پیش‏‌بینی ساختار مناسب دارو با استفاده از الگوریتم تکامل تفاضلی مبتنی بر نقطه‏‌ی مخالف

نوع مقاله: مقاله کامل پژوهشی

نویسندگان

1 دانشجوی کارشناسی ارشد مهندسی‏ کامپیوتر گرایش هوش ‏مصنوعی و رباتیک-دانشگاه علم و صنعت ایران

2 استادیار دانشکده مهندسی‏ کامپیوتر-دانشگاه علم و صنعت ایران

10.22041/ijbme.2012.13170

چکیده

کشف داروهای جدید و بررسی اثرات ‎جانبی آن‏ها یکی از زمینه‏های مهم پژوهشی است که دانشمندان داروساز در آن به فعالیت مشغولند. به دلیل اثرِ مستقیمِ محصولات دارویی بر سلامت انسان‏ها، تحقیقات داروسازی از حساسیت بالایی برخوردار بوده و رسیدن به جوابی مطلوب در این تحقیقات اغلب زمان زیادی احتیاج خواهدداشت. پیش‏بینی ساختار دارو به کمک نرم‏افزارهای شبیه‏سازی، راهکاری است که در سال‏های اخیر مورد توجه محققین داروسازی بوده‏است. در این مسئله دانشمندان به دنبال یافتن بهترین برهم‏کنشِ بین ساختار دارو و گیرنده‏ می‏باشند. این مسئله در منابع علمی با نام پهلوگیری‏مولکولی شناخته می‏شود و می‏توان آن‏را به عنوان یک مسئله جستجو در نظر گرفت که فضای جستجو در آن حالت‏های مختلف برهم‏کنش دارو وگیرنده می‏باشد. هدف نهایی از حل این مسئله انتخاب بهترین برهم‏کنش از میان این فضای جستجو است. در این مقاله از الگوریتم‏ تکامل‏تفاضلی مبتنی بر نقطه مقابل برای یافتن بهترین حالت برهم‏کنش دارو و گیرنده استفاده شده‎است. برای بهبود نتایج، الگوریتم مذکور با یک روش جستجوی محلی و یک عملگر نخبه‏گرا تلفیق شده‏است. الگوریتم ارائه‏شده، مانند دیگر الگوریتم‏های فرااکتشافی یک الگوریتم تکرار شونده می‏باشد که به کمک جمعیتی از بردارهای جواب سعی در یافتن بهترین برهم‏کنش دارد. همچنین تابع ارزیاب استفاده شده در این پژوهش تابع ارزیاب AutoDock می‏باشد. برای ارزیابی الگوریتم پیشنهادی شش ساختار متفاوت گیرنده-دارو استفاده شده‏است. نتایج حاصل از پیش‏بینی ساختار دارو برای هر یک از این شش گیرنده با نتایج الگوریتم ژنتیک لامارکی و الگوریتم سردسازی شبیه‌سازی شده و الگوریتم‏ تکامل‏تفاضلی معمولی مقایسه شده‏است. بر اساس نتایج الگوریتم ارائه شده نسبت به الگوریتم‏های دیگر از عملکرد بهتری برخوردار است.

کلیدواژه‌ها

موضوعات


عنوان مقاله [English]

Suitable drug structure prediction with Opposition-Based Differential Evolution

نویسندگان [English]

  • Mohammad Koohimoghadam 1
  • Adel Torkamaan Rahmani 2
1 M.Sc Student, Department of Computer Engineering, Iran University of Science and Technology
2 Assistant Professor, Department of Computer Engineering, Iran University of Science and Technology
چکیده [English]

Discovery of new drugs and study of their side effects has been an important research field in recent years. Because of direct effect of the pharmaceutical products on human health usually the drug design projects are challenging and technically demanding. The incorporation of computer simulations into drug design projects is one of the best ways to optimize drugs' potency. In this approach, researchers try to find the best interaction between protein structure and drug in a virtual environment; this procedure is called "molecular docking". The molecular docking problem can be considered as a search problem. The search space in this problem is defined with all possible protein-ligand interactions and the best interaction is the solution of problem. In this paper, a new approach for finding the best interaction is proposed. The proposed method is based on opposition based differential evolution algorithm. Also the proposed method is enhanced by a local search algorithm and a pseudo-elitism operator. Like other metaheuristic algorithms, our method uses a population of possible solution and AutoDock scoring function is used to evaluate each vector in the population. Six different protein-ligand complexes are used to verify the efficiency of the proposed algorithm. The experimental results show that the proposed algorithm is more robust and reliable than other algorithms such as simulated annealing and Lamarckian genetic algorithm.

کلیدواژه‌ها [English]

  • Drug
  • receptor
  • Molecular Docking
  • Differential Evolution Algorithm
  • scori
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