Computational Approaches for the Discovery of Human Proteasome Inhibitors: An Overview

• Autor(a) principal: Guedes, Romina A.
• Data de Publicação: 2016
• Outros Autores: Serra, Patrícia, Salvador, Jorge A. R., Guedes, Rita C.
• Tipo de documento: Artigo
• Idioma: eng
• Título da fonte: Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
• Texto Completo: http://hdl.handle.net/10316/108709; https://doi.org/10.3390/molecules21070927
• topic: cancer; proteasome inhibitors; computer-aided drug design; virtual screening; molecular docking; pharmacophore model; Antineoplastic Agents; Binding Sites; Catalytic Domain; Drug Design; Humans; Molecular Conformation; Molecular Docking Simulation; Molecular Dynamics Simulation; Molecular Structure; Proteasome Endopeptidase Complex; Proteasome Inhibitors; Protein Binding; Computer Simulation; Drug Discovery

Proteasome emerged as an important target in recent pharmacological research due to its pivotal role in degrading proteins in the cytoplasm and nucleus of eukaryotic cells, regulating a wide variety of cellular pathways, including cell growth and proliferation, apoptosis, DNA repair, transcription, immune response, and signaling processes. The last two decades witnessed intensive efforts to discover 20S proteasome inhibitors with significant chemical diversity and efficacy. To date, the US FDA approved to market three proteasome inhibitors: bortezomib, carfilzomib, and ixazomib. However new, safer and more efficient drugs are still required. Computer-aided drug discovery has long being used in drug discovery campaigns targeting the human proteasome. The aim of this review is to illustrate selected in silico methods like homology modeling, molecular docking, pharmacophore modeling, virtual screening, and combined methods that have been used in proteasome inhibitors discovery. Applications of these methods to proteasome inhibitors discovery will also be presented and discussed to raise improvements in this particular field.