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In-silico guided discovery of novel CCR9 antagonists

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Abstract

Antagonism of CCR9 is a promising mechanism for treatment of inflammatory bowel disease, including ulcerative colitis and Crohn’s disease. There is limited experimental data on CCR9 and its ligands, complicating efforts to identify new small molecule antagonists. We present here results of a successful virtual screening and rational hit-to-lead campaign that led to the discovery and initial optimization of novel CCR9 antagonists. This work uses a novel data fusion strategy to integrate the output of multiple computational tools, such as 2D similarity search, shape similarity, pharmacophore searching, and molecular docking, as well as the identification and incorporation of privileged chemokine fragments. The application of various ranking strategies, which combined consensus and parallel selection methods to achieve a balance of enrichment and novelty, resulted in 198 virtual screening hits in total, with an overall hit rate of 18%. Several hits were developed into early leads through targeted synthesis and purchase of analogs.

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Notes

  1. A crystal structure of the CCR9 receptor was reported in 2016 after we finished our virtual screening campaign [5].

Abbreviations

CCR9:

CC Chemokine receptor 9

CCL25:

CC Chemokine ligand 25

GPCR:

G-Protein coupled receptor

HTS:

High-throughput screen

LE:

Ligand efficiency

PCA:

Principal component analysis

SAR:

Structure–activity relationship

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Acknowledgements

The authors thank Rory Curtis for biology leadership, Evotec for development and execution of the high-throughput screen, and MultiSpan for running the primary calcium FLIPR assay.

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Authors and Affiliations

  1. Cubist Pharmaceuticals, 65 Hayden Avenue, Lexington, MA, 02143, USA

    Xin Zhang, Jason B. Cross, Jan Romero, Eric Humphries, Katie Hall, Yuchuan Wu, Sabrina Stucka, Jing Zhang, Haoqun Chandonnet, Blaise Lippa, M. Dominic Ryan & J. Christian Baber

  2. Evotec (UK) Ltd., 114 Innovation Drive, Milton Park, Abingdon, Oxfordshire, OX14 4RZ, UK

    Alexander Heifetz

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  1. Xin Zhang
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  2. Jason B. Cross
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Correspondence to Xin Zhang.

Electronic supplementary material

Below is the link to the electronic supplementary material. Assay conditions, structures of reference compounds, and details of computational methods.

Supplementary material 1 (DOCX 756 KB)

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Zhang, X., Cross, J.B., Romero, J. et al. In-silico guided discovery of novel CCR9 antagonists. J Comput Aided Mol Des 32, 573–582 (2018). https://doi.org/10.1007/s10822-018-0113-2

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  • DOI: https://doi.org/10.1007/s10822-018-0113-2

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