Data Analysis in Chemistry and Bio-Medical Sciences

Todeschini, Roberto; Arrasate, Sonia; González-Dı́az, Humberto

doi:10.3390/ijms17122105

Cited by 3 publications

(1 citation statement)

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“…Quantitative structure–activity relationship (QSAR) has been widely used last years in drug discovery and drug design by medicinal chemists [ 7 , 8 ] and in various practical applications [ 9 , 10 ] to provide quantitative analysis of structure and biological activity relationships of compounds. Different QSAR studies were reported to identify important structural features responsible for the biological activity and to develop predictive models for diverse chemicals by different authors [ 11 , 12 ].…”

Section: Introductionmentioning

confidence: 99%

QSAR studies on PIM1 and PIM2 inhibitors using statistical methods: a rustic strategy to screen for 5-(1H-indol-5-yl)-1,3,4-thiadiazol analogues and predict their PIM inhibitory activity

Aouidate

Ghaleb

Ghamali

et al. 2017

Chemistry Central Journal

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BackgroundQuantitative structure activity relationship was carried out to study a series of PIM1 and PIM2 inhibitors. The present study was performed on twenty-five substituted 5-(1H-indol-5-yl)-1,3,4-thiadiazols as PIM1 and PIM2 inhibitors having pIC50 ranging from 5.55 to 9 µM and from 4.66 to 8.22 µM, respectively, using genetic function algorithm for variable selection and multiple linear regression analysis (MLR) to establish unambiguous and simple QSAR models based on topological molecular descriptors.ResultsResults showed that the MLR predict activity in a satisfactory manner for both activities. Consequently, the aim of the current study is twofold, first, a simple linear QSAR model was developed, which could be easily handled by chemist to screen chemical databases, or design for new potent PIM1 and PIM2 inhibitors. Second, the outcomes extracted from the current study were exploited to predict the PIM inhibitory activity of some studied compound analogues.ConclusionsThe goal of this study is to develop easy and convenient QSAR model could be handled by everyone to screen chemical databases or to design newly PIM1 and PIM2 inhibitors derived from 5-(1H-indol-5-yl)-1,3,4-thiadiazol. Graphical abstractFlow chart of the methodology used in this work.

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