Studies on the Cloud Points of Nonionic Surfactants with QSPR

Correlations for Easy Calculation of the Critical Coalescence Concentration (CCC) of Simple Frothers

Can the critical coalescence concentration (CCC) of the flotation frothers be predictable? What is the relation between their molecular structure and their CCC values? A literature survey found specific correlations between the hydrophilic-lipophilic balances (HLB) and HLB/Mw (where Mw stands for the molecular mass) of homologue series of frothers and their CCC values, but the results are invalid when the molecule’s functional groups change. For this reason, 37 frothers with known values of CCC were analyzed. The CCC values of seven frothers were determined, and the rest were taken from the literature. The frothers were subdivided in homologue series with an increasing number of the carbon atoms with an account for the type and the location of the functional group, thus deriving three types of correlations lnCCC = f(HLB) applicable for: (i) alcohols; (ii) propylene glycols alkyl ethers and propylene glycols; (iii) ethylene glycols alkyl ethers. The average accuracy of these correlations between CCC and HLB is 93%.

Thermal unfolding of a mammalian pentameric ligand-gated ion channel proceeds at consecutive, distinct steps

Pentameric ligand-gated ion channels (LGICs) play an important role in fast synaptic signal transduction. Binding of agonists to the β-sheet-structured extracellular domain opens an ion channel in the transmembrane α-helical region of the LGIC. How the structurally distinct and distant domains are functionally coupled for such central transmembrane signaling processes remains an open question. To obtain detailed information about the stability of and the coupling between these different functional domains, we analyzed the thermal unfolding of a homopentameric LGIC, the 5-hydroxytryptamine receptor (ligand binding, secondary structure, accessibility of Trp and Cys residues, and aggregation), in plasma membranes as well as during detergent extraction, purification, and reconstitution into artificial lipid bilayers. We found a large loss in thermostability correlating with the loss of the lipid bilayer during membrane solubilization and purification. Thermal unfolding of the 5-hydroxytryptamine receptor occurred in consecutive steps at distinct protein locations. A loss of ligand binding was detected first, followed by formation of different transient low oligomeric states of receptor pentamers, followed by partial unfolding of helical parts of the protein, which finally lead to the formation receptor aggregates. Structural destabilization of the receptor in detergents could be partially reversed by reconstituting the receptor into lipid bilayers. Our results are important because they quantify the stability of LGICs during detergent extraction and purification and can be used to create stabilized receptor proteins for structural and functional studies.

QSPR modeling of nonionic surfactant cloud points: an update

Quantitative structure-property relationship (QSPR) models for the cloud points of nonionic surfactants were developed based on CODESSA descriptors. Essentials accounting for a reliable model were considered carefully. Four descriptors were selected by a generic algorithm (GA) method to link the structures of nonionic surfactants to their corresponding cloud-point values. The descriptors were also analyzed using principal component analysis (PCA). Nonlinear models based on support vector machine (SVM) and projection pursuit regression (PPR) were also developed. All models were validated in two ways, i.e., internal cross-validation (CV) and a test set. The results are discussed in light of the main factors that influence the property under investigation and its modeling. In addition, an independent external data set of 16 nonionic surfactants was used to check the generalization ability of the optimum model.

A review on progress in QSPR studies for surfactants

This paper presents a review on recent progress in quantitative structure-property relationship (QSPR) studies of surfactants and applications of various molecular descriptors. QSPR studies on critical micelle concentration (cmc) and surface tension (γ) of surfactants are introduced. Studies on charge distribution in ionic surfactants by quantum chemical calculations and its effects on the structures and properties of the colloids of surfactants are also reviewed. The trends of QSPR studies on cloud point (for nonionic surfactants), biodegradation potential and some other properties of surfactants are evaluated.