Quantitative analysis of human serum albumin–drug interactions using reversed-phase and ion-exchange liquid chromatography

Hanai, Toshihiko; Miyazaki, Rie; Kinoshita, Toshio

doi:10.1016/s0003-2670(98)00605-9

Cited by 14 publications

(10 citation statements)

References 11 publications

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“…Several attempts have been done to generate mathematical models to predict binding affinities to HSA from drug molecular structure, mainly for specific families of compounds. [43][44][45][46][47][48][49][50][51][52][53] Since much of the data has been obtained from high performance affinity chromatography experiments, these models are usually referred as QSRR (Quantitative Structure-Retention Relationships) ones, because the predicted variable is the compound retention factor in the column (K 0 HSA ). 44 Whether we call them QSRR models, or, using a more typical name, QSAR (Quantitative Structure-Activity Relationships) models, the present section attempts to gather and describe the corresponding equations present in the bibliography.…”

Section: Q S a R M O D E L S F O R D R U G -B I N D I N G A F F I Nmentioning

confidence: 99%

“…There are also some models derived for heterogeneous (although very small) sets of compounds in the bibliography. 51,52 In this case the binding constants were not obtained through affinity chromatography with HSA-immobilized stationary phases, but from a modified Hummer-Dryer method using purified HSA, and further analysis of the data using Scatchard plots. In a first article by these authors, a set of seven acidic drugs were studied.…”

Section: Table III Qsar Models For Drug-hsa Binding In the Bibliographymentioning

confidence: 99%

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In silico prediction of drug‐binding strengths to human serum albumin

Colmenarejo

2003

Medicinal Research Reviews

259

189

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Drug binding to Human Serum Albumin (HSA) is an area of intense research. The pharmacokinetics and pharmacodynamics of drugs are strongly affected by their binding to this protein. In this article, the field is reviewed, as well as our models to predict drug-binding affinities to HSA from drug structure. The physiological role of HSA is described, as well as its influence in drug action. The crystal structures of this protein are discussed, emphasizing the two drug-binding sites and the fatty acids binding sites observed therein. The advantages of using high-performance affinity chromatography to rapidly screen drugs for HSA binding are explained. The different QSAR models for HSA binding of restricted families of drugs (both from other groups and our group) are enumerated. Finally, a detailed description of our general models to predict drug-binding strengths to HSA from structure is given. It is expected for these models to be useful in drug design and pharmaceutical research.

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Section: Q S a R M O D E L S F O R D R U G -B I N D I N G A F F I Nmentioning

confidence: 99%

Section: Table III Qsar Models For Drug-hsa Binding In the Bibliographymentioning

confidence: 99%

In silico prediction of drug‐binding strengths to human serum albumin

Colmenarejo

2003

Medicinal Research Reviews

259

189

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“…However, the throughput of these assays is limited because of the need to directly detect the free compound, typically through HPLC or radiometric detection. As a result, alternative methods that make use of chromatography, [29] mass spectrometry, [30] microcalorimetry, [31] and fluorescence spectroscopy [32,33] have been proposed for measuring the affinity constant of a compound for HSA. NMR has also been used to monitor compound binding to albumin, with the earliest report being from Oleg Jardetzky's lab in the study of penicillin binding to albumin.…”

Section: Measuring Compound Affinity For Human Serum Albuminmentioning

confidence: 99%

NMR in Pharmacokinetic and Pharmacodynamic Profiling

2005

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“…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.…”

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confidence: 99%

Molecular Modeling for Quantitative Analysis of Molecular Interaction†

Hanai¹

2005

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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].

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Quantitative analysis of human serum albumin–drug interactions using reversed-phase and ion-exchange liquid chromatography

Cited by 14 publications

References 11 publications

In silico prediction of drug‐binding strengths to human serum albumin

In silico prediction of drug‐binding strengths to human serum albumin

NMR in Pharmacokinetic and Pharmacodynamic Profiling

Molecular Modeling for Quantitative Analysis of Molecular Interaction†

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Quantitative analysis of human serum albumin–drug interactions using reversed-phase and ion-exchange liquid chromatography

Cited by 14 publications

References 11 publications

In silico prediction of drug‐binding strengths to human serum albumin

In silico prediction of drug‐binding strengths to human serum albumin

NMR in Pharmacokinetic and Pharmacodynamic Profiling

Molecular Modeling for Quantitative Analysis of Molecular Interaction&#x2020;

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Molecular Modeling for Quantitative Analysis of Molecular Interaction†