Plasmodium falciparum DDX17 is an RNA helicase crucial for parasite development

In-Silico Functional Annotation of Plasmodium falciparum Hypothetical Proteins to Identify Novel Drug Targets

Plasmodium falciparum is one of the plasmodium species responsible for the majority of life-threatening malaria cases. The current antimalarial therapies are becoming less effective due to growing drug resistance, leading to the urgent requirement for alternative and more effective antimalarial drugs or vaccines. To facilitate the novel drug discovery or vaccine development efforts, recent advances in sequencing technologies provide valuable information about the whole genome of the parasite, yet a lot more needs to be deciphered due to its incomplete proteome annotation. Surprisingly, out of the 5,389 proteins currently annotated in the Plasmodium falciparum 3D7 strain, 1,626 proteins (∼30% data) are annotated as hypothetical proteins. In parasite genomic studies, the challenge to annotate hypothetical proteins is often ignored, which may obscure the crucial information related to the pathogenicity of the parasite. In this study, we attempt to characterize hypothetical proteins of the parasite to identify novel drug targets using a computational pipeline. The study reveals that out of the overall pool of the hypothetical proteins, 266 proteins have conserved functional signatures. Furthermore, the pathway analysis of these proteins revealed that 23 proteins have an essential role in various biochemical, signalling and metabolic pathways. Additionally, all the proteins (266) were subjected to computational structure analysis. We could successfully model 11 proteins. We validated and checked the structural stability of the models by performing molecular dynamics simulation. Interestingly, eight proteins show stable conformations, and seven proteins are specific for Plasmodium falciparum, based on homology analysis. Lastly, mapping the seven shortlisted hypothetical proteins on the Plasmodium falciparum protein-protein interaction network revealed 3,299 nodes and 2,750,692 edges. Our study revealed interesting functional details of seven hypothetical proteins of the parasite, which help learn more about the less-studied molecules and their interactions, providing valuable clues to unravel the role of these proteins via future experimental validation.