رابطه کمی ساختار-فعالیت تعدادی از مشتق¬های فلاونوئیدی به-‏عنوان مهارکننده¬های استیل‌کولین‌استراز‎ ‎برپایه الگوریتم مونت ‏‏‌کارلو

زهرا نظری ¹ ( دانشجوی دکترای عمومی داروسازی، گروه شیمی دارویی، دانشکده داروسازی،‎ ‎علوم ‏پزشکی تهران، دانشگاه آزاد اسلامی، تهران، ایران.‏ )
شهین احمدی ² ( دانشیار گروه شیمی دارویی، دانشکده شیمی دارویی، علوم پزشکی تهران، دانشگاه ‏آزاد اسلامی، تهران، ایران.‏ )
علی الماسی راد ³ ( استاد گروه شیمی دارویی، دانشکده داروسازی، علوم پزشکی تهران، دانشگاه آزاد ‏اسلامی، تهران، ایران.‏ )

تاريخ الإرسال : 28 الأربعاء , صفر, 1445 تاريخ التأكيد : 22 الإثنين , جمادى الثانية, 1446

الکلمات المفتاحية: QSAR, فلاونوئیدها, مهارکننده¬های استیل‌کولین‌استراز, ‏SMILES, شاخص ‏آرمانی همبستگی.‏,

ملخص المقالة :

در­سال­های اخیر، روشی مبتنی بر رویکرد مستقل از بهینه‌سازی مولکول برپایه توصیفگرهای ساختاری مولکولی و توپولوژیکی، به­عنوان یک رویکرد جذاب در مدل‌سازی QSAR معرفی شده است. یکی از ویژگی­های کلیدی این رویکرد به استفاده از توصیفگرها برپایه سامانه ورودی-خط ورودی-مولکولی ساده‌شده (SMILES) برای توسعه مدل QSAR اشاره دارد. در این پژوهش، با هدف مطالعه و بررسی QSAR برخی از مشتق­های فلاونوئیدی به­عنوان مهارکننده­های استیل‌کولین‌استراز بر­پایه الگوریتم مونت کارلو، مجموعه­ای از 88 مهارکننده استیل‌کولین‌استراز از مقاله­های معتبر  انتخاب شد. ساختار ترکیب­های با نماد SMILES به­عنوان فایل­های ورودی نرم افزار تعریف و به­طور تصادفی به چهار سری شامل آموزش، آموزش نامرئی، واسنجی و مجموعه اعتبارسنجی تقسیم و مدل­سازی انجام شد. توصیفگرهای بهینه مورداستفاده در مدل از ترکیب SMILES و نمودار بدون هیدروژن بر­پایه تابع هدف جدید انتخاب شدند. قدرت پیش‌بینی مدل‌ها با مجموعه‌های اعتبارسنجی، ارزیابی شد. نتیجه­های به­دست‌آمده از چهار سری تصادفی نشان داد که مدل‌ها پیشگو و قابل ‌اعتماد از لحاظ آماری، هستند. توصیفگرهای بااهمیت افزاینده و کاهنده فعالیت مهارکنندگی استیل‌کولین‌استراز مشتق­های فلاونوئید شناسایی شدند. همچنین، pIC₅₀ تعداد زیادی از مشتق­های فلاونوئید طبیعی مهارکننده آنزیم استیل‌کولین‌استراز محاسبه و گزارش شد. 

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