3D-QSAR study of corticotropin-releasing factor 1 antagonists and pharmacophore-based drug design

Ye, Yingda; Liao, Qinghua; Wei, Jing; Gao, Qingzhi

doi:10.1016/j.neuint.2009.09.008

Cited by 10 publications

(2 citation statements)

References 40 publications

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“…Among all of these models, Hypogen1, composed of HBA and 4H chemical features, had the lowest total cost (91.20), highest cost difference (69.50), lowest RMS (0.50), best correlation coefficient (0.99), and highest fit value (11.89). Cost analysis was applied to determine the statistical significance of the Hypogen models (Ye et al, 2010). The cost difference of Hypogen1 (69.4973), the difference between the null cost and total cost indicated more than 90 instances of statistical significance of achieving an acceptable pharmacophore (Kavitha et al, 2015;Kumar et al, 2015).…”

Section: Construction Of Hypogen Modelmentioning

confidence: 99%

The Discovery of Novel BCR-ABL Tyrosine Kinase Inhibitors Using a Pharmacophore Modeling and Virtual Screening Approach

Huang

Wang

Qiang

et al. 2021

Front. Cell Dev. Biol.

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Chronic myelogenous leukemia (CML) typically results from a reciprocal translocation between chromosomes 9 and 22 to produce the bcr-abl oncogene that when translated, yields the p210 BCR-ABL protein in more than 90% of all CML patients. This protein has constitutive tyrosine kinase activity that activates numerous downstream pathways that ultimately produces uncontrolled myeloid proliferation. Although the use of the BCR-ABL tyrosine kinase inhibitors (TKIs), such as imatinib, nilotinib, dasatinib, bosutinib, and ponatinib have increased the overall survival of CML patients, their use is limited by drug resistance and severe adverse effects. Therefore, there is the need to develop novel compounds that can overcome these problems that limit the use of these drugs. Therefore, in this study, we sought to find novel compounds using Hypogen and Hiphip pharmacophore models based on the structures of clinically approved BCR-ABL TKIs. We also used optimal pharmacophore models such as three-dimensional queries to screen the ZINC database to search for potential BCR-ABL inhibitors. The hit compounds were further screened using Lipinski’s rule of five, ADMET and molecular docking, and the efficacy of the hit compounds was evaluated. Our in vitro results indicated that compound ZINC21710815 significantly inhibited the proliferation of K562, BaF3/WT, and BaF3/T315I leukemia cells by inducing cell cycle arrest. The compound ZINC21710815 decreased the expression of p-BCR-ABL, STAT5, and Crkl and produced apoptosis and autophagy. Our results suggest that ZINC21710815 may be a potential BCR-ABL inhibitor that should undergo in vivo evaluation.

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Section: Construction Of Hypogen Modelmentioning

confidence: 99%

The Discovery of Novel BCR-ABL Tyrosine Kinase Inhibitors Using a Pharmacophore Modeling and Virtual Screening Approach

Huang

Wang

Qiang

et al. 2021

Front. Cell Dev. Biol.

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“…This is a big limitation but also an essential advantage of QSAR. After all, not all of the targetshave been or can be separated 43 .…”

mentioning

confidence: 99%

Trend of Multi-Scale QSAR in Drug Design

Qiao¹,

Cai²,

He³

et al. 2014

Asian J. Chem.

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Quantitative structure-activity relationship (QSAR) indicates the relationship between structural property and biological activity of compounds, which are widely used in the field of pharmacy, materials science, agronomy, environment, etc. 1,2. The basic construction procedures of QSAR model include four important steps.Firstly, as the structural description of the training set compounds is recorded, this structural information and relative biological activity are used to construct correlation function model by suitable algorithm. Afterwards, statistical methods are applied for internal validation of the model. Finally, the test set is used for external test of the model. Reliable QSAR model should be satisfied with the requirement of internal validation and external validation 3,4. The main purpose of QSAR model is to predict the activity of compounds, guide compound design and optimize leads. Classification of QSAR methodologies: Different classification methods of QSAR were presented to make the study more reliable and credible. The two main methods, introduced as following, have been widely accepted by QSAR researchers.

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Site‐Selective CH Borylation of Quinolines at the C8 Position Catalyzed by a Silica‐Supported Phosphane–Iridium System

Konishi

Kawamorita

Iwai

et al. 2013

Chemistry An Asian Journal

104

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3D-QSAR study of corticotropin-releasing factor 1 antagonists and pharmacophore-based drug design

Cited by 10 publications

References 40 publications

The Discovery of Novel BCR-ABL Tyrosine Kinase Inhibitors Using a Pharmacophore Modeling and Virtual Screening Approach

The Discovery of Novel BCR-ABL Tyrosine Kinase Inhibitors Using a Pharmacophore Modeling and Virtual Screening Approach

Trend of Multi-Scale QSAR in Drug Design

Site‐Selective CH Borylation of Quinolines at the C8 Position Catalyzed by a Silica‐Supported Phosphane–Iridium System

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