de Juan David, Mellado Mario, Rodríguez-Frade José Miguel, Hernanz-Falcón Patricia, Serrano Antonio, del Sol Antonio, Valencia Alfonso, Martínez-A Carlos, Rojas Ana María
Protein Design Group, National Center of Biotechnology (CNB-CSIC) Cantoblanco, Madrid, Spain.
Bioinformatics. 2005 Sep 1;21 Suppl 2:ii13-8. doi: 10.1093/bioinformatics/bti1101.
Solving relevant biological problems requires answering complex questions. Addressing such questions traditionally implied the design of time-consuming experimental procedures which most of the time are not accessible to average-sized laboratories. The current trend is to move towards a multidisciplinary approach integrating both theoretical knowledge and experimental work. This combination creates a powerful tool for shedding light on biological problems. To illustrate this concept, we present here a descriptive example of where computational methods were shown to be a key aspect in detecting crucial players in an important biological problem: the dimerization of chemokine receptors. Using evolutionary based sequence analysis in combination with structural predictions two CCR5 residues were selected as important for dimerization and further validated experimentally. The experimental validation of computational procedures demonstrated here provides a wealth of valuable information not obtainable by any of the individual approaches alone.
解决相关生物学问题需要回答复杂的问题。传统上,解决这类问题意味着设计耗时的实验程序,而大多数情况下,中等规模的实验室无法进行这些实验。当前的趋势是朝着整合理论知识和实验工作的多学科方法发展。这种结合创造了一个强大的工具,用于阐明生物学问题。为了说明这一概念,我们在此给出一个描述性示例,展示了计算方法如何成为检测一个重要生物学问题(趋化因子受体二聚化)中关键因素的关键方面。通过基于进化的序列分析与结构预测相结合,选择了两个对CCR5二聚化重要的残基,并通过实验进一步验证。此处展示的计算程序的实验验证提供了大量单独采用任何一种方法都无法获得的有价值信息。