توجه: محتویات این صفحه به صورت خودکار پردازش شده و مقاله‌های نویسندگانی با تشابه اسمی، همگی در بخش یکسان نمایش داده می‌شوند.
۱QSAR STUDY ON N–1–ARYLBENZIMIDAZOLES AS HIV–1 INHIBITORS
نویسنده(ها): ،
اطلاعات انتشار: اولین همایش ملی تکنیک های نوین در تجهیزات و مواد آزمایشگاهی صنعت نفت ایران، سال
تعداد صفحات: ۱۰
Quantitative structure–activity relationship (QSAR) studies were performed on N–1– aryl–benzimidazoles 2–substituted derivatives for prediction of their activities as novel HIV–1non–nucleoside reverse transcriptase inhibitors. The activities of these compounds were calculated using the theoretical descriptors generated from their molecular structures. QSARmethodologies carried out based on Bayesian regularized artificial neural network (BR–ANN).The statistically significant 2D–QSAR model having determination coefficient (R2) = 0.9712 and mean square error (MSE) =0.0663 with determination coefficient of prediction R2 = 0.8814 andMSE of prediction =0.061 developed by stepwise multiple linear regression method and Leaveone–out cross–validation (LOOCV) method. The methods showed that can to be potential tools for estimation of IC50 of new drug–like candidates at early stages of drug development. And these results showed that N–1–aryl–benzimidazoles 2–substituted derivatives can be active as novel HIV–1 non–nucleoside reverse transcriptase inhibitors.<\div>
نمایش نتایج ۱ تا ۱ از میان ۱ نتیجه