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1.
J Biomol Screen ; 12(2): 276-84, 2007 Mar.
Artículo en Inglés | MEDLINE | ID: mdl-17272827

RESUMEN

Among the several goals of a high-throughput screening campaign is the identification of as many active chemotypes as possible for further evaluation. Often, however, the number of concentration response curves (e.g., IC(50)s or K(i)s) that can be collected following a primary screen is limited by practical constraints such as protein supply, screening workload, and so forth. One possible approach to this dilemma is to cluster the hits from the primary screen and sample only a few compounds from each cluster. This introduces the question as to how many compounds must be selected from a cluster to ensure that an active compound is identified, if it exists at all. This article seeks to address this question using a Monte Carlo simulation in which the dependence of the success of sampling is directly linked to screening data variability. Furthermore, the authors demonstrate that the use of replicated compounds in the screening collection can easily assess this variability and provide a priori guidance to the screener and chemist as to the extent of sampling required to maximize chemotype identification during the triage process. The individual steps of the Monte Carlo simulation provide insight into the correspondence between the percentage inhibition and eventual IC(50) curves.


Asunto(s)
Evaluación Preclínica de Medicamentos/métodos , Proteínas Quinasas/análisis , Proteínas Tirosina Quinasas Receptoras/análisis , Receptores Acoplados a Proteínas G/análisis , Adenosina Trifosfato/metabolismo , Materiales Biocompatibles/química , Biotinilación , Análisis por Conglomerados , Simulación por Computador , Cumarinas/metabolismo , Fluoresceína , Transferencia Resonante de Energía de Fluorescencia , Colorantes Fluorescentes , Concentración 50 Inhibidora , Método de Montecarlo , Poliestirenos/química , Proteínas Tirosina Quinasas Receptoras/antagonistas & inhibidores , Receptores Acoplados a Proteínas G/antagonistas & inhibidores , Muestreo , Conteo por Cintilación/métodos , Diseño de Software , Espectrofotometría , Aglutininas del Germen de Trigo/química
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