چاپ صفحه |  صفحه نخست سامانه |  چکیده مقاله |  نویسندگان |  دانلود مقاله | دانشگاه علوم پزشکی تبریز |
| نویسنده ثبت کننده مقاله | سیاوش دستمالچی |
| مرحله جاری مقاله | تایید نهایی |
| دانشکده/مرکز مربوطه | مرکز تحقیقات بیوتکنولوژی(زیست فناوری) |
| کد مقاله | 61729 |
| عنوان فارسی مقاله | An alignment-independent 3D-QSAR study of FGFR2 tyrosine kinase inhibitors |
| عنوان لاتین مقاله | An alignment-independent 3D-QSAR study of FGFR2 tyrosine kinase inhibitors |
| ناشر | 5 |
| آیا مقاله از طرح تحقیقاتی و یا منتورشیپ استخراج شده است؟ | بلی |
| عنوان نشریه (خارج از لیست فوق) | |
| نوع مقاله | Original Article |
| نحوه ایندکس شدن مقاله | ایندکس شده سطح یک – ISI - Web of Science |
| آدرس لینک مقاله/ همایش در شبکه اینترنت | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5651062/ |
| Purpose: Receptor tyrosine kinase (RTK) inhibitors are widely used pharmaceuticals in cancer therapy. Fibroblast growth factor receptors (FGFRs) are members of RTK superfamily which are highly expressed on the surface of carcinoma associate fibroblasts (CAFs). The involvement of FGFRs in different types of cancer makes them promising target in cancer therapy and hence, the identification of novel FGFR inhibitors is of great interest. In the current study we aimed to develop an alignment independent three dimensional quantitative structure-activity relationship (3D-QSAR) model for a set of 26 FGFR2 kinase inhibitors allowing the prediction of activity and identification of important structural features for these inhibitors. Methods: Pentacle software was used to calculate grid independent descriptors (GRIND) for the active conformers generated by docking followed by the selection of significant variables using fractional factorial design (FFD). The partial least squares (PLS) model generated based on the remaining descriptors was assessed by internal and external validation methods. Results: Six variables were identified as the most important probes-interacting descriptors with high impact on the biological activity of the compounds. Internal and external validations were lead to good statistical parameters (r2 values of 0.93 and 0.665, respectively). Conclusion: The results showed that the model has good predictive power and may be used for designing novel FGFR2 inhibitors. |
| نویسنده | نفر چندم مقاله |
|---|---|
| سیاوش دستمالچی | پنجم |
| مریم حمزه میوه رود | دوم |
| بهزاد جعفری | اول |
| علی اکبر علیزاده | سوم |
| مهدی شریفی | چهارم |
| نام فایل | تاریخ درج فایل | اندازه فایل | دانلود |
|---|---|---|---|
| apb-7-409.pdf | 1396/08/16 | 1149157 | دانلود |
