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Incorporating Virtual Reactions into a Logic-based Ligand-based Virtual Screening Method to Discover New Leads.

Reynolds CR, Muggleton SH, Sternberg MJ - Mol Inform (2015)

Bottom Line: PLoRRS uses logical rules from the INDDEx model to select reactants for the de novo generation of potentially active products.The PLoRRS method is found to increase significantly the likelihood of retrieving molecules similar to known actives with a p-value of 0.016.Case studies demonstrate that the virtual reactions produce molecules highly similar to known actives, including known blockbuster drugs.

View Article: PubMed Central - PubMed

Affiliation: Department of Bioinformatics, Imperial College London, South Kensington Campus London SW7 2AZ, UK.

ABSTRACT

The use of virtual screening has become increasingly central to the drug development pipeline, with ligand-based virtual screening used to screen databases of compounds to predict their bioactivity against a target. These databases can only represent a small fraction of chemical space, and this paper describes a method of exploring synthetic space by applying virtual reactions to promising compounds within a database, and generating focussed libraries of predicted derivatives. A ligand-based virtual screening tool Investigational Novel Drug Discovery by Example (INDDEx) is used as the basis for a system of virtual reactions. The use of virtual reactions is estimated to open up a potential space of 1.21×10(12) potential molecules. A de novo design algorithm known as Partial Logical-Rule Reactant Selection (PLoRRS) is introduced and incorporated into the INDDEx methodology. PLoRRS uses logical rules from the INDDEx model to select reactants for the de novo generation of potentially active products. The PLoRRS method is found to increase significantly the likelihood of retrieving molecules similar to known actives with a p-value of 0.016. Case studies demonstrate that the virtual reactions produce molecules highly similar to known actives, including known blockbuster drugs.

No MeSH data available.


Desirability plotted against similarity for EGFr for the two hundred most active virtual product molecules in the consensus screening.
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fig12: Desirability plotted against similarity for EGFr for the two hundred most active virtual product molecules in the consensus screening.

Mentions: Figure 12 shows that looking at the top two hundred results of the consensus EGFr screening, 69 % are above 0.5 desirability and 21 % are above 0.7 desirability. Raising the desirability cut-off to 0.5 decreases the rank of the first similar hit (with 0.79 similarity) from 532nd to 166th, and raising it to 0.7 decreases it to 12th.


Incorporating Virtual Reactions into a Logic-based Ligand-based Virtual Screening Method to Discover New Leads.

Reynolds CR, Muggleton SH, Sternberg MJ - Mol Inform (2015)

Desirability plotted against similarity for EGFr for the two hundred most active virtual product molecules in the consensus screening.
© Copyright Policy
Related In: Results  -  Collection

Show All Figures
getmorefigures.php?uid=PMC4641463&req=5

fig12: Desirability plotted against similarity for EGFr for the two hundred most active virtual product molecules in the consensus screening.
Mentions: Figure 12 shows that looking at the top two hundred results of the consensus EGFr screening, 69 % are above 0.5 desirability and 21 % are above 0.7 desirability. Raising the desirability cut-off to 0.5 decreases the rank of the first similar hit (with 0.79 similarity) from 532nd to 166th, and raising it to 0.7 decreases it to 12th.

Bottom Line: PLoRRS uses logical rules from the INDDEx model to select reactants for the de novo generation of potentially active products.The PLoRRS method is found to increase significantly the likelihood of retrieving molecules similar to known actives with a p-value of 0.016.Case studies demonstrate that the virtual reactions produce molecules highly similar to known actives, including known blockbuster drugs.

View Article: PubMed Central - PubMed

Affiliation: Department of Bioinformatics, Imperial College London, South Kensington Campus London SW7 2AZ, UK.

ABSTRACT

The use of virtual screening has become increasingly central to the drug development pipeline, with ligand-based virtual screening used to screen databases of compounds to predict their bioactivity against a target. These databases can only represent a small fraction of chemical space, and this paper describes a method of exploring synthetic space by applying virtual reactions to promising compounds within a database, and generating focussed libraries of predicted derivatives. A ligand-based virtual screening tool Investigational Novel Drug Discovery by Example (INDDEx) is used as the basis for a system of virtual reactions. The use of virtual reactions is estimated to open up a potential space of 1.21×10(12) potential molecules. A de novo design algorithm known as Partial Logical-Rule Reactant Selection (PLoRRS) is introduced and incorporated into the INDDEx methodology. PLoRRS uses logical rules from the INDDEx model to select reactants for the de novo generation of potentially active products. The PLoRRS method is found to increase significantly the likelihood of retrieving molecules similar to known actives with a p-value of 0.016. Case studies demonstrate that the virtual reactions produce molecules highly similar to known actives, including known blockbuster drugs.

No MeSH data available.