QSAR study of anthranilic acid sulfonamides as inhibitors of methionine aminopeptidase-2 using LS-SVM and GRNN based on principal components

European Journal of Medicinal Chemistry

Volumn 45, Issue 10, 2010, Pages 4499-4508

  Shahlaei, Mohsen ^a,b   Sabet, Razieh ^b   Ziari, Maryam Bahman ^c   Moeinifard, Behzad ^c   Fassihi, Afshin ^b,d   Karbakhsh, Reza ^e  

^a KERMANSHAH UNIVERSITY OF MEDICAL SCIENCES   (Iran)

^b ISFAHAN UNIVERSITY OF MEDICAL SCIENCES   (Iran)

^c ISLAMIC AZAD UNIVERSITY   (Iran)

^d Isfahan Pharmaceutical Sciences Research Center   (Iran)

^e ISLAMIC AZAD UNIVERSITY   (Iran)

Author keywords

Anthranilic acid sulfonamides; General regression neural network; Least squares support vector machine; Methionine aminopeptidase 2; Principal component analysis; QSAR

Indexed keywords

ANTHRANILIC ACID DERIVATIVE; ANTHRANILIC ACID SULFONAMIDE DERIVATIVE; METHIONYL AMINOPEPTIDASE 2; METHIONYL AMINOPEPTIDASE 2 INHIBITOR; PEPTIDE HYDROLASE INHIBITOR; SULFONAMIDE; UNCLASSIFIED DRUG;

ALGORITHM; ARTICLE; ARTIFICIAL NEURAL NETWORK; DRUG CYTOTOXICITY; DRUG EFFICACY; GENERAL REGRESSION NEURAL NETWORK; LEAST SQUARES SUPPORT VECTOR MACHINE; QUANTITATIVE STRUCTURE ACTIVITY RELATION; STATISTICAL MODEL;

AMINOPEPTIDASES; ANTHRANILIC ACIDS; LEAST-SQUARES ANALYSIS; METALLOENDOPEPTIDASES; NEURAL NETWORKS (COMPUTER); NONLINEAR DYNAMICS; PRINCIPAL COMPONENT ANALYSIS; QUANTITATIVE STRUCTURE-ACTIVITY RELATIONSHIP; SULFONAMIDES;

EID: 77956186611     PISSN: 02235234     EISSN: 17683254     Source Type: Journal    
DOI: 10.1016/j.ejmech.2010.07.010     Document Type: Article

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