Unknown

Dataset Information

0

Comprehensive Modeling and Discovery of Mebendazole as a Novel TRAF2- and NCK-interacting Kinase Inhibitor.


ABSTRACT: TRAF2- and NCK-interacting kinase (TNIK) represents one of the crucial targets for Wnt-activated colorectal cancer. In this study, we curated two datasets and conducted a comprehensive modeling study to explore novel TNIK inhibitors with desirable biopharmaceutical properties. With Dataset I, we derived Comparative Molecular Similarity Indices Analysis (CoMSIA) and variable-selection k-nearest neighbor models, from which 3D-molecular fields and 2D-descriptors critical for the TNIK inhibitor activity were revealed. Based on Dataset II, predictive CoMSIA-SIMCA (Soft Independent Modelling by Class Analogy) models were obtained and employed to screen 1,448 FDA-approved small molecule drugs. Upon experimental evaluations, we discovered that mebendazole, an approved anthelmintic drug, could selectively inhibit TNIK kinase activity with a dissociation constant Kd?=?~1??M. The subsequent CoMSIA and kNN analyses indicated that mebendazole bears the favorable molecular features that are needed to bind and inhibit TNIK.

SUBMITTER: Tan Z 

PROVIDER: S-EPMC5030704 | biostudies-literature | 2016 Sep

REPOSITORIES: biostudies-literature

altmetric image

Publications

Comprehensive Modeling and Discovery of Mebendazole as a Novel TRAF2- and NCK-interacting Kinase Inhibitor.

Tan Zhi Z   Chen Lu L   Zhang Shuxing S  

Scientific reports 20160921


TRAF2- and NCK-interacting kinase (TNIK) represents one of the crucial targets for Wnt-activated colorectal cancer. In this study, we curated two datasets and conducted a comprehensive modeling study to explore novel TNIK inhibitors with desirable biopharmaceutical properties. With Dataset I, we derived Comparative Molecular Similarity Indices Analysis (CoMSIA) and variable-selection k-nearest neighbor models, from which 3D-molecular fields and 2D-descriptors critical for the TNIK inhibitor acti  ...[more]

Similar Datasets

| S-EPMC7281028 | biostudies-literature
| S-EPMC10826163 | biostudies-literature
| S-EPMC4619995 | biostudies-literature
2017-03-08 | GSE95766 | GEO
| S-EPMC7782820 | biostudies-literature
| S-EPMC2924048 | biostudies-literature
2015-11-21 | GSE64258 | GEO
| S-EPMC10196212 | biostudies-literature
2015-11-21 | E-GEOD-64258 | biostudies-arrayexpress
2016-07-22 | GSE71222 | GEO