Synthesis, Biological Evaluation and Machine Learning Prediction Model for Fluorinated Cinchona Alkaloid-Based Derivatives as Cholinesterase Inhibitors
Abstract
:1. Introduction
2. Results and Discussion
2.1. Synthesis
2.2. Inhibition of Cholinesterases
2.2.1. Inhibition by Cinchonine and Cinchonidine Derivatives
2.2.2. Inhibition by 10, 11-Dihydrocinchonine and 10, 11-Dihydrocinchonidine and Their Derivatives
2.2.3. Selectivity of Inhibition
2.2.4. Stereoselectivity of Inhibition by Pseudo-Enantiomers
2.3. In Silico Modelling
2.4. PCA and Activity/PES Model Established by Machine Learning
3. Materials and Methods
3.1. Chemicals
3.2. Synthesis
3.3. Kinetic Measurements
3.3.1. Enzymes
3.3.2. Enzymes Activity Measurement
3.3.3. Enzyme-Inhibitor Dissociation Constants
3.4. In Silico Prediction of Drug-Likeness
3.5. In Silico Prediction of Blood-Brain Barrier Penetration
3.6. Principal Component Analysis
3.7. Sampling of the Potential Energy Surfaces
3.8. Machine Learning Multivariate Linear Regression
4. Conclusions
Author Contributions
Funding
Institutional Review Board Statement
Informed Consent Statement
Data Availability Statement
Acknowledgments
Conflicts of Interest
References
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Compound | Ki/µM | SI * | Compound | Ki/µM | SI * | ||
---|---|---|---|---|---|---|---|
BChE | AChE | BChE | AChE | ||||
CD Bzl | 0.075 ± 0.007 | 15 ± 2 | 200 | CN Bzl | 2.9 ± 0.3 | 121 ± 12 | 42 |
CD 2F | 0.82 ± 0.03 | 33 ± 1 | 40 | CN 2F | 2.4 ± 0.1 | 80 ± 2 | 33 |
CD 3F | 0.075 ± 0.005 | 40 ± 2 | 533 | CN 3F | 6.1 ± 0.3 | 13 ± 0.4 | 2.1 |
CD 4F | 1.5 ± 0.1 | 69 ± 3 | 46 | CN 4F | 2.6 ± 0.1 | 3.9 ± 0.2 | 1.5 |
CD 3CF3 | 2.4 ± 0.1 | 34 ± 1 | 14 | CN 3CF3 | 4.4 ± 0.2 | 59 ± 2 | 13 |
CD 4CF3 | 2.0 ± 0.1 | 21 ± 1 | 11 | CN 4CF3 | 6.0 ± 0.3 | 31 ± 1 | 5.2 |
CD 3,5F | 0.081 ± 0.01 | 10 ± 1 | 123 | CN 3,5F | 6.3 ± 0.2 | 34 ± 3 | 5.4 |
CD 3,4F | 1.3 ± 0.1 | 13 ± 1 | 10 | CN 3,4F | 6.1 ± 0.2 | 14 ± 0.2 | 2.3 |
CD 2,3F | 0.75 ±0.03 | 19 ± 1 | 25 | CN 2,3F | 9.6 ± 0.4 | 46 ± 3 | 4.8 |
CD 2,4F | 6.1 ± 0.5 | 6.4 ± 0.3 | 1.1 | CN 2,4F | 6.0 ± 0.2 | 27 ± 1 | 4.5 |
CD 2,6F | 9.9 ±0.4 | 7.7 ± 0.5 | 0.77 | CN 2,6F | 5.2 ± 0.2 | 30 ± 2 | 5.8 |
CD 3OCF3 | 7.4 ±0.4 | 8.2 ± 1.1 | 1.1 | CN 3OCF3 | 4.7 ± 0.2 | 41 ± 2 | 8.7 |
CD 4OCF3 | 7.6 ± 0.5 | 7.3 ± 0.5 | 0.96 | CN 4OCF3 | 7.8 ± 0.3 | 19 ± 2 | 2.4 |
CD 2F-6CF3 | 5.7 ± 0.6 | 35 ± 4 | 6.1 | CN 2F-6CF3 | 7.7 ± 0.4 | 61 ± 2 | 7.9 |
CD 2F-4Br | 0.68 ± 0.05 | 7.2 ± 0.4 | 10 | CN 2F-4Br | 5.5 ± 0.3 | 16 ± 1 | 2.9 |
CD 2Cl-6F | 5.0 ± 0.3 | 9.9 ± 0.8 | 1.9 | CN 2Cl-6F | 1.2 ± 0.0 | 17 ± 1 | 14 |
Compound | Ki/µM | SI * | Compound | Ki/µM | SI * | ||
---|---|---|---|---|---|---|---|
BChE | AChE | BChE | AChE | ||||
DHCD | 19 ± 2 | 206 ± 6 | 11 | DHCN | 1.2 ± 0.1 | 43 ± 2 | 43 |
DHCD Bzl | 0.4 ± 0.02 | 4.8 ± 0.4 | 12 | DHCN Bzl | 0.9 ± 0.04 | 21 ± 1 | 23 |
DHCD 3F | 0.3 ± 0.02 | 27 ± 2 | 84 | DHCN 3F | 1.2 ± 0.1 | 20 ± 1 | 20 |
DHCD 4F | 4.3 ± 0.2 | 31 ± 1 | 8 | DHCN 4F | 1.6 ± 0.1 | 64 ± 2 | 40 |
DHCD 3CF3 | 1.4 ± 0.1 | 25 ± 1 | 18 | DHCN 3CF3 | 1.2 ± 0.05 | 41 ± 2 | 34 |
DHCD 4CF3 | 3.2 ± 0.2 | 15 ± 1 | 5 | DHCN 4CF3 | 1.6 ± 0.1 | 18 ± 1 | 9 |
DHCD 3OCF3 | 6.8 ± 0.3 | 36 ± 1 | 5 | DHCN 3OCF3 | 1.3 ± 0.5 | 68 ± 1 | 52 |
DHCD 4OCF3 | 5.9 ± 0.2 | 17 ± 1 | 3 | DHCN 4OCF3 | 2.2 ± 0.1 | 22 ± 1 | 10 |
2F | 3F | 4F | 3CF3 | 4CF3 | 3,5F | 3,4F | 2,3F | 2,4F | 2,6F | 3OCF3 | 4OCF3 | 2F-6CF3 | 2F-4Br | 6F-2Cl | ||
---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
Ki(CN/CD) | BChE | 2.9 | 81 | 1.7 | 1.8 | 3.0 | 78 | 4.7 | 13 | 1.0 | 0.53 | 0.64 | 1.0 | 1.4 | 8.1 | 0.24 |
AChE | 2.4 | 0.33 | 0.056 | 1.7 | 1.5 | 3.4 | 1.1 | 2.4 | 4.2 | 3.9 | 5 | 2.6 | 1.7 | 2.2 | 1.7 |
- | Bzl | 3F | 4F | 3CF3 | 4CF3 | 3OCF3 | 4OCF3 | ||
---|---|---|---|---|---|---|---|---|---|
Ki(DHCN/DHCD) | BChE | 0.063 | 2.2 | 4.0 | 0.37 | 0.86 | 0.50 | 0.19 | 0.37 |
AChE | 0.21 | 4.4 | 0.74 | 2.1 | 1.6 | 1.2 | 1.9 | 1.3 |
Compounds | MW/100 | clogP | HBD | HBA | RB | PSA/10 |
---|---|---|---|---|---|---|
CD 2F, 3F, 4F | 4.83425 | 0.376 | 1 | 2 | 5 | 3.312 |
CD 3CF3, 4CF3 | 5.33433 | 1.111 | 1 | 2 | 6 | 3.312 |
CD 3,5F, 3,4F, 2,3F, 2,4F, 2,6F | 5.01416 | 0.519 | 1 | 2 | 5 | 3.312 |
CD 3OCF3, 4OCF3 | 5.49432 | 1.664 | 1 | 3 | 7 | 4.235 |
CD 2F-6CF3 | 5.51424 | 1.625 | 1 | 2 | 6 | 3.312 |
CD 2F-4Br | 5.62321 | 1.145 | 1 | 2 | 5 | 3.312 |
CD 6F-2Cl | 5.1787 | 0.98 | 1 | 2 | 5 | 3.312 |
DHCD | 3.76319 | 2.975 | 1 | 3 | 3 | 3.636 |
DHCD Bzl | 4.6616 | 0.537 | 1 | 2 | 5 | 3.312 |
DHCD 3F, 4F | 4.85441 | 0.68 | 1 | 2 | 5 | 3.312 |
DHCD 3CF3, 4CF3 | 5.341493 | 1.415 | 1 | 2 | 6 | 3.312 |
DHCD 3OCF3, 4OCF3 | 5.550144 | 1.968 | 1 | 3 | 7 | 4.235 |
Recommended values | 5 | 5 | 3 | 7 | 8 | 7 |
Penetration Levels * | 0 | 1 |
---|---|---|
Compounds | CD 3OCF3, CD 4OCF3, CN 3OCF3, DHCN 3OCF3, DHCN 4OCF3, DHCD 3OCF3, DHCD 4OCF3 | CD 2F, CD 3F, CD 4F, CD 3CF3, CD 4CF3, CN 2F, CN 3F, CN 4F, CN 3CF3, CD 3,5F, CD 3,4F, CN 4CF3, CD 2,3F, CD 2,4F, CD 2,6F, CN 3,5F, CN 3,4F, CN 2,3F, CN 2,4F, CN 2,6F, CD 2F-6CF3, CD 2F-4Br, CD 2Cl-6F, CN 2F-6CF3, CN 2F-4Br, CN 2Cl-6F, DHCD, DHCD 3F, DHCD 4F, DHCD 4CF3, DHCD 3CF3, DHCD Bzl, DHCN, DHCN Bzl, DHCN 4CF3, DHCN 3F, DHCN 3CF3, Tacrine |
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Ramić, A.; Matošević, A.; Debanić, B.; Mikelić, A.; Primožič, I.; Bosak, A.; Hrenar, T. Synthesis, Biological Evaluation and Machine Learning Prediction Model for Fluorinated Cinchona Alkaloid-Based Derivatives as Cholinesterase Inhibitors. Pharmaceuticals 2022, 15, 1214. https://doi.org/10.3390/ph15101214
Ramić A, Matošević A, Debanić B, Mikelić A, Primožič I, Bosak A, Hrenar T. Synthesis, Biological Evaluation and Machine Learning Prediction Model for Fluorinated Cinchona Alkaloid-Based Derivatives as Cholinesterase Inhibitors. Pharmaceuticals. 2022; 15(10):1214. https://doi.org/10.3390/ph15101214
Chicago/Turabian StyleRamić, Alma, Ana Matošević, Barbara Debanić, Ana Mikelić, Ines Primožič, Anita Bosak, and Tomica Hrenar. 2022. "Synthesis, Biological Evaluation and Machine Learning Prediction Model for Fluorinated Cinchona Alkaloid-Based Derivatives as Cholinesterase Inhibitors" Pharmaceuticals 15, no. 10: 1214. https://doi.org/10.3390/ph15101214
APA StyleRamić, A., Matošević, A., Debanić, B., Mikelić, A., Primožič, I., Bosak, A., & Hrenar, T. (2022). Synthesis, Biological Evaluation and Machine Learning Prediction Model for Fluorinated Cinchona Alkaloid-Based Derivatives as Cholinesterase Inhibitors. Pharmaceuticals, 15(10), 1214. https://doi.org/10.3390/ph15101214