The searching for agents for Alzheimer’s disease treatment via the system of self-consistent models
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216208%3A11110%2F22%3A10453925" target="_blank" >RIV/00216208:11110/22:10453925 - isvavai.cz</a>
Result on the web
<a href="https://verso.is.cuni.cz/pub/verso.fpl?fname=obd_publikace_handle&handle=DEmweMc4mW" target="_blank" >https://verso.is.cuni.cz/pub/verso.fpl?fname=obd_publikace_handle&handle=DEmweMc4mW</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1080/15376516.2022.2053918" target="_blank" >10.1080/15376516.2022.2053918</a>
Alternative languages
Result language
angličtina
Original language name
The searching for agents for Alzheimer’s disease treatment via the system of self-consistent models
Original language description
Robust quantitative structure-activity relationships (QSARs) for hBACE-1 inhibitors (pIC50) for a large database (n = 1706) are established. New statistical criteria of the predictive potential of models are suggested and tested. These criteria are the index of ideality of correlation (IIC) and the correlation intensity index (CII). The system of self-consistent models is a new approach to validate the predictive potential of QSAR-models. The statistical quality of models obtained using the CORAL software (http://www.insilico.eu/coral) for the validation sets is characterized by the average determination coefficient R2v= 0.923, and RMSE = 0.345. Three new promising molecular structures which can become inhibitors hBACE-1 are suggested.
Czech name
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Czech description
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Classification
Type
J<sub>imp</sub> - Article in a specialist periodical, which is included in the Web of Science database
CEP classification
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OECD FORD branch
30202 - Endocrinology and metabolism (including diabetes, hormones)
Result continuities
Project
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Continuities
V - Vyzkumna aktivita podporovana z jinych verejnych zdroju
Others
Publication year
2022
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Name of the periodical
Toxicology Mechanisms and Methods
ISSN
1537-6516
e-ISSN
1537-6524
Volume of the periodical
32
Issue of the periodical within the volume
7
Country of publishing house
US - UNITED STATES
Number of pages
9
Pages from-to
549-557
UT code for WoS article
000779542400001
EID of the result in the Scopus database
2-s2.0-85129148080