Molecular topology as novel strategy for Alzheimer’s disease drug discovery

PLoS ONE (Impact Factor: 3.23). 03/2014; 9(3):e92750. DOI: 10.1371/journal.pone.0092750
Source: PubMed


In this study, we demonstrate the use of Molecular topology (MT) in an Alzheimer's disease (AD) drug discovery program. MT uses and expands upon the principles governing the molecular connectivity theory of numerically characterizing molecular structures, in the present case, active anti-AD drugs/agents, using topological descriptors to build models. Topological characterization has been shown to embody sufficient molecular information to provide strong correlation to therapeutic efficacy.
We used MT to include multiple bioactive properties that allows for the identification of multi-functional single agent compounds, in this case, the dual functions of β-amyloid (Aβ) -lowering and anti-oligomerization. Using this technology, we identified and designed novel compounds in chemical classes unrelated to current anti-AD agents that exert dual Aβ lowering and anti-Aβ oligomerization activities in animal models of AD. AD is a multifaceted disease with different pathological features.
Our study, for the first time, demonstrated that MT can provide novel strategy for discovering drugs with Aβ lowering and anti-aggregation dual activities for AD.

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Available from: Kenjiro Ono, Mar 31, 2014
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    ABSTRACT: Introduction: Molecular topology (MT) has emerged in recent years as a powerful approach for the in silico generation of new drugs. In the last decade, its application has become more and more popular among the leading research groups in the field of quantitative structure-activity relationships (QSAR) and drug design. This has, in turn, contributed to the rapid development of new techniques and applications of MT in QSAR studies, as well as the introduction of new topological indices. Areas covered: This review collates the main innovative techniques in the field of MT and provides a description of the novel topological indices recently introduced, through an exhaustive recompilation of the most significant works carried out by the leading research groups in the field of drug design and discovery. The objective is to show the importance of MT methods combined with the effectiveness of the descriptors. Expert opinion: Recent years have witnessed a remarkable rise in QSAR methods based on MT and its application to drug design. New methodologies have been introduced in the area such as QSAR multi-target, Markov networks or perturbation methods. Moreover, novel topological indices, such as Bourgas' descriptors and other new concepts as the derivative of a graph or cliques capable to distinguish between conformers, have also been introduced. New drugs have also been discovered, including anticonvulsants, anineoplastics, antimalarials or antiallergics, just to name a few. In the authors' opinion, MT and QSAR have moved from an attractive possibility to representing a foundation stone in the process of drug discovery.
    No preview · Article · Jul 2015 · Expert Opinion on Drug Discovery