Mode of binding, kinetic and thermodynamic properties of a lipid-like drug (Fingolimod) interacting with Human Serum Albumin.

Introduction: Fingolimod is a drug that is used to treat multiple sclerosis (MS). It has pH-dependent solubility and low solubility when buffering agents are present. Multi-spectroscopic and molecular modeling methods were used to investigate the molecular mechanism of Fingolimod interaction with human serum albumin (HSA), and the resulting data were fitted to the appropriate models to investigate the molecular mechanism of interaction, binding constant, and thermodynamic properties. Methods: The interaction of Fingolimod with HSA was investigated in a NaCl aqueous solution (0.1 mM). The working solutions had a pH of 6.5. Data was collected using UV-vis, fluorescence quenching titrations, FTIR, and molecular modeling methods. Results: According to the results of the fluorescence quenching titrations, the quenching mechanism is static. The apparent binding constant value (KA = 4.26×103) showed that Fingolimod is a moderate HSA binder. The reduction of the KA at higher temperatures could be a result of protein unfolding. Hydrogen bonding and van der Waals interactions are the main contributors to Fingolimod-HSA complex formation. FTIR and CD characterizations suggested a slight decrease in the α-helix and ß-sheets of the secondary structure of HSA due to Fingolimod binding. Fingolimod binds to the binding site II, while a smaller tendency to the binding site I was observed as well. The results of the site marker competitive experiment and the thermodynamic studies agreed with the results of the molecular docking. Conclusion: The pharmacokinetic properties of fingolimod can be influenced by its HSA binding. In addition, considering its mild interaction, site II binding drugs are likely to compete. The methodology described here may be used to investigate the molecular mechanism of HSA interaction with lipid-like drugs with low aqueous solubility or pH-dependent solubility.

Investigations of the molecular mechanism of diltiazem binding to human serum albumin in the presence of metal ions, glucose and urea.

The molecular mechanism and thermodynamic properties of the interaction between diltiazem (DTZ) and human serum albumin (HSA), has been studied in vitro using spectroscopic techniques (UV-Vis, fluorescence, FTIR), and molecular docking methods. The effect of acidic and basic pH, glucose, urea, and metal ions on the DTZ-HSA binding has been investigated as well. According to the results, there is a 1:1 interaction between DTZ and HSA, while the quenching mechanism is static up to 313 K. The apparent binding constant was 2.09 × 106 M-1 that indicates a strong binding between DTZ and HSA. DTZ binding was increased in acidic pH while its binding was slowly decreased in the presence of glucose, urea, and metal ions. Thermodynamic studies showed that DTZ binds to HSA via an exothermic and spontaneous reaction via hydrogen bonding and electrostatic interactions. The conformational alteration of HSA is obvious according to the FTIR study. The site marker competitive study confirmed the binding of DTZ to the warfarin binding site. Molecular docking studies showed that DTZ binds to subdomain IB (-9.22 kcal mol-1) and subdomain IIIA (-9.03 kcal mol-1) with a higher tendency. Also, the results showed that the oxygen and nitrogen atoms of hydroxyl and amino functional groups of DTZ facilitate hydrogen bond formation. HighlightsStrong binding of diltiazem to HSA was studied and confirmed by fluorescence quenching titrations.Diltiazem binding to HSA reduces in the presence of metal ions, glucose, urea and alkaline pH.Diltiazem binding to HSA is exothermic and spontaneous.

Kinetic and thermodynamic study of beta-Boswellic acid interaction with Tau protein investigated by surface plasmon resonance and molecular modeling methods.

Introduction: Beta-Boswellic acid (BBA) is a pentacyclic terpene which has been obtained from frankincense and its beneficial effects on neurodegenerative disorders such as Alzheimer's disease (AD) have been addressed. Methods: In the present study, thermodynamic and kinetic aspects of BBA interaction with Tau protein as one of the important proteins involved in AD in the absence and presence of glucose has been investigated using surface plasmon resonance (SPR) method. Tau protein was immobilized onto the carboxy methyl dextran chip and its binding interactions with BBA were studied at physiological pH at various temperatures. Glucose interference with these interactions was also investigated. Results: Results showed that BBA forms a stable complex with Tau (KD=8.45×10-7 M) at 298 K. Molecular modeling analysis showed a hydrophobic interaction between BBA and HVPGGG segment of R2 and R4 repeated domains of Tau. Conclusion: The binding affinity increased by temperature enhancement, while it decreased significantly in the presence of glucose. Both association and dissociation of the BBA-Tau complex were accompanied with an entropic activation barrier; however, positive enthalpy and entropy changes revealed that hydrophobic bonding is the main force involved in the interaction.

QSBR study of bitter taste of peptides: application of GA-PLS in combination with MLR, SVM, and ANN approaches.

Detailed information about the relationships between structures and properties/activities of peptides as drugs and nutrients is useful in the development of drugs and functional foods containing peptides as active compounds. The bitterness of the peptides is an undesirable property which should be reduced during drug/nutrient production, and quantitative structure bitter taste relationship (QSBR) studies can help researchers to design less bitter peptides with higher target efficiency. Calculated structural parameters were used to develop three different QSBR models (i.e., multiple linear regression, support vector machine, and artificial neural network) to predict the bitterness of 229 peptides (containing 2-12 amino acids, obtained from the literature). The developed models were validated using internal and external validation methods, and the prediction errors were checked using mean percentage deviation and absolute average error values. All developed models predicted the activities successfully (with prediction errors less than experimental error values), whereas the prediction errors for nonlinear methods were less than those for linear methods. The selected structural descriptors successfully differentiated between bitter and nonbitter peptides.