ProtoQSAR’s study on computational methods against alzheimer has been published
The article of ProtoQSAR entitled “Recent advances in computational approaches for designing potential anti-Alzheimer’s agents” has just been published in the last book of the series “Neuromethods” by Springer.
This volume describes different computational methods encompassing ligand-based approaches and structure-based approaches combined with virtual screening for the design of anti-Alzheimer drugs. Following the “Neuromethods series” style, chapters include the kind of detail and key advice from the specialists needed to understand the last novelties on the field.
Alzheimer disease (AD) is one of the most challenging human diseases, firstly because of its enormous incidence in older people worldwide and secondly because there is currently not an efficient treatment available. Several symptomatic drugs have been commercialized but there is a huge need to discover compounds able to target the complex mechanisms that affect the brain leading to AD.
In the ProtoQSAR review, we have reported a selection of studies related to the discovery or design of novel compounds with potential therapeutic efficacy in the treatment of AD through the application of computational approaches. Molecular docking, QSAR predictive models, pharmacophore approaches,and MD simulations have been successfully applied to find new hits in virtual screening campaigns or to optimize chemical series and propose new potential leads as drugs in AD treatment. We have focused on three enzymes that are potential targets for the treatment of AD, namely, acetylcholinesterase (AChE), glycogen synthase kinase-3 (GSK-3),and β-amyloid cleaving enzyme 1 (BACE1).
Reference: Recent advances in computational approaches for designing potential anti-alzheimer’s agents.Sergi Gómez-Ganau, Jesús Vicente de Julián-Ortiz, Rafael Gozalbes. Springer Book “Computational Modeling of Drugs Against Alzheimer’s Disease” Chapter 2, Pages 25-59 (Series: Neuromethods, Kunal Roy (ed.), Vol. 132, DOI 10.1007/978-1-4939-7404-7_2, © Springer Science+Business Media LLC 2018 ISBN 978-1-4939-7404-7)