Results from the Use of Molecular Descriptors Family on Structure Property/Activity Relationships
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CONTRIBUTORS:
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JOURNAL:
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YEAR:
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2007
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PUB TYPE:
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Journal Article
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SUBJECT(S):
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chemistry - computational; chemistry - organic; informatics - applied; informatics - databases; informatics - models implementation; informatics - web programming; research - evaluation
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DISCIPLINE:
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Biochemistry
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HTTP:
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http://lori.academicdirect.org/works/?f=121
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LANGUAGE:
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English
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PUB ID:
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103-435-833
(Last edited on
2007/07/03 09:09:50 GMT-6)
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SPONSOR(S):
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ABSTRACT:
The aim of the paper is to present the results obtained by utilization of an original approach called Molecular Descriptors Family on Structure-Property (MDF-SPR) and Structure-Activity Relationships (MDF-SAR) applied on classes of chemical compounds and its usefulness as precursors of models elaboration of new compounds with better properties and/or activities and low production costs. The MDF-SPR/MDF-SAR methodology integrates the complex information obtained from compound’s structure in unitary efficient models in order to explain properties/activities. The methodology has been applied on a number of thirty sets of chemical compounds. The best subsets of molecular descriptors family members able to estimate and predict property/activity of interest were identified and were statistically and visually analyzed. The MDF-SPR/MDF-SAR models were validated through internal and/or external validation methods. The estimation and prediction abilities of the MDF-SPR/MDF-SAR models were compared with previous reported models by applying of correlated correlation analysis, which revealed that the MDF-SPR/MDF-SAR methodology is reliable. The MDF-SPR/MDF-SAR methodology opens a new pathway in understanding the relationships between compound’s structure and property/activity, in property/activity prediction, and in discovery, investigation and characterization of new chemical compounds, more competitive as costs and property/activity, being a method less expensive comparative with experimental methods.
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STATISTICS
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24
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17
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