Biology subjects

Buchwald, P.

Publications and source records attributed to Buchwald, P..

10 recordsLinked to original sources

bioRxiv2026

Effect of Immunosuppressive Drugs on Glucose-Stimulated Insulin Secretion: Concentration-Response Studies in Dynamic Perifusion Assays

Immunosuppressive drugs, which are required to maintain graft function in transplant recipients, are associated with many unavoidable side effects including posttransplant diabetes mellitus (PTDM) that involves both peripheral insulin resistance and impairment of insulin secretion. To characterize in detail the concentration-dependency of the effect of well-known immunosuppressive drugs on glucose-stimulated insulin secretion (GSIS), we performed dynamic perifusion studies with human pancreatic islets. The effect on the time-profile of GSIS has been assessed over a wide concentration range for several clinically relevant immunomodulatory therapies, including small-molecule drugs (cyclosporine, sirolimus, tacrolimus, prednisolone acetate, and loteprednol etabonate) and biologics (abatacept and anti-CD40L), plus a prospective {beta}-cell proliferation-inducing agent (harmine). While biologics showed no significant detrimental effects after one-day treatment even at relatively high concentrations (5 {micro}M), all small-molecule drugs inhibited insulin secretion in a concentration-dependent manner, although glucocorticoids showed a distinct response pattern. Calcineurin and mTOR inhibitors preserved GSIS within their therapeutic ranges but progressively distorted its time-profile at higher concentrations and completely suppressed secretion at the highest levels. Cyclosporine exhibited the least, only about 35-fold, separation between its therapeutic target (Ctarg) and half-maximal GSIS inhibitory (IC50) concentrations. Glucocorticoids did not alter the shape of the time-profile but inhibited overall insulin secretion even at therapeutic levels. Their inhibitory effect only increased slowly with concentration and did not follow a classic sigmoid pattern that has unity Hill slope. These findings establish quantitative benchmarks for immunosuppressant-induced {beta}-cell toxicity and provide a framework for optimizing immunosuppressive regimens to reduce the risk of PTDM.

pharmacology and toxicology↗

bioRxiv2025

Assessing the Rate-Dependence of the First Phase of Glucose-Stimulated Insulin Secretion: Dynamic Perifusion Studies with Isolated Human Pancreatic Islets

Insulin released in response to a stepwise increase in glucose (square wave) is biphasic with a transient first-phase peak of 5-10 min and a more sustained second phase. While it is usually assumed that the first phase is rate- and the second is concentration-dependent, there are no detailed investigations into the rate-sensitivity of the first phase. We performed dynamic perifusion studies with isolated human pancreatic islets in a system that allowed fully customizable glucose ramps and established the corresponding insulin secretion time-profiles with high (once-a-minute) time-resolution. We considered the first-phase release to be the excess amount of insulin in addition to what would be expected from the glucose concentration-dependent second-phase release and examined its dependence on the glucose gradient (rate of increase). The average first-phase insulin release rate calculated this way increased with the gradient and could be fitted well with a Hill-type sigmoid function having a half-maximal value around 1.25 mM/min (nHill=1.8, r2=0.96). This agrees well with our previously introduced glucose-insulin control system built on a general framework of a sigmoid proportional-integral-derivative ({sigma}PID) controller, a generalized PID controller more suitable for biological systems than classic linear ones as biological responses are always limited between zero and a possible maximum. Experimental results obtained here were used to slightly readjust the parameters of this local glucose concentration-based computational model resulting in predictions in good agreement with measured first- and second-phase insulin secretions (r2>0.90). Thus, glucose-stimulated insulin secretion (GSIS) of perifused human islets can be described well as the sum of a rate-sensitive first phase, which is a sigmoid function of the glucose gradient with half-maximal value around 1.25 mM/min, and a concentration-sensitive second phase, which is a sigmoid function of the glucose concentration with half-maximal value around 8 mM.

physiology↗

bioRxiv2024

Quantification of Signal Amplification for Receptors: The Kd/EC50 Ratio of Full Agonists as a Gain Parameter

AO_SCPLOWBSTRACTC_SCPLOWConcentration-response relationships connecting the concentration of ligands to the responses they produce are central to pharmacology in general and form the core of quantitative pharmacology. While typically they can be well-described by hyperbolic functions (sigmoid on commonly used semi-log scales) and characterized by half-maximal concentrations values (EC50), their connection to receptor occupancy, characterized in a similar manner by the equilibrium dissociation constant Kd, can be complex due to the intermixing of the effects from occupancy-induced activation with those from partial agonism, constitutive activity, and pathway-specific signal amplification. Here, it is proposed that, as long as both occupancy and response follow such typical concentration-dependencies, signal amplification can be quantified using the gain parameter gK={kappa}=Kd/EC50 measured for full agonists. This is similar to the gain parameter used in electronics (e.g., gV=Vout/Vin for voltage). On customarily used semi-log representations, log gK corresponds to the horizontal shift between the response and occupancy curves, logKd-logEC50, the presence of which (i.e., Kd>EC50) is generally considered as evidence for the existence of "receptor reserve" or "spare receptors". The latter is a misnomer that should be avoided since even if there are excess receptors, there is no special pool of receptors "not required for ordinary use" as spare would imply. For partial agonists, the{kappa} =Kd/EC50 shift is smaller than for full agonists as not all occupied receptors are active. The gK gain parameter (full agonist Kd/EC50) correspond to the{gamma} gain parameter of the SABRE receptor model; for partial agonists ({varepsilon}<1), SABRE predicts a corresponding shift of{kappa} ={varepsilon}{gamma}-{varepsilon}+1.

pharmacology and toxicology↗

bioRxiv2024

A Composite Biomarker Signature of Type 1 Diabetes Risk Identified via Augmentation of Parallel Multi-Omics Data from a Small Cohort

BackgroundBiomarkers of early pathogenesis of type 1 diabetes (T1D) are crucial to enable effective prevention measures in at-risk populations before significant damage occurs to their insulin producing beta-cell mass. We recently introduced the concept of integrated parallel multi-omics and employed a novel data augmentation approach which identified promising candidate biomarkers from a small cohort of high-risk T1D subjects. We now validate selected biomarkers to generate a potential composite signature of T1D risk MethodsTwelve candidate biomarkers, which were identified in the augmented data and selected based on their fold-change relative to healthy controls and cross-reference to proteomics data previously obtained in the expansive TEDDY and DAISY cohorts, were measured in the original samples by ELISA ResultsAll 12 biomarkers had established connections with lipid/lipoprotein metabolism, immune function, inflammation, and diabetes, but only 7 were found to be markedly changed in the high-risk subjects compared to the healthy controls: ApoC1 and PON1 were reduced while CETP, CD36, FGFR1, IGHM, PCSK9, SOD1, and VCAM1 were elevated ConclusionsResults further highlight the promise of our data augmentation approach in unmasking important patterns and pathologically significant features in parallel multi-omics datasets obtained from small sample cohorts to facilitate the identification of promising candidate T1D biomarkers for downstream validation. They also support the potential utility of a composite biomarker signature of T1D risk characterized by the changes in the above markers.

biochemistry↗

bioRxiv2023

Quantitative Receptor Model for Responses That Are Left- or Right-Shifted Versus Occupancy (Are More or Less Concentration Sensitive): The SABRE Approach

AO_SCPLOWBSTRACTC_SCPLOWSimple one-to three-parameter models routinely used to fit typical dose-response curves and calculate EC50 values using the Hill or Clark equation cannot provide the full picture connecting measured response to receptor occupancy, which can be quite complex due to the interplay between partial agonism and (pathway-dependent) signal amplification. The recently introduced SABRE quantitative receptor model is the first one that explicitly includes a parameter for signal amplification ({gamma}) in addition to those for binding affinity (Kd), receptor-activation efficacy ({varepsilon}), constitutive activity ({varepsilon}R0), and steepness of response (Hill slope, n). It can provide a unified framework to fit complex cases, where fractional response and occupancy do not match, as well as simple ones, where parameters constrained to specific values can be used (e.g.,{varepsilon} R0=0,{gamma} =1, or n=1). Here, it is shown that SABRE can fit not only typical cases where response curves are left-shifted compared to occupancy ({kappa}=Kd/EC50>1) due to signal amplification ({gamma}>1), but also less common ones where they are right-shifted (i.e., less concentration-sensitive;{kappa} =Kd/EC50<1) by modeling them as apparent signal attenuation/loss ({gamma}<1). Illustrations are provided with -opioid receptor (MOPr) data from three different experiments with one left- and one right-shifted response (G protein activation and {beta}-arrestin2 recruitment, respectively; EC50,Gprt<Kd<EC50,{beta}Arr). For such cases of diverging pathways with differently shifted responses, partial agonists can cause very weak responses in the less concentration-sensitive pathway without having to be biased ligands due to the combination of low ligand efficacy and signal attenuation/loss - an illustration with SABRE-fitted oliceridine data is included.

pharmacology and toxicology↗

bioRxiv2022

Quantification of Receptor Binding from Response Data Obtained at Different Receptor Levels: A Simple Individual Sigmoid Fitting and a Unified SABRE Approach

Methods that allow quantification of receptor binding (occupancy) by measuring response (effect) data only are of interest as they can be used to allow characterization of binding properties (e.g., dissociation constant, Kd) without having to perform explicit ligand binding experiments that require different setups (e.g., use of labeled ligands). However, since response depends not just on the binding affinity-determined receptor occupancy, but also on receptor activation, which is affected by ligand efficacy (plus constitutive activity, if present), and downstream pathway amplification, this requires the acquisition and fitting of multiple concentration-response data. Here, two alternative methods, which both are straightforward to implement using nonlinear regression software, are described to fit such multiple responses measured at different receptor levels that can be obtained, for example, by partial irreversible receptor inactivation (i.e., Furchgott method) or different expression levels. One is a simple method via straightforward fitting of each response with sigmoid functions and estimation of Kd from the obtained Emax and EC50 values as Kd=(Emax{middle dot}EC50-Emax{middle dot}EC50)/(Emax-Emax). This is less error-prone than the original Furchgott method of double-reciprocal fit and simpler than alternatives that require concentration interpolations, thus, should allow more widespread use of this so-far underutilized approach to estimate binding properties. Relative efficacies can then be compared using Emax{middle dot}Kd/EC50 values. The other is a complex method that uses the SABRE receptor model to obtain a unified fit of the multiple concentration-response curves with a single set of parameters that include binding affinity Kd, efficacy{varepsilon} , amplification{gamma} , and Hill coefficient n. Illustrations with simulated and experimental data are presented including with activity data of three muscarinic agonists measured in rabbit myocardium.

pharmacology and toxicology↗

bioRxiv2022

Methylene Blue Is a Nonspecific Protein-Protein Interaction Inhibitor with Potential for Repurposing as an Antiviral for COVID-19

We have previously identified methylene blue, a tricyclic phenothiazine dye approved for clinical use for the treatment of methemoglobinemia and used for other medical applications, as a small-molecule inhibitor of the protein-protein interaction (PPI) between the spike protein of the SARS-CoV-2 coronavirus and ACE2, the first critical step of the attachment and entry of this coronavirus responsible for the COVID-19 pandemic. Here, we show that methylene blue concentration-dependently inhibits this PPI for the spike protein of the original strain as well as for those of variants of concerns such as the D614G mutant and delta (B.1.617.2) with IC50 in the low micromolar range (1-5 M). Methylene blue also showed promiscuous activity and inhibited several other PPIs of viral proteins (e.g., HCoV-NL63 - ACE2, hepatitis C virus E - CD81) as well as others (e.g., IL-2 - IL-2R) with similar potency. This non-specificity notwithstanding, methylene blue inhibited the entry of pseudoviruses bearing the spike protein of SARS-CoV-2 in hACE2-expressing host cells both for the original strain and the delta variant. It also blocked SARS-CoV-2 (B.1.5) virus replication in Vero E6 cells with an IC50 in the low micromolar range (1.7 M) when assayed using quantitative PCR of the viral RNA. Thus, while it seems to be a promiscuous PPI inhibitor with low micromolar activity and it has a relatively narrow therapeutic index, methylene blue inhibits entry and replication of SARS-CoV-2, including several of its mutant variants, and has potential as a possible inexpensive, broad-spectrum, orally bioactive small-molecule antiviral for the prevention and treatment of COVID-19.

pharmacology and toxicology↗

bioRxiv2020

Small-Molecule In Vitro Inhibitors of the Coronavirus Spike - ACE2 Protein-Protein Interaction as Blockers of Viral Attachment and Entry for SARS-CoV-2

Inhibitors of the protein-protein interaction (PPI) between the SARS-CoV-2 spike protein and ACE2, which acts as a ligand-receptor pair that initiates the viral attachment and cellular entry of this coronavirus causing the ongoing COVID-19 pandemic, are of considerable interest as potential antiviral agents. While blockade of such PPIs with small molecules is more challenging than with antibodies, small-molecule inhibitors (SMIs) might offer alternatives that are less strain- and mutation-sensitive, suitable for oral or inhaled administration, and more controllable / less immunogenic. Here, we report the identification of SMIs of this PPI by screening our compound-library that is focused on the chemical space of organic dyes. Among promising candidates identified, several dyes (Congo red, direct violet 1, Evans blue) and novel drug-like compounds (DRI-C23041, DRI-C91005) inhibited the interaction of hACE2 with the spike proteins of SARS-CoV-2 as well as SARS-CoV with low micromolar activity in our cell-free ELISA-type assays (IC50s of 0.2-3.0 M); whereas, control compounds, such as sunset yellow FCF, chloroquine, and suramin, showed no activity. Protein thermal shift assays indicated that the SMIs identified here bind SARS-CoV-2-S and not ACE2. Selected promising compounds inhibited the entry of a SARS-CoV-2-S expressing pseudovirus into ACE2-expressing cells in concentration-dependent manner with low micromolar IC50s (6-30 M). This provides proof-of-principle evidence for the feasibility of small-molecule inhibition of PPIs critical for coronavirus attachment/entry and serves as a first guide in the search for SMI-based alternative antiviral therapies for the prevention and treatment of diseases caused by coronaviruses in general and COVID-19 in particular.

pharmacology and toxicology↗

bioRxiv2020

Methylene Blue Inhibits In Vitro the SARS-CoV-2 Spike - ACE2 Protein-Protein Interaction - A Mechanism That Can Contribute to Its Antiviral Activity Against COVID-19

Due to our interest in the chemical space of organic dyes to identify potential small-molecule inhibitors (SMIs) for protein-protein interactions (PPIs), we initiated a screen of such compounds to assess their inhibitory activity against the interaction between SARS-CoV-2 spike protein and its cognate receptor ACE2, which is the first critical step initiating the viral attachment and entry of this coronavirus responsible for the ongoing COVID-19 pandemic. As part of this, we found that methylene blue, a tricyclic phenothiazine compound approved by the FDA for the treatment of methemoglobinemia and used for other medical applications (including the inactivation of viruses in blood products prior to transfusion when activated by light), inhibits this interaction. We confirmed that it does so in a concentration-dependent manner with a low micromolar half-maximal inhibitory concentration (IC50 = 3 M) in our protein-based ELISA-type setup, while chloroquine, siramesine, and suramin showed no inhibitory activity in this assay. Erythrosine B, which we have shown before to be a promiscuous SMI of PPIs, also inhibited this interaction with an activity similar, possibly slightly higher, than those found for it for other PPIs. This PPI inhibitory activity of methylene blue could contribute to its antiviral activity against SARS-CoV-2 even in the absence of light by blocking its attachment to ACE2-expressing cells and making this inexpensive and widely available drug potentially useful in the prevention and treatment of COVID-19 as an oral or inhaled medication.

pharmacology and toxicology↗

bioRxiv2020

Cdc42 GTPase Activating Proteins (GAPs) Maintain Generational Inheritance of Cell Polarity and Cell Shape in Fission Yeast

The highly conserved small GTPase Cdc42 regulates polarized cell growth and morphogenesis from yeast to humans. We previously reported that Cdc42 activation exhibits oscillatory dynamics in Schizosaccharomyces pombe cells. Mathematical modeling suggests that this dynamic behavior enables a variety of symmetric and asymmetric Cdc42 distributions to coexist in cell populations. For individual wild type cells, however, growth follows a stereotypical pattern where Cdc42 distribution is initially asymmetrical in young daughter cells and becomes more symmetrical as cell volume increases, enabling bipolar growth activation. To explore whether different states of Cdc42 activation are possible in a biological context, we examined S. pombe rga4{Delta} mutant cells, lacking the Cdc42 GTPase activating protein (GAP) Rga4. We found that monopolar rga4{Delta} mother cells divide asymmetrically leading to the emergence of both symmetric and asymmetric Cdc42 distributions in rga4{Delta} daughter cells. Using genetic screening approaches to identify mutants that alter the rga4{Delta} phenotype, we tested the predictions of different computational models that reproduce the unequal fate of daughter cells. We found experimentally that the unequal distribution of active Cdc42 GTPase in daughter cells is consistent with an unequal inheritance of another Cdc42 GAP, Rga6, in the two daughter cells. Our findings highlight the crucial role of Cdc42 GAP protein localization in determining the morphological fate of cell progeny and ensuring consistent Cdc42 activation and growth patterns across generations.

cell biology↗