Multiple grid arrangement improves ligand docking with unknown binding sites: Application to the inverse docking problem. (April 2018)

• Record Type: Journal Article
• Authors: Ban, Tomohiro; Ohue, Masahito; Akiyama, Yutaka
• Is Part Of: Computational biology and chemistry. Volume 73(2018)
• Page Start: 139
• Page End: 146
• Publication Date: 2018-04
• Subjects: Computational ligand docking -- Conformational search space -- Drug–target interactions -- Inverse docking -- Multiple grid arrangement -- Structure-based drug design -- Scoring function -- Virtual screening; Chemistry -- Data processing -- Periodicals; Biology -- Data processing -- Periodicals; Biochemistry -- Data processing; Biology -- Data processing; Molecular biology -- Data processing; Periodicals; Electronic journals; 542.85
• DOI: 10.1016/j.compbiolchem.2018.02.008
• Languages: English
• ISSNs: 1476-9271

Abstract

Graphical abstract: Highlights: We propose a multiple grid arrangement method for protein–ligand docking software. It covers arbitrarily sized binding sites and enables modeling of ligand binding to proteins with unknown binding sites. The correct rate of re-docking with the Astex dataset improved from 27.1% to 34.1%. The script for Schrödinger Glide is available at http://www.bi.cs.titech.ac.jp/mga_glide/ . Abstract: The identification of comprehensive drug–target interactions is important in drug discovery. Although numerous computational methods have been developed over the years, a gold standard technique has not been established. Computational ligand docking and structure-based drug design allow researchers to predict the binding affinity between a compound and a target protein, and thus, they are often used to virtually screen compound libraries. In addition, docking techniques have also been applied to the virtual screening of target proteins (inverse docking) to predict target proteins of a drug candidate. Nevertheless, a more accurate docking method is currently required. In this study, we proposed a method in which a predicted ligand-binding site is covered by multiple grids, termed multiple grid arrangement. Notably, multiple grid arrangement facilitates the conformational search for a grid-based ligand docking software and can be applied to the state-of-the-art commercial docking software Glide (Schrödinger, LLC). We validated the proposed method by re-docking with the Astex diverse benchmark dataset and blind binding site situations, which improved the correct prediction rate of the top scoring docking pose from 27.1% to 34.1%; however, only a slight improvement in target prediction accuracy was observed with inverse docking scenarios. These findings highlight the limitations and challenges of current scoring functions and the need for more accurate docking methods. The proposed multiple grid arrangement method was implemented in Glide by modifying a cross-docking script for Glide, xglide.py. The script of our method is freely available online at http://www.bi.cs.titech.ac.jp/mga_glide/ .