Gene toxicity probability forecasting method based on molecule electrophilic vector and extend supporting vector machine

A technology of support vector machine and genotoxicity, which is applied in the direction of biochemical equipment and methods, microbial measurement/testing, analysis materials, etc., can solve the problems that cannot meet the needs, etc.

Inactive Publication Date: 2008-02-27
SHANGHAI INST OF MATERIA MEDICA CHINESE ACAD OF SCI
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Problems solved by technology

[0008] In addition to performance limitations, current virtual toxicity prediction methods rarely involve the prediction of toxicity probabilities, such as the prediction of genotoxicity is usually considered as a binary classification problem
However, in practical applications, the simple way of expressing whether a compound is toxic or not is usually not enough to meet the needs

Method used

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  • Gene toxicity probability forecasting method based on molecule electrophilic vector and extend supporting vector machine
  • Gene toxicity probability forecasting method based on molecule electrophilic vector and extend supporting vector machine
  • Gene toxicity probability forecasting method based on molecule electrophilic vector and extend supporting vector machine

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Embodiment Construction

[0030] The establishment of a molecular genotoxicity evaluation model based on MEV and extended SVM mainly involves five steps:

[0031] 1) Perform an atomic classification of the compounds in the dataset:

[0032] In view of the portability and convenience of implementation, we use the text-based chemical structure questioning language SMARTS (SMiles ARbitrary Target Specification) to describe all atom classifications (Table 4). The type of each atom is determined by its own chemical properties and the type of neighboring atoms and bonds that reflect its chemical environment. Then we use the programmable atom classification PATTY (Programmable atom typer) backtracking algorithm (Bush and Sheridan, 1993) in the OpenBabel (http: / / openbabel.sourceforge.net) C++ library to complete the atom type specification. By using SMARTS and PATTY, we can conveniently classify atoms flexibly and effectively from the perspective of chemistry and toxicology.

[0033] Table 4.52 definition ru...

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Abstract

The invention relates to the gene toxicity probability preparation method based on the MEV and SVM which is proper for the dummy toxicity appraise and selection according to the organic compound molecule structure information. Firstly, it classifies the molecule structure based on the SMARTS and PATTY according to predefine rule; then to compute the atom descriptor (front track electron density, electron superdelocalizability and atom pi-charge) of every atom type according to the H¿˜ckel method and set the MEV to descript the electrophilicity; Last to statistic the gene toxicity data and MEV according to the SVM and get the posterior probability estimation of the molecule gene toxicity.

Description

technical field [0001] The invention relates to a genotoxicity probability prediction method based on molecular electrophile vector (MEV) and extended support vector machine (SVM), which is suitable for virtual toxicity evaluation and screening of the compound according to the molecular structure information of the organic compound. Background technique [0002] Drug development relies on the discovery of compounds with targeted activity while having low toxic side effects. Over the past few decades, drug discovery techniques such as combinatorial chemistry and high-throughput screening (HTS) have made substantial progress in early identification of lead compounds. However, toxicity issues remain an important factor in late drug failure (Caldwell, et al., 2001). Currently, in order to evaluate the safety of drugs, a series of toxicity testing experiments are required. In addition to huge economic and labor costs, such tests are generally limited by low-throughput screening ...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G01N35/00G01N33/00C12Q1/68G06F17/00
Inventor 蒋华良罗小民朱维良陈凯先郑明月刘治国薛春霞
Owner SHANGHAI INST OF MATERIA MEDICA CHINESE ACAD OF SCI
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