Immunology Laboratory, Institute of Microbial Technology, Sector 39A, Chandigarh-160 036, India.
Expert Rev Proteomics. 2009 Oct;6(5):527-37. doi: 10.1586/epr.09.71.
In silico tools offer an attractive alternative strategy to the cumbersome experimental approaches to identify T-cell epitopes. These computational tools have metamorphosed over the years into complex algorithms that attempt to efficiently predict the binding of a plethora of peptides to HLA alleles. In recent years, the scientific community has embraced these techniques to reduce the burden of wet-laboratory experimentation. Although there are some splendid examples of the utility of these methods, there are also evidences where they fall short and remain inconsistent. Hence, are these computational tools 'Dr Jekyll' or 'Mr Hyde' to the researcher, who wishes to utilize them intrepidly? This article reviews the progress and pitfalls of the in silico tools that identify T-cell epitopes.
计算机工具为识别 T 细胞表位提供了一种有吸引力的替代策略,而不是繁琐的实验方法。这些计算工具多年来已经演变成复杂的算法,试图有效地预测大量肽与 HLA 等位基因的结合。近年来,科学界已经接受了这些技术,以减轻湿实验室实验的负担。尽管这些方法有一些很好的应用实例,但也有证据表明它们存在不足,而且结果不一致。那么,对于那些希望大胆使用这些工具的研究人员来说,这些计算工具到底是“杰基尔博士”还是“海德先生”呢?本文回顾了识别 T 细胞表位的计算机工具的进展和陷阱。