Abstract
Rapid in silico selection of target focused libraries from commercial repositories is an attractive and cost effective approach. If structures of active compounds are available rapid 2D similarity search can be performed on multimillion compound databases but the generated library requires further focusing by various 2D/3D chemoinformatics tools. We report here a combination of the 2D approach with a ligand-based 3D method (Screen3D) which applies flexible matching to align reference and target compounds in a dynamic manner and thus to assess their structural and conformational similarity. In the first case study we compared the 2D and 3D similarity scores on an existing dataset derived from the biological evaluation of a PDE5 focused library. Based on the obtained similarity metrices a fusion score was proposed. The fusion score was applied to refine the 2D similarity search in a second case study where we aimed at selecting and evaluating a PDE4B focused library. The application of this fused 2D/3D similarity measure led to an increase of the hit rate from 8.5% (1st round, 47% inhibition at 10 µM) to 28.5% (2nd round at 50% inhibition at 10 µM) and the best two hits had 53 nM inhibitory activities.
Highlights
In the recent years we have witnessed an explosion in the number of compounds available for biological screening
Combining the the 2D (T2D)/T3D similarities into a single fusion score we found that T2D + T3D is ranging between 1.22 (0.8 + 0.42) and 1.71 (0.8 + 0.91) for the second round screening
Based on the above study we envisaged that combination of the 2D/3D similarity measures could have definite advantages in ligand-based virtual screening
Summary
In the recent years we have witnessed an explosion in the number of compounds available for biological screening. Up to present various ligand-based (LBVS) and structure-based virtual screening (SBVS) methods [10] have been reported for selecting focused libraries from compounds repositories [11]. Ligand-based approaches do not take the target structure directly into account These techniques are based on the assumption that compounds with similar topology have similar biological activities. During the alignment procedure atom-type information would be capable of generating alignments where patterns with similar binding character are oriented in a similar fashion in the known active and the candidate structures. This provides a more realistic picture of the potential bioactive similarity of the molecules. As starting points we collected 44 structurally different active PDE5 inhibitors and 44 PDE4 inhibitors representing from literature and available databases (see Supplementary Material)
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