RESUMO
High-throughput screening (HTS) is an effective method for lead and probe discovery that is widely used in industry and academia to identify novel chemical matter and to initiate the drug discovery process. However, HTS can be time consuming and costly and the use of subsets as an efficient alternative to screening entire compound collections has been investigated. Subsets may be selected on the basis of chemical diversity, molecular properties, biological activity diversity or biological target focus. Previously, we described a novel form of subset screening: plate-based diversity subset (PBDS) screening, in which the screening subset is constructed by plate selection (rather than individual compound cherry-picking), using algorithms that select for compound quality and chemical diversity on a plate basis. In this paper, we describe a second-generation approach to the construction of an updated subset: PBDS2, using both plate and individual compound selection, that has an improved coverage of the chemical space of the screening file, whilst only selecting the same number of plates for screening. We describe the validation of PBDS2 and its successful use in hit and lead discovery. PBDS2 screening became the default mode of singleton (one compound per well) HTS for lead discovery in Pfizer.
Assuntos
Descoberta de Drogas/métodos , Ensaios de Triagem em Larga Escala/métodos , Algoritmos , Simulação por Computador , Descoberta de Drogas/normas , Avaliação Pré-Clínica de Medicamentos , Ensaios de Triagem em Larga Escala/normas , Reprodutibilidade dos Testes , Bibliotecas de Moléculas PequenasRESUMO
Over the past 20 years, the toolbox for discovering small-molecule therapeutic starting points has expanded considerably. Pharmaceutical researchers can now choose from technologies that, in addition to traditional high-throughput knowledge-based and diversity screening, now include the screening of fragment and fragment-like libraries, affinity selection mass spectrometry, and selection against DNA-encoded libraries (DELs). Each of these techniques has its own unique combination of advantages and limitations that makes them more, or less, suitable for different target classes or discovery objectives, such as desired mechanism of action. Layered on top of this are the constraints of the drug-hunters themselves, including budgets, timelines, and available platform capacity; each of these can play a part in dictating the hit identification strategy for a discovery program. In this article, we discuss some of the factors that we use to govern our building of a hit identification roadmap for a program and describe the increasing role that DELs are playing in our discovery strategy. Furthermore, we share our learning during our initial exploration of DEL and highlight the approaches we have evolved to maximize the value returned from DEL selections. Topics addressed include the optimization of library design and production, reagent validation, data analysis, and hit confirmation. We describe how our thinking in these areas has led us to build a DEL platform that has begun to deliver tractable matter to our global discovery portfolio.
Assuntos
Descoberta de Drogas/métodos , Biblioteca Gênica , Bibliotecas de Moléculas Pequenas , Descoberta de Drogas/normas , HumanosRESUMO
Phospholipid transfer protein (PLTP) plays an important role in atherogenesis, and its function goes well beyond that of transferring phospholipids between lipoprotein particles. Previous studies showed that genetic deficiency of PLTP in mice causes a substantially impaired hepatic secretion of apolipoprotein-B (apoB), the major protein of atherogenic lipoproteins. To understand whether the impaired apoB secretion is a direct result from lack of PLTP activity, in this study, we further investigated the function of PLTP in apoB secretion by using PLTP inhibitors. We identified a series of compounds containing a 3-benzazepine core structure that inhibit PLTP activity. Compound A, the most potent inhibitor, was characterized further and had little cross-reactivity with microsomal triglyceride transfer protein. Compound A reduced apoB secretion in human hepatoma cell lines and mouse primary hepatocytes. Furthermore, we confirmed that the reduction of apoB secretion mediated by compound A is PLTP-dependent, because the PLTP inhibitor had no effect on apoB secretion from PLTP-deficient hepatocytes. These studies provided evidence that PLTP activity regulates apoB secretion and pharmacologic inhibition of PLTP may be a new therapy for dyslipidemia by reducing apoB secretion.
Assuntos
Apolipoproteínas B/metabolismo , Benzazepinas/farmacologia , Hepatócitos/efeitos dos fármacos , Proteínas de Transferência de Fosfolipídeos/antagonistas & inibidores , Animais , Benzazepinas/química , Linhagem Celular Tumoral , Hepatócitos/metabolismo , Ensaios de Triagem em Larga Escala , Humanos , Técnicas In Vitro , Camundongos , Camundongos Knockout , Proteínas de Transferência de Fosfolipídeos/química , Proteínas de Transferência de Fosfolipídeos/genética , Relação Estrutura-AtividadeRESUMO
The promise of phenotypic screening resides in its track record of novel biology and first-in-class therapies. However, challenges stemming from major differences between target-based and phenotypic screening do exist. These challenges prompted us to rethink the critical stage of hit triage and validation on the road to clinical candidates and novel drug targets. Whereas this process is usually straightforward for target screening hits, phenotypic screening hits act through a variety of mostly unknown mechanisms within a large and poorly understood biological space. Our analysis suggests successful hit triage and validation is enabled by three types of biological knowledge-known mechanisms, disease biology, and safety-while structure-based hit triage may be counterproductive.
Assuntos
Triagem , Descoberta de Drogas , Humanos , FenótipoRESUMO
Phenotypic drug discovery approaches can positively affect the translation of preclinical findings to patients. However, not all phenotypic assays are created equal. A critical question then follows: What are the characteristics of the optimal assays? We analyze this question and propose three specific criteria related to the disease relevance of the assay-system, stimulus, and end point-to help design the most predictive phenotypic assays.