Drug-protein Binding Research Articles

Effect of protein binding on the pharmacokinetics of the six substrates in the Basel phenotyping cocktail in healthy subjects and patients with liver cirrhosis

Phenotyping serves to estimate enzyme activities in healthy persons and patients in vivo. Low doses of enzyme-specific substrates are administered, and activities estimated using metabolic ratios (MR, calculated as AUCmetabolite/AUCparent). We administered the Basel phenotyping cocktail containing caffeine (CYP1A2 substrate), efavirenz (CYP2B6), flurbiprofen (CYP2C9), omeprazole (CYP2C19), metoprolol (CYP2D6) and midazolam (CYP3A) to 36 patients with liver cirrhosis and 12 control subjects and determined free and total plasma concentrations over 24 h. Aims were to assess whether MRs reflect CYP activities in patients with liver cirrhosis and whether MRs calculated with free plasma concentrations (MRfree) provide better estimates than with total concentrations (MRtotal). The correlation of MRtotal with MRfree was excellent (R2 >0.910) for substrates with low (<30 %, caffeine and metoprolol) and intermediate protein binding (≥30 and <99 %, midazolam and omeprazole) but weak (R2 <0.30) for substrates with high protein binding (≥99 %, efavirenz and flurbiprofen). The correlations between MRtotal and MRfree with CYP activities were good (R2 >0.820) for CYP1A2, CYP2C19 and CYP2D6. CYP3A4 activity was reflected better by midazolam elimination than by midazolam MRtotal or MRfree. The correlation between MRtotal and MRfree with CYP activity was not significant or weak for CYP2B6 and CYP2C9. In conclusion, MRs of substrates with an extensive protein binding (>99 %) show high inter-patient variabilities and do not accurately reflect CYP activity in patients with liver cirrhosis. Protein binding of the probe drugs has a high impact on the precision of CYP activity estimates and probe drugs with low or intermediate protein binding should be preferred.

Physicochemical Stimuli-Mediated Precipitation Approach for the Modulation of Rifampicin's Dissolution and Oral Bioavailability.

The intricate process of protein binding orchestrates crucial drug interactions within the bloodstream, facilitating the formation of soluble complexes. This research endeavours to improve the dissolution and oral bioavailability of Rifampicin (RMP) by strategically manipulating drug-protein binding dynamics and the hydrophobic characteristics of human serum albumin (HSA). Various precipitation techniques leveraging methanol, ammonium sulfate, and heat treatment were meticulously employed to tailor the properties of colloidal albumin (HSA NPs). The resultant complexes underwent comprehensive characterization encompassing evaluations of hydrophobicity, size distribution, surface charge, and structural analyses through FTIR, TG-DSC, XRD, and morphological examinations. The findings revealed a significant binding affinity of 78.07 ± 6.6% with native albumin, aligning with prior research. Notably, the complex RMP-HSA NPs-M13, synthesized via the methanolic precipitation method, exhibited the most substantial complexation, achieving a remarkable 3.5-fold increase, followed by the ammonium sulfate (twofold) and heat treatment (1.07-fold) methods in comparison to native albumin binding. The gastric simulated media exhibited accelerated drug release kinetics, with maximal dissolution achieved within two hours, contrasting with the prolonged release observed under intestinal pH conditions. These findings translated into significant improvements in drug permeation, as evidenced by pharmacokinetic profiles demonstrating elevated Cmax, AUC, t1/2, and MRT values for RMP-HSA NPs-M13 compared to free RMP. In summary, this innovative approach underscores the potential of precipitation methods in engineering stable colloidal carrier systems tailored to enhance the oral bioavailability of poorly soluble drugs, offering a pragmatic and scalable alternative to conventional surfactants, polymers, or high-energy methods for complex formation and production.

Dual-Probe Activity-Based Protein Profiling Reveals Site-Specific Differences in Protein Binding of EGFR-Directed Drugs.

Comparative, dose-dependent analysis of interactions between small molecule drugs and their targets, as well as off-target interactions, in complex proteomes is crucial for selecting optimal drug candidates. The affinity of small molecules for targeted proteins is largely dictated by interactions between amino acid side chains and these drugs. Thus, studying drug-protein interactions at an amino acid resolution provides a comprehensive understanding of the drug selectivity and efficacy. In this study, we further refined the site-specific activity-based protein profiling strategy (ABPP), PhosID-ABPP, on a timsTOF HT mass spectrometer. This refinement enables dual dose-dependent competition of inhibitors within a single cellular proteome. Here, a comparative analysis of two activity-based probes (ABPs), developed to selectively target the epidermal growth factor receptor (EGFR), namely, PF-06672131 (PF131) and PF-6422899 (PF899), facilitated the simultaneous identification of ABP-specific binding sites at a proteome-wide scale within a cellular proteome. Dose-dependent probe-binding preferences for proteinaceous cysteines, even at low nanomolar ABP concentrations, could be revealed. Notably, in addition to the intrinsic affinity of the electrophilic probes for specific sites in targeted proteins, the observed labeling intensity is influenced by several other factors. These include the efficiency of cellular uptake, the stability of the probes, and their intracellular distribution. While both ABPs showed comparable labeling efficiency for EGFR, PF131 had a broader off-target reactivity profile. In contrast, PF899 exhibited a higher labeling efficiency for the ERBB2 receptor and bound to catalytic cysteines in several other enzymes, which is likely to disrupt their catalytic activity. Notably, PF131 effectively labeled ADP/ATP translocase proteins at a concentration of just 1 nm, and we found this affected ATP transport. Analysis of the effect of PF131 and its parent inhibitor Afatinib on murine translocase SLC25A4 (ANT1)-mediated ATP transport strongly indicated that PF131 (10 μM) partially blocked ATP transport. Afatinib was less efficient at inhibiting ATP transport by SLC25A4 than PF131, and the reduction of ATP transport by Afatinib was not significant. Follow-up analysis is required to evaluate the affinity of these inhibitors for ADP/ATP translocase SLC25A4 in more detail. Additionally, the analysis of different binding sites within the EGF receptor and the voltage-dependent anion channel 2 revealed secondary binding sites of both probes and provided insights into the binding poses of inhibitors on these proteins. Insights from the PhosID-ABPP analysis of these two ABPs serve as a valuable resource for understanding drug on- and off-target engagement in a dose- and site-specific manner.

Identification of macrophage differentiation related genes and subtypes linking atherosclerosis plaque processing and metabolic syndrome via integrated bulk and single-cell sequence analysis

Metabolic syndrome(MS) is a separate risk factor for the advancement of atherosclerosis(AS) plaque but mechanism behind this remains unclear. There may be a significant role for the immune system in this process. This study aims to identify potential diagnostic genes in MS patients at a higher risk of developing and progressing to AS. Datasets were retrevied from gene expression omnibus(GEO) database and differentially expressed genes were identified. Hub genes, immune cell dysregulation and AS subtypes were identified using a conbination of muliple bioinformatic analysis, machine learning and consensus clustering. Diagnostic value of hub genes was estimated using a nomogram and ROC analysis. Finally, enrichment analysis, competing endogenous RNA(ceRNA) network, single-cell RNA(scRNA) sequencing analysis and drug-protein interaction prediction was constructed to identify the functional roles, potential regulators and distribution for hub genes. Four hub genes and two macrophage-related subtypes were identified. Their strong diagnostic value was validated and functional process were identified. ScRNA analysis identified the macrophage differentiation regulation function of F13A1. CeRNA network and drug-protein binding modes revealed the potential therapeutic method. Four immune-correlated hub genes(F13A1, MMRN1, SLCO2A1 and ZNF521) were identified with their diagnostic value being assesed, which F13A1 was found strong correlated with macrophage differentiation and could be potential diagnostic and therapeutic marker for AS progression in MS patients.

Sex-specific considerations in cardiovascular drug therapy.

Despite major advances in cardiac research over the past three decades, cardiovascular disease (CVD) still remains the leading cause of morbidity and mortality in women and men worldwide. However, a major challenge for health care providers is that the current guidelines for cardiovascular drug therapies do not consider the impact of sex in the development of treatment plan for optimizing therapies for women. Clinical research in recent years suggests significant pharmacological and pharmacokinetic differences between females and males, which have been attributed in part to differences in body composition, plasma protein binding capacity, drug metabolism, and excretion. Herein, we provide a comprehensive review regarding sex-specific differences and drugs commonly used for CVDs in women and men. Understanding how sex-related differences influence drug efficacy and CVD outcomes is crucial for not only optimizing treatment strategies for women and men but also to encourage the implementation of specific guidelines that address sex difference as a consideration for the treatment of CVDs.

ARIP: A Tool for Precise Interatomic Contact Area and Volume Calculation in Proteins.

The interplay patterns of amino acid residues are pivotal in determining the tertiary structure and flexibility of proteins, which in turn are intricately linked to their functionality and interactions with other molecules. Here, we introduce ARIP, a novel tool designed to identify contact residues within proteins. ARIP employs a modified version of the dr_sasa algorithm and an atomic overlap weighted algorithm to directly calculate the contact area and volume between atoms based on their van der Waals radius. It also allows for the selection of solvent radii, recognizing that not every atom in proteins can interact with water molecules. The solvent parameters were derived from the analysis of approximately 5000 protein and nucleic acid structures with water molecules determined using X-ray crystallography. One advantage of the modified algorithm is its capability to analyze multiple models within a single PDB file, making it suitable for molecular dynamic capture. The contact volume is symmetrically distributed between the interacting atoms, providing more informative results than contact area for the analysis of intra- and intermolecular interactions and the development of scoring functions. Furthermore, ARIP has been applied to four distinct cases: capturing key residue-residue contacts in NMR structures of P4HB, protein-drug binding of CYP17A1, protein-DNA binding of SPI1, and molecular dynamic simulations of BRD4.

Site-specific immobilization of Cysteinyl leukotriene receptor 1 through enzymatic DNA-protein conjugation strategy for lead screening

Immobilization of functional protein, especially G protein-coupled receptors (GPCRs), is particularly significant in various fields such as the development of assays for diagnosis, lead compound screening, as well as drug-protein interaction analysis. However, there are still some challenges with the immobilized proteins such as undefined loads, orientations, and the loss of activity. Herein, we introduced a DNA conjugation strategy into the immobilization of Cysteinyl leukotriene receptor 1(CysLTR1) which enables exquisite molecular control and higher activity of the receptor. We used the bacterial relaxases VirD2 as an immobilized tag fused at the C terminus of CysLTR1. Tyrosine residue(Y29) at the core binding site of the VirD2 tag can react with the single-strand piece of DNA(T-DNA) in the form of a covalent bond. Inspired by this strategy, we developed a new immobilization method by mixing the T-DNA-modified silica gel with the cell lysate containing the expressed VirD2-tagged CysLTR1 for 1 hour. We found that the successful formation of DNA-protein conjugate enables the immobilization of CysLTR1 fast, site-specific, and with minimal loss of activity. The feasibility of the immobilized CysLTR1 was evaluated in drug-protein binding interaction by frontal analysis and adsorption energy distribution analysis. The binding of pranlukast, zafirlukast, and MK571 to the immobilized CysLTR1 was realized, and the association constants presented good agreement between the two methods. Rosmarinic acid was retained in the immobilized CysLTR1 column, and the in-vitro test revealed that the compound binds to the receptor in one type of binding site mode. Despite these results, we concluded that the DNA-protein conjugate strategy will probably open up the possibilities for capturing other functional proteins in covalent and site-specific modes from the complex matrices and the immobilized receptor preserves the potential in fishing out lead compounds from natural products.

Effect of irradiated nonionic surfactant on drug-protein binding

In this work, the effect of γ-irradiated surfactants on drug–protein binding has been assessed. Irradiated aqueous solutions of Pluronic F-127, Pluronic L-35, Tween 20, and Tween 80 surfactants were used. Gamma irradiation was carried out for three different doses, to these four surfactants viz., 6, 30, and 36 kGy. Two drugs, Ornidazole (ONZ) and Telmisartan (TMS) were used for the binding study. The effect of four irradiated surfactants in the presence of drug – Bovine serum albumin (BSA) protein was analyzed. The drug solutions in methanol-aqueous media were combined with BSA in the initial step. In the next two succeeding steps, drug–BSA interaction in the presence of unirradiated and irradiated surfactants were carried out. The results of drug-BSA due to addition of irradiated and unirradiated surfactants were compared. The interaction processes were assessed through UV Spectroscopy, DLS, zeta potential, turbidity, and docking studies. Improved binding was observed for both the drugs and four surfactants for irradiated surfactants as determined from the binding constant values using UV spectroscopic studies. The DLS measurements demonstrated no general trend of increase or decrease in micellar size with absorbed dose. The binding and change in the size of micelles were observed to be highly drug and surfactant-specific. Among the four surfactants, irradiated Pluronic F-127 showed higher binding affinity. To the best of our knowledge, this is the first report on the effect of γ-irradiated surfactant on drug–BSA interaction. This can be applied to other drug–protein systems to tune their interaction to the required level. Communicated by Ramaswamy H. Sarma

Investigation of the Interaction of Monoamine Oxidase (MAO) Inhibitor Biscoumarins with Hemoglobin and Albumin Using Multi-Spectroscopic Techniques and Molecular Docking

Coumarin and their derivatives, such as biscoumarins, which are found as active ingredients in a variety of drugs, possess a wide range of biological activities. In this paper, the inhibitory effects of biscoumarin derivatives B1 and B2 on monoamine oxidase (MAO) enzyme activity were studied. Their binding mechanism to bovine serum hemoglobin (BHb) and bovine serum albumin (BSA) was investigated using molecular docking and multi-spectroscopic methods such as absorption, fluorescence, and synchronized fluorescence spectroscopy. The fluorescence quenching processes were analyzed using the Stern-Volmer, Lineweaver-Burk, and Hill methods. In this regard, Stern-Volmer quenching constants (Ksv), Lineweaver-Burk constants (KLB), and binding constants (Ka) were calculated at three temperatures (298, 310 and 322 K). The fluorescence studies showed that the binding of biscoumarins to BHb or BSA was a driven by static quenching. The Ka values of B2 to BHb and BSA (2179.11 and 18453.98 x 105 M-1) was larger than B1 at corresponding temperature (62.75 and 599.90 x105 M-1 for BHb and BSA, respectively), which indicates that the affinity of B2 toward the proteins were higher than that of B1. Moreover, thermodynamic parameters explained that hydrogen bonds were the main binding force stabilizing the protein-ligand complexes. Additionally, molecular docking studies have revealed binding energies, ligand efficiency values, and interactions with amino acid residues of proteins. The results of these investigations may be helpful in analyzing drug-protein binding of biscoumarins for potential future applications.

Using the Dynamic Well-Stirred Model to Extrapolate Hepatic Clearance of Organic Anion-Transporting Polypeptide Transporter Substrates without Assuming Albumin-Mediated Hepatic Drug Uptake.

Extrapolating in vivo hepatic clearance from in vitro uptake data is a known challenge, especially for organic anion-transporting polypeptide transporter (OATP) substrates, and the well-stirred model (WSM) commonly yields systematic underpredictions for those anionic drugs, hypothetically due to "albumin-mediated hepatic drug uptake". In the present study, we demonstrate that the WSM incorporating the dynamic free fraction (f D), a measure of drug protein binding affinity, performs reasonably well in predicting hepatic clearance of OATP substrates. For a selection of anionic drugs, including atorvastatin, fluvastatin, pravastatin, rosuvastatin, pitavastatin, cerivastatin, and repaglinide, this dynamic well-stirred model (dWSM) correctly predicts hepatic plasma clearance within 2-fold error for six out of seven OATP substrates examined. The geometric mean of clearance ratios between the predicted and the observed values falls in the range of 1.21-1.38. As expected, the WSM with unbound fraction (f u) systematically underpredicts hepatic clearance with greater than 2-fold error for five out of seven drugs, and the geometric mean of clearance ratios between the predicted and the observed values is in the range of 0.20-0.29. The results suggest that, despite its simplicity, the dWSM operates well for transporter-mediated uptake clearance, and that clearance under-prediction of OATP substrates may not necessarily be associated with the chemical class of the anionic drugs, nor is it a result of albumin-mediated hepatic drug uptake as currently hypothesized. Instead, the superior prediction power of the dWSM confirms the utility of the dynamic free fraction in clearance prediction and the importance of drug plasma binding kinetics in hepatic uptake clearance. SIGNIFICANCE STATEMENT: The traditional well-stirred model (WSM) consistently underpredicts organin anion-transporting polypeptide transporter (OATP)-mediated hepatic uptake clearance, hypothetically due to the albumin-mediated hepatic drug uptake. In this manuscript, we apply the dynamic WSM to extrapolate hepatic clearance of the OATP substrates, and our results show significant improvements in clearance prediction without assuming albumin-mediated hepatic drug uptake.

De novo design of drug-binding proteins with predictable binding energy and specificity.

The de novo design of small molecule-binding proteins has seen exciting recent progress; however, high-affinity binding and tunable specificity typically require laborious screening and optimization after computational design. We developed a computational procedure to design a protein that recognizes a common pharmacophore in a series of poly(ADP-ribose) polymerase-1 inhibitors. One of three designed proteins bound different inhibitors with affinities ranging from <5 nM to low micromolar. X-ray crystal structures confirmed the accuracy of the designed protein-drug interactions. Molecular dynamics simulations informed the role of water in binding. Binding free energy calculations performed directly on the designed models were in excellent agreement with the experimentally measured affinities. We conclude that de novo design of high-affinity small molecule-binding proteins with tuned interaction energies is feasible entirely from computation.

High-throughput assessment for drug protein binding using magnetized silica beads method in human liver microsomes

High-throughput assessment for drug protein binding using magnetized silica beads method in human liver microsomes

Facing the Facts of Altered Plasma Protein Binding: Do Current Models Correctly Predict Changes in Fraction Unbound in Special Populations?

Accounting for variability in plasma protein binding of drugs is an essential input to physiologically-based pharmacokinetic (PBPK) models of special populations. Prediction of fraction unbound in plasma (fu) in such populations typically considers changes in plasma protein concentration while assuming that the binding affinity remains unchanged. A good correlation between predicted vs observed fu data reported for various drugs in a given special population is often used as a justification for such predictive methods. However, none of these analyses evaluated the prediction of the fold-change in fu in special populations relative to the reference population. This would be a more appropriate assessment of the predictivity, analogous to drug-drug interactions. In this study, predictive performance of the single protein binding model was assessed by predicting fu for alpha-1-acid glycoprotein and albumin bound drugs in hepatic impairment, renal impairment, paediatric, elderly, patients with inflammatory disease, and in different ethnic groups for a dataset of >200 drugs. For albumin models, the concordance correlation coefficients for predicted fu were >0.90 for 16 out of 17 populations with sub-groups, indicating strong agreement between predicted and observed values. In contrast, concordance correlation coefficients for predicted fold-change in fu for the same dataset were <0.38 for all populations and sub-groups. Trends were similar for alpha-1-acid glycoprotein models. Accordingly, the predictions of fu solely based on changes in protein concentrations in plasma cannot explain the observed values in some special populations. We recommend further consideration of the impact of changes in special populations to endogenous substances that competitively bind to plasma proteins, and changes in albumin structure due to posttranslational modifications. PBPK models of special populations for highly bound drugs should preferably use measured fu data to ensure reliable prediction of drug exposure or compare predicted unbound drug exposure between populations knowing that these will not be sensitive to changes in fu.

Development of Tat-fused drug binding protein to improve anti-cancer effect of mammalian target of rapamycin inhibitors

Development of Tat-fused drug binding protein to improve anti-cancer effect of mammalian target of rapamycin inhibitors

A Secreted BBE-Like Enzyme Acting as a Drug-Binding Efflux Carrier Confers Microbial Self-Resistance to Mitomycin C.

The berberine bridge enzyme (BBE)-like flavoproteins have attracted continuous attention for their capability to catalyze various oxidative reactions. Here we demonstrate that MitR, a secreted BBE-like enzyme, functions as a special drug-binding efflux protein evolved from quinone reductase. Moreover, this protein provides self-resistance to its hosts toward the DNA-alkylating agent mitomycin C with a distinctive strategy, featured by independently performing drug binding and efflux.

A Tandem-Affinity Purification Method for Identification of Primary Intracellular Drug-Binding Proteins.

In the field of drug discovery, understanding how small molecule drugs interact with cellular components is crucial. Our study introduces a novel methodology to uncover primary drug targets using Tandem Affinity Purification for identification of Drug-Binding Proteins (TAP-DBP). Central to our approach is the generation of a FLAG-hemagglutinin (HA)-tagged chimeric protein featuring the FKBP12(F36V) adaptor protein and the TurboID enzyme. Conjugation of drug molecules with the FKBP12(F36V) ligand allows for the coordinated recruitment of drug-binding partners effectively enabling in-cell TurboID-mediated biotinylation. By employing a tandem affinity purification protocol based on FLAG-immunoprecipitation and streptavidin pulldown, alongside mass spectrometry analysis, TAP-DBP allows for the precise identification of drug-primary binding partners. Overall, this study introduces a systematic, unbiased method for identification of drug-protein interactions, contributing a clear understanding of target engagement and drug selectivity to advance the mode of action of a drug in cells.

Introducing the Dynamic Well-Stirred Model for Predicting Hepatic Clearance and Extraction Ratio

The well-stirred model (WSM) incorporating the fraction of unbound drug (fu) to account for the effect of plasma binding on intrinsic clearance has been widely used for predicting hepatic clearance under the assumption that drug protein binding reaches equilibrium instantaneously. Our theoretical analysis reveals that the effect of protein binding on intrinsic clearance is better accounted for with the dynamic free fraction (fD), a measure of drug protein binding affinity, which leads to a putative dynamic well-stirred model (dWSM) without the instantaneous equilibrium assumption. Using recombinant CYP3A4 as the in vitro clearance system, we demonstrate that the binding effect of albumin on the intrinsic clearance of both highly bound midazolam and highly free verapamil is fully corrected by their corresponding fD values, respectively. On the other hand, fu only corrects the binding effect of albumin on the intrinsic clearance of verapamil, and yields severe over-correction of the intrinsic clearance of midazolam. The results suggest that the traditional WSM is suitable for highly free drugs like verapamil but not necessarily for highly bound drugs such as midazolam due to the violation of the instantaneous equilibrium assumption or under-estimating the true free drug concentration. In comparison, the dWSM incorporating fD holds true as long as drug elimination follows steady-state kinetics, and hence, it is more broadly applicable to drugs with different protein binding characteristics. Here we demonstrate with 36 diverse drugs, that the dWSM significantly improves the accuracy of predicting human hepatic clearance and liver extraction ratio from in vitro microsomal clearance data, highlighting the importance of drug plasma protein binding kinetics in addressing the under-prediction of hepatic clearance by the WSM.

Computational analysis of RNA methyltransferase Rv3366 as a potential drug target for combating drug-resistant Mycobacterium tuberculosis.

Mycobacterium tuberculosis (M.tb) remains a formidable global health threat. The increasing drug resistance among M.tb clinical isolates is exacerbating the current tuberculosis (TB) burden. In this study we focused on identifying novel repurposed drugs that could be further investigated as potential anti-TB drugs. We utilized M.tb RNA methyltransferase Rv3366 (spoU) as a potential drug target due to its imperative activity in RNA modification and no structural homology with human proteins. Using computational modeling approaches the structure of Rv3366 was determined followed by high throughput virtual screening of Food and Drug Administration (FDA) approved drugs to screen potential binders of Rv3366. Molecular dynamics (MD) simulations were performed to assess the drug-protein binding interactions, complex stability and rigidity. Through this multi-step structure-based drug repurposing workflow two promising inhibitors of Rv3366 were identified, namely, Levodopa and Droxidopa. This study highlights the significance of targeting M.tb RNA methyltransferases to combat drug-resistant M.tb. and proposes Levodopa and Droxidopa as promising inhibitors of Rv3366 for future pre-clinical investigations.

Topical blood products modulate the effects of ophthalmic antibiotics against common bacterial pathogens in dogs with infectious keratitis.

Bacterial keratitis is a common and serious condition that often leads to vision impairment and potential loss of the eye if not treated promptly and adequately. Topical blood products are often used concurrently with topical antibiotics, helping to mitigate corneal 'melt' from proteases released on the ocular surface. However, blood products are rich in albumin and could affect the efficacy of antibiotics due to drug-protein binding. In this study, serum and plasma samples were harvested from 10 healthy dogs and 10 healthy horses, obtaining fresh and frozen (1 month at -20°C) aliquots for in vitro experiments. Albumin levels were quantified using species-specific ELISA kits. Thirty bacteria (10 Staphylococcus pseudintermedius, 10 Streptococcus canis, 10 Pseudomonas aeruginosa), isolated from canine patients with infectious keratitis, were each tested with blank plates as well as commercial susceptibility plates (Sensititre™ JOEYE2) to assess the minimal inhibitory concentration (MIC) of 17 different antibiotics in the absence (control) or presence of eight test groups: serum or plasma (fresh or frozen) from canines or equines. Albumin concentrations ranged from 13.8-14.6 mg/mL and 25.9-26.5 mg/mL in canine and equine blood products, respectively. A direct antimicrobial effect was observed mostly with equine vs. canine blood products (specifically serum and to a lesser degree plasma), and mostly for Staphylococcus pseudintermedius isolates. MICs generally increased in the presence of blood products (up to 10.8-fold), although MICs also decreased (down to 0.25-fold) for selected antibiotics and ocular pathogens. Median (range) fold changes in MICs were significantly greater (p = 0.004) with the canine blood products [2 (0.67-8.1)] than the equine blood products [2 (0.5-5)]. In practice, clinicians should consider equine over canine blood products (lesser impact on antimicrobial susceptibility), serum over plasma (greater antimicrobial effects), and administering the blood product ≥15 min following the last antibiotic eyedrop to minimize the amount of albumin-antibiotic binding in tear film.

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

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