High-throughput screening (HTS) is widely used for the identification of chemical starting points in small molecule drug discovery projects in the pharma industry. While HTS typically delivers several scaffolds suitable for further exploration its large operational costs hurdles its application on full in-house libraries. Virtual screening (VS) provides an efficient approach to supplement HTS by prioritizing compounds for biological testing. During the last years, several strategies have been evaluated for the integration of VS and HTS. Here we show the evaluation of an iterative approach consisting of the following steps: (i) enrichment test with known actives and random decoys, (ii) VS of full in-house library with the best settings, (iii) HTS on the top 10% of virtual hits, (iv) enrichment test with HTS actives and inactives, (v) VS of the remaining 90% of the in-house library with the best optimized settings, (vi) HTS on the top 10% of virtual hits.We have evaluated this iterative VS-HTS integration strategy on a c-Jun N-terminal kinase 3 (JNK3) HTS dataset (PubChem BioAssay AID: 746). This approach yielded superior results compared to other VS-HTS integration approaches.

Integration strategies for virtual and experimental screening. A case study on c-Jun N-terminal kinase 3 (JNK3)

244th National Meeting (2012)

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