ArticleInternational journal of molecular sciences2016
Structural Investigation for Optimization of Anthranilic Acid Derivatives as Partial FXR Agonists by in Silico Approaches.
Article in International journal of molecular sciences, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.
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Who cites it
7 citing papers in PubMed.
- The Molecular Mechanism of Farnesoid X Receptor Alleviating Glucose Intolerance in Turbot (Cells · 2024Article
- Development and Validation of an Explainable Machine Learning-Based Prediction Model for Drug-Food Interactions from Chemical Structures.Sensors (Basel, Switzerland) · 2023Article
- Fast Identification of Adverse Drug Reactions (ADRs) of Digestive and Nervous Systems of Organic Drugs by In Silico Models.Molecules (Basel, Switzerland) · 2021Article
- Farnesoid X receptor (FXR): Structures and ligands.Computational and structural biotechnology journal · 2021Review
- Identfication of Potent LXRβ-Selective Agonists without LXRα Activation by In Silico Approaches.Molecules (Basel, Switzerland) · 2018Article
- Systematic Understanding of Mechanisms of a Chinese Herbal Formula in Treatment of Metabolic Syndrome by an Integrated Pharmacology Approach.International journal of molecular sciences · 2016Article
- Data Analysis in Chemistry and Bio-Medical Sciences.International journal of molecular sciences · 2016Article
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6 authors.
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Abstract
In this paper, a three level in silico approach was applied to investigate some important structural and physicochemical aspects of a series of anthranilic acid derivatives (AAD) newly identified as potent partial farnesoid X receptor (FXR) agonists. Initially, both two and three-dimensional quantitative structure activity relationship (2D- and 3D-QSAR) studies were performed based on such AAD by a stepwise technology combined with multiple linear regression and comparative molecular field analysis. The obtained 2D-QSAR model gave a high predictive ability (R²(train) = 0.935, R²(test) = 0.902, Q²(LOO) = 0.899). It also uncovered that number of rotatable single bonds (b_rotN), relative negative partial charges (RPC(-)), oprea's lead-like (opr_leadlike), subdivided van der Waal's surface area (SlogP_VSA2) and accessible surface area (ASA) were important features in defining activity. Additionally, the derived3D-QSAR model presented a higher predictive ability (R²(train) = 0.944, R²(test) = 0.892, Q²(LOO) = 0.802). Meanwhile, the derived contour maps from the 3D-QSAR model revealed the significant structural features (steric and electronic effects) required for improving FXR agonist activity. Finally, nine newly designed AAD with higher predicted EC50 values than the known template compound were docked into the FXR active site. The excellent molecular binding patterns of these molecules also suggested that they can be robust and potent partial FXR agonists in agreement with the QSAR results. Overall, these derived models may help to identify and design novel AAD with better FXR agonist activity.
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