ReviewMolecules (Basel, Switzerland)2023
Computer-Aided Drug Design towards New Psychotropic and Neurological Drugs.
Review in Molecules (Basel, Switzerland), 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 16 papers.
What it found
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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.
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Who cites it
16 citing papers in PubMed.
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- Potential of Small Molecule TAAR-1 Agonists for the Therapy of Neurodegenerative Psychosis: A Medicinal Chemistry Perspective.Mini reviews in medicinal chemistry · 2026Review
- Machine Learning Meets Physics-based Modeling: A Mass-spring System to Predict Protein-ligand Binding Affinity.Current medicinal chemistry · 2025Review
- Advances and challenges in drug design against dental caries: Application ofJournal of pharmaceutical analysis · 2025Review
- Computer-Aided Drug Design and Drug Discovery.Pharmaceuticals (Basel, Switzerland) · 2025Article
- Novel insights from comprehensive analysis: The role of cuproptosis and peripheral immune infiltration in Alzheimer's disease.PloS one · 2025Article
- The impact of artificial intelligence on drug discovery for neuropsychiatric disorders.EXCLI journal · 2025Review
- [Experiences and subjective transformations: suffering and coercion in the use of psychotropic drugs in psychiatric treatment in Chile].Salud colectiva · 2024Article
- Recent Advances in the Discovery of SIRT1/2 Inhibitors via Computational Methods: A Perspective.Pharmaceuticals (Basel, Switzerland) · 2024Review
- Discovery of a Novel Chemo-Type for TAAR1 Agonism via Molecular Modeling.Molecules (Basel, Switzerland) · 2024Article
- Updating the Pharmacological Effects of α-Mangostin Compound and Unraveling Its Mechanism of Action: A Computational Study Review.Drug design, development and therapy · 2024Review
- Advances in Developing Small Molecule Drugs for Alzheimer's Disease.Current Alzheimer research · 2024Review
- Computational Drug Design Strategies for Fighting the COVID-19 Pandemic.Advances in experimental medicine and biology · 2024Article
- LDS-CNN: a deep learning framework for drug-target interactions prediction based on large-scale drug screening.Health information science and systems · 2023Article
- Novel Thiazole-Based SIRT2 Inhibitors Discovered via Molecular Modelling Studies and Enzymatic Assays.Pharmaceuticals (Basel, Switzerland) · 2023Article
- Molecular docking analysis of natural compounds as TNF-α inhibitors for Crohn's disease management.Bioinformation · 2023Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
3 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Central nervous system (CNS) disorders are a therapeutic area in drug discovery where demand for new treatments greatly exceeds approved treatment options. This is complicated by the high failure rate in late-stage clinical trials, resulting in exorbitant costs associated with bringing new CNS drugs to market. Computer-aided drug design (CADD) techniques minimise the time and cost burdens associated with drug research and development by ensuring an advantageous starting point for pre-clinical and clinical assessments. The key elements of CADD are divided into ligand-based and structure-based methods. Ligand-based methods encompass techniques including pharmacophore modelling and quantitative structure activity relationships (QSARs), which use the relationship between biological activity and chemical structure to ascertain suitable lead molecules. In contrast, structure-based methods use information about the binding site architecture from an established protein structure to select suitable molecules for further investigation. In recent years, deep learning techniques have been applied in drug design and present an exciting addition to CADD workflows. Despite the difficulties associated with CNS drug discovery, advances towards new pharmaceutical treatments continue to be made, and CADD has supported these findings. This review explores various CADD techniques and discusses applications in CNS drug discovery from 2018 to November 2022.
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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 Socratic graph.