High-Throughput Virtual Screening Using Quantum Mechanical Probes: Discovery of Selective Kinase Inhibitors

被引:39
|
作者
Zhou, Ting [1 ]
Caflisch, Amedeo [1 ]
机构
[1] Univ Zurich, Dept Biochem, CH-8057 Zurich, Switzerland
基金
瑞士国家科学基金会;
关键词
gatekeepers; high-throughput screening; inhibitors; kinases; quantum mechanics; ORBITAL ELECTRONEGATIVITY METHOD; MODIFIED PARTIAL EQUALIZATION; AB-INITIO; HYDROGEN-BONDS; SEMIEMPIRICAL METHODS; TYROSINE KINASES; DRUG DESIGN; BINDING; ENERGY; DFT;
D O I
10.1002/cmdc.201000085
中图分类号
R914 [药物化学];
学科分类号
100701 ;
摘要
A procedure based on semi-empirical quantum mechanical (QM) calculations of interaction energy is proposed for the rapid screening of compound poses generated by high throughput docking. Small molecules (consisting of 2-10 atoms and termed "probes") are overlapped with polar groups in the binding site of the protein target. The interaction energy values between each compound pose and the probes, calculated by a semi empirical Hamiltonian, are used as filters. The QM probe method does not require fixed partial charges and takes into account polarization and charge-transfer effects which are not captured by conventional force fields. The procedure is applied to screen similar to 100 million poses (of 2.7 million commercially available compounds) obtained by high-throughput docking in the ATP binding site of the tyrosine kinase erythropoietin-producing human hepatocellular carcinoma receptor B4 (EphB4). Three QM probes on the hinge region and one at the entrance pocket are employed to select for binding affinity, while a QM probe on the side chain of the so-called gatekeeper residue (a hypervariable residue in the kinome) is used to enforce selectivity. The poses with favorable interactions with the five QM probes are filtered further for hydrophobic matching and low ligand strain. In this way, a single-digit micromolar inhibitor of EphB4 with a relatively good selectivity profile is identified in a multimillion-compound library upon experimental tests of only 23 molecules.
引用
收藏
页码:1007 / 1014
页数:8
相关论文
共 50 条
  • [31] Structure-based prediction of Mycobacterium tuberculosis shikimate kinase inhibitors by high-throughput virtual screening
    Segura-Cabrera, Aldo
    Rodriguez-Perez, Mario A.
    BIOORGANIC & MEDICINAL CHEMISTRY LETTERS, 2008, 18 (11) : 3152 - 3157
  • [32] Discovery of Selective Inhibitors Against EBNA1 via High Throughput In Silico Virtual Screening
    Li, Ning
    Thompson, Scott
    Schultz, David C.
    Zhu, Weiliang
    Jiang, Hualiang
    Luo, Cheng
    Lieberman, Paul M.
    PLOS ONE, 2010, 5 (04):
  • [33] High-Throughput Screening for Biomarker Discovery
    Janvilisri, Tavan
    Suzuki, Haruo
    Scaria, Joy
    Chen, Jenn-Wei
    Charoensawan, Varodom
    DISEASE MARKERS, 2015, 2015
  • [34] High-throughput screening for drug discovery
    Broach, JR
    Thorner, J
    NATURE, 1996, 384 (6604) : 14 - 16
  • [35] Identification of Novel Urease Inhibitors by High-Throughput Virtual and in Vitro Screening
    Abid, Obaid-ur-Rahman
    Babar, Tariq Mahmood
    Ali, Farukh Iftakhar
    Ahmed, Shahzad
    Wadood, Abdul
    Rama, Nasim Hasan
    Uddin, Reaz
    ul-Haq, Zaheer
    Khan, Ajmal
    Choudhary, M. Iqbal
    ACS MEDICINAL CHEMISTRY LETTERS, 2010, 1 (04): : 145 - 149
  • [36] Erratum: Identification of selective inhibitors of uncharacterized enzymes by high-throughput screening with fluorescent activity-based probes
    Daniel A Bachovchin
    Steven J Brown
    Hugh Rosen
    Benjamin F Cravatt
    Nature Biotechnology, 2009, 27 : 485 - 485
  • [37] Identifying sensitizers of aurora kinase inhibitors by high-throughput siRNA screening
    Xie, Lifang
    Kassner, Michelle
    Munoz, Ruben
    Yin, Holly
    Que, Quick
    Kiefer, Jeff
    Mousses, Spyro
    Von Hoff, Daniel
    Han, Haiyong
    CANCER RESEARCH, 2009, 69
  • [38] Integration of virtual and high-throughput screening
    Bajorath, F
    NATURE REVIEWS DRUG DISCOVERY, 2002, 1 (11) : 882 - 894
  • [39] Integration of virtual and high-throughput screening
    Jürgen Bajorath
    Nature Reviews Drug Discovery, 2002, 1 : 882 - 894
  • [40] Discovery of novel angiogenesis inhibitors using transgenic zebrafish as a high-throughput phenotypic screening model
    Min, Jaeki
    Kurtkaya, Serdar
    Sneed, Blossom
    Du, Yuhong
    Sandberg, Eric M.
    Baranowski, Timothy C.
    Sun, Aiming
    Snyder, James P.
    Liotta, Dennis C.
    Dingledine, Raymond
    ABSTRACTS OF PAPERS OF THE AMERICAN CHEMICAL SOCIETY, 2009, 237