This article summarizes the evolution of the screening deck at the Novartis Institutes for BioMedical Research (NIBR). Historically, the screening deck was an assembly of all available compounds. In 2015, we designed a first deck to facilitate access to diverse subsets with optimized properties. We allocated the compounds as plated subsets on a 2D grid with property based ranking in one dimension and increasing structural redundancy in the other. The learnings from the 2015 screening deck were applied to the design of a next generation in 2019. We found that using traditional leadlikeness criteria (mainly MW, clogP) reduces the hit rates of attractive chemical starting points in subset screening. Consequently, the 2019 deck relies on solubility and permeability to select preferred compounds. The 2019 design also uses NIBR’s experimental assay data and inferred biological activity profiles in addition to structural diversity to define redundancy across the compound sets.

The NIBR (Novartis Institutes for BioMedical Research) compound collection enrichment and enhancement project integrates corporate internal combinatorial compound synthesis and external compound acquisition activities in order to build up a comprehensive screening collection for a modern drug discovery organization. The main purpose of the screening collection is to supply the Novartis drug discovery pipeline with hit-to-lead compounds for today's and the future's portfolio of drug discovery programs, and to provide tool compounds for the chemogenomics investigation of novel biological pathways and circuits. As such, it integrates designed focused and diversity-based compound sets from the synthetic and natural paradigms able to cope with druggable and currently deemed undruggable targets and molecular interaction modes. Herein, we will summarize together with new trends published in the literature, scientific challenges faced and key approaches taken at NIBR to match the chemical and biological spaces.

As HTS technologies come of age, pharmaceutical companies are focusing increasingly on the quality of their screening collections. Storage conditions and their influence on compound stability and solubility are debated intensely. At Novartis, a strategy was developed that is different to most other companies: (1) compounds unsuitable for storage in solution are excluded by computational methods; (2) compounds are stored at 4 degrees C/20% relative humidity in a DMSO/water mixture to avoid freeze-thaw cycles and water uptake and to allow rapid plate replication; (3) resolubilisation of compounds at regular intervals.

The impact of storage conditions on compound stability and compound solubility has been debated intensely over the past 5 years. At Novartis, the authors decided to opt for a storage concept that can be considered controversial because they are using a DMSO/water (90/10) mixture as standard solvent. To assess the effect of water in DMSO stocks on compound stability, the authors monitored the purity of a subset of 1404 compounds from ongoing medicinal chemistry projects over several months. The study demonstrated that 85% of the compounds were stable in wet DMSO over a 2-year period at 4 °C. This result validates the storage concept developed at Novartis as a pragmatic approach that takes advantage of the benefits of DMSO/water mixtures while mediating the disadvantages. In addition, the authors describe how purity data collected over the course of the chemical validation of high-throughput screening actives are used to improve the analytical quality of the Novartis screening deck. (Journal of Biomolecular Screening 2008:999-1006

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 approximately 1.2 million compounds. Emphasis is placed on the facts that such campaigns are only feasible because of the now existing HTCP (High throughput 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).