[Special Issue for Honor Award dedicating to Prof Kimito Funatsu]An Electronic-Structure Informatics Study on Inhibitory Activity of Natural Products against Fatty Acid Synthase

Abstract

Fatty acid synthase (FASN) inhibitors are known to work as anti-cancer drugs. In order to find important factors in their structure-activity relationships and to derive a predictive model for the activity, we herein tried to develop regression models by using descriptors representing chemical reactivities and intermolecular interactions. By employing the descriptors calculated with the electronic-structure theory, regression models for the experimental IC50 values were derived. Good correlations between the predicted and experimental values were obtained for the natural products having inhibitor activity to FASN. The obtained models are expected useful for systematic search for more efficient inhibitors. At the same time, the present results justify the use of the newly suggested descriptors evaluated in electronic-structure calculations.

Extended Regression Modeling of the Toxicity of Phenol Derivatives to <i>Tetrahymena pyriformis</i> Using the Electronic-Structure Informatics Descriptor

“…This means that the ESI descriptor set is enough accurate to describe the toxicity of the phenol derivatives. It is also noted that the ESI descriptor has been successful in regression modeling for different types of biological activities [6,7]. This implies that the ESI descriptor has general applicability in various QSAR and quantitative structure-property (QSPR) studies.…”

“…In the set of the ESI descriptors, information on electronically excited states is included. This calculation was carried out using the time-dependent DFT (TDDFT) method where 30 lowlying excited states were calculated [5][6][7]. The solvation energy was evaluated using the polarizable continuum model (PCM).…”

“…The Mathematica 11 software[18] was also used to determine the size parameters (B1, B2, and B3 in Table S1). The details of the evaluation method of the ESI descriptors were explained in [5][6][7].…”

“…We have recently suggested a set of "electronicstructure informatics" (ESI) descriptors. The descriptor set has been successfully applied to predict biological activities such as toxicity and inhibitor activity of small molecules [5][6][7]. In the toxicity prediction of 33 alkylphenols to Tetrahymena pyriformis [5], vertical electron affinity (EAv) and size parameters were found to be dominant among the ESI descriptors.…”