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
  • [1] Between Theory and Practice: Computational/Experimental Integrated Approaches to Understand the Solubility and Lipophilicity of PROTACs
    Venturi, Andrea
    Di Bona, Stefano
    Desantis, Jenny
    Eleuteri, Michela
    Bartalucci, Matteo
    Baroni, Massimo
    Benedetti, Paolo
    Goracci, Laura
    Cruciani, Gabriele
    JOURNAL OF MEDICINAL CHEMISTRY, 2024, 67 (18) : 16355 - 16380
  • [2] Expediting the Design, Discovery and Development of Anticancer Drugs using Computational Approaches
    Basith, Shaherin
    Cui, Minghua
    Macalino, Stephani J. Y.
    Choi, Sun
    CURRENT MEDICINAL CHEMISTRY, 2017, 24 (42) : 4753 - 4778
  • [3] Computational Modeling Approaches to Emotional Development
    Stein, Andrea G.
    Pollak, Seth D.
    DEVELOPMENTAL PSYCHOLOGY, 2024,
  • [4] Computational Approaches to Studying Thrombus Development
    Xu, Zhiliang
    Kamocka, Malgorzata
    Alber, Mark
    Rosen, Elliot D.
    ARTERIOSCLEROSIS THROMBOSIS AND VASCULAR BIOLOGY, 2011, 31 (03) : 500 - 505
  • [5] The use of computational approaches in inhaler development
    Wong, William
    Fletcher, David F.
    Traini, Daniela
    Chan, Hak-Kim
    Young, Paul M.
    ADVANCED DRUG DELIVERY REVIEWS, 2012, 64 (04) : 312 - 322
  • [6] Computational approaches to neural reward and development
    Montague, PR
    Quartz, SR
    MENTAL RETARDATION AND DEVELOPMENTAL DISABILITIES RESEARCH REVIEWS, 1999, 5 (01): : 86 - 99
  • [7] Computational approaches to the development of perceptual expertise
    Palmeri, TJ
    Wong, ACN
    Gauthier, I
    TRENDS IN COGNITIVE SCIENCES, 2004, 8 (08) : 378 - 386
  • [8] Scalp EEG markers of normal infant development using visual and computational approaches
    Goetz, Parker
    Hu, Derek
    To, Phuc Duy
    Garner, Cristal
    Yuen, Tammy
    Skora, Clare
    Shrey, Daniel W.
    Lopour, Beth A.
    2021 43RD ANNUAL INTERNATIONAL CONFERENCE OF THE IEEE ENGINEERING IN MEDICINE & BIOLOGY SOCIETY (EMBC), 2021, : 6528 - 6532
  • [9] Discovery and Development of ATP-Competitive mTOR Inhibitors Using Computational Approaches
    Luo, Yao
    Wang, Ling
    CURRENT PHARMACEUTICAL DESIGN, 2017, 23 (29) : 4321 - 4331
  • [10] Click chemistry in the development of PROTACs
    Yang, Ce
    Tripathi, Ravi
    Wang, Binghe
    RSC CHEMICAL BIOLOGY, 2024, 5 (03): : 189 - 197