Compounds > 5-mercapto-1-3-4-thiadiazole

5-mercapto-1-3-4-thiadiazole and Neoplasms

5-mercapto-1-3-4-thiadiazole has been researched along with Neoplasms* in 1 studies

Other Studies

1 other study(ies) available for 5-mercapto-1-3-4-thiadiazole and Neoplasms

Article	Year
Quantitative structure-activity relationship (QSAR) studies on a series of 1,3,4-thiadiazole-2-thione derivatives as tumor-associated carbonic anhydrase IX inhibitors. Journal of enzyme inhibition and medicinal chemistry, 2009, Volume: 24, Issue:3 A linear quantitative structure-activity relationship (QSAR) study that encodes various aspects of physicochemical, topological and electronic descriptors has been developed for a series of 1,3,4-thiadiazole-2-thione derivatives (1a-r and 2a-c). The carbonic anhydrase IX inhibitory activity of the candidates under study (1a-r and 2a-c) were correlated to the selected parameters using stepwise linear regression analyses to achieve the best QSAR model. Promising results were obtained with the employed tetra-parametric model indicating that the information approach used in the present investigation is quite useful for modeling carbonic anhydrase IX inhibitors. Topics: Algorithms; Antigens, Neoplasm; Biomarkers, Tumor; Carbonic Anhydrase Inhibitors; Carbonic Anhydrase IX; Carbonic Anhydrases; Humans; Inhibitory Concentration 50; Linear Models; Molecular Structure; Neoplasms; Quantitative Structure-Activity Relationship; Thiadiazoles; Thiones	2009

Article

Year

Quantitative structure-activity relationship (QSAR) studies on a series of 1,3,4-thiadiazole-2-thione derivatives as tumor-associated carbonic anhydrase IX inhibitors.

Journal of enzyme inhibition and medicinal chemistry, 2009, Volume: 24, Issue:3

A linear quantitative structure-activity relationship (QSAR) study that encodes various aspects of physicochemical, topological and electronic descriptors has been developed for a series of 1,3,4-thiadiazole-2-thione derivatives (1a-r and 2a-c). The carbonic anhydrase IX inhibitory activity of the candidates under study (1a-r and 2a-c) were correlated to the selected parameters using stepwise linear regression analyses to achieve the best QSAR model. Promising results were obtained with the employed tetra-parametric model indicating that the information approach used in the present investigation is quite useful for modeling carbonic anhydrase IX inhibitors.

Topics: Algorithms; Antigens, Neoplasm; Biomarkers, Tumor; Carbonic Anhydrase Inhibitors; Carbonic Anhydrase IX; Carbonic Anhydrases; Humans; Inhibitory Concentration 50; Linear Models; Molecular Structure; Neoplasms; Quantitative Structure-Activity Relationship; Thiadiazoles; Thiones

2009