Department of Bioinformatics at the Institute of Biochemistry and Biophysics of the Polish Academy of Sciences.
Department of Microbial Chemistry at the Institute of Biochemistry and Biophysics of the Polish Academy of Sciences.
Brief Funct Genomics. 2018 Nov 26;17(6):451-457. doi: 10.1093/bfgp/ely013.
Malaria remains one of the highest mortality infectious diseases. Malaria is caused by parasites from the genus Plasmodium. Most deaths are caused by infections involving Plasmodium falciparum, which has a complex life cycle. Malaria parasites are extremely well adapted for interactions with their host and their host's immune system and are able to suppress the human immune system, erase immunological memory and rapidly alter exposed antigens. Owing to this rapid evolution, parasites develop drug resistance and express novel forms of antigenic proteins that are not recognized by the host immune system. There is an emerging need for novel interventions, including novel drugs and vaccines. Designing novel therapies requires knowledge about host-parasite interactions, which is still limited. However, significant progress has recently been achieved in this field through the application of bioinformatics analysis of parasite genome sequences. In this review, we describe the main achievements in 'malarial' bioinformatics and provide examples of successful applications of protein sequence analysis. These examples include the prediction of protein functions based on homology and the prediction of protein surface localization via domain and motif analysis. Additionally, we describe PlasmoDB, a database that stores accumulated experimental data. This tool allows data mining of the stored information and will play an important role in the development of malaria science. Finally, we illustrate the application of bioinformatics in the development of population genetics research on malaria parasites, an approach referred to as reverse ecology.
疟疾仍然是死亡率最高的传染病之一。疟疾是由疟原虫属的寄生虫引起的。大多数死亡是由涉及恶性疟原虫的感染引起的，恶性疟原虫具有复杂的生命周期。疟原虫极其适应与宿主及其宿主的免疫系统相互作用，并能够抑制人体免疫系统，抹去免疫记忆并迅速改变暴露的抗原。由于这种快速进化，寄生虫产生了耐药性，并表达了宿主免疫系统无法识别的新型抗原蛋白。因此，迫切需要新的干预措施，包括新的药物和疫苗。设计新的疗法需要了解宿主-寄生虫相互作用的知识，但目前这方面的知识仍然有限。然而，通过应用寄生虫基因组序列的生物信息学分析，最近在这一领域取得了重大进展。在这篇综述中，我们描述了“疟原虫”生物信息学的主要成就，并提供了蛋白质序列分析成功应用的例子。这些例子包括基于同源性预测蛋白质功能和通过结构域和基序分析预测蛋白质表面定位。此外，我们还描述了 PlasmoDB，这是一个存储积累实验数据的数据库。该工具允许对存储的信息进行数据挖掘，并将在疟疾科学的发展中发挥重要作用。最后，我们说明了生物信息学在疟疾寄生虫群体遗传学研究中的应用，这种方法被称为反向生态学。
