Using the Correlation Intensity Index to Build a Model of Cardiotoxicity of Piperidine Derivatives

The assessment of cardiotoxicity is a persistent problem in medicinal chemistry. Quantitative structure-activity relationships (QSAR) are one possible way to build up models for cardiotoxicity. Here, we describe the results obtained with the Monte Carlo technique to develop hybrid optimal descriptors correlated with cardiotoxicity. The predictive potential of the cardiotoxicity models (pIC50, Ki in nM) of piperidine derivatives obtained using this approach provided quite good determination coefficients for the external validation set, in the range of 0.90-0.94. The results were best when applying the so-called correlation intensity index, which improves the predictive potential of a model.

Medienart:

E-Artikel

Erscheinungsjahr:

2023

Erschienen:

2023

Enthalten in:

Zur Gesamtaufnahme - volume:28

Enthalten in:

Molecules (Basel, Switzerland) - 28(2023), 18 vom: 12. Sept.

Sprache:

Englisch

Beteiligte Personen:

Toropova, Alla P [VerfasserIn]
Toropov, Andrey A [VerfasserIn]
Roncaglioni, Alessandra [VerfasserIn]
Benfenati, Emilio [VerfasserIn]

Links:

Volltext

Themen:

CORAL software
Cardiotoxicity
Computational chemistry
Correlation intensity index
Journal Article
Monte Carlo method
Piperidines

Anmerkungen:

Date Completed 29.09.2023

Date Revised 03.10.2023

published: Electronic

Citation Status MEDLINE

doi:

10.3390/molecules28186587

funding:

Förderinstitution / Projekttitel:

PPN (Katalog-ID):

NLM362606307