Halogen Bond: Its Role beyond Drug-Target Binding Affinity for Drug Discovery and Development

被引:284
|
作者
Xu, Zhijian [1 ]
Yang, Zhuo [1 ]
Liu, Yingtao [1 ]
Lu, Yunxiang [2 ]
Chen, Kaixian [1 ]
Zhu, Weiliang [1 ]
机构
[1] Chinese Acad Sci, Drug Discovery & Design Ctr, Key Lab Receptor Res, State Key Lab Drug Res,Shanghai Inst Mat Med, Shanghai 201203, Peoples R China
[2] E China Univ Sci & Technol, Dept Chem, Shanghai 200237, Peoples R China
关键词
NONCOVALENT INTERACTIONS; DENSITY FUNCTIONALS; CRYSTAL-STRUCTURES; RATIONAL DESIGN; CHARGE-DENSITY; FORCE-FIELD; TRANSTHYRETIN; GEOMETRY; INHIBITORS; CHEMISTRY;
D O I
10.1021/ci400539q
中图分类号
R914 [药物化学];
学科分类号
100701 ;
摘要
Halogen bond has attracted a great deal of attention in the past years for hit-to-lead-to-candidate optimization aiming at improving drug-target binding affinity. In general, heavy organohalogens (i.e., organochlorines, organobromines, and organoiodines) are capable of forming halogen bonds while organofluorines are not. In order to explore the possible roles that halogen bonds could play beyond improving binding affinity, we performed a detailed database survey and quantum chemistry calculation with close attention paid to (1) the change of the ratio of heavy organohalogens to organofluorines along the drug discovery and development process and (2) the halogen bonds between organohalogens and nonbiopolymers or nontarget biopolymers. Our database survey revealed that (1) an obviously increasing trend of the ratio of heavy organohalogens to organofluorines was observed along the drug discovery and development process, illustrating that more organofluorines are worn and eliminated than heavy organohalogens during the process, suggesting that heavy halogens with the capability of forming halogen bonds should have priority for lead optimization; and (2) more than 16% of the halogen bonds in PDB are formed between organohalogens and water, and nearly 20% of the halogen bonds are formed with the proteins that are involved in the ADME/T process. Our QM/MM calculations validated the contribution of the halogen bond to the binding between organohalogens and plasma transport proteins. Thus, halogen bonds could play roles not only in improving drug-target binding affinity but also in tuning ADME/T property. Therefore, we suggest that albeit halogenation is a valuable approach for improving ligand bioactivity, more attention should be paid in the future to the application of the halogen bond for ligand ADME/T property optimization.
引用
收藏
页码:69 / 78
页数:10
相关论文
共 50 条
  • [21] DGDTA: dynamic graph attention network for predicting drug-target binding affinity
    Zhai, Haixia
    Hou, Hongli
    Luo, Junwei
    Liu, Xiaoyan
    Wu, Zhengjiang
    Wang, Junfeng
    [J]. BMC BIOINFORMATICS, 2023, 24 (01)
  • [22] FingerDTA: A Fingerprint-Embedding Framework for Drug-Target Binding Affinity Prediction
    Zhu, Xuekai
    Liu, Juan
    Zhang, Jian
    Yang, Zhihui
    Yang, Feng
    Zhang, Xiaolei
    [J]. BIG DATA MINING AND ANALYTICS, 2023, 6 (01) : 1 - 10
  • [23] Non-specificity of drug-target ineractions: Consequences for drug discovery
    Maggiora, Gerald
    Gokhale, Vijay
    [J]. ABSTRACTS OF PAPERS OF THE AMERICAN CHEMICAL SOCIETY, 2015, 250
  • [24] Non-Specificity of Drug-Target Interactions - Consequences for Drug Discovery
    Maggiora, Gerald
    Gokhale, Vijay
    [J]. FRONTIERS IN MOLECULAR DESIGN AND CHEMIAL INFORMATION SCIENCE - HERMAN SKOLNIK AWARD SYMPOSIUM 2015: JURGEN BAJORATH, 2016, 1222 : 91 - 142
  • [25] The dynamics of drug-target interactions: drug-target residence time and its impact on efficacy and safety
    Copeland, Robert A.
    [J]. EXPERT OPINION ON DRUG DISCOVERY, 2010, 5 (04) : 305 - 310
  • [26] A Deep Learning Drug-Target Binding Affinity Prediction Based on Compound Microstructure and Its Application in COVID-19 Drug Screening
    Yijie Guo
    Xiumin Shi
    Han Zhou
    [J]. Journal of Beijing Institute of Technology, 2023, 32 (04) : 396 - 405
  • [27] A Deep Learning Drug-Target Binding Affinity Prediction Based on Compound Microstructure and Its Application in COVID-19 Drug Screening
    Guo, Yijie
    Shi, Xiumin
    Zhou, Han
    [J]. Journal of Beijing Institute of Technology (English Edition), 2023, 32 (04): : 396 - 405
  • [28] Fusion-Based Deep Learning Architecture for Detecting Drug-Target Binding Affinity Using Target and Drug Sequence and Structure
    Wang, Kaili
    Li, Min
    [J]. IEEE JOURNAL OF BIOMEDICAL AND HEALTH INFORMATICS, 2023, 27 (12) : 6112 - 6120
  • [29] HBDTA: Hierarchical Bi-LSTM Networks for Drug-target Binding Affinity Prediction
    Wu, Yongqing
    Jin, Yao
    Sun, Peng
    Ding, Zhichen
    [J]. ENGINEERING LETTERS, 2024, 32 (02) : 284 - 295
  • [30] Convolutional neural network with stacked autoencoders for predicting drug-target interaction and binding affinity
    Bahi, Meriem
    Batouche, Mohamed
    [J]. INTERNATIONAL JOURNAL OF DATA MINING MODELLING AND MANAGEMENT, 2021, 13 (1-2) : 81 - 113