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AMMOS: Automated Molecular Mechanics Optimization tool for in silico Screening.

Pencheva T, Lagorce D, Pajeva I, Villoutreix BO, Miteva MA - BMC Bioinformatics (2008)

Bottom Line: 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.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.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.

View Article: PubMed Central - HTML - PubMed

Affiliation: INSERM U648, Bioinformatics-MTI University Paris Diderot, 5 rue Marie-Andrée Lagroua, 75205 Paris Cedex 13, France. tania.pencheva@clbme.bas.bg

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.

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Enrichment graphs for ER (A) and NA (B) inhibitors after AMMOS minimization and rescoring. The y-axis is the % of retrieved actives versus the percentage of the database screened (x-axis): enrichment results after flexible docking step (blue); enrichment results after re-scoring employing AMMOS minimization: case 3 (red), all protein atoms inside a sphere around the ligand can move; case 4 (magenta), all side chain protein atoms inside a sphere around the ligand can move; case 5 (green), the whole protein is rigid.
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Figure 5: Enrichment graphs for ER (A) and NA (B) inhibitors after AMMOS minimization and rescoring. The y-axis is the % of retrieved actives versus the percentage of the database screened (x-axis): enrichment results after flexible docking step (blue); enrichment results after re-scoring employing AMMOS minimization: case 3 (red), all protein atoms inside a sphere around the ligand can move; case 4 (magenta), all side chain protein atoms inside a sphere around the ligand can move; case 5 (green), the whole protein is rigid.

Mentions: Further we validated the importance of using AMMOS as a final step of a hierarchical VLS protocol. We used a two-stage VLS protocol and a compound collection of 37,970 compounds to generate and select protein-ligand complexes with satisfactory shape complementarity, thus reducing the number of protein-ligand complexes to be minimized. The final selected pre-docked protein-ligand complexes for both protein targets containing 60% of the real active compounds were subjected to energy minimization with AMMOS. Figure 5 shows the enrichment graphs for the two targets before and after application of the AMMOS minimization protocol. Enrichments for the ER inhibitors (Figure 5A) when employing cases 3 (red) and 4 (magenta) are better than with the case 5 (green). In both cases 3 and 4, AMMOS retrieved 50% of the inhibitors in the top 3% (1200 compounds) of the entire database.


AMMOS: Automated Molecular Mechanics Optimization tool for in silico Screening.

Pencheva T, Lagorce D, Pajeva I, Villoutreix BO, Miteva MA - BMC Bioinformatics (2008)

Enrichment graphs for ER (A) and NA (B) inhibitors after AMMOS minimization and rescoring. The y-axis is the % of retrieved actives versus the percentage of the database screened (x-axis): enrichment results after flexible docking step (blue); enrichment results after re-scoring employing AMMOS minimization: case 3 (red), all protein atoms inside a sphere around the ligand can move; case 4 (magenta), all side chain protein atoms inside a sphere around the ligand can move; case 5 (green), the whole protein is rigid.
© Copyright Policy - open-access
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC2588602&req=5

Figure 5: Enrichment graphs for ER (A) and NA (B) inhibitors after AMMOS minimization and rescoring. The y-axis is the % of retrieved actives versus the percentage of the database screened (x-axis): enrichment results after flexible docking step (blue); enrichment results after re-scoring employing AMMOS minimization: case 3 (red), all protein atoms inside a sphere around the ligand can move; case 4 (magenta), all side chain protein atoms inside a sphere around the ligand can move; case 5 (green), the whole protein is rigid.
Mentions: Further we validated the importance of using AMMOS as a final step of a hierarchical VLS protocol. We used a two-stage VLS protocol and a compound collection of 37,970 compounds to generate and select protein-ligand complexes with satisfactory shape complementarity, thus reducing the number of protein-ligand complexes to be minimized. The final selected pre-docked protein-ligand complexes for both protein targets containing 60% of the real active compounds were subjected to energy minimization with AMMOS. Figure 5 shows the enrichment graphs for the two targets before and after application of the AMMOS minimization protocol. Enrichments for the ER inhibitors (Figure 5A) when employing cases 3 (red) and 4 (magenta) are better than with the case 5 (green). In both cases 3 and 4, AMMOS retrieved 50% of the inhibitors in the top 3% (1200 compounds) of the entire database.

Bottom Line: 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.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.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.

View Article: PubMed Central - HTML - PubMed

Affiliation: INSERM U648, Bioinformatics-MTI University Paris Diderot, 5 rue Marie-Andrée Lagroua, 75205 Paris Cedex 13, France. tania.pencheva@clbme.bas.bg

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.

Show MeSH
Related in: MedlinePlus