Molecular Modeling for Quantitative Analysis of Molecular Interaction†

Abstract

The binding affinity (log nK) between human serum albumin and acidic drugs was quantitatively analyzed using a computational chemical method with several model phases. A flat guanidino-phase was the most efficient for calculating log nK values, and docking was easily performed. A flowerpot type model phase bonded a guanidino group at the center bottom demonstrating that ion-ion interaction was the main driving force. A large molecule pushed aside the hydrophobic wall of log P = 5, and reached the guanidino group. Ionized acidic compounds may reach the guanidino group inside a protein by ion-ion interaction through a narrow channel of length 10Å.Keywords: Drug-protein interaction, liquid chromatography, computational chemistry, ion-ion interaction. INTRODUCTIONcarry a variety of compounds and the affinity may not be specific. The main binding forces are hydrophobic interaction and ion-ion interaction, and specific steric effects may not be important. Previously, acidic drug-HSA and basic drug-HSA binding affinities were successfully determined by a combination of reversed-phase and ionexchange liquid chromatography without albumin [15][16][17]. Guanidino groups of arginine should work as anionexchange groups and carboxyl groups of aspartic and glutamic acids should work as cation-exchange groups. The chromatographic behavior of acidic and basic drugs was studied using guanidino-and carboxyl-phase columns, and their retention factors correlated well with their log nK values measured by the modified Hümmer-Dreyer method. Using a computational chemical calculation to analyze liquid chromatographic data, the direct interaction between a model-phase and a drug was calculated as energy values using the molecular mechanics (MM2) calculation.Computational chemistry using a model adsorbent is a new method for quantitative analysis of the retention of acidic drugs on a guanidino phase used for ion-exchange liquid chromatography of acidic drugs. The quantitative analysis of drug-albumin binding affinity using an albumin model in silico is difficult, due to the existence of several binding sites in albumin. But the quantitative analysis of retention in liquid chromatography is easy, because a homogenate model phase can be used instead of a complicated protein model for studying docking mechanisms. The computational chemical method demonstrated the possibility of estimating albuminacidic drug binding affinity without chemical experiments. The r 2 value was 0.922 (n = 13) between binding affinity values (log nK) and interaction energy values of the final structure (∆FS) [18].

Age-appropriate design of domestic intelligent medical products: An example of smart blood glucose detector for the elderly with AHP-QFD Joint KE

“…The common factor variance plot indicates the interpretation of the original information of the variable by the extracted common factor and the degree it achieves [ [57] , [58] , [59] ]; the closer the extracted value Is to 1, the more accurate the factor analysis of that variable is. As seen from Table 11 , with extracted values ranging from 0.793 to 0.957, most of the information in the variables of the glucose meter for older adults can be extracted by the common factor; therefore, the factor analysis results are valid.…”

Fundamental Properties of Packing Materials for Liquid Chromatography

“…Furthermore, sp 3 carbon atoms can form a honey comb-type homogeneous support [33]. The model phase was applied to analyze the retention times of phenolic compounds [34] and aromatic acids [35] in addition to drug-albumin binding affinity [36]. Model ion-exchangers were constructed and the chromatographic behavior of acidic drugs on a guanidino ion-exchanger [37] and basic compounds on a carboxyl ion-exchanger [38] was studied.…”

Ecological spectroscopic methodologies for quantifying co-administered drugs in human plasma by photochemical quantum mechanical simulation

“…To analyze the solute-solvent interactions, we use molecular dynamics simulations (MD) to calculate the non-bonding interaction and solvation energies which determine the magnitude of solute-solvent interactions [ 18 ]. We also use quantum mechanical (QM) analysis of the investigated compounds to reveal information about their excited states, the contributing molecular orbitals (MOs), the relation between the stability of each excited state and the utilized solvent, and the resulting morphology of the UV spectrum of each compound.…”