Protein–protein interactions play key roles in leukocyte extravasation process into the brain and have been attractive therapeutic targets for inhibiting brain inflammation using blocking (or neutralizing) antibodies. These targets include protein–protein interactions between cytokines (or chemokines) and their receptors on leukocytes and between adhesion molecules of leukocyte and brain endothelium. While a number of therapeutics against these targets are currently used in clinic for treatment of brain autoimmune and inflammatory disorders (e.g., multiple sclerosis), they are associated with side effects partly due to the off-target actions (i.e., nonspecific targets). There is a need for novel targets involved in the leukocyte extravasation process that are specific to leukocyte subsets or to individual inflammatory disorder and are amenable for drug development (i.e., druggable). We recently described the blood–brain barrier (BBB) Carta Project as a comprehensive collection of molecular “maps” consisting of multiple experimental omics (including RNA sequencing, proteomics, glycoproteomics, glycomics, and metabolomics) and in silico informatic analyses on a number of mammalian species from hundreds of internal, publicly available, or curated datasets. Utilizing the datasets and tools from the BBB Carta Project, we describe a methodology to identify novel “druggable” targets involving protein–protein interactions between activated leukocytes and brain endothelial cells using a combination of proteomics, bioinformatics, and in silico interactomics. The result is a prioritized list of protein–protein interactions in a network consisting of leukocyte–brain endothelial cell communication and contacts. These interactions can be further pursued for development of therapeutics such as neutralizing antibodies and their validation through preclinical testing. In addition to targeting brain inflammation, the method described here is applicable for peripheral inflammation and provides the opportunity to target important cell–cell interactions and communications that are more specific/selective for inflammatory disorders and improve currently available therapies.

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Prioritization of Therapeutic Targets of Inflammation Using Proteomics, Bioinformatics, and In Silico Cell–Cell Interactomics

  • Arsalan S. Haqqani,
  • Danica B. Stanimirovic

摘要

Protein–protein interactions play key roles in leukocyte extravasation process into the brain and have been attractive therapeutic targets for inhibiting brain inflammation using blocking (or neutralizing) antibodies. These targets include protein–protein interactions between cytokines (or chemokines) and their receptors on leukocytes and between adhesion molecules of leukocyte and brain endothelium. While a number of therapeutics against these targets are currently used in clinic for treatment of brain autoimmune and inflammatory disorders (e.g., multiple sclerosis), they are associated with side effects partly due to the off-target actions (i.e., nonspecific targets). There is a need for novel targets involved in the leukocyte extravasation process that are specific to leukocyte subsets or to individual inflammatory disorder and are amenable for drug development (i.e., druggable). We recently described the blood–brain barrier (BBB) Carta Project as a comprehensive collection of molecular “maps” consisting of multiple experimental omics (including RNA sequencing, proteomics, glycoproteomics, glycomics, and metabolomics) and in silico informatic analyses on a number of mammalian species from hundreds of internal, publicly available, or curated datasets. Utilizing the datasets and tools from the BBB Carta Project, we describe a methodology to identify novel “druggable” targets involving protein–protein interactions between activated leukocytes and brain endothelial cells using a combination of proteomics, bioinformatics, and in silico interactomics. The result is a prioritized list of protein–protein interactions in a network consisting of leukocyte–brain endothelial cell communication and contacts. These interactions can be further pursued for development of therapeutics such as neutralizing antibodies and their validation through preclinical testing. In addition to targeting brain inflammation, the method described here is applicable for peripheral inflammation and provides the opportunity to target important cell–cell interactions and communications that are more specific/selective for inflammatory disorders and improve currently available therapies.