Validated quantitative structure-activity relationship analysis of a series of 2-aminothiazole based p56Lck inhibitors

Jiazhong Li; Juan Du; Lili Xi; Huanxiang Liu; Xiaojun Yao; Mancang Liu

doi:10.1016/j.aca.2008.10.026

Validated quantitative structure-activity relationship analysis of a series of 2-aminothiazole based p56^Lck inhibitors

Jiazhong Li, Juan Du, Lili Xi, Huanxiang Liu, Xiaojun Yao, Mancang Liu

Lanzhou University

Research output: Contribution to journal › Article › peer-review

9 Citations (Scopus)

Abstract

In this study, the quantitative structure-activity relationship (QSAR) of a series of 2-aminothiazole based Lck inhibitors was investigated. The key structural features responsible for the inhibition activities were discussed in detail. A population of 100 rigorously validated linear QSAR models were established based on the descriptors calculated in DRAGON program and selected by genetic algorithm (GA). A total of 36 descriptors were involved in all the QSAR models. Then the common descriptors appeared in all the models were extracted to build the final QSAR model. As a result, the final 8-parameter QSAR model was established. After analysis of the eight descriptors, some advice was proposed to help the design of possible novel inhibitors with higher bioactivity.

Original language	English
Pages (from-to)	29-39
Number of pages	11
Journal	Analytica Chimica Acta
Volume	631
Issue number	1
DOIs	https://doi.org/10.1016/j.aca.2008.10.026
Publication status	Published - 5 Jan 2009
Externally published	Yes

Keywords

Genetic algorithm (GA)
Lymphocyte-specific kinase (LCK)
Multiple linear regression (MLR)
Quantitative structure-activity relationship (QSAR)

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10.1016/j.aca.2008.10.026

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title = "Validated quantitative structure-activity relationship analysis of a series of 2-aminothiazole based p56Lck inhibitors",

abstract = "In this study, the quantitative structure-activity relationship (QSAR) of a series of 2-aminothiazole based Lck inhibitors was investigated. The key structural features responsible for the inhibition activities were discussed in detail. A population of 100 rigorously validated linear QSAR models were established based on the descriptors calculated in DRAGON program and selected by genetic algorithm (GA). A total of 36 descriptors were involved in all the QSAR models. Then the common descriptors appeared in all the models were extracted to build the final QSAR model. As a result, the final 8-parameter QSAR model was established. After analysis of the eight descriptors, some advice was proposed to help the design of possible novel inhibitors with higher bioactivity.",

keywords = "Genetic algorithm (GA), Lymphocyte-specific kinase (LCK), Multiple linear regression (MLR), Quantitative structure-activity relationship (QSAR)",

author = "Jiazhong Li and Juan Du and Lili Xi and Huanxiang Liu and Xiaojun Yao and Mancang Liu",

note = "Funding Information: This work was supported by the Program for New Century Excellent Talents in University (No. NCET-07-0399) ",

year = "2009",

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doi = "10.1016/j.aca.2008.10.026",

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T1 - Validated quantitative structure-activity relationship analysis of a series of 2-aminothiazole based p56Lck inhibitors

AU - Li, Jiazhong

AU - Du, Juan

AU - Xi, Lili

AU - Liu, Huanxiang

AU - Yao, Xiaojun

AU - Liu, Mancang

N1 - Funding Information: This work was supported by the Program for New Century Excellent Talents in University (No. NCET-07-0399)

PY - 2009/1/5

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KW - Genetic algorithm (GA)

KW - Lymphocyte-specific kinase (LCK)

KW - Multiple linear regression (MLR)

KW - Quantitative structure-activity relationship (QSAR)

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Validated quantitative structure-activity relationship analysis of a series of 2-aminothiazole based p56^Lck inhibitors

Abstract

Keywords

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