Unveiling the Multitarget Anti-Alzheimer Drug Discovery Landscape: A Bibliometric Analysis
Abstract
:1. Introduction
- (i)
- There is a clear feeling that the number of publications on multitarget anti-AD agents has steadily increased over the past one or two decades, especially since the publication in 2008 of a seminal review article by Cavalli, Bolognesi, Melchiorre, and coworkers [27], but the actual magnitude and evolution of the number of publications on this topic over the years has not been assessed so far.
- (ii)
- A second, quite general notion is that most multitarget anti-AD compounds are designed to hit AChE and another target of interest [28]. Indeed, a large number of multitarget compounds feature pharmacophoric moieties of the approved AChE inhibitors [29,30,31,32], even though publications on multitarget anti-AD agents based on other pharmacophores, especially naturally occurring scaffolds such as β-carbolines [33], naphthoquinones and anthraquinones [34], or chalcones [35], just to name a few of those recently reviewed, are continuously appearing. Apart from AChE, other targets and pathogenic mechanisms that, intuitively, seem to have been commonly addressed when designing multitarget anti-AD compounds are glutamante NMDA receptors [36,37], β-amyloid and tau aggregation [38,39], glycogen synthase kinase 3β (GSK-3β) [40], biometal dyshomeostasis [41], monoamine oxidases (MAOs) [42], or oxidative stress [43].
- (iii)
- It is usually assumed that the linked-pharmacophore strategy is the most popular design strategy, likely because AChE is thought to be the most commonly pursued target in multitarget anti-AD drug design and it is one of those proteins with binding sites buried at the bottom of a deep cavity.
2. Results and Discussion
2.1. Bibliographic Search
2.2. Evolution of the Number of Publications on Multitarget Anti-Alzheimer Compounds in the Period 1990–2020
2.3. Design Strategies of Multitarget Anti-Alzheimer Compounds in the Period 1990–2020
2.4. Pharmacological Profiling of Multitarget Anti-Alzheimer Compounds in the Period 1990–2020
2.5. Geographical Origin of the Works on Multitarget Anti-Alzheimer Compounds in the Period 1990–2020
2.6. Biological Targets and Target Combinations Hit by Multitarget Anti-Alzheimer Compounds in the Period 1990–2020
3. Materials and Methods
3.1. Bibliographic Search
3.2. Creation of the Gephi Graph
4. Conclusions
- It was not until one decade ago (around 2011) that the number of publications on this topic experienced an explosive growth. This upward growth remained at the end of the studied period.
- It is very likely that, because of their ease of design and synthesis and the appropriateness to hit targets with binding sites that extend along deep gorges, commonly pursued in multitarget anti-AD compounds such as AChE, linked hybrids are more common than the smaller-sized fused or merged hybrids and privileged structures, even though the latter should be preferable in terms of better physicochemical and pharmacokinetic properties.
- In addition to the mandatory in vitro evaluation towards the multiple targets, a significant number of in vivo studies have been performed to assess the efficacy of multitarget anti-AD compounds, especially from 2017 (72 in vivo studies out of a total of 100 in the whole period), indicating a clear willingness to advance these candidates to preclinical and clinical testing. By far, the model of amnesia induced by scopolamine in wild-type mice and, to a minor extent, in rats, has been the most widely used animal model, which enables the evaluation of behavioral effects but not the impact on the underlying disease mechanisms. When affordable, other models which better recapitulate the different pathologies of AD, e.g., suitable transgenic animals, should be used to more consistently assess the in vivo efficacy of the multitarget compounds.
- Within the overall studied period, China has been the major contributor to the publications on this topic. Italy, Spain, India, the USA, France, Portugal, Poland, Iran, and the Czech Republic complete the list of the top ten most contributing countries. At the end of the period, China and India were clearly the countries with a greatest productivity. When the number of publications was normalized by the number of researchers of each country, we found that Portugal, Spain, and Italy are the countries in whose scientific communities multitarget anti-AD agents have attracted more interest, followed by the Czech Republic, Iran, India, Poland, China, France, Brazil, Germany, and the USA.
- AChE is clearly the most commonly pursued biological target in multitarget anti-AD compounds, appearing in up to 71.2% of all the research articles on this topic. In the list of the top ten most common targets, we also found Aβ aggregation (56.3%), oxidative stress (50.0%), BChE (47.9%), metal chelation (26.7%), MAO-B (15.6%), BACE-1 (10.1%), MAO-A (8.5%), GSK-3β (4.0%), and tau aggregation (3.7%). Eighty other different targets, including different subtypes and isoforms of some receptors and enzymes, were also pursued in the multitarget compounds developed in the studied period, but most of them only very sporadically.
- Paralleling the frequency at which individual biological targets have been considered in multitarget anti-AD drug design, the binary combinations of the most common targets have been the most widely pursued. In the list of the top ten binary target combinations, we found AChE–BChE (in 44.1% of research articles), AChE–Aβ aggregation (38.7%), AChE–oxidative stress (32.8%), Aβ aggregation–oxidative stress (31.2%), BChE–Aβ aggregation (24.9%), BChE–oxidative stress (20.6%), oxidative stress–metal chelation (20.3%), Aβ aggregation–metal chelation (19.9%), AChE–metal chelation (15.0%), and AChE–MAO-B (11.6%).
Supplementary Materials
Author Contributions
Funding
Institutional Review Board Statement
Informed Consent Statement
Data Availability Statement
Acknowledgments
Conflicts of Interest
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Abbreviation | Target | Abbreviation | Target |
---|---|---|---|
A1/A2 | adenosine A1/A2 receptor | JNK1-3 | c-Jun N-terminal kinases 1-3 |
AChE | acetylcholinesterase | KEAP1 | Kelch-like ECH-associated protein 1 |
Aβ aggr | β-amyloid aggregation | LOX1/5/15 | Lipoxygenase 1/5/15 |
α2 | α2 adrenergic receptor | LTP | long-term potentiation |
α7-nAChR | α7 nicotinic receptor | M1 | muscarinic M1 receptor |
α-syn | α-synuclein aggregation | MAO-A/MAO-B | monoamine oxidase A/B |
BACE-1 | β-secretase | miR-15b | microRNA 15b |
BChE | butyrylcholinesterase | MMP2 | matrix metalloproteinase-2 |
Biometal | biometals chelation | m-nAChR | muscle-type nicotinic receptor |
CA1/CA2 | carbonic anhydrase 1/2 | MPO | myeloperoxidase |
Casp1/Casp3 | caspase 1/3 | MT | microtubule |
CaV | voltage-gated calcium channel | NMDA | N-methyl-D-aspartate receptor |
CB1/CB2 | cannabinoid receptor 1/2 | NO | nitric oxide release |
CDK1/CDK5 | cyclin-dependent kinase 1/5 | NOS | nitric oxide synthase |
CK1 | casein kinase 1 | NRF2 | nuclear factor-erythroid 2 p45-related factor 2 |
CLK1/3 | cdc2-like kinase 1/3 | OS | oxidative stress |
COX1/COX2 | cyclooxygenase 1/2 | P2X7 | purinergic P2X7 receptors |
D2 | dopamine D2 receptor | PARP-1 | poly(ADP-ribose) polymerase 1 |
DYRK1/2 | dual-specificity tyrosine phosphory-lation-regulated kinase 1/2 | PDE4/5/9/10 | phosphodiesterases 4/5/9/10 |
ERK | extracellular signal-regulated kinase | PHOS | serine/threonine phosphatases |
ERα/ERβ | estrogen receptor α/β | PIM1 | Pim1 kinase |
FAAH | fatty acid amide hydrolase | PKC | protein kinase C |
FYN | Fyn kinase | POP | prolyl oligopeptidase |
GSK-3α/3β | glycogen synthase kinase 3α/3β | QR | quinone reductase |
H1/H3 | histamine H1/H3 receptor | ROCK1/2 | Rho-associated coiled-coil kinase 1/2 |
5-HT1/2/4/6/7 | serotonin receptor 1/2/4/6/7 | S1 | sigma-1 receptor |
HDAC1-7,9 | histone deacetylase 1-7,9 | SERT | serotonin reuptake transporter |
HIF1 | hypoxia-inducible factor 1 | SSAO/VAP-1 | semicarbazide-sensitive amine oxidase/vascular adhesion protein-1 |
HSP27 | heat shock protein 27 | TAU | tau aggregation |
IDO1 | indoleamine 2,3-dioxygenase 1 |
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Sampietro, A.; Pérez-Areales, F.J.; Martínez, P.; Arce, E.M.; Galdeano, C.; Muñoz-Torrero, D. Unveiling the Multitarget Anti-Alzheimer Drug Discovery Landscape: A Bibliometric Analysis. Pharmaceuticals 2022, 15, 545. https://doi.org/10.3390/ph15050545
Sampietro A, Pérez-Areales FJ, Martínez P, Arce EM, Galdeano C, Muñoz-Torrero D. Unveiling the Multitarget Anti-Alzheimer Drug Discovery Landscape: A Bibliometric Analysis. Pharmaceuticals. 2022; 15(5):545. https://doi.org/10.3390/ph15050545
Chicago/Turabian StyleSampietro, Anna, F. Javier Pérez-Areales, Paula Martínez, Elsa M. Arce, Carles Galdeano, and Diego Muñoz-Torrero. 2022. "Unveiling the Multitarget Anti-Alzheimer Drug Discovery Landscape: A Bibliometric Analysis" Pharmaceuticals 15, no. 5: 545. https://doi.org/10.3390/ph15050545
APA StyleSampietro, A., Pérez-Areales, F. J., Martínez, P., Arce, E. M., Galdeano, C., & Muñoz-Torrero, D. (2022). Unveiling the Multitarget Anti-Alzheimer Drug Discovery Landscape: A Bibliometric Analysis. Pharmaceuticals, 15(5), 545. https://doi.org/10.3390/ph15050545