title: Targeting protein-protein interactions for parasite control.
abstract: Finding new drug targets for pathogenic infections would be of great utility for humanity, as there is a large need to develop new drugs to fight infections due to the developing resistance and side effects of current treatments. Current drug targets for pathogen infections involve only a single protein. However, proteins rarely act in isolation, and the majority of biological processes occur via interactions with other proteins, so protein-protein interactions (PPIs) offer a realm of unexplored potential drug targets and are thought to be the next-generation of drug targets. Parasitic worms were chosen for this study because they have deleterious effects on human health, livestock, and plants, costing society billions of dollars annually and many sequenced genomes are available. In this study, we present a computational approach that utilizes whole genomes of 6 parasitic and 1 free-living worm species and 2 hosts. The species were placed in orthologous groups, then binned in species-specific orthologous groups. Proteins that are essential and conserved among species that span a phyla are of greatest value, as they provide foundations for developing broad-control strategies. Two PPI databases were used to find PPIs within the species specific bins. PPIs with unique helminth proteins and helminth proteins with unique features relative to the host, such as indels, were prioritized as drug targets. The PPIs were scored based on RNAi phenotype and homology to the PDB (Protein DataBank). EST data for the various life stages, GO annotation, and druggability were also taken into consideration. Several PPIs emerged from this study as potential drug targets. A few interactions were supported by co-localization of expression in M. incognita (plant parasite) and B. malayi (H. sapiens parasite), which have extremely different modes of parasitism. As more genomes of pathogens are sequenced and PPI databases expanded, this methodology will become increasingly applicable.
authors.affiliation: Department of Genetics, The Genome Center, Washington University School of Medicine, St. Louis, Missouri, United States of America.
authors.forename: Christina M
authors.initials: CM
authors.lastname: Taylor
authors.forename: Kerstin
authors.initials: K
authors.lastname: Fischer
authors.forename: Sahar
authors.initials: S
authors.lastname: Abubucker
authors.forename: Zhengyuan
authors.initials: Z
authors.lastname: Wang
authors.forename: John
authors.initials: J
authors.lastname: Martin
authors.forename: Daojun
authors.initials: D
authors.lastname: Jiang
authors.forename: Marc
authors.initials: M
authors.lastname: Magliano
authors.forename: Marie-Noëlle
authors.initials: MN
authors.lastname: Rosso
authors.forename: Ben-Wen
authors.initials: BW
authors.lastname: Li
authors.forename: Peter U
authors.initials: PU
authors.lastname: Fischer
authors.forename: Makedonka
authors.initials: M
authors.lastname: Mitreva
mesh_terms: D000595:Amino Acid Sequence; D000818:Animals; D030562:Databases, Protein; D015801:Helminth Proteins / Q000737:chemistry / Q000378:metabolism*; D006373:Helminthiasis / Q000517:prevention & control*; D006376:Helminths / Q000472:pathogenicity*; D006801:Humans; D008390:Markov Chains; D008958:Models, Molecular; D008969:Molecular Sequence Data; D011485:Protein Binding; D017433:Protein Structure, Secondary; D017386:Sequence Homology, Amino Acid; D013045:Species Specificity
chemical_list: D015801:Helminth Proteins