Search for β2 adrenergic receptor ligands by virtual screening via grid computing and investigation of binding modes by docking and molecular dynamics simulations.

Qifeng Bai,Yonghua Shao,Yang Zhang,Dabo Pan,Xiaojun Yao,Huanxiang Liu,Roland Seifert

doi:10.1371/journal.pone.0107837

Qifeng Bai, Yonghua Shao + Show 5 more

Open Access

https://doi.org/10.1371/journal.pone.0107837

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Abstract

We designed a program called MolGridCal that can be used to screen small molecule database in grid computing on basis of JPPF grid environment. Based on MolGridCal program, we proposed an integrated strategy for virtual screening and binding mode investigation by combining molecular docking, molecular dynamics (MD) simulations and free energy calculations. To test the effectiveness of MolGridCal, we screened potential ligands for β2 adrenergic receptor (β2AR) from a database containing 50,000 small molecules. MolGridCal can not only send tasks to the grid server automatically, but also can distribute tasks using the screensaver function. As for the results of virtual screening, the known agonist BI-167107 of β2AR is ranked among the top 2% of the screened candidates, indicating MolGridCal program can give reasonable results. To further study the binding mode and refine the results of MolGridCal, more accurate docking and scoring methods are used to estimate the binding affinity for the top three molecules (agonist BI-167107, neutral antagonist alprenolol and inverse agonist ICI 118,551). The results indicate agonist BI-167107 has the best binding affinity. MD simulation and free energy calculation are employed to investigate the dynamic interaction mechanism between the ligands and β2AR. The results show that the agonist BI-167107 also has the lowest binding free energy. This study can provide a new way to perform virtual screening effectively through integrating molecular docking based on grid computing, MD simulations and free energy calculations. The source codes of MolGridCal are freely available at http://molgridcal.codeplex.com.

Highlights

Grid computing can collect computer resources from different locations to deal with data more effectively and rapidly [1]
The Algorithm of MolGridCal The MolGridCal program was designed by using grid computing based on the framework of JPPF
We designed MolGridCal program for virtual screening of ligands of b2 adrenergic receptor (b2AR) using grid computing by combination use of molecular docking, Molecular dynamics (MD) simulations and free energy calculations

Summary

Introduction

Grid computing can collect computer resources from different locations to deal with data more effectively and rapidly [1]. This advantage of grid computing has led to its wide and successful applications in many different fields, such as Hadron Collider [2], nuclear magnetic resonance (NMR) [3], image analysis [4] and so on. The grid computing framework of folding@home [14] was used to simulate protein folding process by using the idle computer resources. The screensaver project of grid computing could supply enough computing resource to perform effective virtual screening [25]

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