RESUMO
Identification of active compounds in high-throughput screening (HTS) contexts can be substantially improved by applying classical experimental design and statistical inference principles to all phases of HTS studies. The authors present both experimental and simulated data to illustrate how true-positive rates can be maximized without increasing false-positive rates by the following analytical process. First, the use of robust data preprocessing methods reduces unwanted variation by removing row, column, and plate biases. Second, replicate measurements allow estimation of the magnitude of the remaining random error and the use of formal statistical models to benchmark putative hits relative to what is expected by chance. Receiver Operating Characteristic (ROC) analyses revealed superior power for data preprocessed by a trimmed-mean polish method combined with the RVM t-test, particularly for small- to moderate-sized biological hits.
Assuntos
Ensaios de Triagem em Larga Escala/estatística & dados numéricos , Ensaios de Triagem em Larga Escala/normas , Modelos Estatísticos , Projetos de Pesquisa , Animais , Sistema Livre de Células/efeitos dos fármacos , Simulação por Computador , Avaliação Pré-Clínica de Medicamentos/métodos , Avaliação Pré-Clínica de Medicamentos/normas , Avaliação Pré-Clínica de Medicamentos/estatística & dados numéricos , Reações Falso-Positivas , Imunofluorescência/métodos , Imunofluorescência/normas , Imunofluorescência/estatística & dados numéricos , Ensaios de Triagem em Larga Escala/métodos , Luciferases de Vaga-Lume/análise , Luciferases de Vaga-Lume/metabolismo , Luciferases de Renilla/análise , Luciferases de Renilla/metabolismo , Biossíntese de Proteínas/efeitos dos fármacos , Inibidores da Síntese de Proteínas/isolamento & purificação , Inibidores da Síntese de Proteínas/farmacologia , Curva ROC , Distribuição AleatóriaRESUMO
Numerous studies conclude that the selective adsorption of plasma proteins on materials contacting blood or tissue affects all subsequent interactions related to the biocompatibility of artificial surfaces. However, there are only a few studies available, which clearly demonstrate that there is a correlation between surface chemistry and selective protein adsorption. Detailed knowledge of such correlations would facilitate the design of biocompatible materials. In this study, a rapid, fluorescence-based, screening technique using a 384-well format for polymer-protein interactions was developed. The screening assay was used to measure the adsorption of human fibrinogen on 46 test polymers (44 polyarylates selected from a combinatorial library of tyrosine-derived polyarylates, and two lactide-based polymers). In this library of polyarylates, structural changes are generated by variations in either the polymer backbone or the polymer pendent chain. Although no overall trend between polymer hydrophobicity and fibrinogen adsorption could be identified using the entire set of test polymers (R(2) = 0.43), fibrinogen adsorption was clearly correlated with variations in the pendent chain structure. Thus, when the test polymers were grouped by backbone composition, increased hydrophobicity of the pendent chain was significantly correlated with reduced fibrinogen adsorption. The following R(2) coefficients within the polymer backbone groups were determined: 0.87 (diglycolates); 0.98 (glutarates); 0.73 (adipates); 0.87 (suberates); 0.67 (3-methyl-adipates). Our results demonstrate that it is possible to screen for protein-material interactions in a cost-effective fashion using a miniaturized immunofluorescence technique. Further, we demonstrate that small changes in chemical composition can significantly influence the adsorption of human fibrinogen on polymer surfaces. The lactide-based polymers were among those polymers exhibiting the highest tendency to adsorb fibrinogen. This information may be useful when polymers have to be selected for specific biomaterial applications.