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NMR spectroscopy, molecular modeling, and conductivity experiments were used to investigate micelle formation by the amino acid-based surfactant tridecanoic L-glutamic acid. Amino acid-based biosurfactants are green alternatives to surfactants derived from petroleum. NMR titrations were used to measure the monomeric surfactant’s primary and gamma (γ) carboxylic acid pKa values. Intramolecular hydrogen bonding within the surfactant’s headgroup caused the primary carboxylic acid to be less acidic than the corresponding functional group in free L-glutamic acid. Likewise, intermolecular hydrogen bonding caused the micellar surfactant’s γ carboxylic functional group to be less acidic than the corresponding monomer value. The binding of four positive counterions to the anionic micelles was also investigated. At pH levels below 7.0 when the surfactant headgroup charge was −1, the micelle hydrodynamic radii were larger (~30 Å) and the mole fraction of micelle-bound counterions was in the 0.4–0.7 range. In the pH range of 7.0–10.5, the micelle radii decreased with increasing pH and the mole fraction of micelle bound counterions increased. These observations were attributed to changes in the surfactant headgroup charge with pH. Above pH 10.5, the counterions deprotonated and the mole fraction of micelle-bound counterions decreased further. Finally, critical micelle concentration measurements showed that the micelles formed at lower concentrations at pH 6 when the headgroup charge was predominately −1 and at higher concentrations at pH 7 where headgroups had a mixture of −1 and −2 charges in solution. 

Neurexin-1 (NRXN1) is a membrane protein essential in synapse formation and cell signaling as a cell-adhesion molecule and cell-surface receptor. NRXN1 and its binding partner neuroligin have been associated with deficits in cognition. Recent genetics research has linked NRXN1 missense mutations to increased risk for brain disorders, including schizophrenia (SCZ) and autism spectrum disorder (ASD). Investigation of the structure–function relationship in NRXN1 has proven difficult due to a lack of the experimental full-length membrane protein structure. AlphaFold, a deep learning-based predictor, succeeds in high-quality protein structure prediction and offers a solution for membrane protein model construction. In the study, we applied a computational saturation mutagenesis method to analyze the systemic effects of missense mutations on protein functions in a human NRXN1 structure predicted from AlphaFold and an experimental Bos taurus structure. The folding energy changes were calculated to estimate the effects of the 29,540 mutations of AlphaFold model on protein stability. The comparative study on the experimental and computationally predicted structures shows that these energy changes are highly correlated, demonstrating the reliability of the AlphaFold structure for the downstream bioinformatics analysis. The energy calculation revealed that some target mutations associated with SCZ and ASD could make the protein unstable. The study can provide helpful information for characterizing the disease-causing mutations and elucidating the molecular mechanisms by which the variations cause SCZ and ASD. This methodology could provide the bioinformatics protocol to investigate the effects of target mutations on multiple AlphaFold structures. 

In this study, the chiral separation mechanisms of Dansyl amino acids, including Dansyl-Leucine (Dans-Leu), Dansyl-Norleucine (Dans-Nor), Dansyl-Tryptophan (Dans-Trp) and Dansyl-Phenylalanine (Dans-Phe) binding to poly-sodium N-undecanoyl-(L)-Leucylvalinate, poly (SULV), were investigated using molecular dynamics simulations. Micellar electrokinetic chromatography (MEKC) has previously shown that when separating the enantiomers of these aforementioned Dansyl amino acids, the L-enantiomers bind stronger to poly (SULV) than the D-enantiomers. This study aims to investigate the molecular interactions that govern chiral recognition in these systems using computational methods. This study reveals that the computationally-calculated binding free energy values for Dansyl enantiomers binding to poly (SULV) are in agreement with the enantiomeric order produced in experimental MEKC studies. The L-enantiomers of Dans-Leu, Dans-Nor, Dans-Trp, and Dans-Phe binding to their preferred binding pockets in poly(SULV) yielded binding free energy values of −21.8938, −22.1763, −21.3329 and −13.3349 kJ∙mol−1, respectively. The D-enantiomers of Dans-Leu, Dans-Nor, Dans-Trp, and Dans-Phe binding to their preferred binding pockets in poly(SULV) yielded binding free energy values of −14.5811, −15.9457, −13.6408, and −12.0959 kJ∙mol−1, respectively. Furthermore, hydrogen bonding analyses were used to investigate and elucidate the molecular interactions that govern chiral recognition in these molecular systems. 

Abstract In this study the chiral selectivity of l-undecyl-leucine (und-leu) for binapthyl derivatives was examined with the use of arginine and sodium counterions at pH’s ranging from 7 to 11. The objective of this project was to investigate whether a cationic amino acid, such as arginine would achieve enhanced chiral selectivity when utilized as the counterion in the place of sodium in micellar electrokinetic chromatography. The data indicate that und-leu has significantly improved chiral selectivity toward 1,1′-binaphthyl-2,2′-diyl hydrogenphosphate (BNP) enantiomers in the presence of arginine counterions in comparison to sodium and that, at least in the case of this study, the enantiomeric form of the arginine did not appear to play a role in the chiral selectivity. The maximum resolution (Rs) achieved for BNP when sodium was used as the counterion was ~0.6. However, when arginine was used as the counterion, the maximum resolution for BNP was ~4.1. This was an increase in resolution of ~ 7-fold. However, no significant difference was observed for the enantiomers of 1,1′-bi-2-naphthol. In order to learn more about why this might be the case, NMR studies were conducted to examine what role the counterion might play in enantiomeric recognition.