Analysis of drug interactions with serum proteins and related binding agents by affinity capillary electrophoresis: A review

✅ 全文

亲和毛细管电泳法分析药物与血清蛋白及相关结合剂的相互作用:综述

作者 Sadia Sharmeen; Isaac Kyei; Arden Hatch; David S. Hage 期刊 Electrophoresis 发表日期 2022 ISSN 0173-0835 DOI 10.1002/elps.202200191 类型 原创研究 (Original Research)

📄 中文摘要 Chinese Abstract

中文
当药物进入血液后,常与血清蛋白(如人血清白蛋白(HSA)、α1-酸性糖蛋白(AGP)和脂蛋白)发生相互作用,从而影响其药代动力学、药效学及整体治疗效果。这些相互作用可能具有立体选择性,对手性药物的不同构型产生差异性影响,并受到内源性物质或联合用药竞争的调控。因此,准确表征药物-蛋白结合特性在药物开发、监测和诊断中至关重要。亲和毛细管电泳(ACE)因其高效率、低样品需求及近生理条件操作能力,已成为研究这些相互作用的有力技术手段。

📋 英文结构化总结 English Structured Summary

全文整理

EN

Background:

When a drug enters the bloodstream, it often interacts with serum proteins such as human serum albumin (HSA), alpha 1-acid glycoprotein (AGP), and lipoproteins, which can influence its pharmacokinetics, pharmacodynamics, and overall therapeutic efficacy. These interactions may be stereoselective, affecting chiral drug forms differently, and are modulated by competition with endogenous substances or co-administered drugs. Accurate characterization of drug–protein binding is therefore essential in drug development, monitoring, and diagnostics. Affinity capillary electrophoresis (ACE) has emerged as a powerful technique to study these interactions due to its high efficiency, minimal sample requirements, and ability to operate under near-physiological conditions.

Methods:

This review article examines the principles and applications of affinity capillary electrophoresis (ACE) and related affinity-based CE methods for analyzing drug interactions with serum proteins and other binding agents. The authors describe various ACE formats—including mobility shift ACE, vacancy ACE, Hummel–Dreyer ACE, frontal analysis ACE, partial-filling ACE, and multiple-step ligand injection ACE—and discuss their underlying theoretical frameworks, data analysis methods (e.g., nonlinear regression, Scatchard plots), and experimental considerations such as electroosmotic flow corrections and buffer composition. The review also covers both homogeneous (solution-phase) and heterogeneous (immobilized binding agent) approaches, as well as hybrid techniques like CE-based immunoassays and chiral separations using serum proteins.

Results:

ACE and related CE methods have been successfully applied to quantify binding constants, stoichiometries, and kinetics for numerous drug–protein systems. Examples include the use of mobility shift ACE to study interactions between HSA and catechins, heparinoids, or fluoroquinolones; frontal analysis ACE to characterize binding of β-blockers and NSAIDs to HSA and AGP; and partial-filling ACE to assess displacement studies involving retinol/retinoic acid with HSA. Chiral separations using HSA or AGP as chiral selectors have enabled enantioselective binding analysis for drugs like verapamil, omeprazole, and disopyramide. Hybrid methods, including CE coupled with mass spectrometry or immunoassays, have further expanded the utility of ACE in complex biological matrices.

Data Summary:

Over 2,500 publications on ACE and affinity-based CE for drug–protein interactions appeared between 1990 and 2022, reflecting growing adoption. Binding constants (Kₐ) reported in reviewed studies typically range from 10² to 10⁶ M⁻¹, depending on the drug–protein pair. For example, warfarin binding to BSA yielded Kₐ values around 10⁴–10⁵ M⁻¹, while loureirin B binding to HSA was characterized with high precision using both frontal analysis and partial-filling ACE. Enantioselective binding differences were observed, such as distinct affinities of (R)- and (S)-amlodipine to HSA. The methods generally require only picoliter-to-nanoliter sample volumes and microgram quantities of protein.

Conclusions:

ACE and affinity-based CE methods offer versatile, efficient, and low-consumption platforms for studying drug–serum protein interactions. They provide critical information on binding affinity, kinetics, stoichiometry, and stereoselectivity, supporting drug discovery and clinical monitoring. Recent advances—including online mixing, partial-filling strategies, and coupling with MS or immunoassays—have enhanced applicability to complex or low-abundance systems. The integration of serum proteins as both binding agents and chiral selectors further demonstrates the multifunctional role of these techniques in pharmaceutical analysis.

Practical Significance:

These ACE-based approaches are directly applicable in pharmaceutical development for screening drug candidates, optimizing dosing regimens, and predicting drug–drug interactions. Their compatibility with biological fluids allows direct analysis of serum samples, enabling personalized medicine and therapeutic drug monitoring. Additionally, the ability to resolve and quantify enantiomers supports regulatory compliance in chiral drug development, making ACE a valuable tool in both research and clinical laboratories.

📋 中文结构化总结 Chinese Structured Summary

中文

背景:

当药物进入血液后,常与血清蛋白(如人血清白蛋白(HSA)、α1-酸性糖蛋白(AGP)和脂蛋白)发生相互作用,从而影响其药代动力学、药效学及整体治疗效果。这些相互作用可能具有立体选择性,对手性药物的不同构型产生差异性影响,并受到内源性物质或联合用药竞争的调控。因此,准确表征药物-蛋白结合特性在药物开发、监测和诊断中至关重要。亲和毛细管电泳(ACE)因其高效率、低样品需求及近生理条件操作能力,已成为研究这些相互作用的有力技术手段。

方法:

本综述文章系统阐述了亲和毛细管电泳(ACE)及相关亲和CE方法在分析药物与血清蛋白及其他结合剂相互作用中的原理与应用。作者详细介绍了多种ACE模式,包括迁移率变动ACE、空穴ACE、Hummel-Dreyer ACE、前沿分析ACE、部分填充ACE及多步配体注射ACE,并讨论了其理论基础、数据分析方法(如非线性回归、Scatchard图)以及实验考量因素(如电渗流校正和缓冲液组成)。综述还涵盖了均相(溶液相)和非均相(固定化结合剂)方法,以及基于CE的免疫分析和使用血清蛋白的手性分离等混合技术。

结果:

ACE及相关CE方法已成功应用于多种药物-蛋白系统的结合常数、化学计量比和动力学参数定量分析。实例包括:利用迁移率变动ACE研究HSA与儿茶素、肝素类物质或氟喹诺酮类药物的相互作用;利用前沿分析ACE表征β-受体阻滞剂和非甾体抗炎药与HSA和AGP的结合特性;利用部分填充ACE评估视黄醇/视黄酸与HSA的置换研究。以HSA或AGP为手性选择剂的手性分离技术实现了维拉帕米、奥美拉唑和丙吡胺等药物的对映选择性结合分析。混合方法(包括CE与质谱联用或免疫分析联用)进一步拓展了ACE在复杂生物基质中的应用范围。

数据总结:

1990年至2022年间,关于ACE及亲和CE用于药物-蛋白相互作用的出版物超过2500篇,反映出该技术的日益普及。文献报道的结合常数(Kₐ)通常在10²至10⁶ M⁻¹范围内,具体取决于药物-蛋白配对。例如,华法林与BSA结合的Kₐ值约为10⁴-10⁵ M⁻¹,而路路通B与HSA的结合则通过前沿分析和部分填充ACE实现了高精度表征。研究还观察到对映选择性结合差异,如(R)-和(S)-氨氯地平对HSA具有不同的亲和力。这些方法通常仅需皮升至纳升级的样品体积和微克量的蛋白。

结论:

ACE及亲和CE方法为研究药物-血清蛋白相互作用提供了多功能、高效且低消耗的技术平台。它们能够提供结合亲和力、动力学、化学计量比和立体选择性等关键信息,支持药物发现和临床监测。最新进展(包括在线混合、部分填充策略以及与质谱或免疫分析的联用)增强了该方法在复杂或低丰度体系中的适用性。血清蛋白同时作为结合剂和手性选择剂的整合应用,进一步证明了这些技术在药物分析中的多功能作用。

实际意义:

这些基于ACE的方法可直接应用于药物开发中的候选药物筛选、给药方案优化及药物相互作用预测。其与生物流体的兼容性允许直接分析血清样本,从而实现个体化医疗和治疗药物监测。此外,对映体的分离与定量能力支持手性药物开发中的法规合规性,使ACE成为研究和临床实验室中极具价值的工具。

📖 英文全文 English Full Text

EN

pmc Electrophoresis Electrophoresis 379 blackwellopen ELPS Electrophoresis 0173-0835 1522-2683 pmc-is-collection-domain yes pmc-collection-title Wiley Open Access Collection PMC10098505 PMC10098505.1 10098505 10098505 36250426 10.1002/elps.202200191 ELPS7726 1 Review SPECIAL FOCUS ON BINDING PROPERTIES 2022 General, CE & CEC Analysis of drug interactions with serum proteins and related binding agents by affinity capillary electrophoresis: A review SHARMEEN et al. Sharmeen Sadia

1 Kyei Isaac 1 Hatch Arden 1 Hage David S. https://orcid.org/0000-0003-1145-5003

1 dhage1@unl.edu

1

Department of Chemistry University of Nebraska–Lincoln

Lincoln Nebraska USA

* Correspondence David S. Hage, Chemistry Department, University of Nebraska–Lincoln, Lincoln, NE 68588‐0304, USA. Email: dhage1@unl.edu

10 11 2022 12 2022 43 23-24 433423 10.1002/elps.v43.23-24 Binding Properties 2022 2302 2323

17 9 2022 23 7 2022 05 10 2022 13 04 2023 14 04 2023 15 09 2024 © 2022 The Authors. Electrophoresis published by Wiley‐VCH GmbH. https://creativecommons.org/licenses/by-nc/4.0/ This is an open access article under the terms of the http://creativecommons.org/licenses/by-nc/4.0/ License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited and is not used for commercial purposes. Abstract Biomolecules such as serum proteins can interact with drugs in the body and influence their pharmaceutical effects. Specific and precise methods that analyze these interactions are critical for drug development or monitoring and for diagnostic purposes. Affinity capillary electrophoresis (ACE) is one technique that can be used to examine the binding between drugs and serum proteins, or other agents found in serum or blood. This article will review the basic principles of ACE, along with related affinity‐based capillary electrophoresis (CE) methods, and examine recent developments that have occurred in this field as related to the characterization of drug–protein interactions. An overview will be given of the various formats that can be used in ACE and CE for such work, including the relative advantages or weaknesses of each approach. Various applications of ACE and affinity‐based CE methods for the analysis of drug interactions with serum proteins and other binding agents will also be presented. Applications of ACE and related techniques that will be discussed include drug interaction studies with serum agents, chiral drug separations employing serum proteins, and the use of CE in hybrid methods to characterize drug binding with serum proteins. affinity capillary electrophoresis drug–protein binding Hummel–Dreyer method mobility shift assay serum proteins National Science Foundation

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Sharmeen S , Kyei I , Hatch A , Hage DS . Analysis of drug interactions with serum proteins and related binding agents by affinity capillary electrophoresis: A review . Electrophoresis . 2022 ; 43 : 2302 – 2323 . 10.1002/elps.202200191

36250426 PMC10098505 Abbreviations AGP alpha 1‐acid glycoprotein CE FA frontal analysis ACE ECEEM equilibrium capillary electrophoresis of equilibrated mixtures FTPFACE flow through partial filling ACE HD ACE Hummel–Dreyer ACE LDL low‐density lipoprotein ms ACE mobility shift ACE MSLIACE multiple steps ligand injection ACE NECEEM nonequilibrium capillary electrophoresis of equilibrium mixtures PFACE partial‐filling ACE VACE vacancy ACE 1 INTRODUCTION When a drug enters the blood circulatory system, it may interact with serum proteins or other carrier agents in blood as the drug is transported to its target tissue or receptors to create a therapeutic response [ 1 , 2 , 3 ]. Because the binding of some drugs to proteins can be stereoselective in nature, it is also possible that these interactions may play a role in determining the fate of the different forms of a chiral drug within the body [ 4 , 5 , 6 , 7 ]. In addition, the non‐bound drug (or free form) in the blood circulation is often influenced by interactions of the drug with serum proteins, which can affect the drug's pharmacokinetic and pharmacodynamic properties. The binding of a drug with serum agents and the size of the resulting non‐bound drug fraction can further be affected by competition between the drug and endogenous compounds (e.g., bilirubin, fatty acids) in the blood circulatory system [ 8 , 9 , 10 , 11 ]. Similar effects can occur when a mixture of drugs is administered and direct or indirect competition occurs between two drugs for the same binding proteins [ 1 , 12 ]. Thus, the characterization of drug–protein interactions in serum has great importance during the discovery or development of new drugs and for monitoring and understanding the effect of drugs during their use to treat disease [ 12 ]. There are many methods that have been used to examine drug interactions with proteins and other agents that occur in serum and blood. Two common reference methods for such studies are equilibrium dialysis and ultrafiltration [ 5 ]. Other approaches for this work have included spectroscopic methods based on the measurement of surface plasmon resonance, UV/Vis or infrared absorbance, fluorescence, circular dichroism, and nuclear magnetic resonance [ 13 , 14 , 15 , 16 , 17 , 18 , 19 ]. Additional methods that can be used for such studies are mass spectrometry, affinity chromatography, electrophoresis, partial artificial membrane permeability assays, and isothermal calorimetry [ 13 , 17 , 18 , 19 , 20 ]. However, many of these techniques are slow, require a relatively large amount of sample or binding agent, or are expensive to perform [ 21 ]. Affinity capillary electrophoresis (ACE) is one method that has been developed and explored as a means to overcome many of the limitations in other techniques for drug–protein binding studies [ 20 , 22 , 23 , 24 , 25 ]. ACE combines the use of a system for capillary electrophoresis (CE) with a biologically related binding agent that is used to capture or separate analytes as they are resolved from other sample components based on their differences in electrophoretic mobility [ 26 ]. For instance, if the binding agent is present in the background electrolyte (BGE) and the charge‐to‐size ratio of the analyte changes when it interacts with this binding agent, there will be a shift in the observed mobility for the analyte as it goes from its free to bound forms [ 27 , 28 ]. This allows the binding agent to affect the separation of the analyte from other components in the sample but also provides a means for characterizing the analyte–binding agent interaction [ 28 ]. CE can be carried out by using a binding agent in either a soluble form or in an immobilized form, as shown in Figure 1 [ 29 ]. When the target binding agent is present in a soluble form, the analytes and binding agent interact within the BGE as they pass through the CE system [ 7 , 30 ]. In this method, the separation depends on the mobilities of the free analyte versus the analyte–binding agent complex [ 7 , 31 ]. Alternatively, the binding agent may be immobilized or adsorbed within the capillary, resulting in a separation technique based on electrochromatography [ 26 , 30 , 32 , 33 ]. ACE and related CE methods can provide various types of information on drug–protein interactions. Examples of this information are the binding constant between a drug and protein, the rate constants for this interaction, and the binding stoichiometry [ 34 , 35 , 36 ]. This information is crucial for the evaluation of drug affinity to a given target protein and in understanding the mechanism by which a drug associates with a protein [ 5 , 13 ]. In addition, CE can provide information on the charge of the complex that is formed by this process [ 27 , 36 ]. CE‐based techniques have many potential advantages over alternative methods for drug‐binding studies. For instance, these CE methods frequently require only a small amount of binding agent and have sample injection volumes in the pl–nl range [ 37 , 38 , 39 ]. CE is also noted for having short separation times and high separation efficiencies [ 37 ]. In addition, ACE and related techniques often do not require a prior purification of the sample, which means that biological fluids can be injected directly into the capillary [ 38 ]. Affinity‐based CE approaches can also be used in some cases to examine binding by multiple solutes to a given agent, as demonstrated in the use of such methods to screen a library of candidates for binding to the same target as part of combinatorial studies [ 34 , 40 ]. As is shown in Figure  2 , more than 2500 articles have appeared since 1990 on the use of ACE and related methods to study drug–protein binding or to use these interactions as part of a chemical separation. This review will examine the principles and applications of ACE and affinity‐based CE, with an emphasis on systems that involve drug interactions with serum proteins or related binding agents and on recent developments that have appeared in this area. The analysis formats that have been used in this field will be discussed, along with their advantages or potential limitations. Applications of ACE and related techniques that will be described will include drug–protein interaction studies, chiral drug separations that employ serum proteins, and the use of CE in hybrid methods to characterize drug binding with serum agents. 2 SERUM‐BINDING AGENTS USED IN ACE AND DRUG INTERACTION STUDIES Several types of serum‐binding agents have been used in ACE or other forms of CE for separations and drug‐binding studies. Two examples are the major serum proteins human serum albumin (HSA) and bovine serum albumin (BSA) [ 14 , 41 ]. HSA is a single chain, non‐glycosylated protein with a molar mass of 66.5 kDa. HSA contains 585 amino acids and has an isoelectric point of 4.7 [ 42 ]. BSA has a similar molar mass and composition to HSA but only contains 583 amino acids [ 43 ]. Both HSA and BSA have two major drug‐binding sites: Sudlow site I, which is located in subdomain IIA, and Sudlow site II, which is in subdomain IIIA (see Figure  3 ) [ 41 ]. Sudlow site I has a hydrophobic cavity with two clusters of ionic/polar residues. This site tends to bind to drugs that are bulky, heterocyclic compounds with negative or electronegative groups, such as warfarin, azapropazone, phenylbutazone, and salicylate [ 42 , 44 ]. Sudlow site II has a cluster of cationic residues near its hydrophobic pocket and tends to bind drugs through a combination of hydrophobic, hydrogen bonding, and electrostatic interactions. Examples of compounds that bind to Sudlow site II are aliphatic and aromatic carboxylates such as benzodiazepines, ketoprofen, and l ‐tryptophan [ 42 , 44 ]. Another important plasma protein for the transport of drugs is alpha 1‐acid glycoprotein (AGP) [ 42 ]. Human AGP is a heavily glycosylated protein that has a single chain of 183 amino acids and a typical molar mass between 41 and 43 kDa [ 42 , 45 ]. AGP has a low isoelectric point (2.8–3.8) due to the sialic acid groups in its carbohydrate chains [ 42 ]. A heterogenous mixture of bi‐, tri‐, and tetra‐antennary glycans are attached to five N‐linked glycosylation sites on AGP [ 42 , 45 ]. AGP tends to bind to neutral or cationic drugs and has a high affinity, low‐capacity binding site with three lobes. This site includes a hydrophobic lobe that is surrounded by two negatively charged lobes, which can provide strong binding by drugs to this region [ 42 , 45 ]. An additional set of serum‐binding agents for drugs and small organic solutes are lipoproteins [ 46 , 47 ]. Lipoproteins consist of a hydrophobic core, containing materials such as cholesterol ester and triglycerides, that is surrounded by a shell of phospholipids and free cholesterol that also includes apolipoproteins [ 46 , 47 ]. Plasma lipoproteins are classified based on their densities, giving categories such as high‐density lipoprotein and low‐density lipoprotein (LDL) [ 46 , 48 ]. Plasma lipoproteins bind and transport cholesterol and triglycerides, as well as some hydrophobic and/or basic drugs, in the bloodstream [ 48 ]. 3 GENERAL PRINCIPLES OF ACE IN THE STUDY OF DRUG–PROTEIN INTERACTIONS A typical system that is used for ACE and other forms of CE is illustrated in Figure  4 [ 37 , 38 ]. This system requires a BGE that is placed in the capillary of the CE system and held in two reservoirs that are in contact with the electrodes (i.e., the anode and cathode). The electrodes are used to apply an electric field across the capillary [ 37 , 38 ]. Other components of this system include the separation cartridge (i.e., which houses the capillary), a power supply, an injection system, a computer for data acquisition and system control, and a detector [ 37 , 38 ]. The detector is placed at the opposite end of the capillary to the injection site. Modern CE systems can include online detectors based on UV–vis absorbance, laser‐induced florescence, electrochemical detection, or mass spectrometry [ 37 , 38 ]. The capillary in CE has a typical inner diameter of 20–100 µm and a length of 20–100 cm. The use of a capillary with a small internal diameter provides a high surface‐to‐volume ratio and efficient dissipation of Joule heat, thus allowing the use of a high applied electric potential (i.e., up to 25–30 kV) [ 38 , 49 ]. Both coated and uncoated capillaries are used in CE [ 23 , 24 , 25 , 50 , 51 , 52 , 53 , 54 , 55 ], with the uncoated capillaries typically being made from bare fused silica [ 23 , 24 , 25 ]. Polyimide is usually employed as a coating on the outside of silica capillaries to make them less fragile; however, part of this coating is removed near one end of the capillary to provide a window when using optical detection for analytes [ 27 ]. Capillaries with either permanent or dynamic coatings have also been used in CE and ACE [ 50 , 51 , 52 , 53 ]. A permanent coating consists of a chemical layer that is covalently bound to the interior of the capillary, whereas a dynamic coating makes use of noncovalent adsorption to reversibly place a coating material onto the inner wall of the capillary [ 50 , 51 , 52 ]. Injection of the analytes into a CE system is performed by temporarily replacing one of buffer reservoirs with a sample vial [ 38 ]. A defined amount of sample, often in the range of pl–nl, is introduced into the capillary by either using hydrodynamic flow or electromigration [ 38 ]. In the hydrodynamic mode, the sample is injected into the capillary by applying a pressure difference between the two ends of the capillary [ 56 ]. This injection mode is often chosen when low viscosity buffers are used for CE or ACE [ 56 , 57 ]. For the electromigration or electrokinetic mode of injection, sample is introduced into the capillary in the presence of an applied potential [ 56 ]. In this method, the amount of an injected substance will depend on the mobility of this compound and can vary between different analytes in the sample [ 56 , 58 ]. Electroosmotic flow (EOF) is an important phenomenon that must be considered in CE and ACE. If a silica capillary is used, EOF is produced when a negative charge is present on the interior wall of the capillary due to the acid dissociation of silanol groups [ 50 , 51 ]. This negative charge attracts cations from the BGE, creating a fixed Helmholtz plane and a mobile outer layer of charge [ 50 , 51 ]. In the presence of an applied potential, cations in the outer mobile layer are pulled toward the negative electrode (or cathode) [ 51 ]. This situation results in a net movement of the BGE and its solutes toward the cathode, where a detector can be located to monitor analytes that are migrating with or against the EOF [ 51 ]. The size of the EOF will depend on such factors as temperature, the amount of charge on the interior surface of the capillary, and the pH of the BGE [ 59 , 60 , 61 ]. CE can be conducted in either a normal polarity mode or reversed polarity mode [ 37 , 38 , 49 , 50 , 51 , 62 ]. In the normal polarity mode, the sample is injected at the anode end of a silica capillary, with the sample components then migrating with different migration velocities and in the presence of the EOF to a detector located near the cathode end [ 37 , 38 ]. In the reversed polarity mode, the CE separation is carried out in the presence of suppressed or absent EOF. Under these conditions, the sample is injected at the electrode with same relative charge as the analytes, with these analytes then traveling through electromigration to the electrode of the opposite charge [ 62 ]. For instance, in the reversed polarity mode, a sample containing anions would be injected at the cathode end of the capillary and detected as they migrate to the anode end [ 62 ]. 4 PRINCIPLES OF ACE FOR STUDYING DRUG–PROTEIN INTERACTIONS The binding of many drugs with serum proteins and related agents can be described as a reversible and noncovalent process [ 39 ]. This process can be represented by the following reaction and equations, where a drug (D) binds to a serum protein (P) or similar agent to form a drug–protein/binding agent complex (C) [ 5 ].

(1) D + P ⇌ C

(2) K a = k on k off = C D P

(3) K d = 1 K a = k off k on = D P C

In these relationships, [D] and [P] are the equilibrium molar concentrations of the non‐bound forms of the drug and the protein or binding agent, respectively, and [C] is the equilibrium molar concentration of their complex. The terms k on and k off are the association and dissociation rate constants for this reaction, whereas K a and K d are the corresponding association and dissociation equilibrium constants for this process. This description is a simplification of the overall steps that are involved as a drug forms a reversible complex with a serum protein or related agent. However, Equations ( 1 )–( 3 ) usually provide a good description of the overall extent and net reaction rate of such a process [ 5 , 39 , 63 ]. One possible exception occurs when allosteric interactions are present, for which more complex reaction models should instead be employed [ 5 ]. One method that can be used in ACE to study drug–protein interactions is a mobility shift assay (see Section  5.1.1 ). This method is used when a drug and a protein/binding agent have fast association/dissociation kinetics during their reaction, and there is a significant difference in mobilities for the non‐bound form of the drug and drug–binding agent complex [ 5 , 39 , 63 , 64 ]. Under these conditions, a shift should be seen in the overall position of the drug's peak during CE as the concentration of the binding agent within the BGE and capillary is varied (see Figure  5A ) [ 65 ]. The apparent mobility (μ app ) of the drug is calculated from the experimental data by using Equation ( 4 ) along with the known total length of the capillary ( L t o t ) , the effective length of the capillary from the injection end to the location of the detection window ( L e f f ), the measured migration time for the drug ( t ), and the applied voltage ( V ) [ 5 ]:

(4) μ app = L eff L tot tV

When ACE is used to estimate association or dissociation equilibrium constants, the mobility of the drug (μ) can be obtained from the drug's apparent electrophoretic mobility by making a separate measurement of the mobility due to EOF (μ EOF ) and using the relationship shown in the following equation:

(5) μ = μ app − μ EOF

In the case where a drug's observed mobility changes as the binding agent concentration is varied, the binding constant for this system can be obtained by using the following equation [ 63 ]:

(6) μ = μ f + μ C K a P 1 + K a P

In this relationship, μ C and μ f are the effective electrophoretic mobilities of the complex and the free, non‐bound drug [ 5 , 39 , 63 , 64 ]. Factors such as temperature, ionic strength, change in solution viscosity, and interactions of proteins with the capillary wall, all of which may affect the observed mobilities, should be taken in account when using such equations [ 66 ]. Nonlinear least squares regression based on Equation ( 6 ) or related expressions is the current preferred approach for obtaining binding constants from ACE data [ 63 , 67 , 68 ]. However, Equation ( 6 ) can also be rearranged into a linear form by using one of the following relationships [ 5 , 69 ]:

(7) μ − μ f P = − K a μ − μ f + K a μ C − μ f

(8) P μ − μ f = 1 ( μ C − μ f ) P + 1 μ C − μ f K a

(9) 1 μ − μ f = 1 ( μ C − μ f ) K a 1 P + 1 μ C − μ f

When using Equation ( 7 ), a plot of ( μ − μ f ) [ P ] versus ( μ − μ f ) should produce a best fit line with a slope that gives the value of the association equilibrium constant ( K a ) [ 5 , 69 ]. One advantage of this equation is it does not have any co‐dependence in the left‐ and right‐hand terms on the value of [P] [ 5 ]. Several reports have suggested the use of such data treatment to evaluate the binding constants of drug–protein interactions [ 30 , 36 , 40 , 64 , 70 ]. In addition, analysis based on Equation ( 7 ) can be valuable when work is being carried out with a large or a highly charged binding agent (e.g., protein) that does not exhibit a significant mobility shift upon binding to the drug of interest [ 5 ]. Reciprocal plots can also be prepared based on Equations ( 8 ) and ( 9 ). For Equation ( 8 ), a plot of [ P ] ( μ − μ f ) versus [P] can provide the value of K a from the ratio of the slope to the intercept. For Equation ( 9 ), a plot of 1 ( μ − μ f ) versus 1 [ P ] gives the value of K a from the ratio of the intercept to the slope [ 5 , 69 , 70 ]. The same type of relationships, as given in Equations ( (7) , (8) , (9) ), can be employed to estimate a binding constant by reversing the role of drug and protein. For instance, this can be done by using [D] in place of [P] in Equations ( 7 )–( 9 ) [ 40 ]. This approach is useful in situations where only small amounts of a protein or peptide are available or in which a mixture of multiple proteins and peptides is present in the sample [ 40 , 68 , 69 , 71 ]. A statistical advantage of using nonlinear regression based on Equation (6) instead of linear regression with Equations ( 7 )–( 9 ) is the former approach avoids a dependent variable appearing in both the x ‐ and y ‐axis values that are used for data analysis [ 63 , 67 , 68 , 72 ]. If variations in the EOF are present during the study of drug–protein binding, a correction for these variations can be made through the use of mobility ratios [ 23 , 24 , 25 , 27 , 39 , 73 , 74 , 75 ]. For instance, a mobility ratio ( M ) can be calculated by using the following equation [ 73 , 74 , 75 ]:

(10) M = μ + μ EOF μ EOF

Based on the definition of μ that was given in Equation ( 4 ), factors such as L tot , L eff , and V that are the same for the analyte and EOF will appear in both the numerator and denominator in Equation ( 10 ) and be removed as sources of variation when using a mobility ratio. This is indicated more clearly by an equivalent expression for the mobility ratio that is provided in Equation ( 11 ) [ 73 , 74 , 75 ],

(11) M = t EOF t + 1 where t EOF is the migration time of an EOF marker and t is the migration time of the analyte. The fact that mobility ratios are independent of capillary length, applied voltage, and variations in the EOF makes these values a more reproducible means of estimating binding constants by ACE than the direct use of absolute mobilities or migration times [ 73 , 74 , 75 ]. 5 APPROACHES OF ACE USED IN THE STUDY OF DRUG–PROTEIN INTERACTIONS ACE can be performed in several modes to study drug–protein binding or other types of biomolecular interactions. The first mode is used when the kinetics of the interaction are relatively fast on the time scale of the CE separation, creating a dynamic equilibrium in the system [ 30 , 40 ]. The second mode is based on the use of pre‐equilibration of the interacting components [ 25 , 30 , 40 ]. The third mode is known as kinetic ACE and is used for systems with intermediate reaction rates that are similar to the CE separation time [ 69 ]. Each of these modes is described in more detail in this section. 5.1 Dynamic equilibrium mode of ACE There are several approaches that can be used when two interacting components have a relatively fast rate of binding and dissociation, thus allowing a dynamic equilibrium to be created as these components pass through a CE system. Techniques that can be employed in this situation include mobility shift ACE (ms ACE), ACE assays based on vacancy peaks, and ACE techniques that use the Hummel–Dreyer method [ 7 , 69 , 71 , 76 , 77 , 78 , 79 , 80 , 81 ]. 5.1.1 Mobility shift ACE ms ACE has been used in many studies to examine drug–protein interactions [ 2 , 35 , 39 , 82 , 83 , 84 , 85 , 86 , 87 , 88 ]. In this method, several concentrations of one of the interacting agents (i.e., the binding target, T) are placed into the BGE of the CE system. A fixed concentration of the complementary agent (i.e., the drug or analyte, A) is dissolved in BGE, usually with an EOF marker, and injected as a sample. The apparent mobility of the injected agent and the mobility of the EOF marker are then determined from the corresponding electropherograms (see Figure  5A ). The observed mobility shift of the injected agent is then related to the concentration of the complementary component in the BGE and used to find the binding constant for the system [ 89 ]. This type of analysis is typically carried out by using a concentration for the binding target in the BGE that is 10–100 times higher than the concentration of the injected analyte [ 90 ]. The temporal and spatial variations in the concentration of the binding target along the zone of the injected analyte are generally negligible under these conditions because the BGE contains a large excess of the target [ 2 ]. Careful analysis of peak shapes and widths along with the determination of mobility and the elution profile can be used in ms ACE to provide information on both equilibrium and kinetic parameters for a biological interaction [ 91 , 92 , 93 , 94 , 95 , 96 , 97 , 98 ]. The simplicity of ms ACE and its ease of data evaluation make this method appealing for the study of drug–protein interactions [ 2 , 99 ]. However, ms ACE does have disadvantages. For instance, the use of a high concentration of the target can produce systematic errors (e.g., by changing the viscosity and ionic strength of the BGE) when estimating a binding constant [ 85 , 86 ]. Corrections for this must be made to minimize any associated errors in the analysis of binding [ 74 , 90 , 100 ]. In addition, factors such as temperature, buffer electrolysis, and the characteristics of the capillary surface (e.g., if one of the two binding partners can adsorb onto the capillary) must be considered as these can affect the reproducibility of the migration times [ 74 ]. The use of a relatively high concentration of the injected analyte in ms ACE may be needed to obtain a sufficient signal but can introduce deviations in the local concentration of the binding target in the BGE [ 91 , 92 , 101 ]. Use of an analyte concentration that is too high can also result in shifts in the observed mobility for this agent [ 102 ]. ms ACE has been used to examine many types of drug–protein interactions and related systems [ 6 , 61 , 75 , 103 ]. For example, ms ACE has been used to analyze the interactions of heparin with antithrombin variants [ 104 ]. Other reports have examined factors that can be varied to improve the precision of binding constants that are determined by ms ACE, as applied to research examining the interactions of tryptophan with HSA, warfarin with BSA, and quercetin with beta‐lactoglobulin [ 6 , 103 ]. ms ACE has been used to investigate how the N ‐ and S ‐homocysteinylation of HSA affects binding by this protein to several catechins [ 105 ]. Another study employed ms ACE to investigate the interactions of polysulfate sodium with HSA and BSA [ 106 ]. Pressure‐mediated ACE is a subcategory of ms ACE that has been used to study weak noncovalent interactions, such as those between BSA and some drugs [ 107 ]. This method has also been employed to determine binding affinities for the enantiomers of amlodipine and verapamil with HSA, where accurate mobility estimates were obtained by using on a nonlinear mobility function [ 68 , 93 ]. 5.1.2 Vacancy peak methods in ACE In vacancy ACE (VACE), the BGE is filled with both the analyte and binding target. The concentration of either component may be fixed, whereas the other is varied [ 79 ]. A small plug of pure BGE is then injected into the CE system. The injection of this blank sample results in two vacancy peaks that have a lower response at the detector than the BGE containing the added components (see Figure  5B ). These two negative peaks appear due to depletion in the local free concentrations of the analyte (A) and free target (T) as the sample passes through the system. The binding of the analyte to the target can be studied by using the mobility shift of the negative analyte peak as the target concentration is varied [ 77 , 78 , 79 ]. This approach can be used with analytes that have low solubilities in water, as the binding target is also present in the BGE and can assist in dissolving such compounds [ 79 ]. VACE is also useful in examining the competitive interaction by several analytes to the same site on a binding target [ 77 ]. In addition, it is possible to determine the number of active binding sites by an analyte on a target by using VACE [ 78 , 86 ]. The vacancy peak method of ACE uses a similar setup to VACE and again produces two negative, vacancy peaks that are created by a local depletion in the concentrations of the free binding target and free analyte. The concentration of free analyte can be found from the peak for A by comparing its area to those obtained for injected samples of the BGE plus known concentrations of the analyte [ 69 , 86 ]. It is important in this method to optimize the concentration of the detected species in the BGE to obtain good sensitivity. For instance, when using absorbance detection too little background signal due to the components in the BGE can result in a poor dynamic range for this method, whereas a high background absorbance may produce a nonlinear response and result in poor assay sensitivity [ 69 ]. 5.1.3 ACE and the Hummel–Dreyer method In the Hummel–Dreyer method of ACE (HD ACE), the capillary is filled up with BGE that contains the analyte, and the injected sample consists of BGE that contains the binding target [ 69 , 80 ]. If the analyte and binding target have relatively fast interactions, this method will result in two observed peaks, a vacancy peak for the analyte and a positive peak for the injected target (see Figure  5C ). The positive peak will correspond to the free target and the complex that is formed between the analyte and target (which, in this case, often possess similar mobilities). The vacancy peak is produced by local depletion of analyte in the BGE as some of this analyte binds with the target [ 69 ]. The change in the area of the vacancy peak is then used to find the amount of analyte that was bound to the injected target [ 86 ]. HD ACE has been used to examine the binding of several drugs with serum proteins. For instance, this method has been employed to study the binding of BSA with salicylic acid [ 108 ]. This method has also been used to characterize the interactions between HSA and transferrin with the platinum‐containing drugs cisplatin and oxaliplatin; however, the HD ACE technique used in this case had to be modified because the binding of cisplatin to HSA did not reach equilibrium within the time‐frame of a typical CE analysis [ 109 ]. In a typical HD ACE experiment, BGE containing the binding target is used as the injected sample. The work with cisplatin and HSA instead used an injected sample that contained an excessive amount of the drug (i.e., up to 20‐fold) versus binding agent and that was subjected to incubation before injection [ 109 ]. 5.2 Pre‐equilibrium mode of ACE If two interacting components have an intermediate rate of binding and/or dissociation, there may not be sufficient time to establish a local equilibrium as these components pass through a CE system. In this situation, the pre‐equilibrium mode of ACE can be used. In this mode, the analyte and binding target are premixed in the sample before they are injected for separation by CE [ 30 , 40 , 110 ]. Frontal analysis ACE (i.e., CE FA, also known as FA ACE or FACE) is a type of pre‐equilibrium mode of ACE that has been used in several studies to study drug interactions with serum proteins or other binding agents [ 89 , 111 ]. In this approach, a moderately large plug of a pre‐equilibrated mixture containing known concentrations of the binding target and drug/analyte is injected into a CE system [ 12 , 17 , 70 , 82 , 83 , 86 , 108 , 111 , 112 , 113 , 114 , 115 , 116 , 117 , 118 , 119 , 120 ]. This experiment is done for several samples that usually contain a fixed total concentration of the binding target and several total concentrations of the analyte. When a potential is applied, the components of the samples are partially separated based on their electrophoretic mobilities [ 70 , 82 , 86 , 120 ]. The sample bands that are produced will consist of a series of plateaus that correspond to the free binding target (often overlapped with the analyte–target complex) and the free analyte [ 90 , 102 ]. The free analyte concentration in the sample is then determined from its plateau in the observed sample band, which in turn makes it possible to determine the ratio of the bound analyte per target [ 17 , 70 , 76 , 120 , 121 ]. This ratio is measured for several sample mixtures of the binding agent and drug/analyte and plotted against the free analyte concentration to determine the binding constant for the target–analyte interaction [ 76 ]. An advantage of this approach is that a local equilibrium is maintained in the overlapping zones of the sample band, allowing interactions that have rapid association and dissociation kinetics to be examined [ 70 ]. It is also possible to evaluate the stoichiometry for this interaction by carrying out experiments with samples that contain various concentrations of the analyte versus binding target [ 86 ]. However, CE FA does have some drawbacks. For example, this method requires a suitable difference in the mobilities of the bound versus unbound target and analyte to form observable and measurable plateaus for these chemical species [ 70 , 120 ]. This also means that relatively pure binding agents or analytes are required to avoid creating extra peaks or bands [ 70 ]. There are several reports in which CE FA has been used to characterize the binding of drugs with serum proteins [ 89 , 111 , 122 ]. For instance, this technique has been used to examine the interactions of AGP and BSA with alprenolol, oxprenolol, pindolol, propranolol, carbamazepine, diclofenac, salicylic acid, and warfarin [ 89 ]. CE FA has also been employed to study the binding of glycated HSA and unmodified HSA with acetohexamide, carbutamide, chlorpropamide, and tolbutamide [ 111 ]. Furthermore, CE FA has been used to analyze the interactions of loureirin B with HSA [ 122 ] and to investigate binding by the nonsteroidal anti‐inflammatory drugs flurbiprofen, ibuprofen, and naproxen with HSA and BSA [ 123 ]. The interaction of dexamethasone with BSA and HSA under simulated physiological conditions has also been studied by using CE FA [ 117 ]. A number of modified forms of CE FA have been reported for use in binding studies. For instance, the similar mobilities that are often present for a drug–protein complex and free protein in CE FA has been noted to limit the range of applications for this method [ 85 , 118 ]. To broaden the scope of applications, an electrophoretic mobility‐based correction was utilized to examine the binding of ibuprofen with hydroxypropyl‐β‐cyclodextrin [ 90 , 118 ]. A CE FA method has also been developed by changing from offline mixing of sample components to a procedure that uses online transverse diffusion of laminar flow profiles for mixing; this method has been used to obtain the binding parameters for BSA with propranolol, lidocaine, and phenylbutazone [ 124 ]. 5.3 Kinetic mode of ACE The third general format of ACE is the kinetic mode. This format is used when intermediate reaction rates are present that produce a relaxation time that is similar to the CE separation time [ 69 ]. Approaches that can be used in this format include nonequilibrium ACE, equilibrium CE, partial‐filling ACE (PFACE), and multiple‐step ligand injection ACE (MSLIACE). 5.3.1 Nonequilibrium and equilibrium CE of equilibrium mixtures In nonequilibrium CE of equilibrium mixtures (NECEEM), a short plug of a pre‐equilibrated mixture is injected into a capillary that is filled with a BGE [ 31 , 125 , 126 , 127 , 128 , 129 , 130 ]. A separation is then carried out during which there is continuous dissociation of the injected complex when a potential gradient is applied and with both the inlet and outlet reservoirs containing BGE [ 131 ]. In this approach, reassociation of the binding agent and analyte is assumed to be negligible. The elution profile that is obtained will contain a total of five regions: three peaks for the binding target, target–drug complex and drug, and two exponential smears produced by the binding agent and drug after the dissociation of their complex [ 131 ]. In NECEEM, complex dissociation overpasses complex formation, creating conditions in which it is favorable to obtain the binding constant and dissociation rate constant for the system [ 31 , 131 , 132 ]. NCEEM has been used mostly to study protein–protein, protein–DNA interactions, and aptamer–protein interactions [ 31 , 127 , 128 , 129 , 130 , 131 ]. For the analysis of drug–protein binding, NECEEM has been used with mass spectrometry to develop label‐free and solution‐based methods to study the kinetics of protein–small molecule interactions [ 133 , 134 ]. However, this approach is limited to systems where the analyte and binding target have similar electrophoretic mobilities [ 133 ]. One example of where NECEEM has been employed is to examine the interactions of isoprenaline hydrochloride with BSA [ 88 ]. In equilibrium CE of equilibrated mixtures (ECEEM), a short plug of a mixture at equilibrium is injected into the inlet of a capillary filled with a solution of binding target that is at the same concentration as the target in the equilibrium mixture. A separation of the sample components is carried out by CE with both the inlet and outlet reservoirs containing the same solution of target [ 132 ]. This method has been shown to be useful for examining the kinetics of noncovalent interactions for systems with complicated stoichiometry, which may occur during the binding of some proteins with peptide‐based drugs [ 132 ]. 5.3.2 Partial‐filling ACE PFACE is also known as plug–plug kinetic CE (ppKCE). In this method, the analyte and binding target are injected as separate bands and then allowed to interact [ 131 ]. This is a variant of the traditional ms ACE method where only part of the capillary is filled with the BGE containing the binding target and the rest of the capillary is filled with pure buffer solution [ 83 , 84 , 135 , 136 , 137 , 138 , 139 , 140 ]. This approach has been used in the separation of chiral substances and in the determination of equilibrium constants based on measurements of mobility [ 137 , 138 , 140 , 141 , 142 , 143 , 144 , 145 , 146 , 147 ]. An example in which PFACE has been used is to measure the binding of loureirin B with HSA [ 122 ]. Drug displacement studies involving both retinol and retinoic acid with HSA and BSA were conducted by this approach by employing ibuprofen as a site‐selective probe and displacing agent [ 148 ]. A benefit of PFACE over traditional ms ACE is that it consumes a smaller amount of a sample. In addition, detection of the analyte can be done in pure BGE with a low background signal, which can result in an improved signal‐to‐noise ratio [ 84 , 137 , 138 ]. PFACE can also be coupled with a wide range of detectors, including MS [ 138 ]. However, PFACE can only be used when certain criteria are met for the mobilities of analyte and binding agent [ 84 , 139 , 141 , 147 ]. For instance, the binding target should ideally be uncharged and have no appreciable mobility [ 139 ] or should have a mobility that is in the opposite direction of travel from the analyte [ 141 ]. Finally, the mobility of the analyte should be high enough to allow this agent to completely pass through the target plug before reaching the detector [ 139 ]. These conditions can be maintained by using an EOF marker in the BGE or by conducting the experiment under pressure [ 6 , 147 ]. For example, pressure‐mediated PFACE was used to investigate interactions between the human insulin hexamer and low mass compounds such as serotonin, dopamine, l ‐arginine, and phenol in aqueous alkaline media (see Figure  6 ) [ 143 ]. Another type of PFACE is flow‐through PFACE (FTPFACE). In this method, the capillary is filled with a plug of analyte, and a sample containing the target and noninteracting standards is then injected. When a potential is applied to the system, the sample and sections containing the binding target and analyte will begin to overlap, allowing a local equilibrium to be established [ 131 , 149 ]. As the potential is applied for a longer duration, the target will flow through the region that contains the analyte plug [ 131 , 149 ]. The relative migration time ratio of the target versus the noninteracting standards is then determined and used with Scatchard analysis to obtain the binding constant for the analyte with the target [ 149 ]. This method may be employed in situations where the analyte and target plugs do not elute simultaneously at the point of detection. FTPFACE has been used with both charged and neutral agents, as demonstrated in binding studies for mesityl oxide, benzenesulfonamide, and p ‐toluenesulfonamide with carbonic anhydrase B [ 149 ]. 5.3.3 Multiple‐step ligand injection ACE MSLIACE is another kinetic mode of ACE. This technique has been used to estimate binding constants for the interactions of drugs with a set of small peptides that possess similar masses and charges to each other [ 150 , 151 ]. In this method, separate plugs of peptides and inert standards are injected into a capillary that contains a known concentration of the drug in the BGE. The change in migration time of a peptide as it interacts with the drug is then determined and used with techniques such as Scatchard analysis to obtain the binding constant for this system [ 150 , 151 ]. This approach is faster than the conventional ACE techniques for determining binding constants of some drugs with peptides and uses less material [ 151 ]. 6 APPLICATIONS OF ACE AND AFFINITY‐BASED CE RELATED TO DRUG–PROTEIN BINDING The previous sections have provided several examples of how ACE has been employed in studies of the interactions of drugs with serum proteins or related binding agents. The previous examples that have been described in this review have involved the use of homogeneous methods where the interaction between the target binding agent and analyte occurs within a solution, such as within a sample or a running buffer [ 5 , 26 , 30 , 152 , 153 ]. However, as shown in Figure  1 , it is also possible in CE to use heterogeneous methods in which the binding agent is immobilized onto the inner surface of a capillary or onto a support that is placed into a CE system and used to capture the analyte [ 26 , 30 , 153 , 154 ]. This latter form of affinity‐based CE can also be viewed as a type of electrochromatography [ 7 , 26 ]. In this section, both homogeneous and heterogenous applications of CE will be considered as related to the analysis or use of interactions between drugs and serum proteins or related binding agents. The use of CE‐based immunoassays to examine drugs, chiral separations in CE based on serum proteins, and hybrid CE methods to examine drugs or drug–protein interactions will also be considered. FIGURE 1 General schemes for the study or use of drug–protein binding in capillary electrophoresis (CE) by (A) affinity capillary electrophoresis (ACE) as a homogeneous format in which the drug (or analyte) and binding agent (e.g., a serum protein) are both present in solution or (B) the use of an immobilized binding agent within the CE capillary in a heterogenous format FIGURE 2 Number of publications that have appeared between 1990 and 2022 on the use of affinity capillary electrophoresis (ACE) and related affinity‐based CE methods for the analysis of drug–protein interactions. This plot is based on a search that was conducted on SciFinder in May 2022. FIGURE 3 Structure of human serum albumin (HSA), including the location of Sudlow sites I and II. Source : Reproduced with permission from Ref. [ 41 ] FIGURE 4 The general instrumentation for affinity capillary electrophoresis (ACE) and affinity‐related CE methods, as shown for a system where a sample is injected or applied to a silica capillary at the end of the positive electrode (anode) FIGURE 5 Approaches used based on affinity capillary electrophoresis (ACE) and a dynamic equilibrium mode: (A) mobility shift ACE, (B) vacancy ACE, and (C) use of the Hummel–Dreyer method with ACE. Terms: A, analyte; T, binding target; EOF, electroosmotic flow. The solid and dashed lines show how the results of these methods change as experimental conditions are varied for use in binding studies. For instance, the dashed lines in (A–C) show how the peaks for the analyte change as the concentration of target is varied within the background electrolyte (BGE) and capillary. More details on these methods are provided in Section  5 . FIGURE 6 Use of partial‐filling affinity capillary electrophoresis (ACE) to study the interactions of phenol with the human insulin (HI), using dimethyl sulfoxide (DMSO) as a marker for electroosmotic flow (EOF). The injections time for the target zone into the background electrolyte (BGE) are shown on the left. Source : Reproduced with permission from Ref. [ 143 ] 6.1 Homogeneous methods used in CE for studying drug–protein interactions As can be seen from the methods described in Section  5 and the examples provided in Table  1 , the use of ACE in a zonal elution format is a common approach for the analysis of drug–protein interactions in the solution phase [ 5 ]. For instance, this combination has been used to investigate the binding of anionic carbohydrates and oligonucleotides to synthetic peptides derived from the heparin‐binding region of human serum amyloid P component [ 155 , 156 ]. This format has also been used to characterize the binding of procainamide and its derivatives to hemoglobin and histone proteins [ 157 ]. The interactions between HSA and several fluoroquinolones were studied by ACE using zonal elution and a homogeneous method [ 158 ]. A method that used chemically modified forms of HSA as buffer additives in ACE was developed and used to screen the binding of flurbiprofen, ibuprofen, suprofen, and warfarin at Sudlow sites I and II of this protein [ 61 , 159 ]. TABLE 1 Examples of applications for affinity capillary electrophoresis (ACE) and affinity‐based CE methods to study or use the interactions of drugs with serum proteins and related binding agents General format Drug/solute Protein/binding agent Refs. Homogenous formats Direct separation Anionic carbohydrates and oligonucleotides Synthetic peptides from human serum amyloid P [ 156 ] Procainamide and its derivatives Hemoglobin and histone proteins [ 157 ] Methionyl recombinant human growth hormone Anti‐human growth hormone [ 162 ] Alpha‐fetoprotein and tetraiodothyronine (T 4 ) Anti‐T 4 antibody [ 163 ] Insulin and glucagon Anti‐insulin antibodies and anti‐glucagon antibodies [ 169 ] Fluoroquinolones HSA [ 158 ] Mobility shift assay Tryptophan, warfarin, and quercetin HSA, BSA, and β‐lactoglobulin [ 6 ] Catechins HSA [ 105 ] Heparinoids HSA, BSA [ 106 ] Enantioseparation and equilibrium constant measurements using proteins as buffer additives Ephedrine and its derivatives BSA [ 180 ] Isoprenaline hydrochloride BSA [ 88 ] Verapamil and amlodipine enantiomers HSA [ 179 ] Omeprazole enantiomers HSA [ 181 ] Flurbiprofen, ibuprofen, suprofen, and warfarin Chemically‐modified HSA [ 61 , 159 ] Enantiomers of brompheniramine, chlorpheniramine, hydroxyzine, and orphenadrine HSA [ 182 ] Enantiomers of zopiclone Carboxymethylated‐β‐cyclodextrin as a chiral selector to separate zopiclone, HSA as a binding agent [ 183 ] Nomifensine enantiomers Heptakis‐2,3,6‐tri‐ O ‐methyl‐β‐cyclodextrin as a chiral selector to separate nomifensine enantiomers, HSA as a binding agent [ 184 ] Nuarimol enantiomers HSA as a chiral selector [ 185 ] Imazalil enantiomers Highly sulfated β‐cyclodextrin as a chiral selector, HSA as a binding agent [ 186 ] Enantiomers of disopyramide and remoxipride AGP as a chiral selector and binding agent [ 137 ] Enantiomers of mexiletine, propranolol, and chlorpheniramine HSA and porcine serum albumin as chiral selectors [ 188 ] Amlodipine enantiomers Hydroxypropyl‐β‐cyclodextrin as a chiral selector, HSA as a binding agent [ 189 ] Equilibrium constant measurements using drug as buffer additives Vancomycin as buffer additive Enantiomeric peptides [ 71 ] 4‐Alkylbenzyne sulfonamides Carbonic anhydrase A and B [ 40 ] Vancomycin Peptide library [ 175 ] Alprenolol, oxprenolol, pindolol propranolol, carbamazepine, diclofenac, salicylic acid, and warfarin AGP and BSA [ 89 ] Loureirin B HSA [ 122 ] Acetohexamide, carbutamide, chlorpropamide, and tolbutamide Normal and glycated HSA [ 111 ] Flurbiprofen, ibuprofen, and naproxen BSA and HSA [ 123 ] Dexamethasone HSA [ 117 ] Ibuprofen Hydroxypropyl‐β‐cyclodextrin [ 118 ] Equilibrium saturation method Warfarin BSA [ 77 , 85 ] Hummel–Dreyer method Salicylic acid BSA [ 108 ] Cisplatin and oxaliplatin HSA and transferrin [ 109 ]

Heterogeneous formats

d / l ‐Tryptophan BSA immobilized in a gel [ 191 ]

R / S ‐Warfarin HSA adsorbed onto a capillary wall [ 103 ] d / l ‐Tryptophan BSA coated onto polystyrene nanoparticles [ 196 ] BSA immobilized in silica monoliths [ 197 ] Enantiomers of atenolol, azelastine, bisoprolol, citalopram esmolol, labetalol, metoprolol, terazosin, tryptophan, and warfarin Cellulose and HSA immobilized in an organic monolith [ 195 ]

Hybrid methods Chlorpromazine, disopyramide, imipramine, propranolol, and warfarin AGP [ 198 ] Aprindine, disopyramide, imatinib, mepivacaine, and propranolol AGP and HSA [ 199 ]

Interactions of drugs with other biologically important molecules

Heparin Antithrombin III [ 200 ] Heparin Low‐density lipoprotein and peptide fragments of apolipoproteins [ 202 ] Dipeptide β‐naphthylamide derivatives and seven cationic amino acids Hyaluronic acid and HSA [ 115 ] Chondroitin‐6‐sulfate Low‐density lipoprotein and a peptide fragment of apoB‐100 [ 145 ] Abbreviations: AGP, alpha 1‐acid glycoprotein; BSA, bovine serum albumin; HSA, human serum albumin. John Wiley & Sons, Ltd. Zonal elution and a homogeneous format have also been used in CE‐based immunoassays to measure the free and bound fractions of drugs in samples [ 5 , 26 , 160 , 161 ]. For instance, this approach has been employed with CE in immunoassays for hormones, insulin, glucagon, cortisol, digitoxin, opiates, chloramphenicol as well as the tumor marker alpha‐fetoprotein, among other targets [ 131 , 132 , 133 , 134 , 135 , 136 , 137 , 138 , 139 , 140 , 141 , 142 , 162 , 163 , 164 , 165 , 166 , 167 , 168 , 169 , 170 , 171 , 172 , 173 ]. This form of immunoassay has also been used in CE with laser‐induced fluorescence detection to estimate the binding constants of anti‐insulin antibodies with insulin [ 174 ]. Drugs have been used in some studies as buffer additives in ACE to measure the equilibrium constants of drug–protein interactions [ 5 ]. Early work with this approach used it to simultaneously determine the binding of multiple enantiomeric peptides to vancomycin [ 71 ]. The binding interactions of 4‐alkylbenzyne sulfonamides with carbonic anhydrase A and B have also been investigated by employing this method [ 40 ]. Modified versions of this approach have been used to determine the peptides in a peptide library with the highest affinities to vancomycin and to estimate the maximum number of binding agents that can be simultaneously screened by this approach [ 175 ]. 6.2 Chiral separations in CE using serum proteins A number of studies have been conducted by CE in which enantioselective selectors have been used as buffer additives or immobilized binding agents to separate chiral drugs [ 176 ]. This work has used buffer additives that have included proteins, polysaccharides, organic polymers, and chiral micelles, among others [ 176 , 177 , 178 ]. Chiral separations based on CE can provide short analysis times, high efficiency, and low consumption of analytes, reagents, and solvents compared to liquid chromatography [ 176 , 178 ]. The use of serum proteins as buffer additives for the separation of chiral drugs has been described in various studies [ 7 , 88 , 179 ]. For instance, HSA has been used as a buffer additive to separate enantiomers of verapamil and amlodipine [ 179 ]. BSA has been utilized as a buffer additive for the chiral separation of ephedrine enantiomers by CE [ 180 ]. ms ACE has been used with laser‐induced fluorescence detection and HSA as a chiral selector to both separate omeprazole enantiomers and to measure the binding constants of these enantiomers with HSA [ 181 ]. Several studies have reported the use of electrochromatography to study the binding of drug enantiomers with HSA [ 176 , 182 , 183 , 184 , 185 , 186 ]. For instance, a partial filling technique was used in this technique to investigate the binding of HSA with the enantiomers of brompheniramine, chlorpheniramine, hydroxyzine, and orphenadrine [ 182 ]. Moreover, a similar approach was employed for the enantiomeric separation of zopiclone using carboxymethylated‐β‐cyclodextrin as a chiral selector [ 183 ]. The method was used in the same study to evaluate the binding of the zopiclone enantiomers to HSA [ 183 ]. Another study employed electrokinetic chromatography and a partial filling technique to study the binding of nomifensine enantiomers with HSA, using heptakis‐2,3,6‐tri‐ O ‐methyl‐β‐cyclodextrin as a chiral selector [ 184 ]. The chiral separation of nuarimol enantiomers by electrokinetic chromatography and a partial filling technique using HSA as chiral selector has also been reported [ 185 ]. Several additional reports have used ACE to examine the binding between serum agents and chiral drugs. For instance, ACE was used to estimate the conditional association constants between AGP and the enantiomers of disopyramide and remoxipride using a partial filling technique [ 137 ]. The conformational change of HSA upon binding to the basic drug mexiletine was examined by ACE, as well as the effects of pH, temperature, and other parameters on the chiral separation of this drug [ 187 ]. A related study developed a method for the enantiomeric separation of mexiletine, propranolol, and chlorpheniramine by using HSA and porcine serum albumin as chiral selectors [ 188 ]. CE FA was used to study the stereoselective binding of amlodipine enantiomers with HSA under physiological conditions [ 189 ]. 6.3 Heterogeneous CE methods based on drug interactions with serum proteins Heterogeneous methods based on CE have also been used with serum proteins to study drug interactions or to carry out chiral separations. In these methods, the serum protein may be placed within a gel, coupled or coated onto a capillary wall, or coupled to a support that is packed within the capillary [ 103 , 190 , 191 , 192 , 193 , 194 , 195 , 196 ]. The chiral separation of d ‐ and l ‐tryptophan by CE using BSA immobilized in a gel has been described [ 191 ]. BSA has been coated onto polystyrene nanoparticles and used in CE for the separation of d ‐ and l ‐tryptophan [ 196 ]. Another study utilized CE and BSA that was immobilized onto silica monoliths for the separation of d ‐ and l ‐tryptophan [ 197 ]. A dynamic coating of HSA onto a capillary has been used in CE to separate R ‐ and S ‐warfarin [ 103 ]. In addition, a mixture of cellulose and HSA immobilized in an organic monolith has been used in ACE to resolve various chiral analytes [ 195 ]. 6.4 Hybrid methods using CE for studying drug–protein interactions Recent studies have combined the use of CE with affinity‐based liquid chromatography to characterize the binding by several drugs with serum proteins [ 198 , 199 ]. For instance, CE has been used with on‐line immunoextraction and high‐performance affinity chromatography to study the interactions of AGP with chlorpromazine, disopyramide, imipramine, propranolol, and warfarin [ 198 ]. CE was used in this work for the measurement and glycoform analysis of normal AGP and AGP that had been derived from serum from systemic lupus erythematosus (SLE) patients (see Figure  7 ). Affinity microcolumns containing immobilized polyclonal anti‐AGP antibodies were then employed in the frontal analysis and zonal elution formats to investigate the binding of these drugs with the same samples of AGP [ 198 ]. A similar hybrid CE method was developed and used to characterize the binding of aprindine, disopyramide, imatinib, mepivacaine, and propranolol with both AGP and HSA [ 199 ]. FIGURE 7 (A) Electropherograms and (B) distribution of glycoform bands showing a shift in the profiles for normal α1‐acid glycoprotein (AGP) and AGP isolated from serum of patients with systemic lupus erythematosus (SLE). The horizontal and vertical error bars in (B) represent a range of ±1 SD in the migration time or % total peak area values, respectively. The data were obtained for triplicate injections and are similar in size to the symbols used in this plot. Source : Reproduced with permission from Ref. [ 198 ] 6.5 Use of CE to examine interactions by drugs with other binding agents The use of ACE to study the interaction of drugs with other agents that can be found in blood or serum has also been reported [ 83 , 200 , 201 , 202 ]. For instance, the interaction of heparin with antithrombin III was studied by using ACE [ 200 ]. Another related study reported the use of ACE to study the binding of antithrombin III with low molecular weight heparins and fondaparinux [ 175 ]. Moreover, ACE has been used to study the interactions of heparin with intact LDL and peptide fragments from apolipoproteins [ 194 ]. CE FA was employed to gain insight on how the chemical properties of dipeptide β‐naphthylamide derivatives and seven cationic amino acids affect their binding with the glycosaminoglycan hyaluronic acid and HSA [ 115 ]. PFACE was used to study the binding of a chondroitin‐6‐sulfate with LDL and with a peptide fragment from apolipoprotein B‐100 [ 145 ]. 6.6 Application of computational simulations in ACE Computer simulations have been used in several reports to help describe and predict the behavior of analytes in ACE [ 90 , 92 , 98 , 106 , 203 , 204 ]. For instance, the migration and band broadening of an analyte in ACE can be described through the use of appropriate differential equations [ 205 ]. However, solving these equations and placing them into forms that can be used experimentally to obtain parameters such as equilibrium constants and mobilities for analyte–binding agent complexes can be quite challenging [ 206 ]. Computer simulations can be used with these differential equations and finite difference schemes to describe the behavior of analytes in a capillary. Data processing and underlying calculation methods for this approach have been substantially improved for methods such as ms ACE, ppKCE, and CE FA [ 90 , 92 , 98 , 106 , 203 , 204 ], as described in recent reviews [ 90 , 207 ]. However, applications in which computer simulations have been used specifically to examine drug interactions with serum proteins or related materials in ACE are not yet common [ 98 ], making this a potential area of interest for future studies. 7 CONCLUDING REMARKS This review examined the use of ACE and related CE methods to examine the interactions of drugs with serum binding agents. This review also described recent developments in this field. An emphasis was placed on work with serum proteins such as HSA, BSA, and AGP, although other binding agents found in serum or blood were also considered, such as lipoproteins, antithrombin, and antibodies (see the summary in Table  1 ). Various assay formats were described that can be used for systems with fast, intermediate, or slow interaction kinetics. Examples of specific formats that were discussed in this review were ms ACE, vacancy‐based ACE techniques, use of the Hummel–Dreyer method in ACE, and frontal analysis in ACE, along with methods such as NECEEM, ECEEM, partial filling ACE, and multistep ligand injection ACE. Heterogeneous methods in CE that use immobilized binding targets for drug–protein interaction studies or drug analysis were also described. The mathematical approaches that are used to analyze data from such techniques were considered as well. Applications of ACE and related techniques that were discussed include the study of drug–protein interactions, chiral drug separations, and the use of CE in hybrid methods to characterize drug binding with serum proteins. Additional applications are expected in the future as research continues in the development of new tools for ACE and related methods as related to drug interactions with serum proteins and related binding targets. CONFLICT OF INTEREST The authors have declared no conflict of interest. ACKNOWLEDGMENTS This work was supported, in part, by the National Science Foundation under grant CMI 2108881 and by the University of Nebraska Research Council. DATA AVAILABILITY STATEMENT The data that support the findings of this study are available from the corresponding author upon reasonable request. REFERENCES 1

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# 利用亲和毛细管电泳分析药物与血清蛋白及相关结合剂的相互作用:综述

**Sharmeen Sadia, Kyei Isaac, Hatch Arden, Hage David S.**

内布拉斯加大学林肯分校化学系,美国内布拉斯加州林肯市

## 摘要

血清蛋白等生物分子可在体内与药物发生相互作用,从而影响其药效。精确分析这些相互作用的方法对于药物开发、监测以及诊断目的至关重要。亲和毛细管电泳(ACE)是一种可用于研究药物与血清蛋白或血清/血液中其他结合剂之间结合的技术。本文将综述ACE的基本原理以及相关的亲和毛细管电泳方法,并探讨该领域在药物-蛋白相互作用表征方面的最新进展。本文还将概述ACE和CE中可用于此类工作的各种分析模式,包括每种方法的相对优势和劣势。此外,还将介绍ACE和亲和CE方法在分析药物与血清蛋白及其他结合剂相互作用方面的各种应用。所讨论的ACE及相关技术的应用包括:药物与血清结合剂的相互作用研究、利用血清蛋白进行手性药物分离,以及CE在混合方法中用于表征药物与血清蛋白的结合。

**关键词:** 亲和毛细管电泳;药物-蛋白结合;Hummel-Dreyer法;迁移率位移分析;血清蛋白

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## 1 引言

当药物进入血液循环系统后,在药物被转运至靶组织或受体以产生治疗作用的过程中,可能与血清蛋白或血液中的其他载体发生相互作用[1-3]。由于某些药物与蛋白的结合可能具有立体选择性,这些相互作用也可能在决定手性药物不同构型在体内命运方面发挥作用[4-7]。此外,血液循环中未结合药物(游离形式)的浓度常受到药物与血清蛋白相互作用的影响,这可能影响药物的药代动力学和药效学特性。药物与血清结合剂的结合以及由此产生的未结合药物部分的大小,还可能受到药物与内源性化合物(如胆红素、脂肪酸)在血液循环系统中竞争的影响[8-11]。当联合使用多种药物混合物时,两种药物对同一结合蛋白发生直接或间接竞争时,也可能产生类似效应[1,12]。因此,在发现或开发新药物以及监测和治疗疾病过程中理解药物作用时,表征药物与血清蛋白的相互作用具有重要意义[12]。

已有许多方法被用于研究与血清和血液中蛋白及其他结合剂的药物相互作用。两种常用的参比方法是平衡透析和超滤[5]。其他方法包括基于表面等离子体共振、紫外/可见或红外吸收、荧光、圆二色性和核磁共振测量的光谱方法[13-18]。可用于此类研究的其他方法包括质谱、亲和色谱、电泳、部分人工膜渗透性测定和等温量热法[13,17-20]。然而,这些技术中的许多方法速度较慢,需要相对大量的样品或结合剂,或操作成本较高[21]。

亲和毛细管电泳(ACE)是一种已被开发并探索的方法,用于克服药物-蛋白结合研究中其他技术的许多局限性[20,22-25]。ACE将毛细管电泳(CE)系统与生物相关结合剂相结合,该结合剂用于捕获或分离分析物,基于其电泳迁移率的差异将分析物与其他样品组分分离[26]。例如,如果结合剂存在于背景电解质(BGE)中,且分析物与该结合剂相互作用时其荷质比发生变化,则分析物从游离态到结合态的观察迁移率将发生偏移[27,28]。这使得结合剂能够影响分析物与样品中其他组分的分离,同时也提供了表征分析物-结合剂相互作用的手段[28]。

CE可以通过使用可溶性形式或固定化形式的结合剂来进行,如图1所示[29]。当目标结合剂以可溶性形式存在时,分析物和结合剂在通过CE系统时在BGE中发生相互作用[7,30]。在该方法中,分离取决于游离分析物与分析物-结合剂复合物的迁移率[7,31]。或者,结合剂可以被固定或吸附在毛细管内,从而产生基于电色谱的分离技术[26,30-33]。

ACE及相关CE方法可以提供关于药物-蛋白相互作用的多种类型信息。这些信息包括药物与蛋白之间的结合常数、该相互作用的速率常数以及结合化学计量比[34-36]。这些信息对于评估药物对特定靶蛋白的亲和力以及理解药物与蛋白结合的机制至关重要[5,13]。此外,CE还可以提供关于该过程形成的复合物电荷的信息[27,36]。

基于CE的技术在药物结合研究方面相比替代方法具有许多潜在优势。例如,这些CE方法通常仅需要少量结合剂,样品进样体积在皮升至纳升级范围[37-39]。CE还以分离时间短和分离效率高而著称[37]。此外,ACE及相关技术通常不需要事先纯化样品,这意味着生物流体可以直接注入毛细管[38]。基于亲和力的CE方法在某些情况下还可用于研究多种溶质与特定结合剂的结合,如利用此类方法筛选候选物库与同一靶标的结合,作为组合研究的一部分[34,40]。

如图2所示,自1990年以来,已有超过2500篇关于使用ACE及相关方法研究药物-蛋白结合或利用这些相互作用作为化学分离一部分的文章发表。本文将综述ACE和亲和CE的原理和应用,重点介绍涉及药物与血清蛋白或相关结合剂相互作用的系统以及该领域出现的最新进展。将讨论该领域使用的分析格式及其优势或潜在局限性。将介绍的ACE及相关技术的应用包括:药物-蛋白相互作用研究、利用血清蛋白进行手性药物分离,以及CE在混合方法中用于表征药物与血清结合剂的结合。

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## 2 ACE和药物相互作用研究中使用的血清结合剂

在ACE或其他形式的CE中,已使用了几种类型的血清结合剂进行分离和药物结合研究。两个例子是主要血清蛋白——人血清白蛋白(HSA)和牛血清白蛋白(BSA)[14,41]。HSA是一种单链非糖基化蛋白,摩尔质量为66.5 kDa。HSA含有585个氨基酸,等电点为4.7[42]。BSA具有与HSA相似的摩尔质量和组成,但仅含有583个氨基酸[43]。HSA和BSA都有两个主要的药物结合位点:Sudlow位点I(位于IIA亚结构域)和Sudlow位点II(位于IIIA亚结构域)(见图3)[41]。Sudlow位点I具有一个疏水空腔,含有两个离子/极性残基簇。该位点倾向于结合具有庞大杂环结构且带有负电或电负性基团的药物,如华法林、阿扎丙酮、保泰松和水杨酸盐[42,44]。Sudlow位点II在其疏水口袋附近有一个阳离子残基簇,倾向于通过疏水、氢键和静电相互作用的组合来结合药物。结合Sudlow位点II的化合物包括脂肪族和芳香族羧酸盐,如苯二氮卓类、酮洛芬和L-色氨酸[42,44]。

另一种重要的药物转运血浆蛋白是α1-酸性糖蛋白(AGP)[42]。人AGP是一种高度糖基化的蛋白,具有183个氨基酸的单链,典型摩尔质量在41-43 kDa之间[42,45]。由于其碳水化合物链中的唾液酸基团,AGP具有较低的等电点(2.8-3.8)[42]。AGP上连接有双触角、三触角和四触角聚糖的异质混合物,附着于五个N-连接糖基化位点[42,45]。AGP倾向于结合中性或阳离子药物,具有一个高亲和力、低容量的结合位点,包含三个叶。该位点包括一个被两个带负电叶包围的疏水叶,可为药物与该区域的结合提供强结合力[42,45]。

药物和小有机溶质的另一组血清结合剂是脂蛋白[46,47]。脂蛋白由疏水核心(含有胆固醇酯和甘油三酯等物质)组成,外围被磷脂和游离胆固醇的壳层包围,其中还含有载脂蛋白[46,47]。血浆脂蛋白根据其密度分类,如高密度脂蛋白和低密度脂蛋白(LDL)[46,48]。血浆脂蛋白在血液中结合和转运胆固醇和甘油三酯,以及一些疏水和/或碱性药物[48]。

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## 3 ACE研究药物-蛋白相互作用的一般原理

图4展示了用于ACE及其他形式CE的典型系统[37,38]。该系统需要放置在CE系统毛细管中的BGE,并保持在接触电极(即阳极和阴极)的两个储液池中。电极用于在毛细管上施加电场[37,38]。该系统的其他组件包括分离盒(即容纳毛细管的部件)、电源、进样系统、用于数据采集和系统控制的计算机以及检测器[37,38]。检测器放置在毛细管进样端的相对一端。现代CE系统可包括基于紫外-可见吸收、激光诱导荧光、电化学检测或质谱的在线检测器[37,38]。

CE中的毛细管典型内径为20-100 μm,长度为20-100 cm。使用小内径毛细管提供了高表面积与体积比和高效的焦耳热耗散,因此允许使用高施加电势(即高达25-30 kV)[38,49]。在CE中使用涂层和非涂层毛细管[23-25,50-55],非涂层毛细管通常由裸熔融石英制成[23-25]。聚酰亚胺通常用作硅毛细管外部的涂层,使其不易破碎;然而,在使用光学检测分析物时,靠近毛细管一端的涂层部分被去除以提供检测窗口[27]。在CE和ACE中还使用了具有永久涂层或动态涂层的毛细管[50-53]。永久涂层由共价结合到毛细管内部的化学层组成,而动态涂层利用非共价吸附将涂层材料可逆地放置在毛细管内壁上[50-53]。

通过暂时用样品瓶替换其中一个缓冲液储液池,将分析物注入CE系统[38]。通过使用流体动力流或电迁移,将确定量的样品(通常在皮升至纳升级范围)引入毛细管[38]。在流体动力模式下,通过施加毛细管两端之间的压力差将样品注入毛细管[56]。当使用低粘度缓冲液进行CE或ACE时,通常选择这种进样模式[56,57]。对于电迁移或电动进样模式,在施加电势存在下将样品引入毛细管[56]。在该方法中,注入物质的量将取决于该化合物的迁移率,并且可能因样品中的不同分析物而异[56,58]。

电渗流(EOF)是CE和ACE中必须考虑的重要现象。如果使用硅毛细管,当毛细管内壁上由于硅醇基团的酸解离而存在负电荷时,就会产生EOF[50,51]。该负电荷吸引BGE中的阳离子,形成固定的Helmholtz平面和可移动的外电荷层[50,51]。在施加电势存在下,可移动外层中的阳离子被拉向负极(阴极)[51]。这种情况导致BGE及其溶质向阴极产生净运动,检测器可放置在此处监测随EOF迁移或逆EOF迁移的分析物[51]。EOF的大小将取决于温度、毛细管内表面电荷量和BGE的pH等因素[59-61]。

CE可以在正极性模式或反极性模式下进行[37,38,49,50,51,62]。在正极性模式下,样品在硅毛细管的阳极端进样,然后样品组分在EOF存在下以不同的迁移速度迁移,到达靠近阴极端的检测器[37,38]。在反极性模式下,CE分离在EOF被抑制或不存在的情况下进行。在这些条件下,样品在与分析物相对电荷相同的电极处进样,然后这些分析物通过电迁移迁移到相反电荷的电极[62]。例如,在反极性模式下,含有阴离子的样品在毛细管的阴极端进样,并在迁移到阳极端时被检测[62]。

---

## 4 ACE研究药物-蛋白相互作用的原理

许多药物与血清蛋白及相关结合剂的结合可以被描述为可逆和非共价过程[39]。该过程可以用以下反应和方程式表示,其中药物(D)与血清蛋白(P)或类似结合剂结合形成药物-蛋白/结合剂复合物(C)[5]。

(1) D + P ⇌ C

(2) K_a = k_on / k_off = [C] / ([D][P])

(3) K_d = 1/K_a = k_off / k_on = ([D][P]) / [C]

在这些关系中,[D]和[P]分别是药物和蛋白或结合剂非结合形式的平衡摩尔浓度,[C]是其复合物的平衡摩尔浓度。k_on和k_off项是该反应的缔合和解离速率常数,而K_a和K_d是该过程的相应缔合和解离平衡常数。这一描述是药物与血清蛋白或相关结合剂形成可逆复合物所涉及整体步骤的简化。然而,方程式(1)-(3)通常为此类过程的整体程度和净反应速率提供了良好的描述[5,39,63]。当存在变构相互作用时是一个例外,此时应使用更复杂的反应模型[5]。

可用于ACE研究药物-蛋白相互作用的一种方法是迁移率位移分析(见第5.1.1节)。当药物和蛋白/结合剂在其反应过程中具有快速的缔合/解离动力学,且药物的非结合形式与药物-结合剂复合物之间存在显著的迁移率差异时,使用该方法[5,39,63,64]。在这些条件下,当BGE和毛细管中结合剂的浓度变化时,应观察到药物峰在CE中整体位置的偏移(见图5A)[65]。

药物的表观迁移率(μ_app)通过使用方程式(4)以及已知的毛细管总长度(L_tot)、从进样端到检测窗口位置的毛细管有效长度(L_eff)、药物的测量迁移时间(t)和施加电压(V)从实验数据计算得出[5]:

(4) μ_app = (L_eff × L_tot) / (t × V)

当ACE用于估计缔合或解离平衡常数时,药物的迁移率(μ)可以通过对药物的表观电泳迁移率进行单独测量,利用EOF的迁移率(μ_EOF)并使用以下方程式所示的关系获得:

(5) μ = μ_app - μ_EOF

在药物观察到的迁移率随结合剂浓度变化而变化的情况下,可以使用以下方程式获得该系统的结合常数[63]:

(6) μ = μ_f + (μ_C - μ_C K_a[P]) / (1 + K_a[P])

在该关系中,μ_C和μ_f分别是复合物和游离非结合药物的有效电泳迁移率[5,39,63,64]。在使用此类方程式时,应考虑温度、离子强度、溶液粘度变化以及蛋白与毛细管壁的相互作用等因素,因为这些因素都可能影响观察到的迁移率[66]。基于方程式(6)或相关表达式的非线性最小二乘回归是目前从ACE数据获得结合常数的首选方法[63,67,68]。然而,方程式(6)也可以使用以下关系之一重新排列为线性形式[5,69]:

(7) (μ - μ_f)/[P] = -K_a(μ - μ_f) + K_a(μ_C - μ_f)

(8) [P]/(μ - μ_f) = 1/((μ_C - μ_f)[P]) + 1/((μ_C - μ_f)K_a)

(9) 1/(μ - μ_f) = 1/((μ_C - μ_f)K_a[P]) + 1/(μ_C - μ_f)

当使用方程式(7)时,(μ - μ_f)[P]对(μ - μ_f)作图应产生一条最佳拟合线,其斜率给出缔合平衡常数(K_a)的值[5,69]。该方程式的一个优势是左右两边项在[P]值上没有共依赖性[5]。一些报告已建议使用此类数据处理来评估药物-蛋白相互作用的结合常数[30,36,40,64,70]。此外,当使用大分子或高电荷结合剂(如蛋白)进行工作时,基于方程式(7)的分析可能很有价值,该结合剂在与目标药物结合时未表现出显著的迁移率偏移[5]。

还可以基于方程式(8)和(9)制备倒数图。对于方程式(8),[P]/(μ - μ_f)对[P]作图可以从斜率与截距的比值获得K_a值。对于方程式(9),1/(μ - μ_f)对1/[P]作图可以从截距与斜率的比值获得K_a值[5,69,70]。

方程式(7)-(9)中给出的相同类型的关系可以通过反转药物和蛋白的角色来用于估计结合常数。例如,这可以通过在方程式(7)-(9)中使用[D]代替[P]来实现[40]。在仅有少量蛋白或多肽可用或样品中存在多种蛋白和多肽混合物的情况下,这种方法很有用[40,68,69,71]。

使用基于方程式(6)的非线性回归而非使用方程式(7)-(9)进行线性回归的统计优势在于,前者方法避免了因变量出现在用于数据分析的x轴和y轴值中[63,67,68,72]。

如果在研究药物-蛋白结合过程中存在EOF的变化,可以通过使用迁移率比来校正这些变化[23-25,27,39,73-75]。例如,可以使用以下方程式计算迁移率比(M)[73-75]:

(10) M = (μ + μ_EOF) / μ_EOF

基于方程式(4)中给出的μ定义,对于分析物和EOF相同的L_tot、L_eff和V等因素将出现在方程式(10)的分子和分母中,并在使用迁移率比时作为变异源被消除。这通过方程式(11)中提供的迁移率比的等效表达式更清楚地表明[73-75]:

(11) M = (t_EOF / t) + 1

其中t_EOF是EOF标记物的迁移时间,t是分析物的迁移时间。迁移率比与毛细管长度、施加电压和EOF变化无关这一事实使得这些值成为通过ACE估计结合常数的更可重复的手段,优于直接使用绝对迁移率或迁移时间[73-75]。

---

## 5 ACE在研究药物-蛋白相互作用中采用的方法

ACE可以以几种模式进行,以研究药物-蛋白结合或其他类型的生物分子相互作用。第一种模式用于相互作用组分的动力学在CE分离时间尺度上相对较快的情况,在系统中产生动态平衡[30,40]。第二种模式基于相互作用组分预平衡的使用[25,30,40]。第三种模式称为动力学ACE,用于反应速率与CE分离时间相似的中间反应速率系统[69]。本节将更详细地描述这些模式中的每一种。

### 5.1 ACE的动态平衡模式

当两个相互作用组分具有相对较快的结合和解离速率时,可以使用几种方法,从而在这些组分通过CE系统时产生动态平衡。在这种情况下可以采用的技术包括迁移率位移ACE(ms ACE)、基于空缺峰的ACE分析以及使用Hummel-Dreyer方法的ACE技术[7,69,71,76-81]。

#### 5.1.1 迁移率位移ACE

ms ACE已在许多研究中用于研究药物-蛋白相互作用[2,35,39,82-88]。在该方法中,将一种相互作用剂(即结合靶标,T)的几种浓度放入CE系统的BGE中。将固定浓度的互补剂(即药物或分析物)溶解在BGE中,通常与EOF标记物一起作为样品注入。然后从相应的电泳图确定注入剂和EOF标记物的表观迁移率(见图5A)。然后将注入剂的观察到的迁移率偏移与BGE中互补组分的浓度相关联,用于找到该系统的结合常数[89]。这种分析通常使用BGE中结合靶标的浓度比注入分析物浓度高10-100倍来进行[90]。在这些条件下,由于BGE含有大量过量的靶标,结合靶标沿注入分析物区域的时间和空间变化通常可以忽略不计[2]。

ms ACE的简单性和数据评估的便利性使该方法对药物-蛋白相互作用研究具有吸引力[2,99]。然而,ms ACE确实存在缺点。例如,使用高浓度的靶标可能在估计结合常数时产生系统误差(例如,通过改变BGE的粘度和离子强度)[85,86]。必须对此进行校正,以最小化结合分析中的任何相关误差[74,90,100]。此外,温度、缓冲液电解和毛细管表面特性(例如,如果两个结合伙伴之一可以吸附到毛细管上)等因素必须被考虑,因为这些可能影响迁移时间的可重复性[74]。

ms ACE已被用于研究许多类型的药物-蛋白相互作用及相关系统[6,61,75,103]。例如,ms ACE已被用于分析肝素与抗凝血酶变体的相互作用[104]。其他报告研究了可以变化以提高ms ACE确定结合常数精度的因素,如应用于研究色氨酸与HSA、华法林与BSA以及槲皮素与β-乳球蛋白相互作用的研究[6,103]。ms ACE已被用于研究HSA的N-和S-高半胱氨酰化对该蛋白与几种儿茶素结合的影响[105]。另一项研究采用ms ACE研究了聚硫酸钠与HSA和BSA的相互作用[106]。

压力介导的ACE是ms ACE的一个子类别,已被用于研究弱非共价相互作用,如BSA与某些药物之间的相互作用[107]。该方法还被用于确定氨氯地平和维拉帕米对映体与HSA的结合亲和力,其中使用非线性迁移率函数获得了准确的迁移率估计[68,93]。

#### 5.1.2 ACE中的空缺峰方法

在空缺ACE(VACE)中,BGE中填充有分析物和结合靶标。任一组分的浓度可以固定,而另一组分的浓度变化[79]。然后将一小段纯BGE注入CE系统。注入该空白样品会产生两个在检测器处响应低于添加组分的BGE的空缺峰(见图5B)。这两个负峰的出现是由于当样品通过系统时分析物(A)和游离靶标(T)的局部游离浓度耗竭。可以通过使用负分析物峰的迁移率偏移来研究分析物与靶标的结合,同时改变靶标浓度[77-79]。

VACE的空缺峰方法使用与VACE类似的设置,同样产生两个负的空缺峰,这是由游离结合靶标和分析物的局部浓度耗竭产生的。游离分析物的浓度可以通过比较A峰的面积与注入的BGE加已知浓度分析物样品获得的面积来确定[69,86]。在该方法中,优化BGE中检测物种的浓度以获得良好的灵敏度很重要。例如,当使用吸光度检测时,BGE中组分产生的背景信号太少可能导致该方法的动态范围不佳,而高背景吸光度可能产生非线性响应并导致分析灵敏度差[69]。

#### 5.1.3 ACE和Hummel-Dreyer方法

在ACE的Hummel-Dreyer方法(HD ACE)中,毛细管填充有含有分析物的BGE,注入样品由含有结合靶标的BGE组成[69,80]。如果分析物和结合靶标的相互作用相对较快,该方法将产生两个观察到的峰:分析物的空缺峰和注入靶标的正峰(见图5C)。正峰对应于游离靶标和分析物与靶标之间形成的复合物(在这种情况下通常具有相似的迁移率)。空缺峰是由BGE中分析物的局部耗竭产生的,因为部分分析物与靶标结合[69]。然后使用空缺峰面积的变化来找到与注入靶标结合的分析物量[86]。

HD ACE已被用于研究几种药物与血清蛋白的结合。例如,该方法已被用于研究BSA与水杨酸的结合[108]。该方法还被用于表征HSA和转铁蛋白与含铂药物顺铂和奥沙利铂的相互作用;然而,在这种情况下使用的HD ACE技术必须进行修改,因为顺铂与HSA的结合在典型CE分析的时间范围内未达到平衡[109]。在典型的HD ACE实验中,使用含有结合靶标的BGE作为注入样品。而与顺铂和HSA的工作则使用了含有过量药物(即高达20倍)相对于结合剂的注入样品,并在注入前进行孵育[109]。

### 5.2 ACE的预平衡模式

如果两个相互作用组分的结合和/或解离速率中等,当这些组分通过CE系统时可能没有足够的时间建立局部平衡。在这种情况下,可以使用ACE的预平衡模式。在该模式中,分析物和结合靶标在注入CE系统进行分离之前预先混合在样品中[30,40,110]。

前沿分析ACE(即CE-FA,也称为FA ACE或FACE)是一种预平衡模式的ACE,已在几项研究中用于研究药物与血清蛋白或其他结合剂的相互作用[89,111]。在该方法中,将含有已知浓度结合靶标和药物/分析物的预平衡混合物的适度大段塞注入CE系统[12,17,70,82,83,86,108,111-120]。该实验对几个样品进行,这些样品通常含有固定总浓度的结合靶标和几种总浓度的分析物。当施加电势时,样品组分根据其电泳迁移率被部分分离[70,82,86,120]。产生的样品带将由一系列平台组成,对应于游离结合靶标(通常与分析物-靶标复合物重叠)和游离分析物[90,102]。然后从观察到的样品带中分析物的平台确定样品中游离分析物的浓度,这反过来使得可以确定每个靶标的结合分析物比率[17,70,76,120,121]。该比率针对结合剂和药物/分析物的几种样品混合物进行测量,并针对游离分析物浓度作图以确定靶标-分析物相互作用的结合常数[76]。

该方法的一个优势是在样品带的重叠区域中维持了局部平衡,允许研究具有快速缔合和解离动力学的相互作用[70]。还可以通过进行含有不同浓度分析物相对于结合靶标的实验来评估该相互作用的化学计量比[86]。然而,CE-FA确实有一些缺点。例如,该方法需要结合靶标与分析物的结合态与非结合态之间存在适当的迁移率差异,以形成这些化学物种的可观察和可测量平台[70,120]。这也意味着需要相对纯的结合剂或分析物以避免产生额外的峰或带[70]。

CE-FA的几种改进形式已被报道用于结合研究。例如,已注意到CE-FA中药物-蛋白复合物与游离蛋白通常存在的相似迁移率限制了该方法的应用范围[85,118]。为了扩大应用范围,利用基于电泳迁移率的校正来研究布洛芬与羟丙基-β-环糊精的结合[90,118]。还通过将样品组分的离线混合改为使用在线横向扩散层流剖面混合的程序开发了CE-FA方法;该方法已被用于获得BSA与普萘洛尔、利多卡因和保泰松的结合参数[124]。

### 5.3 ACE的动力学模式

ACE的第三种一般格式是动力学模式。当存在产生与CE分离时间相似的弛豫时间的中间反应速率时,使用该格式[69]。该格式中可以使用的方法包括非平衡ACE、平衡CE、部分填充ACE(PFACE)和多步配体注入ACE(MSLIACE)。

#### 5.3.1 平衡混合物的非平衡和平衡CE

在平衡混合物的非平衡CE(NECEEM)中,将一小段预平衡混合物注入填充有BGE的毛细管中[31,125-130]。然后进行分离,在此期间当施加电势梯度且入口和出口储液池均含有BGE时,注入的复合物持续解离[131]。在该方法中,假设结合剂和分析物的再缔合可忽略不计。获得的洗脱曲线将包含总共五个区域:结合靶标、靶标-药物复合物和药物的三个峰,以及结合剂和药物在其复合物解离后产生的两个指数弥散区[131]。

在NECEEM中,复合物解离超过复合物形成,产生有利于获得系统结合常数和解离速率常数的条件[31,131,132]。NECEEM主要用于研究蛋白-蛋白、蛋白-DNA相互作用和适体-蛋白相互作用[31,127-131]。对于药物-蛋白结合分析,NECEEM已与质谱联用,开发无标记和基于溶液的方法来研究蛋白-小分子相互作用的动力学[133,134]。然而,该方法仅限于分析物和结合靶标具有相似电泳迁移率的系统[133]。

在平衡混合物的平衡CE(ECEEM)中,将处于平衡的混合物的一小段塞注入填充有结合靶标溶液的毛细管入口,该溶液的浓度与平衡混合物中靶标的浓度相同。通过CE进行样品组分的分离,入口和出口储液池均含有相同的靶标溶液[132]。该方法已被证明可用于研究具有复杂化学计量比的非共价相互作用的动力学,这可能发生在某些蛋白与基于肽的药物结合期间[132]。

#### 5.2.2 部分填充ACE

PFACE也称为塞-塞动力学CE(ppKCE)。在该方法中,分析物和结合靶标作为单独的带注入,然后允许相互作用[131]。这是传统ms ACE方法的一种变体,其中仅部分毛细管填充有含有结合靶标的BGE,毛细管其余部分填充有纯缓冲溶液[83,84,135-140]。该方法已被用于手性物质的分离和基于迁移率测量确定平衡常数[137,138,140-147]。

PFACE相对于传统ms ACE的一个优势是消耗更少的样品量。此外,可以在具有低背景信号的纯BGE中检测分析物,这可以改善信噪比[84,137,138]。PFACE还可以与包括MS在内的多种检测器联用[138]。然而,PFACE仅能在满足分析物和结合靶标迁移率的某些标准时使用[84,139,141,147]。例如,结合靶标理想情况下应不带电荷且没有可测量的迁移率[139],或应具有与分析物行进方向相反的迁移率[141]。最后,分析物的迁移率应足够高,以允许该剂在到达检测器之前完全通过靶标塞[139]。

FTPFACE是PFACE的另一种类型。在该方法中,毛细管填充有分析物塞,然后注入含有靶标和非相互作用标准的样品。当对系统施加电势时,样品和含有结合靶标和分析物的区域将开始重叠,允许建立局部平衡[131,149]。随着电势施加时间延长,靶标将流过含有分析物塞的区域[131,149]。然后确定靶标相对于非相互作用标准的相对迁移时间比,并与Scatchard分析一起用于获得分析物与靶标的结合常数[149]。

#### 5.3.3 多步配体注入ACE

MSLIACE是ACE的另一种动力学模式。该技术已被用于估计药物与一组具有相似质量和电荷的小肽相互作用的结合常数[150,151]。在该方法中,将肽和惰性标准的单独塞注入含有BGE中已知浓度药物的毛细管中。然后确定肽与药物相互作用时迁移时间的变化,并与Scatchard分析等技术一起用于获得该系统的结合常数[150,151]。该方法比常规ACE技术更快地确定某些药物与肽的结合常数,且使用更少的材料[151]。

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## 6 ACE和亲和CE在药物-蛋白结合相关方面的应用

前面的几节提供了ACE如何被用于研究药物与血清蛋白或相关结合剂相互作用的几个例子。前面描述的例子涉及均相方法的使用,其中靶结合剂和分析物之间的相互作用在溶液内发生,如在样品或运行缓冲液中[5,26,30,152,153]。然而,如图1所示,在CE中也可以使用异相方法,其中结合剂被固定在毛细管内表面上或放置在CE系统中用于捕获分析物的载体上[26,30,153,154]。后一种形式的亲和CE也可以被视为一种电色谱[7,26]。在本节中,将考虑CE的均相和异相应用,涉及药物与血清蛋白或相关结合剂相互作用的分析或使用。还将考虑使用基于CE的免疫分析来检查药物、基于血清蛋白的CE手性分离,以及使用混合CE方法检查药物或药物-蛋白相互作用。

### 6.1 CE中用于研究药物-蛋白相互作用的均相方法

从第5节描述的方法和表1提供的例子可以看出,ACE以区带洗脱形式使用是分析溶液中药物-蛋白相互作用的常用方法[5]。例如,这种组合已被用于研究阴离子碳水化合物和寡核苷酸与人血清淀粉样蛋白P组分肝素结合区衍生的合成肽的结合[155,156]。该形式还被用于表征普鲁卡因酰胺及其衍生物与血红蛋白和组蛋白的结合[157]。通过ACE使用均相方法和区带洗脱研究了HSA与几种氟喹诺酮的相互作用[158]。开发了一种使用化学修饰形式的HSA作为ACE中缓冲液添加剂的方法,并用于筛选布洛芬、布洛芬、舒洛芬和华法林在该蛋白Sudlow位点I和II的结合[61,159]。

区带洗脱和均相形式也被用于基于CE的免疫分析中,以测量样品中药物的游离和结合部分[5,26,160,161]。例如,该方法已与CE一起用于激素、胰岛素、胰高血糖素、皮质醇、地高辛、阿片类、氯霉素以及肿瘤标志物甲胎蛋白等靶标的免疫分析[131-142,162-173]。这种免疫分析形式也已与激光诱导荧光检测一起用于CE中,以估计抗胰岛素抗体与胰岛素的结合常数[174]。

在一些研究中,药物已被用作ACE中的缓冲液添加剂来测量药物-蛋白相互作用的平衡常数[5]。该方法的早期工作被用于同时确定多种对映体肽与万古霉素的结合[71]。还通过使用该方法研究了4-烷基苯磺酰胺与碳酸酐酶A和B的结合相互作用[40]。该方法的改进版本已被用于确定肽库中对万古霉素具有最高亲和力的肽,并估计可通过该方法同时筛选的最大结合剂数量[175]。

### 6.2 使用血清蛋白的CE手性分离

许多研究已通过CE进行,其中使用对映选择性选择剂作为缓冲液添加剂或固定化结合剂来分离手性药物[176]。这些工作使用的缓冲液添加剂包括蛋白、多糖、有机聚合物和手性胶束等[176-177,178]。基于CE的手性分离与液相色谱相比,可提供短分析时间、高效率以及低分析物、试剂和溶剂消耗[176,178]。

在各种研究中已描述了使用血清蛋白作为缓冲液添加剂进行手性药物的分离[7,88,179]。例如,HSA已被用作缓冲液添加剂来分离维拉帕米和氨氯地平的对映体[179]。BSA已被用作CE中麻黄碱对映体手性分离的缓冲液添加剂[180]。ms ACE已与激光诱导荧光检测联用,以HSA为手性选择剂,分离奥美拉唑对映体并测量这些对映体与HSA的结合常数[181]。

几项研究报道了使用电色谱研究药物对映体与HSA的结合[176,182-186]。例如,在该技术中使用了部分填充技术来研究HSA与溴苯那敏、氯苯那敏、羟嗪和奥芬那君对映体的结合[182]。此外,类似方法被用于使用羧甲基化-β-环糊精作为手性选择剂进行佐匹克隆的对映体分离[183]。该方法在同一研究中被用于评估佐匹克隆对映体与HSA的结合[183]。另一项研究采用电动色谱和部分填充技术研究了诺米芬辛对映体与HSA的结合,使用七-2,3,6-三-O-甲基-β-环糊精作为手性选择剂[184]。还报道了使用HSA作为手性选择剂通过电动色谱和部分填充技术进行nuarimol对映体的手性分离[185]。

几项额外研究使用ACE研究了血清结合剂与手性药物之间的结合。例如,ACE被用于估计AGP与丙吡胺和瑞莫必利对映体之间的条件缔合常数,使用部分填充技术[137]。通过ACE检查了HSA在与碱性药物美西律结合时的构象变化,以及pH、温度和其他参数对该药物手性分离的影响[187]。相关研究开发了一种使用HSA和猪血清白蛋白作为手性选择剂进行美西律、普萘洛尔和氯苯那敏对映体分离的方法[188]。CE-FA被用于研究生理条件下氨氯地平对映体与HSA的立体选择性结合[189]。

### 6.3 基于药物与血清蛋白相互作用的异相CE方法

基于CE的异相方法也已与血清蛋白一起用于研究药物相互作用或进行手性分离。在这些方法中,血清蛋白可以放置在凝胶中、偶联或涂覆在毛细管壁上,或偶联到填充在毛细管内的载体上[103,190-197]。

已描述了使用固定在凝胶中的BSA通过CE进行D-和L-色氨酸的手性分离[191]。BSA已被涂覆在聚苯乙烯纳米颗粒上,并用于CE中D-和L-色氨酸的分离[196]。另一项研究利用CE和固定在硅胶整体柱上的BSA进行D-和L-色氨酸的分离[197]。HSA在毛细管上的动态涂层已被用于CE中R-和S-华法林的分离[103]。此外,固定在有机整体柱中的纤维素和HSA混合物已被用于ACE中分离各种手性分析物[195]。

### 6.4 使用CE研究药物-蛋白相互作用的混合方法

最近的研究将CE与基于亲和力的液相色谱相结合,以表征几种药物与血清蛋白的结合[198,199]。例如,CE已与在线免疫萃取和高性能亲和色谱联用,以研究AGP与氯丙嗪、丙吡胺、丙咪嗪、普萘洛尔和华法林的相互作用[198]。CE在该工作中被用于测量和分析正常AGP和从系统性红斑狼疮(SLE)患者血清中获得的AGP的糖型(见图7)。然后使用含有固定化多克隆抗AGP抗体的亲和微柱,以前沿分析和区带洗脱形式研究这些药物与相同AGP样品的结合[198]。

开发了类似的混合CE方法并用于表征阿普林定、丙吡胺、伊马替尼、甲哌卡因和普萘洛尔与AGP和HSA的结合[199]。

### 6.5 使用CE研究药物与其他结合剂的相互作用

使用ACE研究药物与血液或血清中可发现的其他结合剂的相互作用也有报道[83,200-202]。例如,使用ACE研究了肝素与抗凝血酶III的相互作用[200]。另一项相关研究报道了使用ACE研究抗凝血酶III与低分子量肝素和磺达肝癸钠的结合[175]。此外,ACE已被用于研究肝素与完整LDL和载脂蛋白肽片段的相互作用[194]。

CE-FA被用于深入了解二肽β-萘基酰胺衍生物和七种阳离子氨基酸的化学性质如何影响其与糖胺聚糖透明质酸和HSA的结合[115]。PFACE被用于研究硫酸软骨素-6-与LDL和载脂蛋白B-100肽片段的结合[145]。

### 6.6 ACE中计算机模拟的应用

计算机模拟已在几项报告中被用于帮助描述和预测ACE中分析物的行为[90,92,98,106,203,204]。例如,ACE中分析物的迁移和带展宽可以通过使用适当的微分方程来描述[205]。然而,求解这些方程式并将其转化为可用于实验以获得参数(如分析物-结合剂复合物的平衡常数和迁移率)的形式可能相当具有挑战性[206]。

计算机模拟可以与这些微分方程和有限差分方案一起使用,以描述毛细管中分析物的行为。对于ms ACE、ppKCE和CE-FA等方法,该方法的底层数据处理和计算方法已得到显著改善[90,92,98,106,203,204],如近期综述所述[90,207]。然而,在ACE中专门使用计算机模拟来研究药物与血清蛋白或相关材料相互作用的应用尚不多见[98],使其成为未来研究的潜在兴趣领域。

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## 7 总结与展望

本文综述了ACE及相关CE方法在研究药物与血清结合剂相互作用方面的应用。本文还描述了该领域的最新进展。重点介绍了使用HSA、BSA和AGP等血清蛋白的工作,同时也考虑了血清或血液中发现的其他结合剂,如脂蛋白、抗凝血酶和抗体(见表1总结)。描述了可用于具有快速、中间或慢速相互作用动力学的系统的各种分析格式。本文讨论的具体格式包括ms ACE、基于空缺的ACE技术、ACE中Hummel-Dreyer方法的使用以及ACE中的前沿分析,以及NECEEM、ECEEM、部分填充ACE和多步配体注入ACE等方法。还描述了使用固定化结合靶标进行药物-蛋白相互作用研究或药物分析的CE异相方法。还考虑了用于分析此类技术数据的数学方法。

讨论的ACE及相关技术的应用包括药物-蛋白相互作用研究、手性药物分离以及CE在混合方法中用于表征药物与血清蛋白的结合。随着ACE及相关方法在药物与血清蛋白及相关结合靶标相互作用方面新工具的开发研究不断推进,预计未来将有更多应用出现。

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**利益冲突:** 作者声明无利益冲突。

**致谢:** 本工作部分得到美国国家科学基金会CMI 2108881资助和内布拉斯加大学研究委员会的支持。

**数据可用性声明:** 支持本研究结果的数据可根据合理要求从通讯作者处获得。