Literature DB >> 12086521

Effective descriptions of molecular structures and the quantitative structure-activity relationship studies.

Lu Xu1, Jia-An Yang, Ya-Ping Wu.   

Abstract

In this research, we found CoMFA alone could not obtain sufficiently a strong equation to allow confident prediction for aminobenzenes. When some other parameter, such as heat of molecular formation of the compounds, was introduced into the CoMFA model, the results were improved greatly. It gives us a hint that a better description for molecular structures will yield a better prediction model, and this hint challenged us to look for another method--the projection areas of molecules in 3D space for 3D-QSAR. It is surprising that much better results than that obtained by using CoMFA were achieved. Besides the CoMFA analysis, multiregression analysis and neural network methods for building the models were used in this paper.

Entities:  

Year:  2002        PMID: 12086521     DOI: 10.1021/ci010092r

Source DB:  PubMed          Journal:  J Chem Inf Comput Sci        ISSN: 0095-2338


  1 in total

1.  Development of novel in silico model to predict corneal permeability for congeneric drugs: a QSPR approach.

Authors:  Charu Sharma; Thirumurthy Velpandian; Nihar Ranjan Biswas; Niranjan Nayak; Rasik Bihari Vajpayee; Supriyo Ghose
Journal:  J Biomed Biotechnol       Date:  2011-02-20
  1 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.