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Open Access Methodology article

AMMOS: Automated Molecular Mechanics Optimization tool for in silico Screening

Tania Pencheva12, David Lagorce1, Ilza Pajeva2, Bruno O Villoutreix1 and Maria A Miteva1*

Author Affiliations

1 INSERM U648, Bioinformatics-MTI University Paris Diderot, 5 rue Marie-Andrée Lagroua, 75205 Paris Cedex 13, France

2 Centre of Biomedical Engineering "Prof. Ivan Daskalov", Bulgarian Academy of Sciences, 105, Akad. Georgi Bonchev Str., 1113 Sofia, Bulgaria

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BMC Bioinformatics 2008, 9:438  doi:10.1186/1471-2105-9-438

Published: 16 October 2008

Abstract

Background

Virtual or in silico ligand screening combined with other computational methods is one of the most promising methods to search for new lead compounds, thereby greatly assisting the drug discovery process. Despite considerable progresses made in virtual screening methodologies, available computer programs do not easily address problems such as: structural optimization of compounds in a screening library, receptor flexibility/induced-fit, and accurate prediction of protein-ligand interactions. It has been shown that structural optimization of chemical compounds and that post-docking optimization in multi-step structure-based virtual screening approaches help to further improve the overall efficiency of the methods. To address some of these points, we developed the program AMMOS for refining both, the 3D structures of the small molecules present in chemical libraries and the predicted receptor-ligand complexes through allowing partial to full atom flexibility through molecular mechanics optimization.

Results

The program AMMOS carries out an automatic procedure that allows for the structural refinement of compound collections and energy minimization of protein-ligand complexes using the open source program AMMP. The performance of our package was evaluated by comparing the structures of small chemical entities minimized by AMMOS with those minimized with the Tripos and MMFF94s force fields. Next, AMMOS was used for full flexible minimization of protein-ligands complexes obtained from a mutli-step virtual screening. Enrichment studies of the selected pre-docked complexes containing 60% of the initially added inhibitors were carried out with or without final AMMOS minimization on two protein targets having different binding pocket properties. AMMOS was able to improve the enrichment after the pre-docking stage with 40 to 60% of the initially added active compounds found in the top 3% to 5% of the entire compound collection.

Conclusion

The open source AMMOS program can be helpful in a broad range of in silico drug design studies such as optimization of small molecules or energy minimization of pre-docked protein-ligand complexes. Our enrichment study suggests that AMMOS, designed to minimize a large number of ligands pre-docked in a protein target, can successfully be applied in a final post-processing step and that it can take into account some receptor flexibility within the binding site area.