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Exploration of structural requirements for azole chemicals towards human aromatase CYP19A1 activity: Classification modeling, structure-activity relationships and read-across study
被引:6
|作者:
Alfonso, Ana Y. Caballero
[1
,2
]
Mora Lagares, Liadys
[2
,3
]
Novic, Marjana
[3
]
Benfenati, Emilio
[1
]
Kumar, Anil
[4
]
Chayawan
[1
]
机构:
[1] Ist Ric Farmacol Mario Negri IRCCS, Lab Environm Chem & Toxicol, Dept Environm Hlth Sci, Milan, Italy
[2] Jozef Stefan Int Postgrad Sch, Jamova Cesta 39, Ljubljana 1000, Slovenia
[3] Natl Inst Chem, Theory Dept, Lab Cheminformat, Ljubljana, Slovenia
[4] Panjab Univ, Univ Inst Engn & Technol, Dept Appl Sci, Chandigarh 160014, India
基金:
欧盟地平线“2020”;
关键词:
Human aromatase;
Agonist;
Antagonist;
Azoles;
Structural alerts;
Classification model;
Structure-activity relationship (SAR);
Read-across;
IMIDAZOLIUM IONIC LIQUIDS;
MOLECULAR DOCKING;
BREAST-CANCER;
BIOLOGICAL EVALUATION;
INHIBITORS;
TISSUE;
DERIVATIVES;
EXPRESSION;
PHYSIOLOGY;
MECHANISM;
D O I:
10.1016/j.tiv.2022.105332
中图分类号:
R99 [毒物学(毒理学)];
学科分类号:
100405 ;
摘要:
Human ammatase, also called CYP19A1, plays a major role in the conversion of androgens into estrogens. Inhibition of aromatase is an important target for estrogen receptor (ER)-responsive breast cancer therapy. Use of azole compounds as aromatase inhibitors is widespread despite their low selectivity. A toxicological evaluation of commonly used azole-based drugs and agrochemicals with respect to CYP19A1 is currently requested by the European Union- Registration, Evaluation, Authorization and Restriction of Chemicals (EU-REACH) regulations due to their potential as endocrine disruptors. In this connection, identification of structural alerts (SAs) is an effective strategy for the toxicological assessment and safe drug design. The present study describes the identification of SAs of azole-based chemicals as guiding experts to predict the aromatase activity. Total 21 SAs associated with aromatase activity were extracted from dataset of 326 azole-based drugs/chemicals obtained from Tox21 library. A cross-validated classification model having high accuracy (error rate 5%) was proposed which can precisely classify azole chemicals into active/inactive toward aromatase. In addition, mechanistic details and toxicological properties (agonism/antagonism) of azoles with respect to aromatase were explored by comparing active and inactive chemicals using structure-activity relationships (SAR). Lastly, few structural alerts were applied to form chemical categories for read-across applications.
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页数:15
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