Recent advances in the determination of unbound concentration and plasma protein binding of drugs: Analytical methods

An ultra-fast method for therapeutic drug monitoring of tacrolimus, sirolimus and cyclosporine A

Therapeutic drug monitoring for immunosuppressants is a widely conducted global practice. Traditionally, the pretreatment of whole blood involves the use of metal ions combined with organic solvents. However, this method requires multiple reagent additions, repeated opening, closing, and vortexing of vials, and it also leads to heavy metal pollution. Given the typically large sample volumes, optimizing this process is crucial for increasing throughput, reducing the workload of clinical staff, and lowering costs. We discovered that treating whole blood with a 60 to 75% acetonitrile (ACN) solution effectively releases tacrolimus, sirolimus, and cyclosporine A while simultaneously precipitating protein. This allowed us to significantly simplify the pretreatment process to just adding 65% ACN solution containing internal standards, manually shaking for 20 s, and centrifuging for 2 min. The resulted supernatant can then be directly analyzed by mass spectrometry. Method validation demonstrated that the new approach can accurately quantify tacrolimus in the range of 0.64 to 37.5 ng/ml, cyclosporine A at 12 to 976 ng/ml, and sirolimus at 0.99 to 43.4 ng/ml. A comparison of paired samples showed the new method to be perfectly consistent with the classical method, with 293 out of 300 results deviating by no more than ± 20%. This study has greatly simplified the workflow, increased throughput, and resolved environmental concerns for therapeutic drug monitoring of immunosuppressants, including tacrolimus, sirolimus, and cyclosporine A, in whole blood samples. The proposed method is a viable replacement for existing protocols and deserves to be adopted in all clinical laboratories with relevant practical needs globally.

Experimental and computational analysis of lipophilicity and plasma protein binding properties of potent tacrine based cholinesterase inhibitors

The lipophilicity of thirteen tacrine/piperidine-4-carboxamide derivatives was assessed using reversed-phase thin-layer chromatography (RP-TLC) with MeOH and acetonitrile (ACN) as organic modifiers. Among the parameters evaluated, the RM0 and C0 values obtained using MeOH were identified as the most reliable for characterizing the lipophilicity of the investigated compounds. The observed differences in lipophilicity among the derivatives resulted from a delicate interplay of substituent effects (hydrophobicity, polarity, steric hindrance, and electronic effects), positional influence, and characteristics of the organic modifier. The plasma protein-binding (PPB) properties of the tacrine derivatives were analyzed using an HPLC method with a human serum albumin (HSA) stationary phase and a mobile phase composed of phosphate buffer (pH = 7) and 2-propanol. The experimental %PPB values calculated using from two experiments ranged from 82.38 % to 94.54 %, and 84.29 % to 98.16 % suggesting that most compounds bind efficiently but not excessively to plasma proteins. Docking analysis revealed that all investigated ligands bind to Sudlow site I within HSA, which is the main binding site for heterocyclic aromatic compounds such as warfarine, azoprazone and tacrine. The key binding interactions are primarily hydrogen bonding and aromatic interactions. Principal component analysis (PCA), conducted on both experimentally determined and predicted lipophilicity values, as well as on predicted adsorption and experimentally and predicted distribution data, underscored the significant role of lipophilicity in influencing adsorption and distribution processes.

Unraveling binding interactions between methasterone and bovine serum albumin (BSA): A spectroscopic and computational study

In this study, binding interactions between methasterone and bovine serum albumin (BSA) were analyzed using spectroscopic techniques and molecular docking. UV absorption spectroscopy showed the formation of a ground-state complex between methasterone and bovine serum albumin (BSA). Thermodynamic parameters from fluorometric analysis indicated that the hydrogen bonding and van der Waal forces were the main interacting forces between the complex and the reaction was found to be spontaneous. Molecular docking further validated it. Nano differential scanning fluorimetry showed the protein was found to be more thermally stable in the presence of methasterone. Circular dichroism spectroscopy revealed slight reduction in the helicity after binding with methasterone suggesting conformational changes to promote binding. As no prior information exists on the binding interactions between methasterone and BSA, this study provides insights into methasterone-BSA interactions, which can serve as a foundation for future investigations into its pharmacological properties.

A Sequential Ultrafiltration Method to Enhance the Accuracy and Throughput in Plasma Protein Binding Tests

Objectives: Ultrafiltration (UF) is widely accepted as a method for assessing the plasma protein binding (PPB) of drugs. However, it is vulnerable to non-specific binding (NSB) to the device, which can result in inaccuracies. This study presents a straightforward, high-throughput modified UF method aimed at minimizing bias due to NSB. Methods: The modified UF method, sequential UF, features the addition of a 2 min pre-UF phase designed to saturate the NSB in the device, followed by the main 20 min UF procedure, compared to the conventional UF method. To evaluate the feasibility of this sequential UF method, we measured the PPB of nine compounds using sequential UF and compared these results to those obtained with the conventional mass balance UF method, recognized as a standard for NSB correction. Results: The PPB values determined through sequential UF were generally consistent with those derived from the mass balance UF method. The fold differences ranged from 97.9% to 113.8%, with an average of 103.5%. No significant differences were observed between the two methods for all compounds, with the exception of quercetin, which showed an unusually high PPB. Conclusions: Sequential UF was effective in correcting NSB to the device while providing advantages in terms of simplicity and efficiency.

The state-of-the-art machine learning model for plasma protein binding prediction: Computational modeling with OCHEM and experimental validation

Plasma protein binding (PPB) is closely related to pharmacokinetics, pharmacodynamics and drug toxicity. Existing models for predicting PPB often suffer from low prediction accuracy and poor interpretability, especially for high PPB compounds, and are most often not experimentally validated. Here, we carried out a strict data curation protocol, and applied consensus modeling to obtain a model with a coefficient of determination of 0.90 and 0.91 on the training set and the test set, respectively. This model (available on the OCHEM platform https://ochem.eu/article/29) was further retrospectively validated for a set of 63 poly-fluorinated molecules and prospectively validated for a set of 25 highly diverse compounds, and its performance for both these sets was superior to that of the other previously reported models. Furthermore, we identified the physicochemical and structural characteristics of high and low PPB molecules for further structural optimization. Finally, we provide practical and detailed recommendations for structural optimization to decrease PPB binding of lead compounds.

Virtual screening and evaluation of bioactive peptides from Haliotis discus hannai as potential HMGCR inhibitors for hyperlipidemia treatment

Introduction

Hyperlipidemia remains a major disease threatening global public health. The morbidity and mortality associated with cardiovascular diseases have been increasing. The inhibition of 3-Hydroxy-3-methylglutaryl-coenzyme A reductase (HMGCR), a key enzyme in the cholesterol synthesis pathway, can effectively reduce cholesterol levels.

Methods and results

In this study, the most suitable protease for preparing HMGCR inhibitory peptides was screened using the evaluation indexes of peptide yield and HMGCR inhibition rate. Peptide sequences with molecular weights <1 kDa were identified, and peptide fragments were docked with HMGCR for virtual screening. The inhibitory effects of these peptides on HMGCR activity were evaluated in vitro using a high-fat Hep-G2 cell model. The screened peptides possessed significant HMGCR inhibitory activity and reduced cholesterol micelle solubility and total cholesterol and triglyceride levels in hyperlipidemic Hep-G2 cells.

Conclusion

This study provides novel insights into developing natural drugs for hyperlipidemia; moreover, the results will facilitate the functional application of marine bioactive peptides.

Prediction of the binding interactions between rosmarinic acid and cysteinyl leukotriene receptor type 1 by molecular docking and immobilized receptor chromatography

Drug-protein interaction analysis is still at the center of research efforts to illustrate binding mechanisms and provide valuable information for selecting drug candidates with ideal properties in the early drug discovery stage. We present the prediction of the binding of rosmarinic acid (RA) to cysteinyl leukotriene receptor type1 (CysLTR1) by molecular docking. According to our findings, CysLTR1 is a potential anti-inflammatory target of RA. Under this assumption, we prepared the immobilized CysLTR1 column via a one-step method and characterized the immobilized CysLTR1 by fluorescent and chromatographic analyses. Furthermore, we used the immobilized CysLTR1 column to evaluate the binding interactions between RA and the immobilized receptor. Molecular docking showed that Tyr 249, Phe 174, Thr 280, Pro 177, and Thr 100 are the main sites for RA to interact with CysLTR1. The main forces that drive the findings are hydrogen bonds and hydrophobic interactions. Characterization results show that CysLTR1 is successfully immobilized with high specificity and stability. Almost no non-specific binding is observed on the immobilized CysLTR1 gels. The association constant and the binding sites are calculated to be 7.268 × 105 L mol-1 and 1.237 × 10-8 mol L-1 by injection amount-dependent method. These results, taken together, confirm the potential target of RA on the anti-inflammatory effect. We believe that it can provide valuable reference information on the in-depth exploration of drug-protein interaction mechanisms, and lead compound screening by this method.

Free serum concentrations of antibiotics determined by ultrafiltration: extensive evaluation of experimental variables

Aim: To assess the impact of experimental conditions on free serum concentrations as determined by ultrafiltration and HPLC-DAD analysis in a wide range of antibiotics.Materials & methods: Relative centrifugation force (RCF), temperature, pH and buffer were varied and the results compared with the standard protocol (phosphate buffer pH 7.4, 37°C, 1000 × g).Results: Generally, at 10,000 × g the unbound fraction (fu) decreased with increasing molecular weight, and was lower at 22°C. In unbuffered serum, the fu of flucloxacillin or valproic acid was increased, that of basic or amphoteric drugs considerably decreased. Comparable results were obtained using phosphate or HEPES buffer except for drugs which form metal chelate complexes.Conclusion: Maintaining a physiological pH is more important than strictly maintaining body temperature.

Recent advances in computational and experimental protein-ligand affinity determination techniques

INTRODUCTION

Modern drug discovery revolves around designing ligands that target the chosen biomolecule, typically proteins. For this, the evaluation of affinities of putative ligands is crucial. This has given rise to a multitude of dedicated computational and experimental methods that are constantly being developed and improved.

AREAS COVERED

In this review, the authors reassess both the industry mainstays and the newest trends among the methods for protein - small-molecule affinity determination. They discuss both computational affinity predictions and experimental techniques, describing their basic principles, main limitations, and advantages. Together, this serves as initial guide to the currently most popular and cutting-edge ligand-binding assays employed in rational drug design.

EXPERT OPINION

The affinity determination methods continue to develop toward miniaturization, high-throughput, and in-cell application. Moreover, the availability of data analysis tools has been constantly increasing. Nevertheless, cross-verification of data using at least two different techniques and careful result interpretation remain of utmost importance.

A developed and validated centrifugal ultrafiltration coupled with high performance liquid chromatography-tandem mass spectrometry method for rapid quantification of unbound lenvatinib in human plasma

In clinical practice, the determination of unbound drug concentration is very important for dose adjustment and toxicity prediction because only the unbound fraction can achieve a pharmacological effect. A fast, sensitive and accurate analytical method of centrifugal ultrafiltration coupled with high performance liquid chromatography-tandem mass spectrometry method was developed and applied to allow the quantification of unbound lenvatinib concentration. The application of linear regression analysis was used to examine the effects of centrifugal force, centrifugal time, and protein content on ultrafiltrate volume (Vu). The results indicated that the centrifugal force and centrifugal time have an influence on Vu that is significantly positive (P < 0.05). This developed method with good linearity (r2 = 0.9996), good accuracy (bias % ≤ 2.24 %), good precision (CV % ≤ 7.10 %), and good recovery (95.46 %-106.46 %) was suitable for routine clinical practice and studies. Particularly, the ultrafiltration membrane had no non-specific binding to lenvatinib. The unbound fractions can be separated in just 15 min. This method was applied to quantify clinical samples and to determine the plasma protein binding and unbound fraction of lenvatinib. This study provides a more effective and promising method for determination of unbound lenvatinib. It could be beneficial to measure the unbound concentration of lenvatinib in personalized medicine and therapeutic drug monitoring in routine clinical practice.

SERS-based detection of the antibiotic ceftriaxone in spiked fresh plasma and microdialysate matrix by using silver-functionalized silicon nanowire substrates

Therapeutic drug monitoring (TDM) is an important tool in precision medicine as it allows estimating pharmacodynamic and pharmacokinetic effects of drugs in clinical settings. An accurate, fast and real-time determination of the drug concentrations in patients ensures fast decision-making processes at the bedside to optimize the clinical treatment. Surface-enhanced Raman spectroscopy (SERS), which is based on the application of metallic nanostructured substrates to amplify the inherent weak Raman signal, is a promising technique in medical research due to its molecular specificity and trace sensitivity accompanied with short detection times. Therefore, we developed a SERS-based detection scheme using silicon nanowires decorated with silver nanoparticles, fabricated by means of top-down etching combined with chemical deposition, to detect the antibiotic ceftriaxone (CRO) in spiked fresh plasma and microdialysis samples. We successfully detected CRO in both matrices with an LOD of 94 μM in protein-depleted fresh plasma and 1.4 μM in microdialysate.

Development of a hollow fiber-liquid phase microextraction method using tissue culture oil for the extraction of free metoprolol from plasma samples

In this research, a method known as a hollow fiber-liquid-phase microextraction was employed to extract and concentrate free metoprolol from plasma samples. The extracted analyte was subsequently determined using high-performance liquid chromatography coupled with a diode-array detector. Several parameters, including hollow fiber length, sonication time, extraction temperature, and salt addition, were investigated and optimized to enhance extraction efficiency. After extracting the analyte under optimum conditions from plasma samples, the enrichment factor and extraction recovery were 50 and 86 %, respectively. Moreover, the method exhibited detection and quantification limits of 0.41 and 1.30 ng mL-1, respectively. The analysis of real samples demonstrated satisfactory relative recoveries in the range of 91-99 %.

Effects of vitamin C on the pharmacokinetics and pharmacodynamics of nimodipine in rats

In recent years, researchers have shown a growing interest in the interactions between different pharmaceutical agents. An intriguing instance lies in the possible interaction between nimodipine and vitamin C. To investigate the pharmacokinetic and pharmacodynamic effects of vitamin C on nimodipine in rats, rats were randomly divided into a nimodipine only group and a combination group (nimodipine + vitamin C). The two groups were given intragastric administration and nimodipine blood concentrations were determined using high-performance liquid chromatography-tandem mass spectrum at different time points. Blood pressure and heart rate were measured via carotid artery cannulation. Pharmacokinetic differences were observed between the nimodipine only group and the combination group at the same dose. Compared with the nimodipine only group, the combination group's main pharmacokinetic parameters of peak concentration and area under the curve increased significantly, and the difference was statistically significant (p < 0.05); furthermore, the combination group exhibited a significant reduction in average blood pressure, while no significant effects on heart rate were observed. Vitamin C did not affect the activity of CYP450 in rat liver. The pharmacokinetic characteristics and pharmacodynamics of nimodipine were changed by vitamin C administration in rats.

Targeted Protein Degraders- The Druggability Perspective

Targeted Protein degraders (TPDs) show promise in harnessing cellular machinery to eliminate disease-causing proteins, even those previously considered undruggable. Especially if protein turnover is low, targeted protein removal bestows lasting therapeutic effect over typical inhibition. The demonstrated safety and efficacy profile of clinical candidates has fueled the surge in the number of potential candidates across different therapeutic areas. As TPDs often do not comply with Lipinski's rule of five, developing novel TPDs and unlocking their full potential requires overcoming solubility, permeability and oral bioavailability challenges. Tailored in-vitro assays are key to precise profiling and optimization, propelling breakthroughs in targeted protein degradation.

A ternary nucleotide-lanthanide coordination nanoprobe for ratiometric fluorescence detection of ciprofloxacin

Ciprofloxacin (CIP) is a widely used broad-spectrum antibiotic and has been associated with various side effects, making its accurate detection crucial for patient safety, drug quality compliance, and environmental and food safety. This study presents the development of a ternary nucleotide-lanthanide coordination nanoprobe, GMP-Tb-BDC (GMP: guanosine 5'-monophosphate, BDC: 2-amino-1,4-benzenedicarboxylic acid), for the sensitive and ratiometric detection of CIP. The GMP-Tb-BDC nanoprobe was constructed by incorporating the blue-emissive ligand BDC into the Tb/GMP coordination polymers. Upon the addition of CIP, the fluorescence of terbium ion (Tb3+ ) was significantly enhanced due to the coordination and fluorescence sensitization properties of CIP, while the emission of the BDC ligand remained unchanged. The nanoprobe demonstrated good linearity in the concentration range of 0-10 μM CIP. By leveraging mobile phone software to analyze the color signals, rapid on-site analysis of CIP was achieved. Furthermore, the nanoprobe exhibited accurate analysis of CIP in actual drug and milk samples. This study showcases the potential of the GMP-Tb-BDC nanoprobe for practical applications in CIP detection.

In Vitro Metabolism and In Vivo Pharmacokinetics Profiles of Hydroxy-α-Sanshool

Hydroxy-α-sanshool (HAS) is the predominant active compound in Zanthoxylum bungeanum Maxim (ZBM). Our present work was aimed to explore the in vitro metabolism characteristics, and in vivo pharmacokinetic (PK) profile of HAS. Plasma (human), liver microsomes, and hepatocytes (human, monkey, dog, mouse, and rat) were collected for HAS metabolism studies in vitro and HAS elimination rates in liver microsomes and hepatocytes of different species were investigated. In addition, five recombinant human CYP enzymes were used to identify CYP isoforms of HAS. Finally, the PK properties of HAS in rats in vivo were studied by oral administration (p.o.). The results showed that HAS stably metabolized in human and rat liver microsomes and human hepatocytes, and the binding of HAS to human plasma proteins was nonspecific; HAS has strong inhibitory effects on CYP2C9 and CYP2D6 of human liver microsomes. In addition, in vivo PK study, HAS is rapidly absorbed in rats after oral administration. In conclusion, the in vivo and in vitro metabolic studies of HAS in this study provide data support for its further development and application, and the metabolic profiles of different species can be used as a reference for its safety evaluation.

Deep Learning for Drug Development: Using CNNs in MIA-QSAR to Predict Plasma Protein Binding of Drugs

Predicting plasma protein binding (PPB) is crucial in drug development due to its profound impact on drug efficacy and safety. In our study, we employed a convolutional neural network (CNN) as a tool to extract valuable information from the molecular structures of 100 different drugs. These extracted features were then used as inputs for a feedforward network to predict the PPB of each drug. Through this approach, we successfully obtained 10 specific numerical features from each drug's molecular structure, which represent fundamental aspects of their molecular composition. Leveraging the CNN's ability to capture these features significantly improved the precision of our predictions. Our modeling results revealed impressive accuracy, with an R2 train value of 0.89 for the training dataset, a [Formula: see text] of 0.98, a [Formula: see text] of 0.931 for the external validation dataset, and a low cross-validation mean squared error (CV-MSE) of 0.0213. These metrics highlight the effectiveness of our deep learning techniques in the fields of pharmacokinetics and drug development. This study makes a substantial contribution to the expanding body of research exploring the application of artificial intelligence (AI) and machine learning in drug development. By adeptly capturing and utilizing molecular features, our method holds promise for enhancing drug efficacy and safety assessments in pharmaceutical research. These findings underscore the potential for future investigations in this exciting and transformative field.

Identification of a Pentasaccharide Lead Compound with High Affinity to the SARS-CoV-2 Spike Protein via In Silico Screening

The spike (S) protein on the surface of the SARS-CoV-2 virus is critical to mediate fusion with the host cell membrane through interaction with angiotensin-converting enzyme 2 (ACE2). Additionally, heparan sulfate (HS) on the host cell surface acts as an attachment factor to facilitate the binding of the S receptor binding domain (RBD) to the ACE2 receptor. Aiming at interfering with the HS-RBD interaction to protect against SARS-CoV-2 infection, we have established a pentasaccharide library composed of 14,112 compounds covering the possible sulfate substitutions on the three sugar units (GlcA, IdoA, and GlcN) of HS. The library was used for virtual screening against RBD domains of SARS-CoV-2. Molecular modeling was carried out to evaluate the potential antiviral properties of the top-hit pentasaccharide focusing on the interactive regions around the interface of RBD-HS-ACE2. The lead pentasaccharide with the highest affinity for RBD was analyzed via drug-likeness calculations, showing better predicted druggable profiles than those currently reported for RBD-binding HS mimetics. The results provide significant information for the development of HS-mimetics as anti-SARS-CoV-2 agents.

Plasma Protein-Mediated Uptake and Contradictions to the Free Drug Hypothesis: A Critical Review

According to the free drug hypothesis (FDH), only free, unbound drug is available to interact with biological targets. This hypothesis is the fundamental principle that continues to explain the vast majority of all pharmacokinetic and pharmacodynamic processes. Under the FDH, the free drug concentration at the target site is considered the driver of pharmacodynamic activity and pharmacokinetic processes. However, deviations from the FDH are observed in hepatic uptake and clearance predictions, where observed unbound intrinsic hepatic clearance (CL_int,u) is larger than expected. Such deviations are commonly observed when plasma proteins are present and form the basis of the so-called plasma protein-mediated uptake effect (PMUE). This review will discuss the basis of plasma protein binding as it pertains to hepatic clearance based on the FDH, as well as several hypotheses that may explain the underlying mechanisms of PMUE. Notably, some, but not all, potential mechanisms remained aligned with the FDH. Finally, we will outline possible experimental strategies to elucidate PMUE mechanisms. Understanding the mechanisms of PMUE and its potential contribution to clearance underprediction is vital to improving the drug development process.

Therapeutic drug monitoring of free vancomycin concentration in practice: A new analytical technique based on the HFCF-UF sample separation method

The aim of this study was to establish a method for free vancomycin concentration determination in human plasma and apply it to clinical therapeutic drug monitoring (TDM). The unbound vancomycin in plasma was separated by the hollow fiber centrifugal ultrafiltration (HFCF-UF) technique and analyzed by HPLC. Chromatographic conditions were optimized, the specificity, linearity, precision, recovery and stability of the method were examined, and plasma samples of patients were measured. The standard curve for free vancomycin is y = 0.0277x - 0.0080 with good linearity within 0.25-50 μg·mL^-1 . The relative and absolute recovery rates for vancomycin were 98.63-101.0% and 88.41-101.2%, respectively. The intraday and interday precision RSDs were <10%. Plasma was stable under several conditions. The TDM value of the free vancomycin concentration of 20 patients was 0.99-38.51 μg·mL^-1 , and the correlation between the free and total concentrations was not significant. The unbound fraction of vancomycin ranged from 25.5 to 84.8%, with large variation. The operation of free vancomycin separation by HFCF-UF was simple and suitable for TDM in practice. The unbound fraction of vancomycin in clinical samples varied significantly between individuals. It is recommended to perform free concentration TDM in critically ill patients.

Recent Studies of Artificial Intelligence on In Silico Drug Distribution Prediction

Drug distribution is an important process in pharmacokinetics because it has the potential to influence both the amount of medicine reaching the active sites and the effectiveness as well as safety of the drug. The main causes of 90% of drug failures in clinical development are lack of efficacy and uncontrolled toxicity. In recent years, several advances and promising developments in drug distribution property prediction have been achieved, especially in silico, which helped to drastically reduce the time and expense of screening undesired drug candidates. In this study, we provide comprehensive knowledge of drug distribution background, influencing factors, and artificial intelligence-based distribution property prediction models from 2019 to the present. Additionally, we gathered and analyzed public databases and datasets commonly utilized by the scientific community for distribution prediction. The distribution property prediction performance of five large ADMET prediction tools is mentioned as a benchmark for future research. On this basis, we also offer future challenges in drug distribution prediction and research directions. We hope that this review will provide researchers with helpful insight into distribution prediction, thus facilitating the development of innovative approaches for drug discovery.

Sample preparation and chromatographic methods for the determination of protein-bound uremic retention solutes in human biological samples: An overview

Protein-bound uremic retention solutes, such as indole-3-acetic acid, indoxyl sulfate, p-cresol and p-cresol sulfate, are associated with the development of several pathologies, namely renal, cardiovascular, and bone toxicities, due to their potential accumulation in the human body, thus requiring analytical methods for monitoring and evaluation. The present review addresses conventional and advanced sample treatment procedures for sample handling and the chromatographic analytical methods developed for quantification of these compounds in different biological fluids, with particular focus on plasma, serum, and urine. The sample preparation and chromatographic methods coupled to different detection systems are critically discussed, focusing on the different steps involved for sample treatment, namely elimination of interfering compounds present in the sample matrix, and the evaluation of their environmental impact through the AGREEprep tool. There is a clear trend for the application of liquid-chromatography coupled to tandem mass spectrometry, which requires protein precipitation, solid-phase extraction and/or dilution prior to analysis of biological samples. Furthermore, from a sustainability point of view, miniaturized methods resorting to microplate devices are highly recommended.

Structure-guided discovery of food-derived GABA-T inhibitors as hunters for anti-anxiety compounds

With the acceleration of the pace of life, people may face all kinds of pressure, and anxiety has become a common mental issue that is seriously affecting human life. Safe and effective food-derived compounds may be used as anti-anxiety compounds. In this study, anti-anxiety compounds were collected and curated for database construction. Quantitative structure-activity relationship (QSAR) models were developed using a combination of various machine-learning approaches and chemical descriptors to predict natural compounds in food with anti-anxiety effects. High-throughput molecular docking was used to screen out compounds that could function as anti-anxiety molecules by inhibiting γ-aminobutyrate transaminase (GABA-T) enzyme, and 7 compounds were screened for in vitro activity verification. Pharmacokinetic analysis revealed three compounds (quercetin, lithocholic acid, and ferulic acid) that met Lipinski's Rule of Five and inhibited the GABA-T enzyme to alleviate anxiety in vitro. The established QSAR model combined with molecular docking and molecular dynamics was proved by the synthesis and discovery of novel food-derived anti-anxiety compounds.

An Overview of Analytical Methodologies for Determination of Vancomycin in Human Plasma

Vancomycin is regarded as the last resort of defense for a wide range of infections due to drug resistance and toxicity. The detection of vancomycin in plasma has always aroused particular concern because the performance of the assay affects the clinical treatment outcome. This article reviews various methods for vancomycin detection in human plasma and analyzes the advantages and disadvantages of each technique. Immunoassay has been the first choice for vancomycin concentration monitoring due to its simplicity and practicality, occasionally interfered with by other substances. Chromatographic methods have mainly been used for scientific research due to operational complexity and the particular requirement of the instrument. However, the advantages of a small amount of sample needed, high sensitivity, and specificity makes chromatography irreplaceable. Other methods are less commonly used in clinical applications because of the operational feasibility, clinical application, contamination, etc. Simplicity, good performance, economy, and environmental friendliness have been points of laboratory methodological concern. Unfortunately, no one method has met all of the elements so far.

Plasma Protein Binding Rate and Pharmacokinetics of Lekethromycin in Rats

Lekethromycin (LKMS), a novel macrolide lactone, is still unclear regarding its absorption. Thus, we conducted this study to investigate the characteristics of LKMS in rats. We chose the ultrafiltration method to measure the plasma protein binding rate of LKMS. As a result, LKMS was characterized by quick absorption, delayed elimination, and extensive distribution in rats following intramuscular (im) and subcutaneous (sc) administration. Moreover, LKMS has a high protein binding rate (78–91%) in rats at a concentration range of 10–800 ng/mL. LKMS bioavailability was found to be approximately 84–139% and 52–77% after im and sc administration, respectively; however, LKMS was found to have extremely poor bioavailability after oral administration (po) in rats. The pharmacokinetic parameters cannot be considered linearly correlated with the administered dose. Additionally, LKMS and its corresponding metabolites were shown to be metabolically stable in the liver microsomes of rats, dogs, pigs, and humans. Notably, only one phase I metabolite was identified during in vitro study, suggesting most of drug was not converted. Collectively, LKMS had quick absorption but poor absorption after oral administration, extensive tissue distribution, metabolic stability, and slow elimination in rats.

Clinical Pharmacokinetic Monitoring of Free Valproic Acid Levels: A Systematic Review

BACKGROUND

Current guidelines recommend therapeutic drug monitoring as a critical component of valproic acid (VPA) therapy. Due to high protein binding, the active unbound (free) portion of VPA can be misrepresented by total VPA serum levels in certain clinical scenarios. Monitoring free VPA serum levels may be warranted when assessing the clinical response to VPA therapy.

OBJECTIVES

The aims were to conduct a systematic review to identify a therapeutic range for free VPA serum levels; to explore the correlation of free VPA serum levels with clinical toxicity and therapeutic benefit; and to examine predictors of discordance between free and total VPA levels.

METHODS

Medline, EMBASE, Cochrane Central Register of Controlled Trials (CENTRAL), PsycINFO, BIOSIS Previews, and Cumulative Index to Nursing and Allied Health Literature (CINAHL) were searched from the time of database inception to June 20, 2021. Randomized controlled trials and observational studies that evaluated any patient receiving VPA with free VPA level monitoring were included.

RESULTS

Of 189 citations, we identified 27 relevant studies, which included 14 observational studies, two case series, and 11 case reports. Three studies provided a therapeutic range for free VPA levels between 20 and 410 μmol/L. Two studies suggested the occurrence of hyperammonemia and thrombocytopenia at free VPA serum levels above 60 µmol/L and 103.3 µmol/L, respectively. Two studies suggested an upper limit for neurotoxicity at free VPA serum levels of 70 µmol/L and 207.9 µmol/L. Hypoalbuminemia was identified as a predictor of therapeutic discordance.

CONCLUSIONS

This review demonstrates a paucity of data informing the clinical utility of free VPA serum levels. Further high-quality trials are needed to validate an optimal therapeutic range for free VPA levels.

[Annual review of capillary electrophoresis technology in 2021]

This paper provides an annual review of capillary electrophoresis (CE) technology in 2021. A total of 291 research papers related to CE technology published in 2021 were retrieved from the ISI Web of Science using the keywords, "capillary electrophoresis-mass spectrometry" "capillary isoelectric focusing" "micellar electrokinetic chromatography", or "capillary electrophoresis" (not "capillary electrochromatography" "microchip" and "capillary monolithic column"). In addition, nine research papers related to CE technology in Chinese journals were reviewed: Chinese Journal of Chromatography and Chinese Journal of Analytical Chemistry. This review focused on seven papers published in Coordination Chemistry Reviews, Angewandte Chemie-International Edition, Nature Protocols, TrAC-Trends in Analytical Chemistry, and Signal Transduction and Targeted Therapy with impact factors (IFs) greater than 10.0, as well as 42 papers reported in Analytical Chemistry, Analytica Chimica Acta, Talanta, and Food Chemistry with IFs between 5.0 and 10.0. This review also provides a comprehensive overview of representative CE works in Journal of Chromatography A and Electrophoresis with IFs<5.0, as well as important Chinese journals, Chinese Journal of Chromatography and Chinese Journal of Analytical Chemistry. According to the IF, this paper introduces the representative work of CE-related papers to allow readers to quickly understand the important research progress of CE technology in the past year.

The importance of plasma protein and tissue binding in a drug discovery program to successfully deliver a preclinical candidate

Plasma protein binding and tissue binding are arguably two of the most critical parameters that are measured as part of a drug discovery program since, according to the free drug hypothesis, it is the free drug that is responsible for both efficacy and toxicity. This chapter aims to deconstruct the role of plasma protein and tissue binding in drug discovery programs, and to consider the conclusion made by Pfizer and Genentech/Depomed a decade ago that optimising plasma protein binding as an independent parameter does not significantly influence efficacy. This chapter will also examine how binding metrics are applied in drug discovery programs and explore circumstances where optimising plasma protein or tissue binding can be an effective strategy to deliver a candidate molecule for preclinical development with an early indication of sufficient therapeutic index.

IDL-PPBopt: A Strategy for Prediction and Optimization of Human Plasma Protein Binding of Compounds via an Interpretable Deep Learning Method

The prediction and optimization of pharmacokinetic properties are essential in lead optimization. Traditional strategies mainly depend on the empirical chemical rules from medicinal chemists. However, with the rising amount of data, it is getting more difficult to manually extract useful medicinal chemistry knowledge. To this end, we introduced IDL-PPBopt, a computational strategy for predicting and optimizing the plasma protein binding (PPB) property based on an interpretable deep learning method. At first, a curated PPB data set was used to construct an interpretable deep learning model, which showed excellent predictive performance with a root mean squared error of 0.112 for the entire test set. Then, we designed a detection protocol based on the model and Wilcoxon test to identify the PPB-related substructures (named privileged substructures, PSubs) for each molecule. In total, 22 general privileged substructures (GPSubs) were identified, which shared some common features such as nitrogen-containing groups, diamines with two carbon units, and azetidine. Furthermore, a series of second-level chemical rules for each GPSub were derived through a statistical test and then summarized into substructure pairs. We demonstrated that these substructure pairs were equally applicable outside the training set and accordingly customized the structural modification schemes for each GPSub, which provided alternatives for the optimization of the PPB property. Therefore, IDL-PPBopt provides a promising scheme for the prediction and optimization of the PPB property and would be helpful for lead optimization of other pharmacokinetic properties.

Comparison of liquid-liquid extraction, microextraction and ultrafiltration for measuring free concentrations of testosterone and phenytoin

Aim: The purpose of the study was to find methods suitable for measuring the free concentrations of testosterone and phenytoin. Materials & methods: Sample solutions of the compounds in buffer and human albumin were processed using liquid-liquid extraction, microextraction and ultrafiltration and analyzed by LC-MS/MS. Results: Liquid-liquid extraction with dibutyl phthalate provided complete extraction from buffer solutions and partial extraction from albumin samples. Spintip C18 devices provided exhaustive extraction from buffer and albumin samples. Spintip C8 devices offered complete extraction from buffer and approximately 50% recovery from albumin samples. Centrifree ultrafiltration devices showed high recovery of free concentrations from all the samples, while Amicon and Nanosep devices provided partial recovery. Conclusion: Spintip C8 and Centrifree devices proved useful for measuring free concentrations.

A rapid and simple electrochemical detection of the free drug concentration in human serum using boron-doped diamond electrodes

Monitoring drug concentration in blood and reflecting this in the dosage are crucial for safe and effective drug treatment.

Optimizing a High-Throughput Solid-Phase Microextraction System to Determine the Plasma Protein Binding of Drugs in Human Plasma

Plasma protein binding refers to the binding of a drug to plasma proteins after entering the body. The measurement of plasma protein binding is essential during drug development and in clinical practice, as it provides a more detailed understanding of the available free concentration of a drug in the blood, which is in turn critical for pharmacokinetics and pharmacodynamics studies. In addition, the accurate determination of the free concentration of a drug in the blood is also highly important for therapeutic drug monitoring and in personalized medicine. The present study uses C₁₈-coated solid-phase microextraction 96-pin devices to determine the free concentrations of a set of drugs in plasma, as well as the plasma protein binding of drugs with a wide range of physicochemical properties. It should be noted that the extracted amounts used to calculate the binding constants and plasma protein bindings should be measured at respective equilibrium for plasma and phosphate buffer. Therefore, special attention is placed on properly determining the equilibration times required to correctly estimate the free concentrations of drugs in the investigated systems. The plasma protein binding values obtained with the 96-pin devices are consistent with those reported in the literature. The 96-pin device used in this research can be easily coupled with a Concept96 or other automated robotic systems to create an automated plasma protein binding determination protocol that is both more time and labor efficient compared to conventional equilibrium dialysis and ultrafiltration methods.

Solid-phase microextraction for assessment of plasma protein binding, a complement to rapid equilibrium dialysis

Aim: Determination of plasma protein binding (PPB) is considered vital for better understanding of pharmacokinetic and pharmacodynamic activities of drugs due to the role of free concentration in pharmacological response. Methodology & results: Solid-phase microextraction (SPME) was investigated for measurement of PPB from biological matrices and compared with a gold standard approach (rapid equilibrium dialysis [RED]). Discussion & conclusion: SPME-derived values of PPB correlated well with literature values, and those determined by RED. Respectively, average protein binding across three concentrations by RED and SPME was 33.1 and 31.7% for metoprolol, 89.0 and 86.6% for propranolol and 99.2 and 99.0% for diclofenac. This study generates some evidence for SPME as an alternative platform for the determination of PPB.