Summary
Chemogenomics knowledge-based drug discovery approaches aim to extract the knowledge gained from one target and to apply it for the discovery of ligands and hopefully drugs of a new target which is related to the parent target by homology or conserved molecular recognition. Herein, we demonstrate the potential of knowledge-based virtual screening by applying it to the MDM4-p53 protein–protein interaction where the MDM2-p53 protein–protein interaction constitutes the parent reference system; both systems are potentially relevant to cancer therapy. We show that a combination of virtual screening methods, including homology based similarity searching, QSAR (Quantitative Structure–Activity Relationship) methods, HTD (High Throughput Docking), and UNITY pharmacophore searching provide a successful approach to the discovery of inhibitors. The virtual screening hit list is of the magnitude of 50,000 compounds picked from the corporate compound library of ∼1.2 million compounds. Emphasis is placed on the facts that such campaigns are only feasible because of the now existing HTCP (Highthroughput Cherry-Picking) automation systems in combination with robust MTS (Medium Throughput Screening) fluorescence-based assays. Given that the MDM2-p53 system constitutes the reference system, it is not surprising that significantly more and stronger hits are found for this interaction compared to the MDM4-p53 system. Novel, selective and dual hits are discovered for both systems. A hit rate analysis will be provided compared to the full HTS (High-throughput Screening).
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Acknowledgments
Drs. P. Chene and P. Fuerst (all NIBR associates) are acknowledged for various support and discussions.
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Jacoby, E. et al. (2009). Knowledge-Based Virtual Screening: Application to the MDM4/p53 Protein–Protein Interaction. In: Jacoby, E. (eds) Chemogenomics. Methods in Molecular Biology, vol 575. Humana Press, Totowa, NJ. https://doi.org/10.1007/978-1-60761-274-2_7
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DOI: https://doi.org/10.1007/978-1-60761-274-2_7
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