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Multi-target spectral moment: QSAR for antifungal drugs vs. different fungi species by Francisco J. Prado-Prado; Fernanda Borges; Lazaro G. Perez-Montoto; Humberto González-Díaz is a Chemistry article available to read on EtoBox.

What is Multi-target spectral moment: QSAR for antifungal drugs vs. different fungi species about?

The most important limitation of antifungal QSAR models is that they predict the biological activity of drugs against only one fungal species. This is determined due the fact that most of the up-to-date reported molecular descriptors encode only information about the molecular structure. Consequently, predicting the probability with which a drug is active against different fungal species with a single unifying model is a goal of major importance. Herein, we use the Markov Chain theory to calculate new multi-target spectral moments to fit a QSAR model that predicts the antifungal activity of more than 280 drugs against 90 fungi species. Linear discriminant analysis (LDA) was used to classify drugs into two classes as active or non-active against the different tested fungal species whose data we processed. The model correctly classifies 12 434 out of 12 566 non-active compounds (98.95%) and 421 out of 468 active compounds (89.96%). Overall training predictability was 98.63%. Validation of the model was carried out by means of external predicting series, the model classifying, thus, 6216 out of 6277 non-active compounds and 215 out of 239 active compounds. Overall training predictabil

Who reads Multi-target spectral moment: QSAR for antifungal drugs vs. different fungi species?

Author

Francisco J. Prado-Prado; Fernanda Borges; Lazaro G. Perez-Montoto; Humberto González-Díaz

Publisher

Elsevier Science; Elsevier ; Elsevier BV (ISSN 0223-5234)

Published

2009

Language

EN

Field

Chemistry (Physical Sciences)