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QSPR between molecular structures of polymers and micellar properties based on block unit autocorrelation (BUA) descriptors.

Authors :
Wu, Wensheng
Zhang, Ran
Peng, Shiyuan
Li, Xiuxi
Zhang, Lijuan
Source :
Chemometrics & Intelligent Laboratory Systems. Oct2016, Vol. 157, p7-15. 9p.
Publication Year :
2016

Abstract

Polymeric micelles are a type of complex chemical product with multiple phases and components, and polymeric molecular structures are among the main factors influencing the micellar properties. In this study, based on block unit autocorrelation (BUA) descriptors, we employed a genetic function approximation (GFA) algorithm and multiple linear regression (MLR) to develop quantitative structure–property relationship (QSPR) models between the multi-topological structures of polymers and micellar properties including drug loading capacity (LC) and critical micelle concentration (CMC), generating an LC optimization model with five descriptors ( n = 60, R 2 = 0.813, Q 2 LOO-CV = 0.663, Q 2 5 -fold = 0.636, F = 46.880 ( p < 0.001), Q 2 ext = 0.830, Q 2 y-rand = 0.0004) and a CMC optimization model with six descriptors ( n = 22, R 2 = 0.897, Q 2 LOO-CV = 0.702, F = 21.765 ( p < 0.001), Q 2 ext = 0.717, Q 2 y-rand = 0.0009). Based on the model analysis, the factors mainly influencing LC are the lowest unoccupied molecular orbital (LUMO) energy, dipole, electrostatic energy and electronic energy, which are related to the electronic energy level, electron distribution and interaction of electrons in molecules. The main factors affecting CMC are the energies of interactions between polymers and water, charges and branching of polymer structures. The conclusions obtained may help establish the regulatory mechanism between polymer structures and micellar properties and offer guidance for the design and development of polymeric carrier materials. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
01697439
Volume :
157
Database :
Academic Search Index
Journal :
Chemometrics & Intelligent Laboratory Systems
Publication Type :
Academic Journal
Accession number :
118025526
Full Text :
https://doi.org/10.1016/j.chemolab.2016.06.011