QSAR Investigation on Quinolizidinyl Derivatives in Alzheimer’s Disease
المؤلفون المشاركون
Ghasemi, Ghasem
Nirouei, Mihyar
Rastgoo, Zinab
Rashtehroodi, Alireza Nemati
Arshadi, Sattar
Shariati, Shahab
المصدر
Journal of Computational Medicine
العدد
المجلد 2013، العدد 2013 (31 ديسمبر/كانون الأول 2013)، ص ص. 1-8، 8ص.
الناشر
Hindawi Publishing Corporation
تاريخ النشر
2013-04-30
دولة النشر
مصر
عدد الصفحات
8
التخصصات الرئيسية
الملخص EN
Sets of quinolizidinyl derivatives of bi- and tri-cyclic (hetero) aromatic systems were studied as selective inhibitors.
On the pattern, quantitative structure-activity relationship (QSAR) study has been done on quinolizidinyl derivatives as potent inhibitors of acetylcholinesterase in alzheimer’s disease (AD).
Multiple linear regression (MLR), partial least squares (PLSs), principal component regression (PCR), and least absolute shrinkage and selection operator (LASSO) were used to create QSAR models.
Geometry optimization of compounds was carried out by B3LYP method employing 6–31 G basis set.
HyperChem, Gaussian 98 W, and Dragon software programs were used for geometry optimization of the molecules and calculation of the quantum chemical descriptors.
Finally, Unscrambler program was used for the analysis of data.
In the present study, the root mean square error of the calibration and R2 using MLR method were obtained as 0.1434 and 0.95, respectively.
Also, the R and R2 values were obtained as 0.79, 0.62 from stepwise MLR model.
The R2 and mean square values using LASSO method were obtained as 0.766 and 3.226, respectively.
The root mean square error of the calibration and R2 using PLS method were obtained as 0.3726 and 0.62, respectively.
According to the obtained results, it was found that MLR model is the most favorable method in comparison with other statistical methods and is suitable for use in QSAR models.
نمط استشهاد جمعية علماء النفس الأمريكية (APA)
Ghasemi, Ghasem& Arshadi, Sattar& Rashtehroodi, Alireza Nemati& Nirouei, Mihyar& Shariati, Shahab& Rastgoo, Zinab. 2013. QSAR Investigation on Quinolizidinyl Derivatives in Alzheimer’s Disease. Journal of Computational Medicine،Vol. 2013, no. 2013, pp.1-8.
https://search.emarefa.net/detail/BIM-462587
نمط استشهاد الجمعية الأمريكية للغات الحديثة (MLA)
Ghasemi, Ghasem…[et al.]. QSAR Investigation on Quinolizidinyl Derivatives in Alzheimer’s Disease. Journal of Computational Medicine No. 2013 (2013), pp.1-8.
https://search.emarefa.net/detail/BIM-462587
نمط استشهاد الجمعية الطبية الأمريكية (AMA)
Ghasemi, Ghasem& Arshadi, Sattar& Rashtehroodi, Alireza Nemati& Nirouei, Mihyar& Shariati, Shahab& Rastgoo, Zinab. QSAR Investigation on Quinolizidinyl Derivatives in Alzheimer’s Disease. Journal of Computational Medicine. 2013. Vol. 2013, no. 2013, pp.1-8.
https://search.emarefa.net/detail/BIM-462587
نوع البيانات
مقالات
لغة النص
الإنجليزية
الملاحظات
Includes bibliographical references
رقم السجل
BIM-462587
قاعدة معامل التأثير والاستشهادات المرجعية العربي "ارسيف Arcif"
أضخم قاعدة بيانات عربية للاستشهادات المرجعية للمجلات العلمية المحكمة الصادرة في العالم العربي
تقوم هذه الخدمة بالتحقق من التشابه أو الانتحال في الأبحاث والمقالات العلمية والأطروحات الجامعية والكتب والأبحاث باللغة العربية، وتحديد درجة التشابه أو أصالة الأعمال البحثية وحماية ملكيتها الفكرية. تعرف اكثر