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Molecules 2016, 21(7), 927; doi:10.3390/molecules21070927

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

1
iMed.ULisboa, Research Institute for Medicines, Faculdade de Farmácia da Universidade de Lisboa, Av. Prof. Gama Pinto, 1649-003 Lisboa, Portugal
2
Laboratório de Química Farmacêutica, Faculdade de Farmácia da Universidade de Coimbra, Pólo das Ciências da Saúde-Azinhaga de Santa Comba, 3000-548 Coimbra, Portugal
3
Center for Neurosciences and Cell Biology, Universidade de Coimbra, Rua Larga-Faculdade de Medicina, Pólo I, 3004-504 Coimbra, Portugal
*
Author to whom correspondence should be addressed.
Academic Editor: James W. Gauld
Received: 9 May 2016 / Revised: 11 July 2016 / Accepted: 12 July 2016 / Published: 16 July 2016
(This article belongs to the Special Issue Computational Design: A New Approach to Drug and Molecular Discovery)
View Full-Text   |   Download PDF [2768 KB, uploaded 16 July 2016]   |  

Abstract

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. View Full-Text
Keywords: cancer; proteasome inhibitors; computer-aided drug design; virtual screening; molecular docking; pharmacophore model cancer; proteasome inhibitors; computer-aided drug design; virtual screening; molecular docking; pharmacophore model
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Guedes, R.A.; Serra, P.; Salvador, J.A.R.; Guedes, R.C. Computational Approaches for the Discovery of Human Proteasome Inhibitors: An Overview. Molecules 2016, 21, 927.

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