Discovery of tyrosine kinase inhibitors by docking into an inactive kinase conformation generated by molecular dynamics.

نویسندگان

  • Hongtao Zhao
  • Danzhi Huang
  • Amedeo Caflisch
چکیده

Several small molecules that bind to the inactive DFG-out conformation of tyrosine kinases (called type II inhibitors) have shown a good selectivity profile over other kinase targets. To obtain a set of DFG-out structures, we performed an explicit solvent molecular dynamics (MD) simulation of the complex of the catalytic domain of a tyrosine kinase receptor, ephrin type-A receptor 3 (EphA3), and a manually docked type II inhibitor. Automatic docking of four previously reported type II inhibitors was used to select a single snapshot from the MD trajectory for virtual screening. High-throughput docking of a pharmacophore-tailored library of 175,000 molecules resulted in about 4 million poses, which were further filtered by van der Waals efficiency and ranked according to a force-field-based energy function. Notably, around 20 % of the compounds with predicted binding energy smaller than -10 kcal mol(-1) are known type II inhibitors. Moreover, a series of 5-(piperazine-1-yl)isoquinoline derivatives was identified as a novel class of low-micromolar inhibitors of EphA3 and unphosphorylated Abelson tyrosine kinase (Abl1). The in silico predicted binding mode of the new inhibitors suggested a similar affinity to the gatekeeper mutant T315I of Abl1, which was verified in vitro by using a competition binding assay. Additional evidence for the type II binding mode was obtained by two 300 ns MD simulations of the complex between N-(3-chloro-4-(difluoromethoxy)phenyl)-2-(4-(8-nitroisoquinolin-5-yl)piperazin-1-yl)acetamide and EphA3.

برای دانلود رایگان متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید

ثبت نام

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

منابع مشابه

Molecular Docking Based on Virtual Screening, Molecular Dynamics and Atoms in Molecules Studies to Identify the Potential Human Epidermal Receptor 2 Intracellular Domain Inhibitors

Human epidermal growth factor receptor 2 (HER2) is a member of the epidermal growth factor receptor family having tyrosine kinase activity. Overexpression of HER2 usually causes malignant transformation of cells and is responsible for the breast cancer. In this work, the virtual screening, molecular docking, quantum mechanics and molecular dynamics methods were employed to study protein–ligand ...

متن کامل

Receptor Tyrosine Kinase Inhibitory Activities and Molecular Docking Studies of Some Pyrrolo[2,3-d]pyrimidine Derivatives

In this study, we aimed to determine VEGFR-2, EGFR and PDGFR-β tyrosine kinase inhibitory activities of some pyrrolo[2,3-d]pyrimidine derivatives previously synthesized and showed potent cytotoxic and apoptotic effects against several cancer cell lines by our group and to evaluate the relationships between inhibitory activities and binding properties of the active compounds by molecular docking...

متن کامل

Discovery of dual ZAP70 and Syk kinases inhibitors by docking into a rare C-helix-out conformation of Syk.

The non-receptor tyrosine kinase Syk (spleen tyrosine kinase) is a pharmaceutical relevant target because its over-activation is observed in several autoimmune diseases, allergy, and asthma. Here we report the identification of two novel inhibitors of Syk by high-throughput docking into a rare C-helix-out conformation published recently. Interestingly, both compounds are slightly more active on...

متن کامل

2D-QSAR and docking studies of 4-anilinoquinazoline derivatives as epidermal growth factor receptor tyrosine kinase inhibitors

Introduction: Epidermal growth factor receptor (EGFR) tyrosine kinase inhibitor derivatives play an important role in the treatment of cancer. We aim to construct 2D-QSAR models using various chemometrics using 4-anilinoquinazoline-containing EGFR TKIs. In addition, the binding profile of these compounds was evaluated using a docking study. Materials and Methods: In this study, 122 compounds of...

متن کامل

Improving biological activity prediction of protein kinase inhibitors using artificial neural network and partial least square methods

Introduction: Protein kinase causes many diseases, including cancer; therefore, inhibiting them plays an important role in the treatment of many diseases. Traditional discovery inhibitors of this enzyme is a time-consuming and costly process. Finding a reliable computer-aided drug discovery tools which can detect the inhibitors will reduce the cost. In this study, it is attempted to separate ki...

متن کامل

ذخیره در منابع من


  با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید

عنوان ژورنال:
  • ChemMedChem

دوره 7 11  شماره 

صفحات  -

تاریخ انتشار 2012