Organic ER affinity quick screening and forecast method based on receptor binding mode

A technology of receptor binding and prediction methods, applied in biological testing, material inspection products, etc.

Inactive Publication Date: 2007-10-24
NANJING UNIV
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Benefits of technology

This invention relates to an improved method for identifying chemicals that bind specifically to certain substances called estrogens (estrogenic compounds). By comparing this identified molecule against known ones found on our sample we are able to determine which specific agents have been shown to target these harmful materials more effectively than others.

Problems solved by technology

This patented technical solution describes methods for identifying chemical substances called estrogens or estrogene receptive agents associated with various metabolites like estradiolines. These techniques involve studying how these chemotaxis properties change when exposed to other factors involved during this process. By comparing them against each other's effects on cellular responses, they may identify potential sources of contamination from natural resources. However, current approaches require complicated calculations involving multiple variables and cannot distinguish among many possible causes of environmental pollution.

Method used

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  • Organic ER affinity quick screening and forecast method based on receptor binding mode
  • Organic ER affinity quick screening and forecast method based on receptor binding mode
  • Organic ER affinity quick screening and forecast method based on receptor binding mode

Examples

Experimental program
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Effect test

Embodiment 1

[0038] Adopt the method of the present invention to process a group of ER ligands and non-ER ligands (Matthews J., Celius T., Halgren R., et al.Differential estrogen receptor binding of estrogenic substances:aspecies comparison.Journal of Steroid Biochemistry & Molecular Biology, 2000, 74:223-234.) A total of 34 compounds.

[0039] Classification principle: according to the logRBA value, the compounds are divided into 4 categories: 1~logRBA1, corresponding to extremely weak ER affinity There are four types of ER affinity, weak ER affinity, medium-strength ER affinity, and high ER affinity. Compared with the receptor affinity of estradiol, the three interval cut-off points of -3, 0, and 1 correspond to the affinity multiples of estradiol respectively. One hundred thousandth, one hundredth and one tenth of diol. 30 compounds were selected from it as a training group to build a model, and the remaining 4 compounds were used as a test group (corresponding to 4 types) for verifica...

Embodiment 2

[0054] Adopt the method of the present invention to process the ER affinity database (Estrogen receptor bindingdataset, www.fda.gov / nctr / science / centers / toxicoinformatics / edkb / index.htm) of U.S. FDA National Center for Toxicology Research (national center fortoxicological research, NCTR) 232 compounds in it.

[0055] Classification principle: The affinity index between compounds and ER can be divided into 3 categories: 1~logRBA<-3 is a compound with very weak ER affinity, 2~-3≤logRBA<0 is a compound with weak ER affinity, 3~logRBA≥ 0 is a compound with strong affinity for ER. 180 compounds were extracted from 188 non-phytoestrogens as a training group to build a model, including 111, 45, and 24 compounds of types 1, 2, and 3, and 40 compounds were extracted from 44 types of phytoestrogens as a training group. The training group model includes 16, 22, and 2 compounds of types 1, 2, and 3, respectively. The remaining 12 compounds were used as test groups to validate the model. ...

Embodiment 3

[0068] The method of the invention is used to analyze the mode of action between the compound and the active pocket of the receptor. Select dienestrol in the NCTR database to dock with the active pocket of hERα (PDB number 1ERE), and display the schematic diagram of the interaction between the compound and the receptor pocket (attached to Figure 1) (hydrogen bond interaction is represented by a dotted line), and determine the compound Whether there are hydrogen bonds with residues Glu353, Leu387, Gly521, His524, Leu346, crystal water (water) and other sites (other) in the pocket, and the number of hydrogen bonds is calculated. Compound and pocket binding free energy E binding It is -25.1kcal / mol. The figure shows the skeleton structure of the key residues and crystal water that make up the pocket. The main action area of ​​the active pocket is represented by a purple dot matrix. The residue name and sequence number are marked on the α carbon atom of the residue. And the non-h...

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Abstract

The invention discloses a quick selecting predicting method of organic ER affinity force based on acceptor combine mode, which builds QSAR judge model and predict model according to the acceptor combine modes as prior ER affinity force data pollutant, acceptor combine energy, hydrogen bond function mode, acceptor function point reach hardness or the like, and the affinity index, to be applied into the ER affinity force judgment and predication of the compound with unknown affinity force. The invention can select and predict the compounds with different structures in wide active index ranges, to predict the suspected EDCs and hormone acceptor affinity force, with low cost, simple operation, saved time, and high predict ability as 80%, and significant support on the environment management and ecology risk evaluation.

Description

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Claims

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Application Information

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Owner NANJING UNIV
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