Two- and three-dimensional QSAR studies on hURAT1 inhibitors with flexible linkers: topomer CoMFA and HQSAR View Full Text


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Article Info

DATE

2019-03-13

AUTHORS

Tingting Zhao, Zean Zhao, Fengting Lu, Shan Chang, Jiajie Zhang, Jianxin Pang, Yuanxin Tian

ABSTRACT

hURAT1 (human urate transporter 1) is a successful target for hyperuricemia. Recently, the modification work on hURAT1 inhibitors showed that the flexible linkers would benefit biological activity. The study aimed to investigate the contribution of the linkers and give modification strategies on this kind of structures based on QSAR models (HQSAR and topomer CoMFA). The most effective HQSAR and topomer CoMFA models were generated by applying the training set containing 63 compounds, with the cross-validated q2 values of 0.869/0.818 and the non-cross-validated correlation coefficients r2 of 0.951/0.978, respectively. The Y-randomization test was applied to ensure the robustness of the models. The external predictive correlation coefficient (r pred 2 ) grounded on the external test set (21 compounds) of two models was 0.910 and 0.907, respectively. In addition, the models were validated by Golbraikh-Tropsha and Roy methods, as well as other statistical metrics. The results showed that both models were reliable. Topomer CoMFA steric/electrostatic contours and HQSAR atomic contribution maps illustrated the structural features which governed their inhibitory potency. The dependable results could provide important insights to guide the designing of more potential hURAT1 inhibitors. More... »

PAGES

1-14

References to SciGraph publications

Identifiers

URI

http://scigraph.springernature.com/pub.10.1007/s11030-019-09936-5

DOI

http://dx.doi.org/10.1007/s11030-019-09936-5

DIMENSIONS

https://app.dimensions.ai/details/publication/pub.1112731853

PUBMED

https://www.ncbi.nlm.nih.gov/pubmed/30868332


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51 schema:description hURAT1 (human urate transporter 1) is a successful target for hyperuricemia. Recently, the modification work on hURAT1 inhibitors showed that the flexible linkers would benefit biological activity. The study aimed to investigate the contribution of the linkers and give modification strategies on this kind of structures based on QSAR models (HQSAR and topomer CoMFA). The most effective HQSAR and topomer CoMFA models were generated by applying the training set containing 63 compounds, with the cross-validated q<sup>2</sup> values of 0.869/0.818 and the non-cross-validated correlation coefficients r<sup>2</sup> of 0.951/0.978, respectively. The Y-randomization test was applied to ensure the robustness of the models. The external predictive correlation coefficient (r <sub>pred</sub> <sup>2</sup> ) grounded on the external test set (21 compounds) of two models was 0.910 and 0.907, respectively. In addition, the models were validated by Golbraikh-Tropsha and Roy methods, as well as other statistical metrics. The results showed that both models were reliable. Topomer CoMFA steric/electrostatic contours and HQSAR atomic contribution maps illustrated the structural features which governed their inhibitory potency. The dependable results could provide important insights to guide the designing of more potential hURAT1 inhibitors.
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