Novel and Predictive QSAR Model for Steroidal and Nonsteroidal 5α- Reductase Type II Inhibitors
Copyright© Bentham Science Publishers; For any queries, please email at epubbenthamscience.net..
AIMS AND OBJECTIVE: In this study, a novel quantitative structure activity relationship (QSAR) model has been developed for inhibitors of human 5-alpha reductase type II, which are used to treat benign prostate hypertrophy (BPH).
METHODS: The dataset consisted of 113 compounds-mainly nonsteroidal-with known inhibitory concentration. Then 3D structures of compounds were optimized and molecular structure descriptors were calculated. The stepwise multiple linear regression was used to select descriptors encoding the inhibitory activity of the compounds. Multiple linear regression (MLR) was used to build up the linear QSAR model.
RESULTS: The results obtained revealed that the descriptors which best describe the activity were atom type electropological state, carbon type, radial distribution function (RDF), barysz matrix and molecular linear free energy relation. The suggested model could achieve satisfied square correlation coefficient of R2 = 0.72, higher than of many previous studies, indicating its superiority. Rigid validation criteria were met using external data with Q2 ˃ 0.5 and R2 = 0.75, reflecting the predictive power of the model.
CONCLUSION: The QSAR model was applied for screening botanical components of herbal preparations used to treat BPH, and could predict the activity of some, among others, making reasonable attribution to the proposed effect of these preparations. Gamma tocopherol was found to be an active inhibitor, in consistence with many previous studies, anticipating the power of this model in the prediction of new candidate molecules and suggesting further investigations.
| Medienart: |
E-Artikel |
|---|
| Erscheinungsjahr: |
2021 |
|---|---|
| Erschienen: |
2021 |
| Enthalten in: |
Zur Gesamtaufnahme - volume:18 |
|---|---|
| Enthalten in: |
Current drug discovery technologies - 18(2021), 2 vom: 10., Seite 317-332 |
| Sprache: |
Englisch |
|---|
| Beteiligte Personen: |
Mando, Huda [VerfasserIn] |
|---|
| Links: |
|---|
| Anmerkungen: |
Date Completed 10.12.2021 Date Revised 14.12.2021 published: Print Citation Status MEDLINE |
|---|
| doi: |
10.2174/1570163817666200324170457 |
|---|
| funding: |
|
|---|---|
| Förderinstitution / Projekttitel: |
|
| PPN (Katalog-ID): |
NLM307941140 |
|---|
| LEADER | 01000naa a22002652 4500 | ||
|---|---|---|---|
| 001 | NLM307941140 | ||
| 003 | DE-627 | ||
| 005 | 20231225130652.0 | ||
| 007 | cr uuu---uuuuu | ||
| 008 | 231225s2021 xx |||||o 00| ||eng c | ||
| 024 | 7 | |a 10.2174/1570163817666200324170457 |2 doi | |
| 028 | 5 | 2 | |a pubmed24n1026.xml |
| 035 | |a (DE-627)NLM307941140 | ||
| 035 | |a (NLM)32208118 | ||
| 040 | |a DE-627 |b ger |c DE-627 |e rakwb | ||
| 041 | |a eng | ||
| 100 | 1 | |a Mando, Huda |e verfasserin |4 aut | |
| 245 | 1 | 0 | |a Novel and Predictive QSAR Model for Steroidal and Nonsteroidal 5α- Reductase Type II Inhibitors |
| 264 | 1 | |c 2021 | |
| 336 | |a Text |b txt |2 rdacontent | ||
| 337 | |a ƒaComputermedien |b c |2 rdamedia | ||
| 338 | |a ƒa Online-Ressource |b cr |2 rdacarrier | ||
| 500 | |a Date Completed 10.12.2021 | ||
| 500 | |a Date Revised 14.12.2021 | ||
| 500 | |a published: Print | ||
| 500 | |a Citation Status MEDLINE | ||
| 520 | |a Copyright© Bentham Science Publishers; For any queries, please email at epubbenthamscience.net. | ||
| 520 | |a AIMS AND OBJECTIVE: In this study, a novel quantitative structure activity relationship (QSAR) model has been developed for inhibitors of human 5-alpha reductase type II, which are used to treat benign prostate hypertrophy (BPH) | ||
| 520 | |a METHODS: The dataset consisted of 113 compounds-mainly nonsteroidal-with known inhibitory concentration. Then 3D structures of compounds were optimized and molecular structure descriptors were calculated. The stepwise multiple linear regression was used to select descriptors encoding the inhibitory activity of the compounds. Multiple linear regression (MLR) was used to build up the linear QSAR model | ||
| 520 | |a RESULTS: The results obtained revealed that the descriptors which best describe the activity were atom type electropological state, carbon type, radial distribution function (RDF), barysz matrix and molecular linear free energy relation. The suggested model could achieve satisfied square correlation coefficient of R2 = 0.72, higher than of many previous studies, indicating its superiority. Rigid validation criteria were met using external data with Q2 ˃ 0.5 and R2 = 0.75, reflecting the predictive power of the model | ||
| 520 | |a CONCLUSION: The QSAR model was applied for screening botanical components of herbal preparations used to treat BPH, and could predict the activity of some, among others, making reasonable attribution to the proposed effect of these preparations. Gamma tocopherol was found to be an active inhibitor, in consistence with many previous studies, anticipating the power of this model in the prediction of new candidate molecules and suggesting further investigations | ||
| 650 | 4 | |a Journal Article | |
| 650 | 4 | |a 5α-Reductase | |
| 650 | 4 | |a 5α-reductase isozymes | |
| 650 | 4 | |a BHP | |
| 650 | 4 | |a QSAR | |
| 650 | 4 | |a inhibitor | |
| 650 | 4 | |a prostate | |
| 650 | 7 | |a 5-alpha Reductase Inhibitors |2 NLM | |
| 650 | 7 | |a Isoenzymes |2 NLM | |
| 650 | 7 | |a Membrane Proteins |2 NLM | |
| 650 | 7 | |a Plant Preparations |2 NLM | |
| 650 | 7 | |a Dihydrotestosterone |2 NLM | |
| 650 | 7 | |a 08J2K08A3Y |2 NLM | |
| 650 | 7 | |a gamma-Tocopherol |2 NLM | |
| 650 | 7 | |a 8EF1Z1238F |2 NLM | |
| 650 | 7 | |a 3-Oxo-5-alpha-Steroid 4-Dehydrogenase |2 NLM | |
| 650 | 7 | |a EC 1.3.99.5 |2 NLM | |
| 650 | 7 | |a SRD5A2 protein, human |2 NLM | |
| 650 | 7 | |a EC 1.3.99.5 |2 NLM | |
| 700 | 1 | |a Hassan, Ahmad |e verfasserin |4 aut | |
| 700 | 1 | |a Gharaghani, Sajjad |e verfasserin |4 aut | |
| 773 | 0 | 8 | |i Enthalten in |t Current drug discovery technologies |d 2004 |g 18(2021), 2 vom: 10., Seite 317-332 |w (DE-627)NLM160661455 |x 1875-6220 |7 nnns |
| 773 | 1 | 8 | |g volume:18 |g year:2021 |g number:2 |g day:10 |g pages:317-332 |
| 856 | 4 | 0 | |u http://dx.doi.org/10.2174/1570163817666200324170457 |3 Volltext |
| 912 | |a GBV_USEFLAG_A | ||
| 912 | |a GBV_NLM | ||
| 951 | |a AR | ||
| 952 | |d 18 |j 2021 |e 2 |b 10 |h 317-332 | ||