Schistosomiasis drug discovery in the era of automation and artificial intelligence
| dc.creator | Moreira Filho, José Teófilo | |
| dc.creator | Silva, Arthur de Carvalho e | |
| dc.creator | Dantas, Rafael Ferreira | |
| dc.creator | Gomes, Bárbara Figueira | |
| dc.creator | Souza Neto, Lauro Ribeiro de | |
| dc.creator | Brandão Neto, José | |
| dc.creator | Owens, Raymond J. | |
| dc.creator | Furnham, Nicholas | |
| dc.creator | Neves, Bruno Junior | |
| dc.creator | Silva Junior, Floriano Paes | |
| dc.date.accessioned | 2024-09-12T14:16:24Z | |
| dc.date.available | 2024-09-12T14:16:24Z | |
| dc.date.issued | 2021 | |
| dc.description.abstract | Schistosomiasis is a parasitic disease caused by trematode worms of the genus Schistosoma and affects over 200 million people worldwide. The control and treatment of this neglected tropical disease is based on a single drug, praziquantel, which raises concerns about the development of drug resistance. This, and the lack of efficacy of praziquantel against juvenile worms, highlights the urgency for new antischistosomal therapies. In this review we focus on innovative approaches to the identification of antischistosomal drug candidates, including the use of automated assays, fragment based screening, computer-aided and artificial intelligence-based computational methods. We highlight the current developments that may contribute to optimizing research outputs and lead to more effective drugs for this highly prevalent disease, in a more cost-effective drug discovery endeavor. | |
| dc.identifier.citation | MOREIRA-FILHO, José T. et al. Schistosomiasis drug discovery in the era of automation and artificial intelligence. Frontiers in Immunology, Lausanne, v. 12, e642383, 2021. DOI: 10.3389/fimmu.2021.642383. Disponível em: https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8203334/. Acesso em: 6 set. 2024. | |
| dc.identifier.doi | 10.3389/fimmu.2021.642383 | |
| dc.identifier.issn | e- 1664-3224 | |
| dc.identifier.uri | http://repositorio.bc.ufg.br//handle/ri/25497 | |
| dc.language.iso | eng | |
| dc.publisher.country | Suica | |
| dc.publisher.department | Faculdade de Farmácia - FF (RMG) | |
| dc.rights | Acesso Aberto | |
| dc.rights.uri | http://creativecommons.org/licenses/by-nc-nd/4.0/ | |
| dc.subject | Schistosomiasis | |
| dc.subject | Drug discovery | |
| dc.subject | Artificial intelligence | |
| dc.subject | Fragment-based drug discovery | |
| dc.subject | Phenotypic screening | |
| dc.subject | Target-based screening | |
| dc.title | Schistosomiasis drug discovery in the era of automation and artificial intelligence | |
| dc.type | Artigo |