Literature DB >> 16487735

Automatic extraction of structural alerts for predicting chromosome aberrations of organic compounds.

Ernesto Estrada1, Enrique Molina.   

Abstract

We use the topological sub-structural molecular design (TOPS-MODE) approach to formulate structural alert rules for chromosome aberration (CA) of organic compounds. First, a classification model was developed to group chemicals as active/inactive respect to CA. A procedure for extracting structural information from orthogonalized TOPS-MODE descriptors was then implemented. The contributions of bonds to CA in all the molecules studied were then generated using the orthogonalized classification model. Using this information we propose 22 structural alert rules which are ready to be implemented in expert systems for the automatic prediction of CA. They include, among others, structural alerts for N-nitroso compounds (ureas, urethanes, guanidines, triazines), nitro compounds (aromatic and heteroaromatic), alkyl esters or phosphoric acids, alkyl methanesulfonates, sulphonic acids and sulphonamides, epoxides, aromatic amines, azaphenanthrene hydrocarbons, etc. The chemico-biological analysis of some of the structural alerts found is also carried out showing the potential of TOPS-MODE as a knowledge generator.

Entities:  

Mesh:

Substances:

Year:  2006        PMID: 16487735     DOI: 10.1016/j.jmgm.2006.01.002

Source DB:  PubMed          Journal:  J Mol Graph Model        ISSN: 1093-3263            Impact factor:   2.518


  5 in total

1.  Theoretical study of GSK-3α: neural networks QSAR studies for the design of new inhibitors using 2D descriptors.

Authors:  Isela García; Yagamare Fall; Xerardo García-Mera; Francisco Prado-Prado
Journal:  Mol Divers       Date:  2011-07-07       Impact factor: 2.943

2.  CORAL: Building up QSAR models for the chromosome aberration test.

Authors:  Andrey A Toropov; Alla P Toropova; Giuseppa Raitano; Emilio Benfenati
Journal:  Saudi J Biol Sci       Date:  2018-05-09       Impact factor: 4.219

3.  PTML Modeling for Pancreatic Cancer Research: In Silico Design of Simultaneous Multi-Protein and Multi-Cell Inhibitors.

Authors:  Valeria V Kleandrova; Alejandro Speck-Planche
Journal:  Biomedicines       Date:  2022-02-18

4.  Multi-Condition QSAR Model for the Virtual Design of Chemicals with Dual Pan-Antiviral and Anti-Cytokine Storm Profiles.

Authors:  Alejandro Speck-Planche; Valeria V Kleandrova
Journal:  ACS Omega       Date:  2022-08-29

5.  In Silico Model for Chemical-Induced Chromosomal Damages Elucidates Mode of Action and Irrelevant Positives.

Authors:  Yurika Fujita; Osamu Morita; Hiroshi Honda
Journal:  Genes (Basel)       Date:  2020-10-11       Impact factor: 4.096

  5 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.