ArticleTrends in pharmacological sciences2019
Artificial Intelligence: A Novel Approach for Drug Discovery.
Article in Trends in pharmacological sciences, 2019. 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.
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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.
- Obstacles behind the innovation- a peek into Artificial intelligence in the field of orthodontics - A Literature review.The Saudi dental journal · 2024Review
- Machine learning assisted exploration of the influential parameters on the PLGA nanoparticles.Scientific reports · 2024Article
- Drawbacks of Artificial Intelligence and Their Potential Solutions in the Healthcare Sector.Biomedical materials & devices (New York, N.Y.) · 2023Review
- Developing an artificial intelligence method for screening hepatotoxic compounds in traditional Chinese medicine and Western medicine combination.Chinese medicine · 2022Article
- Review
- The concept of justifiable healthcare and how big data can help us to achieve it.BMC medical informatics and decision making · 2021Review
- Statistics for the analysis of molecular dynamics simulations: providing P values for agonist-dependent GPCR activation.Scientific reports · 2020Article
- Diagnostic capacity of skin tumor artificial intelligence-assisted decision-making software in real-world clinical settings.Chinese medical journal · 2020Article
- Machine Learning Force Fields and Coarse-Grained Variables in Molecular Dynamics: Application to Materials and Biological Systems.Journal of chemical theory and computation · 2020Review
- DROIDS 3.0-Detecting Genetic and Drug Class Variant Impact on Conserved Protein Binding Dynamics.Biophysical journal · 2020Article
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Authors and funding
3 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Molecular dynamics (MD) simulations can mechanistically explain receptor function. However, the enormous data sets that they may imply can be a hurdle. Plante and colleagues (Molecules, 2019) recently described a machine learning approach to the analysis of MD simulations. The approach successfully classified ligands and identified functional receptor motifs and thus it seems promising for mechanism-based drug discovery.
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31279568What OpenQuestion holds
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.