3D-QSAR studies of the chemical modification of hydroxyl groups of biomass (cellulose, hemicelluloses and lignin) using quantum chemical descriptors

Abstract

The models of Quantitative Structure-Activity Relationship (QSAR) are indeed useful for understanding the mechanism of chemical modification of wood by the method of acetylation. This study shows that the electrophile index ω in combination with other descriptors, namely LUMO energy, HOMO, hardness (η) and chemical potential (μ), prove their utility in predicting the chemical modification of wood (gain in mass). The QSAR models are developed through use of Multiple Linear Regression (MLR) and Principal Component Analysis (PCA) methods. The statistical results indicate that the multiple correlation coefficient R2 = 0.987, R2 adjusted = 0.981 and RMCE = 0.012. This shows both the favorable estimation stability and the appropriate predictive power. The results also indicate that there are significant correlations between the weight gain and the highest occupied molecular orbital HOMO. They also show that the chemical potential μ which are useful for modeling the wood modification are characterized by large hydrophobic properties and high electrophilic powers and therefore could be applied effectively in estimating the acetylation of wood. Finally, the developed model shows that cellulose and hemicellulose are mostly affected by the chemical modification of hydroxyl groups.

Keywords

• Natural product chemistry
• Organic chemistry
• Biomass
• Chemical modification
• QSAR
• Descriptors