Phenolic Acid–β-Cyclodextrin Complexation Study to Mask Bitterness in Wheat Bran: A Machine Learning-Based QSAR Study
Abstract
:1. Introduction
2. Materials and Methods
2.1. Dataset Preparation
2.2. Binding Constant Calculations
2.3. Docking Procedures
2.4. Molecular Descriptors Generation
2.5. Variable Selection and QSAR Modeling
2.6. Applicability Domain
2.7. Descriptor Significance Plot
3. Results and Discussion
3.1. Binding Score Affinity (Model 1)
3.2. Binding Affinity (Model 2)
3.3. Binding Energy
4. Conclusions
Supplementary Materials
Author Contributions
Funding
Institutional Review Board Statement
Informed Consent Statement
Data Availability Statement
Acknowledgments
Conflicts of Interest
References
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ID | β-CD-Ligand Complex | HOMO a (eV) | LUMO b (eV) | Gap (eV) | Binding Score (kJ/mol) | Binding Affinity (kJ/mol) |
---|---|---|---|---|---|---|
1 | Caffeic acid-in | −9.1890 | −1.0514 | −8.1376 | −4.5 | −51.1831 |
2 | Camphor-in | −10.1147 | 0.0704 | −10.1851 | −3.9 | −34.4419 |
3 | D-Limonene-in | −9.3119 | 0.0092 | −9.3211 | −3.5 | −44.2580 |
4 | Eucalyptol-in | −9.9785 | 0.1605 | −10.139 | −4.0 | −52.1555 |
5 | Eugenol-up | −8.9658 | −0.1518 | −8.8140 | −4.0 | −35.1691 |
6 | Gallic acid-up | −9.5087 | −1.2760 | −8.2327 | −5.0 | −35.6459 |
7 | Geranial-up | −9.5651 | −0.2514 | −9.3137 | −3.2 | −58.3673 |
8 | Heptanol-up | −10.2024 | −0.1426 | −10.0598 | −2.8 | −26.6948 |
9 | Hydroxy Methyl Furfural-up | −9.2240 | −0.4026 | −8.8214 | −3.7 | −64.9081 |
10 | Isoamyl acetate-up | −10.1978 | −0.3113 | −9.8865 | −3.1 | −66.5904 |
11 | Maltol-up | −9.8792 | −1.3000 | −8.5792 | −4.1 | −64.6218 |
12 | Menthol-in | −10.1733 | −0.0167 | −10.1566 | −4.2 | −57.9313 |
13 | Neral-up | −9.7932 | −0.4443 | −9.3489 | −3.4 | −66.7781 |
14 | P-Coumaric acid-in | −9.3920 | −0.3048 | −9.0872 | −4.3 | −63.3347 |
15 | Pinellic acid-in | −9.8072 | 0.0819 | −9.8891 | −3.6 | −63.3198 |
16 | Sinapic acid-up | −9.1111 | −1.1979 | −7.9132 | −4.6 | −90.6849 |
17 | Styrene-up | −9.4684 | −0.4950 | −8.9734 | −2.9 | −45.7564 |
18 | Syringic acid-up | −9.2231 | −0.9025 | −8.3206 | −4.6 | −76.8800 |
19 | Trans Ferulic acid-up | −9.0647 | −1.4466 | −7.6181 | −4.4 | −64.1563 |
20 | Vanillic acid-in | −9.1477 | −0.9277 | −8.2200 | −4.4 | −76.3647 |
Parameters | Log BSA | Log BA | Log BE |
---|---|---|---|
Model # Number of variables | 1 (Equation (3)) 3 | 2 (Equation (4)) 3 | 3 (Equation (5)) 3 |
R2 (training set) | 0.969 | 0.859 | 0.779 |
RMSE (training set) | 0.0116 | 0.0256 | 0.0631 |
MAE (training set) | 0.0095 | 0.0192 | 0.0527 |
CCC (training set) | 0.985 | 0.924 | 0.876 |
F | 126.902 | 24.349 | 14.117 |
R2 (cross-validation) | 0.925 | 0.805 | 0.634 |
RMSE (cross-validation) | 0.0182 | 0.0302 | 0.0812 |
MAE (cross-validation) | 0.0135 | 0.0236 | 0.0698 |
CCC (cross-validation) | 0.961 | 0.897 | 0.790 |
R2 (external test) | 0.984 | 0.956 | 0.663 |
RMSE (external test) | 0.0093 | 0.0156 | 0.0685 |
MAE (external test) | 0.0082 | 0.0146 | 0.0563 |
Descriptor | Description | Class |
---|---|---|
Model 1—Binding Score Affinity | ||
nR06 | Number of 6-membered rings | Ring descriptors |
ATS4m | Broto–Moreau autocorrelation of lag 4 (log function) weighted by mass | 2D Autocorrelations |
BEle3 | Lowest eigenvalue No. 3 of Burden matrix/weighted by atomic Sanderson electronegativities | BCUT descriptors |
Model 2—Binding Affinity | ||
S3K | 3-path Kier alpha-modified shape index | Topological Indices |
EEig03r | Eigenvalues | Edge adjacency indices |
H0e | H autocorrelation of lag 0/weighted by Sanderson electronegativity | GETAWAY descriptors |
Model 3—Binding Energy | ||
GATS8e | Geary autocorrelation of lag 8 weighted by mass | 2D Autocorrelations |
Mor10u | Signal 10/unweighted | 3D-MoRSE descriptors |
TPSA | Topological polar surface area using N,O polar contributions | Molecular properties |
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Iduoku, K.; Ngongang, M.; Kulathunga, J.; Daghighi, A.; Casanola-Martin, G.; Simsek, S.; Rasulev, B. Phenolic Acid–β-Cyclodextrin Complexation Study to Mask Bitterness in Wheat Bran: A Machine Learning-Based QSAR Study. Foods 2024, 13, 2147. https://doi.org/10.3390/foods13132147
Iduoku K, Ngongang M, Kulathunga J, Daghighi A, Casanola-Martin G, Simsek S, Rasulev B. Phenolic Acid–β-Cyclodextrin Complexation Study to Mask Bitterness in Wheat Bran: A Machine Learning-Based QSAR Study. Foods. 2024; 13(13):2147. https://doi.org/10.3390/foods13132147
Chicago/Turabian StyleIduoku, Kweeni, Marvellous Ngongang, Jayani Kulathunga, Amirreza Daghighi, Gerardo Casanola-Martin, Senay Simsek, and Bakhtiyor Rasulev. 2024. "Phenolic Acid–β-Cyclodextrin Complexation Study to Mask Bitterness in Wheat Bran: A Machine Learning-Based QSAR Study" Foods 13, no. 13: 2147. https://doi.org/10.3390/foods13132147
APA StyleIduoku, K., Ngongang, M., Kulathunga, J., Daghighi, A., Casanola-Martin, G., Simsek, S., & Rasulev, B. (2024). Phenolic Acid–β-Cyclodextrin Complexation Study to Mask Bitterness in Wheat Bran: A Machine Learning-Based QSAR Study. Foods, 13(13), 2147. https://doi.org/10.3390/foods13132147