ReviewCurrent neuropharmacology2017
Advantages of Structure-Based Drug Design Approaches in Neurological Disorders.
Review in Current neuropharmacology, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.
What it found
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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.
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Who cites it
10 citing papers in PubMed.
- Integrative bioinformatic analysis to identify potential phytochemical candidates for glioblastoma.Heliyon · 2024Article
- Computer-aided discovery of novel SmDHODH inhibitors for schistosomiasis therapy: Ligand-based drug design, molecular docking, molecular dynamic simulations, drug-likeness, and ADMET studies.PLoS neglected tropical diseases · 2024Article
- Design, synthesis, and molecular docking studies ofJournal of Taibah University Medical Sciences · 2024Article
- Screening and Analysis of Possible Drugs Binding to PDGFRα: A Molecular Modeling Study.International journal of molecular sciences · 2023Article
- Integrated Transcriptome Profiling Identifies Prognostic Hub Genes as Therapeutic Targets of Glioblastoma: Evidenced by Bioinformatics Analysis.ACS omega · 2022Article
- Potential bioactive compounds and mechanisms ofFrontiers in aging neuroscience · 2022Article
- From genomes to molecular dynamics - A bottom up approach in extrication of SARS CoV-2 main protease inhibitors.Computational toxicology (Amsterdam, Netherlands) · 2021Article
- An In silico Approach to Identify High Affinity Small Molecule Targeting m-TOR Inhibitors for the Clinical Treatment of Breast CancerAsian Pacific journal of cancer prevention : APJCP · 2019Article
- Editorial: Improving Neuropharmacology using Big Data, Machine Learning and Computational Algorithms.Current neuropharmacology · 2017Article
- Multifaceted Roles of GSK-3 in Cancer and Autophagy-Related Diseases.Oxidative medicine and cellular longevity · 2017Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
4 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
objectiveThe purpose of the review is to portray the theoretical concept on neurological disorders from research data.
backgroundThe freak changes in chemical response of nerve impulse causes neurological disorders. The research evidence of the effort done in the older history suggests that the biological drug targets and their effective feature with responsive drugs could be valuable in promoting the future development of health statistics structure for improved treatment for curing the nervous disorders.
methodsIn this review, we summarized the most iterative theoretical concept of structure based drug design approaches in various neurological disorders to unfathomable understanding of reported information for future drug design and development.
resultsOn the premise of reported information we analyzed the model of theoretical drug designing process for understanding the mechanism and pathology of the neurological diseases which covers the development of potentially effective inhibitors against the biological drug targets. Finally, it also suggests the management and implementation of the current treatment in improving the human health system behaviors.
conclusionWith the survey of reported information we concluded the development strategies of diagnosis and treatment against neurological diseases which leads to supportive progress in the drug discovery.
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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.