Drug repositioning for psychiatric and neurological disorders through a network medicine approach

Autor(es)

Dias, Thomaz Luscher ^[1] ; Schuch, Viviane ^[2] ; Baleeiro Beltrao-Braga, Patricia Cristina ^{[3, 4]} ; Martins-de-Souza, Daniel ^{[5, 6, 7, 8]} ; Brentani, Helena Paula ^{[9, 10]} ; Franco, Gloria Regina ^[1] ; Nakaya, Helder Imoto ^{[2, 4]}

Afiliação do(s) autor(es)

^[1] Univ Fed Minas Gerais, Inst Biol Sci, Dept Biochem & Immunol, Belo Horizonte, MG - Brazil

^[2] Univ Sao Paulo, Sch Pharmaceut Sci, Dept Clin & Toxicol Anal, Sao Paulo - Brazil

^[3] Univ Sao Paulo, Inst Biomed Sci, Dept Microbiol, Sao Paulo - Brazil

^[4] Sci Platform Pasteur USP, Sao Paulo - Brazil

^[5] Conselho Nacl Desenvolvimento Cient & Tecnol, Inst Nacl Biomarcadores Neuropsiquiatria, Sao Paulo - Brazil

^[6] Univ Estadual Campinas, Inst Biol, Dept Biochem & Tissue Biol, Lab Neuroprote, Campinas - Brazil

^[7] Univ Estadual Campinas, Expt Med Res Cluster EMRC, Campinas - Brazil

^[8] DOr Inst Reasearch & Educ IDOR, Sao Paulo - Brazil

^[9] Natl Inst Dev Psychiat Children & Adolescents INP, Sao Paulo - Brazil

^[10] Univ Sao Paulo, Hosp Clin HCFMUSP, Fac Med, Inst Psiquiatria, Sao Paulo - Brazil

• Tipo de documento: Artigo Científico
• Fonte: TRANSLATIONAL PSYCHIATRY; v. 10, n. 1 MAY 12 2020.
• Citações Web of Science: 0

Resumo

Psychiatric and neurological disorders (PNDs) affect millions worldwide and only a few drugs achieve complete therapeutic success in the treatment of these disorders. Due to the high cost of developing novel drugs, drug repositioning represents a promising alternative method of treatment. In this manuscript, we used a network medicine approach to investigate the molecular characteristics of PNDs and identify novel drug candidates for repositioning. Using IBM Watson for Drug Discovery, a powerful machine learning text-mining application, we built knowledge networks containing connections between PNDs and genes or drugs mentioned in the scientific literature published in the past 50 years. This approach revealed several drugs that target key PND-related genes, which have never been used to treat these disorders to date. We validate our framework by detecting drugs that have been undergoing clinical trial for treating some of the PNDs, but have no published results in their support. Our data provides comprehensive insights into the molecular pathology of PNDs and offers promising drug repositioning candidates for follow-up trials. (AU)

• Processo FAPESP: 17/25588-1 - Da compreensão básica a biomarcadores clínicos para a esquizofrenia: um estudo multidisciplinar centrado na neuroproteômica
• Beneficiário: Daniel Martins-de-Souza
• Modalidade de apoio: Auxílio à Pesquisa - Temático
• Processo FAPESP: 18/03673-0 - Efeitos bioquímicos de canabinóides em oligodendrócitos: implicações para a esquizofrenia
• Beneficiário: Daniel Martins-de-Souza
• Modalidade de apoio: Auxílio à Pesquisa - Regular
• Processo FAPESP: 14/10068-4 - EMU concedido no processo 13/08711-3: espectrômetro de massas Waters SYNAPT G2-Si HDMs + nanoACQUITY UPLC
• Beneficiário: Daniel Martins-de-Souza
• Modalidade de apoio: Auxílio à Pesquisa - Programa Equipamentos Multiusuários
• Processo FAPESP: 19/00098-7 - EMU concedido no processo 2017/25588-1: cromatógrafo Acquity UPLC I-Class
• Beneficiário: Daniel Martins-de-Souza
• Modalidade de apoio: Auxílio à Pesquisa - Programa Equipamentos Multiusuários
• Processo FAPESP: 18/16748-8 - Investigação da ação do zika vírus em células do sistema nervoso central: modelagem da infecção em astrócitos humanos derivados de células pluripotentes induzidas
• Beneficiário: Patricia Cristina Baleeiro Beltrão Braga
• Modalidade de apoio: Auxílio à Pesquisa - Regular