IDENTIFICATION;
D O I
10.2174/1389450119666180801121548
中图分类号
R9 [药学];
学科分类号
1007 ;
摘要
Anticancer peptide (ACP) is a kind of small peptides that can kill cancer cells without damaging normal cells. In recent years, ACP has been pre-clinically used for cancer treatment. Therefore, accurate identification of ACPs will promote their clinical applications. In contrast to labor-intensive experimental techniques, a series of computational methods have been proposed for identifying ACPs. In this review, we briefly summarized the current progress in computational identification of ACPs. The challenges and future perspectives in developing reliable methods for identification of ACPs were also discussed. We anticipate that this review could provide novel insights into future researches on anticancer peptides.
引用
收藏
页码:481 / 487
页数:7
相关论文
共 110 条
  • [1] iACP-GAEnsC: Evolutionary genetic algorithm based ensemble classification of anticancer peptides by utilizing hybrid feature space
    Akbar, Shahid
    Hayat, Maqsood
    Iqbal, Muhammad
    Jan, Mian Ahmad
    [J]. ARTIFICIAL INTELLIGENCE IN MEDICINE, 2017, 79 : 62 - 70
  • [2] Oncolytic Activities of Host Defense Peptides
    Al-Benna, Sammy
    Shai, Yechiel
    Jacobsen, Frank
    Steinstraesser, Lars
    [J]. INTERNATIONAL JOURNAL OF MOLECULAR SCIENCES, 2011, 12 (11) : 8027 - 8051
  • [3] [Anonymous], BIOINFORMATICS
  • [4] [Anonymous], PHARMACEUTICS
  • [5] [Anonymous], DATABASE
  • [6] [Anonymous], INTERDISCIP SCI
  • [7] [Anonymous], BMC GENOMICS S7
  • [8] Activities at the Universal Protein Resource (UniProt)
    Apweiler, Rolf
    Bateman, Alex
    Martin, Maria Jesus
    O'Donovan, Claire
    Magrane, Michele
    Alam-Faruque, Yasmin
    Alpi, Emanuele
    Antunes, Ricardo
    Arganiska, Joanna
    Casanova, Elisabet Barrera
    Bely, Benoit
    Bingley, Mark
    Bonilla, Carlos
    Britto, Ramona
    Bursteinas, Borisas
    Chan, Wei Mun
    Chavali, Gayatri
    Cibrian-Uhalte, Elena
    Da Silva, Alan
    De Giorgi, Maurizio
    Dogan, Tunca
    Fazzini, Francesco
    Gane, Paul
    Castro, Leyla Garcia
    Garmiri, Penelope
    Hatton-Ellis, Emma
    Hieta, Reija
    Huntley, Rachael
    Legge, Duncan
    Liu, Wudong
    Luo, Jie
    MacDougall, Alistair
    Mutowo, Prudence
    Nightingale, 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
    Corbett, Matt
    [J]. NUCLEIC ACIDS RESEARCH, 2014, 42 (D1) : D191 - D198
  • [9] Recent trends in incidence of five common cancers in 26 European countries since 1988: Analysis of the European Cancer Observatory
    Arnold, Melina
    Karim-Kos, Henrike E.
    Coebergh, Jan Willem
    Byrnes, Graham
    Antilla, Ahti
    Ferlay, Jacques
    Renehan, Andrew G.
    Forman, David
    Soerjomataram, Isabelle
    [J]. EUROPEAN JOURNAL OF CANCER, 2015, 51 (09) : 1164 - 1187
  • [10] Biologically active compounds from marine organisms
    Blunden, G
    [J]. PHYTOTHERAPY RESEARCH, 2001, 15 (02) : 89 - 94