Competitive Binding Model Research Articles

Linking Transthyretin-Binding Chemicals and Free Thyroid Hormones: In Vitro to In Vivo Extrapolation Based on a Competitive Binding Model.

Large numbers of pollutants competitively inhibit the binding between thyroid hormones and transthyretin (TTR) in vitro. However, the impact of this unintended binding on free thyroid hormones in vivo has not yet been characterized. Herein, we established a quantitative in vitro to in vivo extrapolation (QIVIVE) method based on a competitive binding model to quantify the effect of TTR-binding chemicals on free thyroid hormones in human blood. Twenty-five TTR-binding chemicals including 6 hydroxyl polybromodiphenyl ethers (OH-PDBEs), 6 hydroxyl polychlorobiphenyls (OH-PCBs), 4 halogenphenols, 5 per- and polyfluorinated substances (PFASs), and 4 phenols were selected for investigation. Incorporating the in vitro binding parameters and human exposure data, the QIVIVE model could well predict the in vivo effect on free thyroid hormones. Co-exposure to twenty-five typical TTR-binding chemicals resulted in median increases of 0.080 and 0.060% in circulating levels of free thyroxine (FT4) and free triiodothyronine (FT3) in the general population. Individuals with occupational exposure to TTR-binding chemicals suffered 1.88-32.2% increases in free thyroid hormone levels. This study provides a quantitative tool to evaluate the thyroid-disrupting risks of TTR-binding chemicals and proposes a new framework for assessing the in vivo effects of chemical exposures on endogenous molecules.

A Phase 1 Study of Plamotamab, an Anti-CD20 x Anti-CD3 Bispecific Antibody, in Patients with Relapsed/Refractory Non-Hodgkin's Lymphoma: Recommended Dose Safety/Efficacy Update and Escalation Exposure-Response Analysis

Introduction: Plamotamab is a humanized bispecific antibody that binds both CD20 and CD3 and recruits cytotoxic T cells to kill CD20-expressing malignant cells. In the dose-escalation phase of an ongoing first-in-human (FIH) Ph 1 study (XmAb13676-01; NCT02924402), plamotamab was well tolerated with manageable cytokine release syndrome (CRS) and demonstrated evidence of clinical activity in heavily pretreated patients (pts) with relapsed/refractory (R/R) non-Hodgkin's lymphoma (NHL) (Patel; ASH 2021). Here, exposure-response (ER) analyses of the dose-escalation cohorts from the same study are reported. Safety and efficacy results from the follicular lymphoma (FL) and diffuse large B-cell lymphoma (DLBCL) escalation (Part C) and expansion cohorts at the proposed recommended dosing regimen (RD) are also reported. Methods: The study is an FIH, multi-center, open-label Ph 1 dose-escalation study in R/R NHL pts. The dose-escalation phase has 3 Parts: Parts A and B using weight-based dosing; Part C using flat step-up doses (SUD). An IV RD was identified from Part C, which was used to expand into FL and DLBCL. Treatment was continued for ≥2 cycles if therapeutic benefit was evident. ER analysis was conducted based on exposure metrics calculated using population pharmacokinetic (popPK) model for plamotamab vs. observed responses related to efficacy/safety from Parts A, B, and C. Results: At data cut-off for RD safety/efficacy evaluation (25July2022), 36 pts were enrolled on or before 01April2022 (median age: 67 years, range: 36-86; 61% male). At baseline, 11.1% had stage III disease and 69.4% had stage IV disease. Median number of prior lines of therapy was 4 (range: 2-10), with 50% pts receiving CAR-T as a prior therapy (16 pts with DLBCL, 2 pts from other NHL subtypes, and no pts with FL). After last therapy, 91.7% of all pts had relapsed/progressed. In the RD safety population (n=36), CRS was the most common adverse event (AE; 72.2%). CRS was mostly confined to Cycle 1 and no Grade (Gr)≥3 CRS was reported. Treatment-emergent AEs (≥25%) included anemia (44.4%), pyrexia and nausea (38.9% each), asthenia (27.8%), and aspartate aminotransferase increase, diarrhea, and hypophosphatemia (25.0% each). Gr≥3 AEs (≥10%; 77.8% overall) were anemia (19.4%), neutropenia and neutrophil count decreased (16.7% each) and thrombocytopenia (11.1%). SAEs (≥5%; 55.6% overall) were CRS (25.0%), COVID-19 (8.3%), pneumonia and sepsis (5.6% each). AEs leading to plamotamab discontinuation occurred in 5 pts (13.9%). Overall, 25 pts were evaluable for efficacy at the RD. DLBCL pts at the RD (n=19) had an objective response (OR) rate of 47.4% (9/19 pts) and CMR/CR rate of 26.3% (5/19 pts); DLBCL pts with prior CAR-T had an OR rate of 46.2% (6/13 pts) and CMR/CR rate of 30.8% (4/13 pts). In FL pts at the RD (n=6), OR rate was 100% (6/6 pts) and CMR/CR rate was 50% (3/6 pts). The median time to initial response was 54 days for DLBCL and 56.5 days for FL. At data cut-off for ER analysis (10Nov2021) of Parts A, B and C only, exposure data were available from 55 pts who received at least 1 dose of plamotamab in the second cycle, were evaluable for CRS and for efficacy and safety at the target dose. For the first "priming” dose, plamotamab exposure correlated significantly with peak IL6 levels as well as incidence of Gr≥2 CRS events. At subsequent SUD, Postdose-Cmax / Predose-Ctrough ratio, indicative of the fold-change with each SUD, was the best predictor of any grade CRS events. At the target dose, no significant relationship exists between plamotamab exposure vs. all Gr≥3 AEs. A positive relationship exists for best OR, which is further improved by accounting for the impact of residual rituximab on plamotamab binding to CD20 using a competitive binding model. Conclusion: Plamotamab demonstrated evidence of clinical activity in heavily pretreated pts with DLBCL and FL with promising responses in pts with prior CAR-T therapy. CRS was generally manageable with premedication. Safety and efficacy evaluation of pts at the RD is currently ongoing, and updated results will be provided. Taken together, popPK/PD analysis of plamotamab exposure with IL6 levels, CRS incidence, high-grade AEs and OR rate provide guidance for RDs to be studied in future trials. A novel exposure metric was proposed to inform step-up dose increases that minimize the risk of CRS, while impact of rituximab on drug efficacy was captured as has been described in the literature. Figure 1View largeDownload PPTFigure 1View largeDownload PPT Close modal

Picomolar fluorescent probes for compound affinity determination to carbonic anhydrase IX expressed in live cancer cells

Numerous human cancers, especially hypoxic solid tumors, express carbonic anhydrase IX (CAIX), a transmembrane protein with its catalytic domain located in the extracellular space. CAIX acidifies the tumor microenvironment, promotes metastases and invasiveness, and is therefore considered a promising anticancer target. We have designed a series of high affinity and high selectivity fluorescein-labeled compounds targeting CAIX to visualize and quantify CAIX expression in cancer cells. The competitive binding model enabled the determination of common CA inhibitors’ dissociation constants for CAIX expressed in exponentially growing cancer cells. All tested sulfonamide compounds bound the proliferating cells with similar affinity as to recombinantly purified CAIX. The probes are applicable for the design of selective drug-like compounds for CAIX and the competition strategy could be applied to other drug targets.

Assessing Prolongation of the Corrected QTInterval with Bedaquiline and Delamanid Coadministration to Predict the Cardiac Safetyof Simplified Dosing Regimens.

Delamanid and bedaquiline are two drugs approved to treat drug‐resistant tuberculosis, and each have been associated with corrected QT interval (QTc) prolongation. We aimed to investigate the relationships between the drugs' plasma concentrations and the prolongation of observed QT interval corrected using Fridericia’s formula (QTcF) and to evaluate their combined effects on QTcF, using a model‐based population approach. Furthermore, we predicted the safety profiles of once daily regimens. Data were obtained from a trial where participants were randomized 1:1:1 to receive delamanid, bedaquiline, or delamanid + bedaquiline. The effect on QTcF of delamanid and/or its metabolite (DM‐6705) and the pharmacodynamic interactions under coadministration were explored based on a published model between bedaquiline's metabolite (M2) and QTcF. The metabolites of each drug were found to be responsible for the drug‐related QTcF prolongation. The final drug‐effect model included a competitive interaction between M2 and DM‐6705 acting on the same cardiac receptor and thereby reducing each other's apparent potency, by 28% (95% confidence interval (CI), 22–40%) for M2 and 33% (95% CI, 24–54%) for DM‐6705. The generated combined effect was not greater but close to “additivity” in the analyzed concentration range. Predictions with the final model suggested a similar QT prolonging potential with simplified, once‐daily dosing regimens compared with the approved regimens, with a maximum median change from baseline QTcF increase of 20 milliseconds in both regimens. The concentrations–QTcF relationship of the combination of bedaquiline and delamanid was best described by a competitive binding model involving the two main metabolites. Model predictions demonstrated that QTcF prolongation with simplified once daily regimens would be comparable to currently used dosing regimens.

CASTING: A Potent Supramolecular Strategy to Cytosolically Deliver STING Agonist for Cancer Immunotherapy and SARS-CoV-2 Vaccination

CASTING: A Potent Supramolecular Strategy to Cytosolically Deliver STING Agonist for Cancer Immunotherapy and SARS-CoV-2 Vaccination

Analysis of a Mathematical Model of Real-Time Competitive Binding on a Microarray

A mathematical model of competitive binding on a microarray in real-time yields a planar system of nonlinear ordinary differential equations. This model can be used to explore dimensionless formulation, linear approximation, and reduction. Real-time competitive binding is proposed as an uncommon approach to advance the study of planar systems of differential equations.

The Selectivity of Immunoassays and of Biomimetic Binding Assays with Imprinted Polymers.

Molecularly imprinted polymers have been shown to be useful in competitive biomimetic binding assays. Recent developments in materials science have further enhanced the capabilities of imprinted polymers. Binding assays, biological and biomimetic alike, owe their usefulness to their selectivity. The selectivity of competitive binding assays has been characterized with the cross-reactivity, which is usually expressed as the ratio of the measured IC50 concentration values of the interferent and the analyte, respectively. Yet this cross-reactivity is only a rough estimate of analytical selectivity. The relationship between cross-reactivity and analytical selectivity has apparently not been thoroughly investigated. The present work shows that this relationship depends on the underlying model of the competitive binding assay. For the simple but widely adopted model, where analyte and interferent compete for a single kind of binding site, we provide a simple formula for analytical selectivity. For reasons of an apparent mathematical problem, this formula had not been found before. We also show the relationship between analytical selectivity and cross-reactivity. Selectivity is also shown to depend on the directly measured quantity, e.g., the bound fraction of the tracer. For those cases where the one-site competitive model is not valid, a practical procedure is adopted to estimate the analytical selectivity. This procedure is then used to analyze the example of the competitive two-site binding model, which has been the main model for describing molecularly imprinted polymer behavior. The results of this work provide a solid foundation for assay development.

Binding of regulatory proteins to nucleosomes is modulated by dynamic histone tails

Little is known about the roles of histone tails in modulating nucleosomal DNA accessibility and its recognition by other macromolecules. Here we generate extensive atomic level conformational ensembles of histone tails in the context of the full nucleosome, totaling 65 microseconds of molecular dynamics simulations. We observe rapid conformational transitions between tail bound and unbound states, and characterize kinetic and thermodynamic properties of histone tail-DNA interactions. Different histone types exhibit distinct binding modes to specific DNA regions. Using a comprehensive set of experimental nucleosome complexes, we find that the majority of them target mutually exclusive regions with histone tails on nucleosomal/linker DNA around the super-helical locations ± 1, ± 2, and ± 7, and histone tails H3 and H4 contribute most to this process. These findings are explained within competitive binding and tail displacement models. Finally, we demonstrate the crosstalk between different histone tail post-translational modifications and mutations; those which change charge, suppress tail-DNA interactions and enhance histone tail dynamics and DNA accessibility.

Odorant Receptor Inhibition Is Fundamental to Odor Encoding

Most natural odors are complex mixtures of volatile components, competing to bind odorant receptors (ORs) expressed in olfactory sensory neurons (OSNs) of the nose. To date, surprisingly little is known about how OR antagonism shapes neuronal representations in the detection layer of the olfactory system. Here, we investigated its prevalence, the degree to which it disrupts OR ensemble activity, and its conservation across phylogenetically related ORs. Calcium imaging microscopy of dissociated OSNs revealed significant inhibition, often complete attenuation, of responses to indole-a commonly occurring volatile associated with both floral and fecal odors-by a set of 36 tested odorants. To confirm an OR mechanism for the observed inhibition, we performed single-cell transcriptomics on OSNs exhibiting specific response profiles to a diagnostic panel of odorants and identified three paralogous receptors-Olfr740, Olfr741, and Olfr743-which, when tested invitro, recapitulated OSN responses. We screened ten ORs from the Olfr740 gene family with ∼800 perfumery-related odorants spanning a range of chemical scaffolds and functional groups. Over half of these compounds (430) antagonized at least one of the ten ORs. OR activity fitted a mathematical model of competitive receptor binding and suggests normalization of OSN ensemble responses to odorant mixtures is the rule rather than the exception. In summary, we observed OR antagonism occurred frequently and in a combinatorial manner. Thus, extensive receptor-mediated computation of mixture information appears to occur in the olfactory epithelium prior to transmission of odor information to the olfactory bulb.

Assessment of romosozumab efficacy in the treatment of postmenopausal osteoporosis: Results from a mechanistic PK-PD mechanostat model of bone remodeling.

This paper introduces a theoretical framework for the study of the efficacy of romosozumab, a humanized monoclonal antibody targeting sclerostin for the treatment of osteoporosis. We developed a comprehensive mechanistic pharmacokinetic-pharmacodynamic (PK-PD) model of the effect of drug treatment on bone remodeling in postmenopausal osteoporosis (PMO). We utilized a one-compartment PK model to represent subcutaneous injections of romosozumab and subsequent absorption into serum. The PD model is based on a recently-developed bone cell population model describing the bone remodeling process at the tissue scale. The latter accounts for mechanical feedback by incorporating nitric oxide (NO) and sclerostin (Scl) as biochemical feedback molecules. Utilizing a competitive binding model, where Wnt and Scl compete for binding to LRP5/6, allows to regulate anabolic bone remodeling responses. Here, we extended this model with respect to romosozumab binding to sclerostin. For the currently approved monthly injections of 210mg, the model predicted a 6.59%, 10.38% and 15.25% increase in BMD at the lumbar spine after 6, 12 and 24months, respectively. These results are in good agreement with the data reported in the literature. Our model is also able to distinguish the bone-site specific drug effects. For instance, at the femoral neck, our model predicts a BMD increase of 3.85% after 12months of 210mg injections, which is consistent with literature observations. Finally, our simulations indicate rapid bone loss after treatment discontinuation, indicating that some additional interventions such as use of bisphosphonates are required to maintain bone mass.

Considerations for improved performance of competition association assays analysed with the Motulsky-Mahan's "kinetics of competitive binding" model.

Background and PurposeTarget engagement dynamics can influence drugs' pharmacological effects. Kinetic parameters for drug:target interactions are often quantified by evaluating competition association experiments—measuring simultaneous protein binding of labelled tracers and unlabelled test compounds over time—with Motulsky–Mahan's “kinetics of competitive binding” model. Despite recent technical improvements, the current assay formats impose practical limitations to this approach. This study aims at the characterisation, understanding and prevention of these experimental constraints, and associated analytical challenges.Experimental ApproachMonte Carlo simulations were used to run virtual kinetic and equilibrium tracer binding and competition experiments in both normal and perturbed assay conditions. Data were fitted to standard equations derived from the mass action law (including Motulsky–Mahan's) and to extended versions aiming to cope with frequently observed deviations of the canonical traces. Results were compared to assess the precision and accuracy of these models and identify experimental factors influencing their performance.Key ResultsKey factors influencing the precision and accuracy of the Motulsky–Mahan model are the interplay between compound dissociation rates, measurement time and interval frequency, tracer concentration and binding kinetics and the relative abundance of equilibrium complexes in vehicle controls. Experimental results produced recommendations for better design of tracer characterisation experiments and new strategies to deal with systematic signal decay.Conclusions and ImplicationsOur data advances our comprehension of the Motulsky–Mahan kinetics of competitive binding models and provides experimental design recommendations, data analysis tools, and general guidelines for its practical application to in vitro pharmacology and drug screening.

Competitive binding predicts nonlinear responses of olfactory receptors to complex mixtures

In color vision, the quantitative rules for mixing lights to make a target color are well understood. By contrast, the rules for mixing odorants to make a target odor remain elusive. A solution to this problem in vision relied on characterizing receptor responses to different wavelengths of light and subsequently relating these responses to perception. In olfaction, experimentally measuring receptor responses to a representative set of complex mixtures is intractable due to the vast number of possibilities. To meet this challenge, we develop a biophysical model that predicts mammalian receptor responses to complex mixtures using responses to single odorants. The dominant nonlinearity in our model is competitive binding (CB): Only one odorant molecule can attach to a receptor binding site at a time. This simple framework predicts receptor responses to mixtures of up to 12 monomolecular odorants to within 15% of experimental observations and provides a powerful method for leveraging limited experimental data. Simple extensions of our model describe phenomena such as synergy, overshadowing, and inhibition. We demonstrate that the presence of such interactions can be identified via systematic deviations from the competitive-binding model.

Odorant Receptor Inhibition is Fundamental to Odor Encoding

Most natural odors are complex mixtures of many volatile components, competing to bind odorant receptors (ORs) expressed in olfactory sensory neurons (OSNs) of the nose. To date surprisingly little is known about how OR antagonism shapes neuronal representations in the periphery of the olfactory system. Here, we investigated its prevalence, the degree to which it disrupts OR ensemble activity, and its conservation across related ORs. Calcium imaging microscopy of dissociated OSNs revealed significant inhibition, often complete attenuation, of responses to indole, a commonly occurring volatile associated with both floral and fecal odors, by a set of 36 tested odorants. To confirm an OR mechanism for the observed inhibition, we performed single-cell transcriptomics on OSNs that exhibited specific response profiles to a diagnostic panel of odorants and identified the receptor Olfr743 which, when tested in vitro, recapitulated ex vivo responses. We screened ten ORs from the Olfr743 clade with 800 perfumery-related odorants spanning a range of chemical scaffolds and functional groups, over half of which (430) antagonized at least one of the ten ORs. Furthermore, OR activity outcomes were divergent rather than redundant, even for the most closely related paralogs. OR activity fitted a mathematical model of competitive receptor binding and suggests that normalization of OSN ensemble responses to odorant mixtures is the rule rather than the exception. In summary, we observed OR antagonism, inverse agonism and partial agonism occurring frequently and in a combinatorial manner. Thus, extensive receptor-mediated computation of mixture information appears to occur in the olfactory epithelium prior to transmission of odor information to the olfactory bulb.

Coregulation of alternative splicing by hnRNPM and ESRP1 during EMT.

The epithelial–mesenchymal transition (EMT) is a fundamental developmental process that is abnormally activated in cancer metastasis. Dynamic changes in alternative splicing occur during EMT. ESRP1 and hnRNPM are splicing regulators that promote an epithelial splicing program and a mesenchymal splicing program, respectively. The functional relationships between these splicing factors in the genome scale remain elusive. Comparing alternative splicing targets of hnRNPM and ESRP1 revealed that they coregulate a set of cassette exon events, with the majority showing discordant splicing regulation. Discordant splicing events regulated by hnRNPM show a positive correlation with splicing during EMT; however, concordant events do not, indicating the role of hnRNPM in regulating alternative splicing during EMT is more complex than previously understood. Motif enrichment analysis near hnRNPM–ESRP1 coregulated exons identifies guanine–uridine rich motifs downstream from hnRNPM-repressed and ESRP1-enhanced exons, supporting a general model of competitive binding to these cis-elements to antagonize alternative splicing. The set of coregulated exons are enriched in genes associated with cell migration and cytoskeletal reorganization, which are pathways associated with EMT. Splicing levels of coregulated exons are associated with breast cancer patient survival and correlate with gene sets involved in EMT and breast cancer subtyping. This study identifies complex modes of interaction between hnRNPM and ESRP1 in regulation of splicing in disease-relevant contexts.

What Silences the Spindle Checkpoint? A Single Particle Study

Accurate mitosis depends on a surveillance system called the spindle assembly checkpoint. The checkpoint acts at kinetochores, which attach chromosomes to the dynamic tips of spindle microtubules. When a kinetochore is unattached or improperly attached, the checkpoint kinase Mps1 phosphorylates core kinetochore components, catalyzing the generation of a diffusible ‘wait’ signal to block anaphase chromosome segregation. When a kinetochore becomes properly attached, this signal is somehow silenced to allow anaphase to proceed. Two classes of models are proposed to explain how Mps1 is selectively silenced at microtubule-attached kinetochores. In competitive binding models, Mps1 and microtubules compete for binding to the kinetochore, either directly or allosterically, such that Mps1 is released upon kinetochore-microtubule attachment. In switch models, kinetochore attachment to the end of a microtubule inhibits Mps1 kinase activity without causing its release. By direct observation of single fluorescent kinetochores in vitro, we find that Mps1 levels are not reduced when a kinetochore binds laterally to the side of a microtubule, nor when it tracks processively with a disassembling tip. Thus, association of Mps1 with a kinetochore is not strictly competitive with microtubule attachment. Incorporating a fluorescent kinase sensor should allow us to test the switch models.

RNA synthesis is associated with multiple TBP-chromatin binding events

Competition ChIP is an experimental method that allows transcription factor (TF) chromatin turnover dynamics to be measured across a genome. We develop and apply a physical model of TF-chromatin competitive binding using chemical reaction rate theory and are able to derive the physical half-life or residence time for TATA-binding protein (TBP) across the yeast genome from competition ChIP data. Using our physical modeling approach where we explicitly include the induction profile of the competitor in the model, we are able to estimate yeast TBP-chromatin residence times as short as 1.3 minutes, demonstrating that competition ChIP is a relatively high temporal-resolution approach. Strikingly, we find a median value of ~5 TBP-chromatin binding events associated with the synthesis of one RNA molecule across Pol II genes, suggesting multiple rounds of pre-initiation complex assembly and disassembly before productive elongation of Pol II is achieved at most genes in the yeast genome.

Surface-Bulk Vibrational Correlation Spectroscopy.

Homo- and heterospectral correlation analysis are powerful methods for investigating the effects of external influences on the spectra acquired using distinct and complementary techniques. Nonlinear vibrational spectroscopy is a selective and sensitive probe of surface structure changes, as bulk molecules are excluded on the basis of symmetry. However, as a result of this exquisite specificity, it is blind to changes that may be occurring in the solution. We demonstrate that correlation analysis between surface-specific techniques and bulk probes such as infrared absorption or Raman scattering may be used to reveal additional details of the adsorption process. Using the adsorption of water and ethanol binary mixtures as an example, we illustrate that this provides support for a competitive binding model and adds new insight into a dimer-to-bilayer transition proposed from previous experiments and simulations.

Mechanism-Based Competitive Binding Model to Investigate the Effect of Neonatal Fc Receptor Binding Affinity on the Pharmacokinetic of Humanized Anti-VEGF Monoclonal IgG1 Antibody in Cynomolgus Monkey.

The quantitative relationship between neonatal Fc receptor (FcRn) binding affinity at both acidic and physiological pH and the pharmacokinetics of protein engineered FcRn IgG1 variants has not yet been reported. Our objective was to develop a quantitatively mechanism-based competitive binding model to describe the effects of FcRn binding affinity at acidic and physiological pH on the pharmacokinetics of anti-VEGF IgG1 antibodies when both endogenous and exogenous antibodies are competing for the same FcRn. Pharmacokinetic (PK) and FcRn binding data from five Fc variants of humanized anti-VEGF IgG1 monoclonal antibodies with wide range of FcRn binding affinity were used for the analysis. Sixty-seven anti-VEGF IgG1 antibody-treated animals and 25 control animals with simulated endogenous IgG levels were used to develop the final model. A hybrid iterative two stages and Monte Carlo parametric expectation-maximization method was used to obtain the final model parameters estimates. The final model well described the observed PK data. Quantitative FcRn binding affinity-pharmacokinetics relationships was constructed to provide important biological insights in better understanding of the FcRn binding effect on pharmacokinetics of anti-VEGF IgG1 antibodies in cynomolgus monkeys and served as an important model-based drug discovery platform to guide the design and development of the future generation of anti-VEGF or other therapeutic IgG1 antibodies.

Learning protein–DNA interaction landscapes by integrating experimental data through computational models

Transcriptional regulation is directly enacted by the interactions between DNA and many proteins, including transcription factors (TFs), nucleosomes and polymerases. A critical step in deciphering transcriptional regulation is to infer, and eventually predict, the precise locations of these interactions, along with their strength and frequency. While recent datasets yield great insight into these interactions, individual data sources often provide only partial information regarding one aspect of the complete interaction landscape. For example, chromatin immunoprecipitation (ChIP) reveals the binding positions of a protein, but only for one protein at a time. In contrast, nucleases like MNase and DNase can be used to reveal binding positions for many different proteins at once, but cannot easily determine the identities of those proteins. Currently, few statistical frameworks jointly model these different data sources to reveal an accurate, holistic view of the in vivo protein-DNA interaction landscape. Here, we develop a novel statistical framework that integrates different sources of experimental information within a thermodynamic model of competitive binding to jointly learn a holistic view of the in vivo protein-DNA interaction landscape. We show that our framework learns an interaction landscape with increased accuracy, explaining multiple sets of data in accordance with thermodynamic principles of competitive DNA binding. The resulting model of genomic occupancy provides a precise mechanistic vantage point from which to explore the role of protein-DNA interactions in transcriptional regulation. The C source code for compete and Python source code for MCMC-based inference are available at http://www.cs.duke.edu/∼amink. amink@cs.duke.edu Supplementary data are available at Bioinformatics online.

Nucleosome repositioning links DNA (de)methylation and differential CTCF binding during stem cell development.

During differentiation of embryonic stem cells, chromatin reorganizes to establish cell type-specific expression programs. Here, we have dissected the linkages between DNA methylation (5mC), hydroxymethylation (5hmC), nucleosome repositioning, and binding of the transcription factor CTCF during this process. By integrating MNase-seq and ChIP-seq experiments in mouse embryonic stem cells (ESC) and their differentiated counterparts with biophysical modeling, we found that the interplay between these factors depends on their genomic context. The mostly unmethylated CpG islands have reduced nucleosome occupancy and are enriched in cell type-independent binding sites for CTCF. The few remaining methylated CpG dinucleotides are preferentially associated with nucleosomes. In contrast, outside of CpG islands most CpGs are methylated, and the average methylation density oscillates so that it is highest in the linker region between nucleosomes. Outside CpG islands, binding of TET1, an enzyme that converts 5mC to 5hmC, is associated with labile, MNase-sensitive nucleosomes. Such nucleosomes are poised for eviction in ESCs and become stably bound in differentiated cells where the TET1 and 5hmC levels go down. This process regulates a class of CTCF binding sites outside CpG islands that are occupied by CTCF in ESCs but lose the protein during differentiation. We rationalize this cell type-dependent targeting of CTCF with a quantitative biophysical model of competitive binding with the histone octamer, depending on the TET1, 5hmC, and 5mC state.