Modelling the Inhibitory Activity on Carbonic Anhydrase I of Some Substituted Thiadiazole and Thiadiazoline-Disulfonamides: Integration of Structure Information
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CONTRIBUTORS:
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JOURNAL:
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Computer-Aided Chemical Engineering,
24(1),
965 -
970.
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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 - biochemistry; chemistry - computational; informatics - applied; informatics - models implementation; mathematics - modeling; mathematics - statistics; medicine - immunology; medicine - informatics
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DISCIPLINE:
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Chemistry
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HTTP:
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http://lori.academicdirect.org/works/?id=133
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LANGUAGE:
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English
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PUB ID:
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103-435-980
(Last edited on
2007/08/02 10:10:21 GMT-6)
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SPONSOR(S):
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ABSTRACT:
Aim: The paper presents the abilities in estimation and prediction of the inhibition on carbonic anhydrase I of some substituted 1,3,4-thiadiazole- and 1,3,4-thiadiazoline-disulfonamides through the integration of complex structures information by using of an original molecular descriptors family on the structure-activity relationships approach.
Material and Method: The proposed approach uses the complex information obtained from substituted 1,3,4-thiadiazole- and 1,3,4-thiadiazoline-disulfonamides structure in order to generate and calculate the molecular descriptors family. The structure-activity relationship models were built based on the generated descriptors. The obtained multivariate models (the models with two, respectively four descriptors) were validated by computing the cross-validation leave-one-out score (r2cv-loo), and analyzed through assessment of the squared correlation coefficients (r2), and the models stability (r2 - r2cv-loo). The prediction ability of the multivariate MDF-SAR model with four descriptors was analyzed in training versus test sets.
Results: The best performing MDF-SAR model proved to be the model with four descriptors (r2 = 0.9175). The MDF-SAR model with four descriptors shown that the inhibition on carbonic anhydrase I of substituted 1,3,4-thiadiazole- and 1,3,4-thiadiazoline-disulfonamides is likely to be of geometry and topology nature, being in relation with the partial charge and relative atomic mass of compounds. The estimation ability of this model is sustained by the multiple correlation coefficient (r = 0.9579, 95%CI = [0.9212, 0.9776]) and by the significance of the model (F = 97, p < 0.001). The prediction ability is sustained by the cross validation leave-one-out score (r2cv-loo = 0.8911), the model stability (r2 - r2cv-loo = 0.0264), and by the results on training versus test analysis. The MDF-SAR model with four descriptors proved to render higher value of the correlation coefficient comparing with previously reported model (p < 0.01).
Conclusion: Modelling the inhibition activity on carbonic anhydrase I of substituted 1,3,4-thiadiazole- and 1,3,4-thiadiazoline-disulfonamides by integration of complex structure information provide stable MDF-SAR models, revealing that there is a relationship between the compounds structure and their inhibition activity on carbonic anhydrase I.
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STATISTICS
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