Abstract
Structure-based lead optimization approaches are increasingly playing a role in the drug-discovery process. Virtual screening by molecular docking has become a largely used approach to lead discovery in the pharmaceutical industry when a high-resolution structure of the biological target of interest is available. The performance of three docking programs (Arguslab, Autodock and FlexX), for virtual database screening, is studied. Autodock and FlexX are well established commercial packages while Arguslab is distributed freely for Windows platforms by Planaria Software. Comparisons of these docking programs and scoring functions using a large and diverse data set of pharmaceutically interesting targets and active compounds are carried out. We focus on the problem of docking and scoring flexible compounds which are sterically capable of docking into a rigid conformation of the receptor. The three dimensional structures of a carefully chosen set of 126 pharmaceutically relevant proteinligand complexes were used for the comparative study. The Autodock methodology is shown to consistently yield enrichments superior to the two alternative methods, while FlexX outperforms largely Arguslab.
Highlights
The development and implementation of a range of molecular docking algorithms, based on different search methods (Taylor et al, 2002; Halperin et al, 2002) was observed in the last few years
Knowledge of the preferred orientation in turn may be used to predict the strength of association or binding affinity between two molecules using for example scoring functions
The best ranking poses predicted by the three programs Arguslab, Autodock and FlexX are shown in the Figure 1 and their root mean square deviation (RMSD) values from the original crystallographic pose determined
Summary
The development and implementation of a range of molecular docking algorithms, based on different search methods (Taylor et al, 2002; Halperin et al, 2002) was observed in the last few years. This approach has had several recent successes in drug discovery (Sechi et al, 2005; Liu et al, 2005). Knowledge of the preferred orientation in turn may be used to predict the strength of association or binding affinity between two molecules using for example scoring functions. Given the biological and pharmaceutical significance of molecular docking, considerable efforts have been directed towards improving the methods used to predict docking
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