Development of PROTACs using computational approaches

被引:4
|
作者
Ge, Jingxuan [1 ,2 ]
Hsieh, Chang-Yu [1 ]
Fang, Meijing [3 ]
Sun, Huiyong [4 ]
Hou, Tingjun [1 ,3 ]
机构
[1] Zhejiang Univ, Coll Pharmaceut Sci, Hangzhou 310058, Zhejiang, Peoples R China
[2] CarbonSilicon AI Technol Co Ltd, Hangzhou 310018, Zhejiang, Peoples R China
[3] Zhejiang Univ, Polytech Inst, Hangzhou 310058, Zhejiang, Peoples R China
[4] China Pharmaceut Univ, Dept Med Chem, Nanjing 210009, Jiangsu, Peoples R China
基金
中国国家自然科学基金;
关键词
PROTEIN-DEGRADATION; PREDICTION; COMPLEX; UBIQUITINATION; KNOCKDOWN; MOLECULES; DISCOVERY; RESOURCE;
D O I
10.1016/j.tips.2024.10.006
中图分类号
R9 [药学];
学科分类号
1007 ;
摘要
Proteolysis-targeting chimeras (PROTACs) are drugs designed to degrade target proteins via the ubiquitin-proteasome system. With the application of computational biology/chemistry technique in drug design, numerous computer-aided drug design and artificial intelligence (AI)-driven drug design (CADD/AIDD) methods have recently emerged to facilitate the development of PROTAC drugs. We systematically review the role of in silico tools in PROTAC drug design, emphasizing how computational software can model PROTAC action and structure, predict activity, and assist in molecule design. We also discuss current challenges in the rational design of PROTACs from an in silico perspective, such as deviations from small-molecule druggability and the limited availability of training data. We provide an overview of recent discoveries and emerging research in this field, and discuss their potential impact on PROTAC design strategies.
引用
收藏
页码:1162 / 1174
页数:13
相关论文
共 50 条
  • [31] Computational Approaches for the Discovery and Development of Pharmacologically Active Natural Products
    Medina-Franco, Jose L.
    BIOMOLECULES, 2021, 11 (05)
  • [32] PROTACs: Emerging Targeted Protein Degradation Approaches for Advanced Druggable Strategies
    Sincere, Nuwayo Ishimwe
    Anand, Krishnan
    Ashique, Sumel
    Yang, Jing
    You, Chongge
    MOLECULES, 2023, 28 (10):
  • [33] Solubility Enhanced Formulation Approaches to Overcome Oral Delivery Obstacles of PROTACs
    Poestges, Florian
    Kayser, Kevin
    Appelhaus, Jan
    Monschke, Marius
    Gutschow, Michael
    Steinebach, Christian
    Wagner, Karl G. G.
    PHARMACEUTICS, 2023, 15 (01)
  • [34] Using computational approaches to model hematite surfaces.
    Lado-Touriño, I
    Tsobnang, F
    Ngoepe, P
    ABSTRACTS OF PAPERS OF THE AMERICAN CHEMICAL SOCIETY, 1999, 217 : U693 - U693
  • [35] Identifying new targets in leukemogenesis using computational approaches
    Jayaraman, Archana
    Jamil, Kaiser
    Khan, Haseeb A.
    SAUDI JOURNAL OF BIOLOGICAL SCIENCES, 2015, 22 (05) : 610 - 622
  • [36] Deconvoluting the Dementia phenotype using functional computational approaches
    Ivanov, D.
    Hill, M.
    Allen, N.
    Thornton, J. M.
    Williams, J.
    Escott-Price, V.
    EUROPEAN JOURNAL OF HUMAN GENETICS, 2019, 27 : 1699 - 1700
  • [37] A Study of Process Optimization Using Computational Intelligence Approaches
    Su, Chao-Ton
    Chang, C. Alec
    2011 INTERNATIONAL CONFERENCE ON FUTURE MANAGEMENT SCIENCE AND ENGINEERING (ICFMSE 2011), VOL 1, 2011, 5 : 6 - 9
  • [38] CRISPR genome editing using computational approaches: A survey
    Alipanahi, Roghayyeh
    Safari, Leila
    Khanteymoori, Alireza
    FRONTIERS IN BIOINFORMATICS, 2023, 2
  • [39] Computational drug discovery using deep learning approaches
    Isayev, Olexandr
    Politi, Regina
    Tropsha, Alexander
    ABSTRACTS OF PAPERS OF THE AMERICAN CHEMICAL SOCIETY, 2016, 251
  • [40] Methodological and Computational Approaches to using NGS for Mutation Quantitation
    McKinzie, P. B.
    Bishop, M. E.
    ENVIRONMENTAL AND MOLECULAR MUTAGENESIS, 2018, 59 : 71 - 71