Dataset Information

Identification of Novel IGF1R Kinase Inhibitors by Molecular Modeling and High-Throughput Screening.

ABSTRACT: The aim of this study was to identify small molecule compounds that inhibit the kinase activity of the IGF1 receptor and represent novel chemical scaffolds, which can be potentially exploited to develop drug candidates that are superior to the existing experimental anti-IGF1R therapeuticals. To this end, targeted compound libraries were produced by virtual screening using molecular modeling and docking strategies, as well as the ligand-based pharmacophore model. High-throughput screening of the resulting compound sets in a biochemical kinase inhibition assay allowed us to identify several novel chemotypes that represent attractive starting points for the development of advanced IGF1R inhibitory compounds.

SUBMITTER: Moriev R

PROVIDER: S-EPMC3695357 | biostudies-literature | 2013 Apr

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Identification of Novel IGF1R Kinase Inhibitors by Molecular Modeling and High-Throughput Screening.

Moriev R R Vasylchenko O O Platonov M M Grygorenko O O Volkova K K Zozulya S S

Acta naturae 20130401 2

The aim of this study was to identify small molecule compounds that inhibit the kinase activity of the IGF1 receptor and represent novel chemical scaffolds, which can be potentially exploited to develop drug candidates that are superior to the existing experimental anti-IGF1R therapeuticals. To this end, targeted compound libraries were produced by virtual screening using molecular modeling and docking strategies, as well as the ligand-based pharmacophore model. High-throughput screening of the ...[more]

PMID: 23819040

Similar Datasets

Project description:Pharmacological tools-'chemical probes'-that intervene in cell signaling cascades are important for complementing genetically-based experimental approaches. Probe development frequently begins with a high-throughput screen (HTS) of a chemical library. Herein, we describe the design, validation, and implementation of the first HTS-compatible strategy against any inositol phosphate kinase. Our target enzyme, PPIP5K, synthesizes 'high-energy' inositol pyrophosphates (PP-InsPs), which regulate cell function at the interface between cellular energy metabolism and signal transduction. We optimized a time-resolved, fluorescence resonance energy transfer ADP-assay to record PPIP5K-catalyzed, ATP-driven phosphorylation of 5-InsP7 to 1,5-InsP8 in 384-well format (Z' = 0.82 ± 0.06). We screened a library of 4745 compounds, all anticipated to be membrane-permeant, which are known-or conjectured based on their structures-to target the nucleotide binding site of protein kinases. At a screening concentration of 13 ?M, fifteen compounds inhibited PPIP5K >50%. The potency of nine of these hits was confirmed by dose-response analyses. Three of these molecules were selected from different structural clusters for analysis of binding to PPIP5K, using isothermal calorimetry. Acceptable thermograms were obtained for two compounds, UNC10112646 (Kd = 7.30 ± 0.03 ?M) and UNC10225498 (Kd = 1.37 ± 0.03 ?M). These Kd values lie within the 1-10 ?M range generally recognized as suitable for further probe development. In silico docking data rationalizes the difference in affinities. HPLC analysis confirmed that UNC10225498 and UNC10112646 directly inhibit PPIP5K-catalyzed phosphorylation of 5-InsP7 to 1,5-InsP8; kinetic experiments showed inhibition to be competitive with ATP. No other biological activity has previously been ascribed to either UNC10225498 or UNC10112646; moreover, at 10 ?M, neither compound inhibits IP6K2, a structurally-unrelated PP-InsP kinase. Our screening strategy may be generally applicable to inhibitor discovery campaigns for other inositol phosphate kinases.

Project description:Acetylcholinesterase (AChE) is an essential enzyme that terminates cholinergic transmission by rapid hydrolysis of the neurotransmitter acetylcholine. Compounds inhibiting this enzyme can be used (inter alia) to treat cholinergic deficiencies (e.g. in Alzheimer's disease), but may also act as dangerous toxins (e.g. nerve agents such as sarin). Treatment of nerve agent poisoning involves use of antidotes, small molecules capable of reactivating AChE. We have screened a collection of organic molecules to assess their ability to inhibit the enzymatic activity of AChE, aiming to find lead compounds for further optimization leading to drugs with increased efficacy and/or decreased side effects. 124 inhibitors were discovered, with considerable chemical diversity regarding size, polarity, flexibility and charge distribution. An extensive structure determination campaign resulted in a set of crystal structures of protein-ligand complexes. Overall, the ligands have substantial interactions with the peripheral anionic site of AChE, and the majority form additional interactions with the catalytic site (CAS). Reproduction of the bioactive conformation of six of the ligands using molecular docking simulations required modification of the default parameter settings of the docking software. The results show that docking-assisted structure-based design of AChE inhibitors is challenging and requires crystallographic support to obtain reliable results, at least with currently available software. The complex formed between C5685 and Mus musculus AChE (C5685•mAChE) is a representative structure for the general binding mode of the determined structures. The CAS binding part of C5685 could not be structurally determined due to a disordered electron density map and the developed docking protocol was used to predict the binding modes of this part of the molecule. We believe that chemical modifications of our discovered inhibitors, biochemical and biophysical characterization, crystallography and computational chemistry provide a route to novel AChE inhibitors and reactivators.

Dataset Information

Identification of Novel IGF1R Kinase Inhibitors by Molecular Modeling and High-Throughput Screening.

Publications

Identification of Novel IGF1R Kinase Inhibitors by Molecular Modeling and High-Throughput Screening.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets