BAY-9835: Discovery of the First Orally Bioavailable ADAMTS7 Inhibitor.

The matrix metalloprotease ADAMTS7 has been identified by multiple genome-wide association studies as being involved in the development of coronary artery disease. Subsequent research revealed the proteolytic function of the enzyme to be relevant for atherogenesis and restenosis after vessel injury. Based on a publicly known dual ADAMTS4/ADAMTS5 inhibitor, we have in silico designed an ADAMTS7 inhibitor of the catalytic domain, which served as a starting point for an optimization campaign. Initially our inhibitors suffered from low selectivity vs MMP12. An X-ray cocrystal structure inspired us to exploit amino acid differences in the binding site of MMP12 and ADAMTS7 to improve selectivity. Further optimization composed of employing 5-membered heteroaromatic groups as hydantoin substituents to become more potent on ADAMTS7. Finally, fine-tuning of DMPK properties yielded BAY-9835, the first orally bioavailable ADAMTS7 inhibitor. Further optimization to improve selectivity vs ADAMTS12 seems possible, and a respective starting point could be identified.

Mechanistic Image-Based Modelling: Concepts and Applications.

Advancements in imaging techniques have led to a rapid growth of available imaging data. Interpretation of the imaging data and extraction of biologically, physiologically and/or medically relevant information, however, remains challenging. In contrast, mechanistic computational modelling provides a means to formalise and dissect mechanisms governing the behaviour of complex systems. However, its application often is limited due to the lack of relevant data for model building and validation. Exploitation of the imaging data to build, parameterise and validate computational models gives rise to an image-based modelling approach. In this chapter, we introduce the basics of the mechanistic image-based modelling approach and review its application in developmental biology and biomedical research as well as for medical device development and drug discovery and development. Implementation of image-based modelling in pharmaceutical industry holds promise to further advance model-informed drug discovery and development and aids substantially in our understanding of drug pharmacokinetic, pharmacodynamic and ultimately de-risk drug development.

Image-based modeling of kidney branching morphogenesis reveals GDNF-RET based Turing-type mechanism and pattern-modulating WNT11 feedback.

Branching patterns and regulatory networks differ between branched organs. It has remained unclear whether a common regulatory mechanism exists and how organ-specific patterns can emerge. Of all previously proposed signalling-based mechanisms, only a ligand-receptor-based Turing mechanism based on FGF10 and SHH quantitatively recapitulates the lung branching patterns. We now show that a GDNF-dependent ligand-receptor-based Turing mechanism quantitatively recapitulates branching of cultured wildtype and mutant ureteric buds, and achieves similar branching patterns when directing domain outgrowth in silico. We further predict and confirm experimentally that the kidney-specific positive feedback between WNT11 and GDNF permits the dense packing of ureteric tips. We conclude that the ligand-receptor based Turing mechanism presents a common regulatory mechanism for lungs and kidneys, despite the differences in the molecular implementation. Given its flexibility and robustness, we expect that the ligand-receptor-based Turing mechanism constitutes a likely general mechanism to guide branching morphogenesis and other symmetry breaks during organogenesis.

Emerging technologies for prediction of drug candidate efficacy in the preclinical pipeline.

The pharmaceutical industry is tackling increasingly complex multifactorial diseases, resulting in increases in research & development (R&D) costs and reductions in the success rates for drug candidates during Phase 2 and 3 clinical trials, with a lack of efficacy being the primary reason for drug candidate failure. This implies that the predictive power of current preclinical assays for drug candidate efficacy is suboptimal and, therefore, that alternatives should be developed. Here, I review emerging in vitro, imaging, and in silico technologies and discuss their potential contribution to drug efficacy assessment. Importantly, these technologies are complimentary and can be bundled into the preclinical platform. In particular, patient-on-a-chip recapitulates both human genetics and physiology. The response of a patient-on-a-chip to drug candidate treatment is monitored with light-sheet fluorescent microscopy and fed into the image-analysis pipeline to reconstruct an image-based systems-level model for disease pathophysiology and drug candidate mode of action. Thus, such models could be useful tools for assessing drug candidate efficacy and safety in humans.

SrGAP2-Dependent Integration of Membrane Geometry and Slit-Robo-Repulsive Cues Regulates Fibroblast Contact Inhibition of Locomotion.

Migrating fibroblasts undergo contact inhibition of locomotion (CIL), a process that was discovered five decades ago and still is not fully understood at the molecular level. We identify the Slit2-Robo4-srGAP2 signaling network as a key regulator of CIL in fibroblasts. CIL involves highly dynamic contact protrusions with a specialized actin cytoskeleton that stochastically explore cell-cell overlaps between colliding fibroblasts. A membrane curvature-sensing F-BAR domain pre-localizes srGAP2 to protruding edges and terminates their extension phase in response to cell collision. A FRET-based biosensor reveals that Rac1 activity is focused in a band at the tip of contact protrusions, in contrast to the broad activation gradient in contact-free protrusions. SrGAP2 specifically controls the duration of Rac1 activity in contact protrusions, but not in contact-free protrusions. We propose that srGAP2 integrates cell edge curvature and Slit-Robo-mediated repulsive cues to fine-tune Rac1 activation dynamics in contact protrusions to spatiotemporally coordinate CIL.

Simulating tissue morphogenesis and signaling.

During embryonic development tissue morphogenesis and signaling are tightly coupled. It is therefore important to simulate both tissue morphogenesis and signaling simultaneously in in silico models of developmental processes. The resolution of the processes depends on the questions of interest. As part of this chapter we introduce different descriptions of tissue morphogenesi s. In the simplest approximation tissue is a continuous domain and tissue expansion is described according to a predefined function of time (and possibly space). In a slightly more advanced version the expansion speed and direction of the tissue may depend on a signaling variable that evolves on the domain. Both versions will be referred to as "prescribed growth." Alternatively tissue can be regarded as incompressible fluid and can be described with Navier-Stokes equations. Local cell expansion, proliferation, and death are then incorporated by a source term. In other applications the cell boundaries may be important and cell-based models must be introduced. Finally, cells may move within the tissue, a process best described by agent-based models.

An interplay of geometry and signaling enables robust lung branching morphogenesis.

Early branching events during lung development are stereotyped. Although key regulatory components have been defined, the branching mechanism remains elusive. We have now used a developmental series of 3D geometric datasets of mouse embryonic lungs as well as time-lapse movies of cultured lungs to obtain physiological geometries and displacement fields. We find that only a ligand-receptor-based Turing model in combination with a particular geometry effect that arises from the distinct expression domains of ligands and receptors successfully predicts the embryonic areas of outgrowth and supports robust branch outgrowth. The geometry effect alone does not support bifurcating outgrowth, while the Turing mechanism alone is not robust to noisy initial conditions. The negative feedback between the individual Turing modules formed by fibroblast growth factor 10 (FGF10) and sonic hedgehog (SHH) enlarges the parameter space for which the embryonic growth field is reproduced. We therefore propose that a signaling mechanism based on FGF10 and SHH directs outgrowth of the lung bud via a ligand-receptor-based Turing mechanism and a geometry effect.

Feedback, receptor clustering, and receptor restriction to single cells yield large Turing spaces for ligand-receptor-based Turing models.

Turing mechanisms can yield a large variety of patterns from noisy, homogenous initial conditions and have been proposed as patterning mechanism for many developmental processes. However, the molecular components that give rise to Turing patterns have remained elusive, and the small size of the parameter space that permits Turing patterns to emerge makes it difficult to explain how Turing patterns could evolve. We have recently shown that Turing patterns can be obtained with a single ligand if the ligand-receptor interaction is taken into account. Here we show that the general properties of ligand-receptor systems result in very large Turing spaces. Thus, the restriction of receptors to single cells, negative feedbacks, regulatory interactions among different ligand-receptor systems, and the clustering of receptors on the cell surface all greatly enlarge the Turing space. We further show that the feedbacks that occur in the FGF10-SHH network that controls lung branching morphogenesis are sufficient to result in large Turing spaces. We conclude that the cellular restriction of receptors provides a mechanism to sufficiently increase the size of the Turing space to make the evolution of Turing patterns likely. Additional feedbacks may then have further enlarged the Turing space. Given their robustness and flexibility, we propose that receptor-ligand-based Turing mechanisms present a general mechanism for patterning in biology.

The control of branching morphogenesis.

Many organs of higher organisms are heavily branched structures and arise by an apparently similar process of branching morphogenesis. Yet the regulatory components and local interactions that have been identified differ greatly in these organs. It is an open question whether the regulatory processes work according to a common principle and how far physical and geometrical constraints determine the branching process. Here, we review the known regulatory factors and physical constraints in lung, kidney, pancreas, prostate, mammary gland and salivary gland branching morphogenesis, and describe the models that have been formulated to analyse their impacts.

Kidney branching morphogenesis under the control of a ligand-receptor-based Turing mechanism.

The main signalling proteins that control early kidney branching have been defined. Yet the underlying mechanism is still elusive. We have previously shown that a Schnakenberg-type Turing mechanism can recapitulate the branching and protein expression patterns in wild-type and mutant lungs, but it is unclear whether this mechanism would extend to other branched organs that are regulated by other proteins. Here, we show that the glial cell line-derived neurotrophic factor-RET regulatory interaction gives rise to a Schnakenberg-type Turing model that reproduces the observed budding of the ureteric bud from the Wolffian duct, its invasion into the mesenchyme and the observed branching pattern. The model also recapitulates all relevant protein expression patterns in wild-type and mutant mice. The lung and kidney models are both based on a particular receptor-ligand interaction and require (1) cooperative binding of ligand and receptor, (2) a lower diffusion coefficient for the receptor than for the ligand and (3) an increase in the receptor concentration in response to receptor-ligand binding (by enhanced transcription, more recycling or similar). These conditions are met also by other receptor-ligand systems. We propose that ligand-receptor-based Turing patterns represent a general mechanism to control branching morphogenesis and other developmental processes.

Digit patterning during limb development as a result of the BMP-receptor interaction.

Turing models have been proposed to explain the emergence of digits during limb development. However, so far the molecular components that would give rise to Turing patterns are elusive. We have recently shown that a particular type of receptor-ligand interaction can give rise to Schnakenberg-type Turing patterns, which reproduce patterning during lung and kidney branching morphogenesis. Recent knockout experiments have identified Smad4 as a key protein in digit patterning. We show here that the BMP-receptor interaction meets the conditions for a Schnakenberg-type Turing pattern, and that the resulting model reproduces available wildtype and mutant data on the expression patterns of BMP, its receptor, and Fgfs in the apical ectodermal ridge (AER) when solved on a realistic 2D domain that we extracted from limb bud images of E11.5 mouse embryos. We propose that receptor-ligand-based mechanisms serve as a molecular basis for the emergence of Turing patterns in many developing tissues.

Simulations demonstrate a simple network to be sufficient to control branch point selection, smooth muscle and vasculature formation during lung branching morphogenesis.

Proper lung functioning requires not only a correct structure of the conducting airway tree, but also the simultaneous development of smooth muscles and vasculature. Lung branching morphogenesis is strongly stereotyped and involves the recursive use of only three modes of branching. We have previously shown that the experimentally described interactions between Fibroblast growth factor (FGF)10, Sonic hedgehog (SHH) and Patched (Ptc) can give rise to a Turing mechanism that not only reproduces the experimentally observed wildtype branching pattern but also, in part counterintuitive, patterns in mutant mice. Here we show that, even though many proteins affect smooth muscle formation and the expression of Vegfa, an inducer of blood vessel formation, it is sufficient to add FGF9 to the FGF10/SHH/Ptc module to successfully predict simultaneously the emergence of smooth muscles in the clefts between growing lung buds, and Vegfa expression in the distal sub-epithelial mesenchyme. Our model reproduces the phenotype of both wildtype and relevant mutant mice, as well as the results of most culture conditions described in the literature.

Branch mode selection during early lung development.

Many organs of higher organisms, such as the vascular system, lung, kidney, pancreas, liver and glands, are heavily branched structures. The branching process during lung development has been studied in great detail and is remarkably stereotyped. The branched tree is generated by the sequential, non-random use of three geometrically simple modes of branching (domain branching, planar and orthogonal bifurcation). While many regulatory components and local interactions have been defined an integrated understanding of the regulatory network that controls the branching process is lacking. We have developed a deterministic, spatio-temporal differential-equation based model of the core signaling network that governs lung branching morphogenesis. The model focuses on the two key signaling factors that have been identified in experiments, fibroblast growth factor (FGF10) and sonic hedgehog (SHH) as well as the SHH receptor patched (Ptc). We show that the reported biochemical interactions give rise to a Schnakenberg-type Turing patterning mechanisms that allows us to reproduce experimental observations in wildtype and mutant mice. The kinetic parameters as well as the domain shape are based on experimental data where available. The developed model is robust to small absolute and large relative changes in the parameter values. At the same time there is a strong regulatory potential in that the switching between branching modes can be achieved by targeted changes in the parameter values. We note that the sequence of different branching events may also be the result of different growth speeds: fast growth triggers lateral branching while slow growth favours bifurcations in our model. We conclude that the FGF10-SHH-Ptc1 module is sufficient to generate pattern that correspond to the observed branching modes.

Microarrays of ring-recessed disk electrodes in transient generator-collector mode: theory and experiment.

The fabrication, characterization, and use of arrays of ring-recessed disk microelectrodes are reported. These devices are operated in generator-collector mode with a disk acting as the generator and the ring as the collector. We report experiments and simulations relating to time-of-flight experiments in which material electrogenerated at a disk is diffusionally transported to the ring. Analysis of the current transient measured at the latter when it is potentiostatted at a value to ensure diffusionally controlled "collection" is shown to sensitively reflect the diffusion coefficients of the species forming the redox couple being driven at the generator electrode. The method is applied to the ferrocene/ferrocenium couple in the room temperature ionic liquid [N(6, 2, 2, 2)][NTf(2)], and the results are found to agree with independent measurements.

Electrodes modified with electroinactive layers: distinguishing through-film transport from pinhole (pore) diffusion.

Electrodes modified with layers, for example, of polymers or self-assembled monolayers, are of great importance from both the fundamental and applied points of view. Two different models of electrodes covered with electroinactive layers can be proposed. First, the electrode is covered with a uniform layer into which the electroactive species dissolves and then diffuses through, or second, the layer contains pinholes that are exclusively responsible for diffusional transport to the electrode. Both models are simulated and then compared to identify conditions under which they can be distinguished. The models are studied for a broad range of parameters reflecting experimentally viable values. Different types of cyclic voltammograms can be observed in the studied models corresponding to classical Randles-Sevcik, thin layer, and steady-state behaviors. We show that the models can be distinguished experimentally through recording cyclic voltammograms over a sufficiently broad range of voltage scan rates.

Investigating the concept of diffusional independence. Potential step transients at nano- and micro-electrode arrays: theory and experiment.

Microelectrode arrays find broad application in electroanalysis offering the enhanced sensitivity associated with microelectrodes, but with a high total current output. Such arrays are often constructed to make the electrodes 'diffusionally independent'. To emphasize that this is a time dependent property, a two-dimensional simulation, in conjunction with the diffusional domain approach, is used to model potential step transient currents at microelectrode arrays. Two types of array, hexagonal and cubic, are considered. In both cases the absolute (not relative) microelectrode separation distance has a significant effect on transient current. Three different regimes of transient current versus time can be observed at microelectrode arrays. At short times the transient response of isolated microelectrodes is seen, then at intermediate times the steady-state response of independent electrodes can be observed. At longer times planar diffusion to the entire array takes over. It follows that only at timescales corresponding to the first two regimes can the electrodes be considered as diffusionally independent. To verify the theory the potential step experiment is performed at a regularly spaced hexagonal iridium microdisk array. Theory is found to be in a good agreement with the experimental results.