RESUMEN
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.
Asunto(s)
Bibliotecas de Moléculas Pequeñas/química , Diseño de Fármacos , Evaluación Preclínica de Medicamentos/métodos , Ensayos Analíticos de Alto Rendimiento/métodos , Bibliotecas de Moléculas Pequeñas/farmacologíaRESUMEN
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 degrees 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.
Asunto(s)
Dimetilsulfóxido/química , Estabilidad de Medicamentos , Bibliotecas de Moléculas Pequeñas/química , Agua/química , Cromatografía Liquida , Espectrometría de Masas , Bibliotecas de Moléculas Pequeñas/aislamiento & purificación , Programas Informáticos , Rayos UltravioletaRESUMEN
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.
Asunto(s)
Diseño de Fármacos , Evaluación Preclínica de Medicamentos/métodos , Genómica/métodos , Animales , Inteligencia Artificial , Técnicas Químicas Combinatorias , Humanos , Biblioteca de PéptidosRESUMEN
In high-throughput screening (HTS), compounds can be tested in self-deconvoluting matrices (SDMs) of 10 compounds per well. The SDM setup is based upon a systematic mixing of compound samples such that each compound appears twice in the screening assay, in two independent mixtures. In order to test the quality of the SDM approach, we compared it with a standard single-compound screening approach. In a CXCR3 scintillation proximity assay, we performed five multiple screening trials of 26,400 compounds at a 10 microM screening concentration to estimate false positive and false negative rates in the compound population. No potent hits (<6.2 microM IC50) were missed in any screening method. Forty-eight percent of all actives were found in every screening trial independent of compound handling method. The SDM strategy had an average of 25 false positives and 15 false negatives as compared with an average of 34 false positives and 15 false negatives with a more conventional single-compound screening approach. Most of the variability resulted from day-to-day variation around the hit cutoff criterion, rather than from any particular screening technique. In the two most extreme examples, a compound with a 7.5 microM IC50 was missed in one out of two mixture trials, and a compound with a 6.2 microM IC50 was missed in one out of three single-compound trials. In the CXCR3 assay presented herein, the SDM screening method had better predictive value than the single-compound screening approach.
Asunto(s)
Receptores de Quimiocina/antagonistas & inhibidores , Animales , Células CHO , Cricetinae , Cricetulus , Interpretación Estadística de Datos , Relación Dosis-Respuesta a Droga , Evaluación Preclínica de Medicamentos/métodos , Reacciones Falso Positivas , Inmunosupresores/farmacología , Concentración 50 Inhibidora , Valor Predictivo de las Pruebas , Receptores CXCR3 , Receptores de Quimiocina/genética , Receptores de Quimiocina/metabolismo , Conteo por Cintilación/métodos , TransfecciónRESUMEN
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).
Asunto(s)
Evaluación Preclínica de Medicamentos/estadística & datos numéricos , Bases del Conocimiento , Proteínas Nucleares/química , Mapeo de Interacción de Proteínas/estadística & datos numéricos , Proteínas Proto-Oncogénicas/química , Proteína p53 Supresora de Tumor/química , Proteínas de Ciclo Celular , Árboles de Decisión , Descubrimiento de Drogas/estadística & datos numéricos , Ensayos Analíticos de Alto Rendimiento/estadística & datos numéricos , Humanos , Modelos Moleculares , Biología Molecular/métodos , Proteínas Nucleares/metabolismo , Proteínas Proto-Oncogénicas/metabolismo , Proteínas Proto-Oncogénicas c-mdm2/química , Proteínas Proto-Oncogénicas c-mdm2/metabolismo , Relación Estructura-Actividad Cuantitativa , Homología Estructural de Proteína , Proteína p53 Supresora de Tumor/metabolismo , Interfaz Usuario-ComputadorRESUMEN
Phenotypic chemogenomics studies require screening strategies that account for the complex nature of the experimental system. Unknown mechanism of action and high frequency of false positives and false negatives necessitate iterative experiments based on hypotheses formed on the basis of results from the previous step. Process-driven High Throughput Screening (HTS), aiming to "industrialize" lead finding and developed to maximize throughput, is rarely affording sufficient flexibility to design hypothesis-based experiments.In this contribution, we describe a High Throughput Cherry Picking (HTCP) system based on acoustic dispensing technology that was developed to support a new screening paradigm. We demonstrate the power of hypothesis-based screening in three chemogenomics studies that were recently conducted.