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. 2022 Apr 28;15(5):545.
doi: 10.3390/ph15050545.

Unveiling the Multitarget Anti-Alzheimer Drug Discovery Landscape: A Bibliometric Analysis

Anna Sampietro  1 , F Javier Pérez-Areales  2 , Paula Martínez  1 , Elsa M Arce  1 , Carles Galdeano  3 , Diego Muñoz-Torrero  1
Affiliations

Unveiling the Multitarget Anti-Alzheimer Drug Discovery Landscape: A Bibliometric Analysis

Anna Sampietro et al. Pharmaceuticals (Basel). .

Abstract

Multitarget anti-Alzheimer agents are the focus of very intensive research. Through a comprehensive bibliometric analysis of the publications in the period 1990-2020, we have identified trends and potential gaps that might guide future directions. We found that: (i) the number of publications boomed by 2011 and continued ascending in 2020; (ii) the linked-pharmacophore strategy was preferred over design approaches based on fusing or merging pharmacophores or privileged structures; (iii) a significant number of in vivo studies, mainly using the scopolamine-induced amnesia mouse model, have been performed, especially since 2017; (iv) China, Italy and Spain are the countries with the largest total number of publications on this topic, whereas Portugal, Spain and Italy are the countries in whose scientific communities this topic has generated greatest interest; (v) acetylcholinesterase, β-amyloid aggregation, oxidative stress, butyrylcholinesterase, and biometal chelation and the binary combinations thereof have been the most commonly pursued, while combinations based on other key targets, such as tau aggregation, glycogen synthase kinase-3β, NMDA receptors, and more than 70 other targets have been only marginally considered. These results might allow us to spot new design opportunities based on innovative target combinations to expand and diversify the repertoire of multitarget drug candidates and increase the likelihood of finding effective therapies for this devastating disease.

Keywords: Alzheimer’s disease; animal models; hybrids; multifactorial diseases; multitarget drug design; multitarget drugs; polypharmacology; target combinations.

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Conflict of interest statement

The authors declare no conflict of interest.

Figures

Figure 1
Figure 1
Design strategies used in the framework combination approach: linked hybrid ((A); the linker is colored in orange), fused hybrid (B); merged hybrid (C). The elements in different colors represent different structural fragments within each pharmacophore.
Figure 2
Figure 2
Bibliographic search workflow used for the bibliometric analysis.
Figure 3
Figure 3
Total number (A) and evolution of the annual number (B) of original research articles (green bar and line), books and reviews (blue bar and line) and patents (orange bar and line) dealing with multitarget anti-AD compounds in the period 1990–2020.
Figure 4
Figure 4
Strategies followed in the design of multitarget anti-AD compounds in the period 1990–2020.
Figure 5
Figure 5
Number of in vitro and in vivo studies (A); type of animals (B) and specific models (C) used for the pharmacological evaluation of multitarget anti-AD compounds in the period 1990–2020.
Figure 6
Figure 6
(A) Geographical origin of the articles on multitarget anti-AD compounds in the period 1990–2020, considering the total number of published articles; (B) evolution of the total number of original research articles on multitarget anti-AD compounds coming from the top five contributor countries in the period 1990–2020; (C) geographical origin of the articles on multitarget anti-AD compounds in the period 1990–2020, considering the total number of articles normalized by the number of researchers in each country.
Figure 7
Figure 7
Biological targets that have been pursued in 5 or more research articles on multitarget anti-AD compounds in the period 1990–2020 and number of articles in which they have been considered.
Figure 8
Figure 8
Combinations of biological targets that have been pursued in 10 or more research articles on multitarget anti-AD compounds in the period 1990–2020 and number of articles in which they have been considered.
Figure 9
Figure 9
Mapping of the binary combinations of biological targets that have been pursued in multitarget anti-AD compounds in the period 1990–2020. For the abbreviations of the names of the biological targets, see Table 1. Individual targets and binary combinations between targets appear as nodes and edges connecting each pair of nodes, respectively. The size of the nodes and the thickness of the edges are proportional to the number of times that each individual target appears in a binary combination and to the number of times that each binary target combination has been pursued, respectively. Color codes have been used to distinguish ranges of frequency in targets and target combinations: gradient bar chart (down), from lower frequency (left) to higher frequency (right).
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