There is a new contributor to the blogosphere…SimBioSys. I recommend adding the blog to your Google Reader. There are some very exciting things going on there right now. I have commented previously about how high performance computing engines such as the Cell Broadband Engine are being brought to bear on scientific problems. SimBioSys appear to be the only group who have chosen the Cell processor to port their virtual high-throughput screening and docking solution to. Their white paper makes for an interesting read.

In their most recent post “Roping in your next scaffold hop with LASSO” they talked about their LASSO publication: LASSO—ligand activity by surface similarity order: a new tool for ligand based virtual screening”. We are presently in the middle of a very exciting project regarding LASSO. We have teamed up to provide the virtual screening results for 40 target families on the full ChemSpider Library, currently containing over 18 million molecules. Using the LASSO similarity search tool, SimBioSys has screened the ChemSpider database against all 40 target families from the Database of Useful Decoys (DUD) dataset.

LASSO descriptors (Ligand Activity by Surface Similarity Order) contain a count of the different Interacting Surface Point Types (ISPT) found on a molecule. LASSO descriptors use 23 different surface point types, ranging from hydrogen bond donors/acceptor, to hydrophobic sites, to pi stacking interactions. Figure 1 shows a “histidinelike” fragment of a molecule. The triangles are the surface point types of this fragment, colored by type. Based on the idea that ligands must have surface properties compatible with the target site in order to bind, LASSO uses a descriptor of Interacting Surface Point Types (ISPT) to find molecules with diverse chemical scaffolds but similar surface properties.

lasso1.png

We are presently populating the ChemSpider database with 10s of millions of LASSO descriptors and this will allow screening of the ChemSpider database to:

● Find molecules which have a higher likelihood of binding to targets.
● Find molecules with better selectivity for a target.
● Reduce toxicity issues.

The 40 Target receptor families included in the screening results were chosen to cover a wide range of receptor classes due to their interest in drug discovery. Each target family had 10s to 100s of known active molecules, which were used as the basis for the query files used by LASSO, one query for each family. The similarity screening was performed on the full ChemSpider database across all 40 targets and the similarity scores for each structure/target pair is available via the ChemSpider website. Thus for each structure in the ChemSpider database, you can find its similarity score (based on surface properties) relative to actives of each of the 40 target receptors. In addition to allowing instant ranking results for a particular target of interest (retrieving molecules that are likely to be active for a receptor) this matrix of screening results can be used to find molecules that have predicted affinity for a target but low predicted affinity for all other targets. Performing such searches promises to improve selectivity and can be a guide to reducing toxicity concerns. More detail about this collaborative project will be forthcoming but the overview is provided here.

Watch this space for updates and an unveiling date.

Stumble it!

One Response to “Announcing the ChemSpider Ligand Activity Project Partnering with SimBioSys”

  1. Andrew Anderson says:

    I wonder if after the HT Computational Screen, anyone would find structure- ligand pairs where in-vitro binding affinity assay data were measured. Considering the volume of structures on ChemSpider, I’d say there’s a good chance! Could be interesting!

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