کد مقاله کد نشریه سال انتشار مقاله انگلیسی نسخه تمام متن
10138684 1645896 2018 23 صفحه PDF دانلود رایگان
عنوان انگلیسی مقاله ISI
Random drift particle swarm optimisation algorithm for highly flexible protein-ligand docking
ترجمه فارسی عنوان
الگوریتم بهینه سازی ذرات ریزش تصادفی برای اتصال انعطاف پذیر پروتئین لیگاند بسیار انعطاف پذیر
موضوعات مرتبط
علوم زیستی و بیوفناوری علوم کشاورزی و بیولوژیک علوم کشاورزی و بیولوژیک (عمومی)
چکیده انگلیسی
Molecular docking has emerged as an important tool in drug design and development. Currently, there is a relatively large and ever-increasing number of molecular docking programs. However, despite the great advances in the docking technique over the last decade, most methods cannot be used to dock highly flexible ligands successfully. In this study, based on the Autodock software, a new search algorithm, hybrid algorithm of Random Drift Particle Swarm Optimisation and local search (LRDPSO), that focuses on protein-ligand applications was presented. In our approach, we considered the ligand flexibility and strategies that aimed to improve binding affinity prediction in the context of a docking-based investigation. The experimental results revealed that our approach led to a substantially lower docking energy and higher docking precision in comparison to the LGA, PSO and QPSO algorithms. The LRDPSO algorithm was able to identify the correct binding mode of 83.6% of the complexes. In comparison, the accuracy of QPSO, PSO and LGA is 73.1%, 68.7% and 68.7%, respectively. For LRDPSO docking, satisfactory docking results can be obtained when relatively big ligands with many rotatable bonds are docked against protein binding pockets in which flexibility does play an important role. Thus, the novel LRDPSO algorithm predictions for highly flexible ligands are more reliable, and would increase the predictive power and widen the applications of this important computational tool.
ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Journal of Theoretical Biology - Volume 457, 14 November 2018, Pages 180-189
نویسندگان
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