Gene/Protein
Disease
Symptom
Drug
Enzyme
Compound
Pivot Concepts:
Gene/Protein
Disease
Symptom
Drug
Enzyme
Compound
Target Concepts:
Gene/Protein
Disease
Symptom
Drug
Enzyme
Compound
Query: EC:2.4.1.14 (
SPS
)
813
document(s) hit in 31,850,051 MEDLINE articles (0.00 seconds)
Mathematical modeling of Quantitative Structure - Property Relationships met great interest in fields of in silico drug design and more recently, pharmaceutical analysis. In our approach we proposed automated method of creation Quantitative Structure-Retention Relationship (QSRR) for analysis of triptans, selective serotonin 5-HT
1
receptor agonists used for the treatment of acute
headache
. The method was created using hybrid machine learning approach, namely Genetic algorithm (GA) coupled with artificial neutral networks (ANN). Performance of proposed hybrid GA-ANN model was evaluated with predicting relative retention times of naratriptan hydrochloride impurities. Several ANN types were coupled with GA and tested: single-layer ANN (SL-ANN), double-layer ANN (D-ANN) and higher order architectures: pi-sigma ANN (PS-ANN) and sigma-pi-sigma ANN (SPS-ANN). Partial Least Squares (PLS) method was used as a reference. The separation of naratriptan hydrochloride and its related products (impurities and degradation products) was obtained by developing a gradient high-performance liquid chromatography method with diode-array detector (HPLC-DAD). Degradation products during acid-basic hydrolysis were identified with an electrospray ionization tandem mass spectrometry (Q-TOF-MS/MS) detector. Independent data for outer validation of QSRR model was obtained from the determination of related products of sumatriptan succinate via an HPLC-DAD method. Accuracy of QSRR was measured by inner-validation on naratriptan data and outer validation on sumatriptan succinate samples. The best performing model were PS-ANN and
SPS
-ANN with mean errors of 8% (Q
2
=0.87) and 15% (Q
2
=0.77) on an inner-validation data set, respectively. Validation on similar samples from an outer validation data set of sumatriptan succinate impurities gave mean errors of 18% (R
2
pred
=0.64) and 17% (R
2
pred
=0.63) for the PS-ANN and
SPS
-ANN models, respectively.
...
PMID:Quantitative structure-retention relationship model for the determination of naratriptan hydrochloride and its impurities based on artificial neural networks coupled with genetic algorithm. 2810 13
