ReviewPharmaceutics2022
New Drug Design Avenues Targeting Alzheimer's Disease by Pharmacoinformatics-Aided Tools.
Review in Pharmaceutics, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
13 citing papers in PubMed.
- Review
- From mechanistic modeling to AI-driven design: computational strategies for targeting the γ-secretase complex.Briefings in bioinformatics · 2026Review
- Design, synthesis and biological evaluation of tacrine-sulphonamide hybrids as a potent acetylcholinesterase inhibitor.RSC advances · 2026Article
- A physics-informed graph neural network to approximate docking-based binding affinity for DYRK2 in Alzheimer's drug repurposing.Scientific reports · 2026Article
- Multi-Target Drug Design in Alzheimer's Disease Treatment: Emerging Technologies, Advantages, Challenges, and Limitations.Pharmacology research & perspectives · 2025Review
- Multi-targeted benzylpiperidine-isatin hybrids: Design, synthesis, biological and in silico evaluation as monoamine oxidases and acetylcholinesterase inhibitors for neurodegenerative disease therapies.Journal of computer-aided molecular design · 2025Article
- Importance of Computer-aided Drug Design in Modern Pharmaceutical Research.Current drug discovery technologies · 2025Review
- The impact of artificial intelligence on drug discovery for neuropsychiatric disorders.EXCLI journal · 2025Review
- Innovative Approaches in Molecular Docking for the Discovery of Novel Inhibitors Against Alzheimer's Disease.Current Alzheimer research · 2025Review
- Resistance Exercise Training as a New Trend in Alzheimer's Disease Research: From Molecular Mechanisms to Prevention.International journal of molecular sciences · 2024Review
- Innovative Therapeutic Strategies in Alzheimer's Disease: A Synergistic Approach to Neurodegenerative Disorders.Pharmaceuticals (Basel, Switzerland) · 2024Review
- Computational studies for pre-evaluation of pharmacological profile of gut microbiota-produced gliclazide metabolites.Frontiers in pharmacology · 2024Article
- Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
16 authors.
Funding
Abstract
Neurodegenerative diseases (NDD) have been of great interest to scientists for a long time due to their multifactorial character. Among these pathologies, Alzheimer's disease (AD) is of special relevance, and despite the existence of approved drugs for its treatment, there is still no efficient pharmacological therapy to stop, slow, or repair neurodegeneration. Existing drugs have certain disadvantages, such as lack of efficacy and side effects. Therefore, there is a real need to discover new drugs that can deal with this problem. However, as AD is multifactorial in nature with so many physiological pathways involved, the most effective approach to modulate more than one of them in a relevant manner and without undesirable consequences is through polypharmacology. In this field, there has been significant progress in recent years in terms of pharmacoinformatics tools that allow the discovery of bioactive molecules with polypharmacological profiles without the need to spend a long time and excessive resources on complex experimental designs, making the drug design and development pipeline more efficient. In this review, we present from different perspectives how pharmacoinformatics tools can be useful when drug design programs are designed to tackle complex diseases such as AD, highlighting essential concepts, showing the relevance of artificial intelligence and new trends, as well as different databases and software with their main results, emphasizing the importance of coupling wet and dry approaches in drug design and development processes.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.