ArticleBMC chemistry2023
In-silico activity prediction and docking studies of some flavonol derivatives as anti-prostate cancer agents based on Monte Carlo optimization.
Article in BMC chemistry, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.
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Who cites it
10 citing papers in PubMed, 18 citations in OpenAlex.
- Quantitative Structure-Activity Relationship Approaches for Exploring the Anticancer Potential of Flavonoids.Chemistry & biodiversity · 2026Review
- A green tandem cyclization approach to substituted 2-aminothiazolesRSC advances · 2026Article
- Artificial intelligence in drug discovery from advanced molecular representation to pipeline applications.Frontiers in bioinformatics · 2026Review
- Synthesis, Characterization, and Screening Anticancer-Antibiofilm Activities of Theophylline Derivatives Containing CFBiology · 2025Article
- Using the Coefficient of Conformism of a Correlative Prediction in Simulation of Cardiotoxicity.Toxics · 2025Article
- Article
- Simulation of the Long-Term Toxicity Towards Bobwhite Quail (Journal of xenobiotics · 2024Article
- Monte Carlo Optimization Method Based QSAR Modeling of Placental Barrier Permeability.Pharmaceutical research · 2024Article
- In Silico and In Vivo Evaluation of the Maqui Berry (Metabolites · 2023Article
- The System of Self-Consistent Models: The Case of Henry's Law Constants.Molecules (Basel, Switzerland) · 2023Article
Corrections and comments
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Authors and funding
5 authors at 4 institutions in 2 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
The QSAR models are employed to predict the anti-proliferative activity of 81 derivatives of flavonol against prostate cancer using the Monte Carlo algorithm based on the index of ideality of correlation (IIC) criterion. CORAL software is employed to design the QSAR models. The molecular structures of flavonols are demonstrated using the simplified molecular input line entry system (SMILES) notation. The models are developed with the hybrid optimal descriptors i.e. using both SMILES and hydrogen-suppressed molecular graph (HSG). The QSAR model developed for split 3 is selected as a prominent model ([Formula: see text]= 0.727, [Formula: see text]= 0.628, [Formula: see text]= 0.642, and [Formula: see text]=0.615). The model is interpreted mechanistically by identifying the characteristics responsible for the promoter of the increase or decrease. The structural attributes as promoters of increase of pIC
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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.