Uma abordagem de Medicina de Redes revela mecanismos moleculares e novas drogas candidatas para doenças neuropsiquiátricas, infecciosas e inflamatórias crônicas

Abstract

Millions of scientific articles are available on online platforms, and thousands of new papers are published every day. Reading all these studies is humanly impossible for the individual researcher. Text mining algorithms associated with cognitive computing such as IBM Watson for Drug Discovery are able to read through the biomedical literature and produce knowledge networks containing known connections between terms such as genes, diseases and drugs. Network Medicine uses complex networks to understand how diseases are related through the genes they share. Neuropsychiatric and chronic inflammatory diseases are widely studied and thousands of articles on the molecular basis of these diseases exist in the literature. However, there are still many aspects of these disorders that are not fully understood, and existing drug treatments are often ineffective. Here, knowledge networks of genes, diseases and drugs obtained with Watson for Drug Discovery were analyzed using a Network Medicine framework to (1) evaluate the evolution of knowledge of genes and biological processes related to neuropsychiatric, inflammatory and infectious diseases in the last 30 years, (2) understand the main molecular mechanisms of neuropsychiatric and chronic inflammatory diseases and (3) find drugs already used for other diseases that have the potential to be repositioned for use in neuropsychiatric and chronic inflammatory diseases.