Ephedrine as a lead compound for the development of new DPP-IV inhibitors

被引:15
|
作者
Jose Ojeda-Montes, Maria [1 ]
Ardid-Ruiz, Andrea [1 ]
Tomas-Hernandez, Sarah [1 ]
Gimeno, Aleix [1 ]
Cereto-Massague, Adria [1 ]
Beltran-Debon, Raul [1 ]
Mulero, Miquel [1 ]
Garcia-Vallve, Santiago [1 ,2 ]
Pujadas, Gerard [1 ,2 ]
Valls, Cristina [1 ]
机构
[1] Univ Rovira & Virgili, Dept Bioquim & Biotecnol, Res Grp Cheminformat & Nutr, Campus Sescelades, E-43007 Tarragona, Catalonia, Spain
[2] EURECAT Technol Ctr Catalonia, Technol Unit Nutr & Hlth, Reus, Spain
关键词
Ephedra extract; natural compounds; protein-ligand docking; structure-based drug design; DIPEPTIDYL-PEPTIDASE-IV; MEDICINAL CHEMISTRY; POTENT; RESIDUES; OPTIMIZATION; DIMERIZATION; DISCOVERY; CATALYSIS; SAFETY; PLANTS;
D O I
10.4155/fmc-2017-0080
中图分类号
R914 [药物化学];
学科分类号
100701 ;
摘要
Aim: Extracts from Ephedra species have been reported to be effective as antidiabetics. A previous in silico study predicted that ephedrine and five ephedrine derivatives could contribute to the described antidiabetic effect of Ephedra extracts by inhibiting dipeptidyl peptidase IV (DPP-IV). Finding selective DPP-IV inhibitors is a current therapeutic strategy for Type 2 diabetes mellitus management. Therefore, the main aim of this work is to experimentally determine whether these alkaloids are DPP-IV inhibitors. Materials & methods: The DPP-IV inhibition of Ephedra's alkaloids was determined via a competitive-binding assay. Then, computational analyses were used in order to find out the protein-ligand interactions and to perform a lead optimization. Results: Our results show that all six molecules are DPP-IV inhibitors, with IC50 ranging from 124 mu M for ephedrine to 28 mM for N-methylpseudoephedrine. Conclusion: Further computational analysis shows how Ephedra's alkaloids could be used as promising lead molecules for designing more potent and selective DPP-IV inhibitors.
引用
收藏
页码:2129 / 2146
页数:18
相关论文
共 50 条
  • [1] DPP-IV inhibitors
    Holt, Richard I. G.
    [J]. DIABETES OBESITY & METABOLISM, 2006, 8 (06): : 716 - 716
  • [2] Development of a novel inhibitor of DPP-IV using a byproduct as the lead compound.
    Kira, K
    Clark, RSJ
    Ikuta, H
    Yoshikawa, S
    Yasuda, N
    Yamazaki, K
    Nagakura, T
    Takenaka, O
    Uehara, T
    [J]. ABSTRACTS OF PAPERS OF THE AMERICAN CHEMICAL SOCIETY, 2004, 228 : U955 - U955
  • [3] Aminomethylpyridines as DPP-IV inhibitors
    Peters, JU
    Weber, S
    Kritter, S
    Weiss, P
    Wallier, A
    Zimmerli, D
    Boehringer, M
    Steger, M
    Loeffler, BM
    [J]. BIOORGANIC & MEDICINAL CHEMISTRY LETTERS, 2004, 14 (13) : 3579 - 3580
  • [4] Discovery of potent DPP-IV inhibitors
    Chen, YX
    Richards, S
    Shuai, Q
    Patel, J
    Madar, D
    Yong, H
    Pei, ZH
    von Geldern, TW
    Longenecker, KL
    Stewart, K
    Lubben, T
    Ballaron, S
    Stashko, M
    Trevillyan, J
    Sham, H
    [J]. ABSTRACTS OF PAPERS OF THE AMERICAN CHEMICAL SOCIETY, 2005, 230 : U2675 - U2675
  • [5] 11 years of cyanopyrrolidines as DPP-IV inhibitors
    Peters, Jens-Uwe
    [J]. CURRENT TOPICS IN MEDICINAL CHEMISTRY, 2007, 7 (06) : 579 - 595
  • [6] DPP-IV inhibitors: Beyond glycaemic control?
    Kwok, Andrew J.
    Mashar, Meghavi
    Khavandi, Kaivan
    Sabir, Ian
    [J]. TRENDS IN CARDIOVASCULAR MEDICINE, 2014, 24 (04) : 157 - 164
  • [7] Indole Alkaloids as New Leads for the Design and Development of Novel DPP-IV Inhibitors for the Treatment of Diabetes
    Dhiraviam, Kannan Narayanan
    Balasubramanian, Suganthana
    Jayavel, Sridhar
    [J]. CURRENT BIOINFORMATICS, 2018, 13 (02) : 157 - 169
  • [8] Natural Products: Potential Source of DPP-IV Inhibitors
    Singla, Rajeev K.
    Kumar, Rishabh
    Khan, Sameer
    Mohit
    Kumari, Kajal
    Garg, Arun
    [J]. CURRENT PROTEIN & PEPTIDE SCIENCE, 2019, 20 (12) : 1218 - 1225
  • [9] Predicting DPP-IV inhibitors with machine learning approaches
    Cai, Jie
    Li, Chanjuan
    Liu, Zhihong
    Du, Jiewen
    Ye, Jiming
    Gu, Qiong
    Xu, Jun
    [J]. JOURNAL OF COMPUTER-AIDED MOLECULAR DESIGN, 2017, 31 (04) : 393 - 402
  • [10] Predicting DPP-IV inhibitors with machine learning approaches
    Jie Cai
    Chanjuan Li
    Zhihong Liu
    Jiewen Du
    Jiming Ye
    Qiong Gu
    Jun Xu
    [J]. Journal of Computer-Aided Molecular Design, 2017, 31 : 393 - 402