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Discovering small molecule ligands of vascular endothelial growth factor that block VEGF-KDR binding using label-free microarray-based assays.

ABSTRACT: We present here a label-free microarray-based assay platform that we used to identify inhibitors of vascular endothelial growth factor (VEGF)-kinase-insertion domain receptor (KDR) binding. Supported by a combination of special ellipsometry-based optical detection and small molecule microarrays (SMM), this platform consists of three assays: (1) the first assay detects binding of a target protein with SMM and identifies ligands to the protein as inhibitor candidates; (2) the second assay detects binding of a receptor protein with identical SMM and subsequent binding of the target protein (a sandwich assay) to identify the ligands to the receptor protein that do not interfere with the target-receptor binding; (3) the third assay detects binding of the target protein to the receptor protein in the presence of the ligands of the target protein identified from the first assay, with the receptor protein immobilized to a solid surface through the ligands identified in the second assay, to yield dose-response curves. Using this platform, we screened 7,961 compounds from the National Cancer Institute and found 12 inhibitors to VEGF-KDR (VEGFR2) interactions with IC?? ranging from 0.3 to 60 ?M. The inhibitory potency of these inhibitors found in the microarray-based assay was confirmed by their inhibition of VEGF-induced VEGFR2 phosphorylation in a cell-based assay.

SUBMITTER: Landry JP

PROVIDER: S-EPMC3685389 | biostudies-literature | 2013 Jun

REPOSITORIES: biostudies-literature

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Discovering small molecule ligands of vascular endothelial growth factor that block VEGF-KDR binding using label-free microarray-based assays.

Landry James P JP Fei Yiyan Y Zhu Xiangdong X Ke Yaohuang Y Yu Guoliang G Lee Pierre P

Assay and drug development technologies 20130601 5

We present here a label-free microarray-based assay platform that we used to identify inhibitors of vascular endothelial growth factor (VEGF)-kinase-insertion domain receptor (KDR) binding. Supported by a combination of special ellipsometry-based optical detection and small molecule microarrays (SMM), this platform consists of three assays: (1) the first assay detects binding of a target protein with SMM and identifies ligands to the protein as inhibitor candidates; (2) the second assay detects ...[more]

PMID: 23772553

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Project description:In biological systems that undergo processes such as differentiation, a clear concept of progression exists. We present a novel computational approach, called Sample Progression Discovery (SPD), to discover patterns of biological progression underlying microarray gene expression data. SPD assumes that individual samples of a microarray dataset are related by an unknown biological process (i.e., differentiation, development, cell cycle, disease progression), and that each sample represents one unknown point along the progression of that process. SPD aims to organize the samples in a manner that reveals the underlying progression and to simultaneously identify subsets of genes that are responsible for that progression. We demonstrate the performance of SPD on a variety of microarray datasets that were generated by sampling a biological process at different points along its progression, without providing SPD any information of the underlying process. When applied to a cell cycle time series microarray dataset, SPD was not provided any prior knowledge of samples' time order or of which genes are cell-cycle regulated, yet SPD recovered the correct time order and identified many genes that have been associated with the cell cycle. When applied to B-cell differentiation data, SPD recovered the correct order of stages of normal B-cell differentiation and the linkage between preB-ALL tumor cells with their cell origin preB. When applied to mouse embryonic stem cell differentiation data, SPD uncovered a landscape of ESC differentiation into various lineages and genes that represent both generic and lineage specific processes. When applied to a prostate cancer microarray dataset, SPD identified gene modules that reflect a progression consistent with disease stages. SPD may be best viewed as a novel tool for synthesizing biological hypotheses because it provides a likely biological progression underlying a microarray dataset and, perhaps more importantly, the candidate genes that regulate that progression.

Dataset Information

Discovering small molecule ligands of vascular endothelial growth factor that block VEGF-KDR binding using label-free microarray-based assays.

Publications

Discovering small molecule ligands of vascular endothelial growth factor that block VEGF-KDR binding using label-free microarray-based assays.

Similar Datasets

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