Hybrid Docking-Nano-QSPR: An Alternative Approach for Prediction of Chemicals Adsorption on Nanoparticles

Heidari, Afsane; Fatemi, M.

doi:10.1142/s1793292016500788

Cited by 10 publications

(3 citation statements)

References 47 publications

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“…Molecular docking is a valuable tool to assess the binding position of molecules with a considered receptor . The X‐ray crystal structure of HSA was extracted from a protein data bank (PDB ID code: 2bxd, Resolution 3.05 Å).…”

Section: Methodsmentioning

confidence: 99%

“…Molecular docking is a valuable tool to assess the binding position of molecules with a considered receptor. [36][37][38][39] The X-ray crystal structure of HSA was extracted from a protein data bank (PDB ID code: 2bxd, Resolution 3.05 Å). Three dimensional (3D) structures of 14 anti-inflammatory drugs were downloaded from ChemSpider as .mol format.…”

Section: Molecular Docking Studymentioning

confidence: 99%

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Study on the interaction of anti‐inflammatory drugs with human serum albumin using molecular docking, quantitative structure–activity relationship, and fluorescence spectroscopy

2019

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The interaction of 14 anti‐inflammatory drugs with human serum albumin (HSA) was investigated using fluorescence quenching, molecular docking studies, and quantitative structure–activity relationship (QSAR) methodology. Binding of anti‐inflammatory drugs to HSA plays a fundamental role in their transport, distribution, delivery, and elimination. Binding constants of these drugs to HSA, obtained using the fluorescence quenching method, were within the range 0.01 × 104 M−1 (acetaminophen) to 1881.05 × 104 M−1 (meloxicam). Binding sites and binding constants of these anti‐inflammatory drugs were estimated using molecular docking. Inspection of the obtained values for docking score, logKb and Kb, showed that the drugs in this data set have a relatively strong binding constant for HSA. QSAR modelling was applied for binding constants obtained from fluorescence quenching and theoretical molecular descriptors. This modelling led to a linear two‐parameter model with a correlation coefficient of 0.95 and adequate robustness. The descriptor results showed the importance of a bonding network and electronegativity as the discriminative structural factors in binding affinity for the HSA molecule.

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Section: Methodsmentioning

confidence: 99%

Section: Molecular Docking Studymentioning

confidence: 99%

Study on the interaction of anti‐inflammatory drugs with human serum albumin using molecular docking, quantitative structure–activity relationship, and fluorescence spectroscopy

2019

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“…They suggested that BSAI could mimic the molecular interactions of nanoparticles with the residues of proteins. In their paper, only log K values of multiwalled carbon nanotubes (MWCNTs) were given, and we used them in our previous work to model hybrid docking‐nano‐QSPR . This study showed that 2D descriptors (graph‐based descriptors) play a significant role in the modeling and prediction of the adsorption coefficients of these compounds.…”

Section: Introductionmentioning

confidence: 99%

A Theoretical Approach to Model and Predict the Adsorption Coefficients of Some Small Aromatic Molecules on Carbon Nanotube

Heidari

Fatemi

2017

J Chinese Chemical Soc

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In this study, for the first time, the CORAL software is used to model the quantitative structureproperty relationship (QSPR) of adsorption coefficients of chemicals on carbon nanotubes. The new method, which includes three-dimensional response surfaces for all subsets, is used to optimize Monte Carlo parameters in the modeling procedure. By using the 3D response surfaces, we obtained a satisfactory value for R 2 test , at the same time keeping the statistical quality of the subtraining and validation sets. Two predictive models were developed by using hydrogen-filled graph-based descriptors (model 1) and hybrid descriptors (model 2) with squared correlation coefficient (R 2 ) values of 0.985 and 0.940, respectively. The prediction power of these models was evaluated on a six-member test set, leading to R 2 values of 0.962 and 0.941 for model 1 and model 2, respectively. Moreover, the leave-one-out cross validation test was used to investigate the robustness of models, which lead to Q 2 values of 0.983 for model 1 and 0.932 for model 2.

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The experimental and theoretical assessment of biopartitioning micellar liquid chromatography to mimic the drug‐protein binding of some pain‐relief drugs

Mohammadnia

Fatemi

Taghizadeh

2020

J Chinese Chemical Soc

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In this work, biopartitioning micellar liquid chromatography (BMLC) was used to the assessment of affinity binding of 13 pain‐relief drugs to human serum albumin (HSA) molecules. The values of BMLC retention factors were determined by aqueous CTAB solution as mobile phase. Then, these values were correlated to some molecular structural descriptors by using a quantitative structure retention relationship methodology. The statistical quality of the obtained models was evaluated by different validation tests. Also, selected descriptors were correlated with protein–drug binding values and resulted in correlation coefficients higher than 0.8. Results indicated that selected descriptors can address the most important structural features influencing the binding affinity of studied drugs to HSA.

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Hybrid Docking-Nano-QSPR: An Alternative Approach for Prediction of Chemicals Adsorption on Nanoparticles

Cited by 10 publications

References 47 publications

Study on the interaction of anti‐inflammatory drugs with human serum albumin using molecular docking, quantitative structure–activity relationship, and fluorescence spectroscopy

Study on the interaction of anti‐inflammatory drugs with human serum albumin using molecular docking, quantitative structure–activity relationship, and fluorescence spectroscopy

A Theoretical Approach to Model and Predict the Adsorption Coefficients of Some Small Aromatic Molecules on Carbon Nanotube

The experimental and theoretical assessment of biopartitioning micellar liquid chromatography to mimic the drug‐protein binding of some pain‐relief drugs

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