Department of Computer and Information Sciences, Covenant University, Km. 10 Idiroko Road, Ota, Ogun State, Nigeria.
Infect Genet Evol. 2011 Jun;11(4):755-64. doi: 10.1016/j.meegid.2010.11.006. Epub 2010 Nov 26.
Malaria is one of the world's most common and serious diseases causing death of about 3 million people each year. Its most severe occurrence is caused by the protozoan Plasmodium falciparum. Reports have shown that the resistance of the parasite to existing drugs is increasing. Therefore, there is a huge and urgent need to discover and validate new drug or vaccine targets to enable the development of new treatments for malaria. The ability to discover these drug or vaccine targets can only be enhanced from our deep understanding of the detailed biology of the parasite, for example how cells function and how proteins organize into modules such as metabolic, regulatory and signal transduction pathways. It has been noted that the knowledge of signalling transduction pathways in Plasmodium is fundamental to aid the design of new strategies against malaria. This work uses a linear-time algorithm for finding paths in a network under modified biologically motivated constraints. We predicted several important signalling transduction pathways in Plasmodium falciparum. We have predicted a viable signalling pathway characterized in terms of the genes responsible that may be the PfPKB pathway recently elucidated in Plasmodium falciparum. We obtained from the FIKK family, a signal transduction pathway that ends up on a chloroquine resistance marker protein, which indicates that interference with FIKK proteins might reverse Plasmodium falciparum from resistant to sensitive phenotype. We also proposed a hypothesis that showed the FIKK proteins in this pathway as enabling the resistance parasite to have a mechanism for releasing chloroquine (via an efflux process). Furthermore, we also predicted a signalling pathway that may have been responsible for signalling the start of the invasion process of Red Blood Cell (RBC) by the merozoites. It has been noted that the understanding of this pathway will give insight into the parasite virulence and will facilitate rational vaccine design against merozoites invasion. And we have a host of other predicted pathways, some of which have been used in this work to predict the functionality of some proteins.
疟疾是世界上最常见和最严重的疾病之一，每年导致约 300 万人死亡。其最严重的发生是由原生动物疟原虫引起的。有报道称，寄生虫对现有药物的耐药性正在增加。因此，迫切需要发现和验证新的药物或疫苗靶点，以开发治疗疟疾的新方法。只有深入了解寄生虫的详细生物学，例如细胞如何运作以及蛋白质如何组织成代谢、调节和信号转导途径等模块，才能提高发现这些药物或疫苗靶点的能力。已经注意到，疟原虫信号转导途径的知识对于设计针对疟疾的新策略至关重要。这项工作使用一种在线性时间算法在修改后的生物动机约束下在网络中寻找路径。我们预测了疟原虫中的几个重要信号转导途径。我们预测了一条可行的信号转导途径，该途径在 PfPKB 途径方面具有特征，该途径最近在疟原虫中得到阐明。我们从 FIKK 家族获得了一条信号转导途径，该途径最终终止于氯喹抗性标记蛋白上，这表明干扰 FIKK 蛋白可能使疟原虫从抗性表型转变为敏感表型。我们还提出了一个假设，表明该途径中的 FIKK 蛋白使抗性寄生虫具有释放氯喹的机制（通过外排过程）。此外，我们还预测了一条信号转导途径，该途径可能负责信号启动疟原虫裂殖子入侵红细胞（RBC）的过程。已经注意到，对该途径的理解将深入了解寄生虫的毒力，并有助于针对裂殖子入侵进行合理的疫苗设计。我们还有许多其他预测途径，其中一些在这项工作中用于预测一些蛋白质的功能。
