CXCR4 is an important therapeutic target for hematopoietic stem cell mobilization, which enhances the success of autologous stem cell transplantation for treating blood cancers such as lymphomas and myeloma. As CXCR4 has been shown to be involved in various inflammatory diseases, cancer progression, and cell entry by the human immunodeficiency virus, understanding the molecular mechanism of CXCR4 inhibitors has potential implications in a wide area of diseases. Here, we present an exploratory study which involves the molecular pharmacological characterization of TG-0 054 (burixafor, GPC-10 0), a clinical candidate for hematopoietic stem cell mobilization. TG-0 054 inhibited CXCL12 binding at CXCR4, and antagonized both Gai and b-arrestin2 recruitment as well as the downstream Gai-attenuation of cAMP signaling pathway, with pIC50 of 7.7, 8.0, and 7.9, respectively. Compared with the clinically used antagonist AMD310 0 and the prototypical inverse agonist Isothiourea-1t (IT1t), TG-0 054 displayed a unique pharmacological profile. Like IT1t, TG-0 054 inhibited the constitutive Gai signaling of CXCR4. However, in contrast to IT1t and other reported inverse agonists, TG-0 054 was not able to induce monomerization of CXCR4 oligomeric complexes. Considering the unique properties of TG-0054 on CXCR4, TG-0 054 is an interesting tool compound for studying the relevance of inverse agonism as well as CXCR4 monomerization in various pathologies. Statement: CXCR4-targeted therapeutics hold important potential for the treatment of blood cancers. TG-0 054 has inverse agonistic properties and is a non-CXCR4-monomerizing small molecule antagonist, unlike other well studied CXCR4 small molecule antagonists. (c) 2025 The Authors. Published by Elsevier Ltd. This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/).

CXCR4 is an important therapeutic target for hematopoietic stem cell mobilization, which enhances the success of autologous stem cell transplantation for treating blood cancers such as lymphomas and myeloma. As CXCR4 has been shown to be involved in various inflammatory diseases, cancer progression, and cell entry by the human immunodeficiency virus, understanding the molecular mechanism of CXCR4 inhibitors has potential implications in a wide area of diseases. Here, we present an exploratory study which involves the molecular pharmacological characterization of TG-0054 (burixafor, GPC-100), a clinical candidate for hematopoietic stem cell mobilization. TG-0054 inhibited CXCL12 binding at CXCR4, and antagonized both Gαi and β-arrestin2 recruitment as well as the downstream Gαi-attenuation of cAMP signaling pathway, with pIC50 of 7.7, 8.0, and 7.9, respectively. Compared with the clinically used antagonist AMD3100 and the prototypical inverse agonist Isothiourea-1t (IT1t), TG-0054 displayed a unique pharmacological profile. Like IT1t, TG-0054 inhibited the constitutive Gαi signaling of CXCR4. However, in contrast to IT1t and other reported inverse agonists, TG-0054 was not able to induce monomerization of CXCR4 oligomeric complexes. Considering the unique properties of TG-0054 on CXCR4, TG-0054 is an interesting tool compound for studying the relevance of inverse agonism as well as CXCR4 monomerization in various pathologies. SIGNIFICANCE STATEMENT: CXCR4-targeted therapeutics hold important potential for the treatment of blood cancers. TG-0054 has inverse agonistic properties and is a non-CXCR4-monomerizing small molecule antagonist, unlike other well studied CXCR4 small molecule antagonists.

In drug discovery, target identification (ID) after phenotypic screens is a resource-intensive endeavor aimed to understand compound’s mechanism of action. Target ID for membrane proteins is particularly challenging due to hurdles such as poor protein solubility, instability and low expression levels. Addressing these hurdles, recent proteomics-based strategies allow to analyze proteins in their native environment, and do not require compound modification or genetic manipulation of target cell lines. Limited proteolysis coupled to mass spectrometry (LiP-MS) is a peptide-centric strategy that exploits structural protein alterations and steric hindrances induced by drug to detect drug-protein interactions, estimate potency (EC50) and predict binding sites across the proteome. Our previous reports (AACR 2020 and 2021) showed the applicability of LiP-MS on cytosolic proteins such as kinases and phosphatases. Here, LiP-MS workflow was adapted for multi-pass membrane proteins which are often underrepresented in global, unbiased target ID approaches. For protein targets in the cytosol or intracellular organelles, LiP-MS deploys a dose-response (DR) analysis recorded by incubating cell lysates with a given compound. Here, to monitor proteins in plasma membrane, live cells were treated with the compound in a DR curve for a short period of time before lysis and subsequent LiP-MS analysis. Live cell treatment allows to achieve target ID by 1) locking the receptor in its native conformation to detect the structural difference between the drug-bound and unbound forms and; 2) detecting structural changes in downstream signaling cascades resulting from changes in protein-protein interactions, post-translational modifications or other mechanisms. We evaluated the performance of this workflow using a tool compound (IAX16840) targeting specific G-protein coupled receptors. Our unbiased LiP scoring identified atypical chemokine receptor 3 (ACKR3), the primary known compound target, among the top 3 hits. Additional 82 proteins were perturbed in drug-treated samples based on the LiP scores. Mapping the altered peptides on the GPCR signaling network showed enrichment of perturbations in ACKR3 downstream pathways, providing additional evidence of ACKR3 binding. Taken together, we demonstrate that the live cell LiP-MS is applicable for target ID of multi-pass membrane proteins. The approach also provides a system-level view of protein and pathway perturbations downstream of a signaling protein (e.g. GPCR), revealing possible mechanisms of its endogenous action. Further optimization of LiP-MS protocol is sought to accommodate different classes of receptors. Citation Format: Martin Soste, Dominique Kamber, Nadine Dobberstein, Mirjam Zimmermann, Aurelien Rizk, Yuehan Feng, Yaroslav Nikolaev, Nigel Beaton. Target identification of a multi-pass transmembrane G protein coupled receptor using limited-proteolysis coupled mass spectrometry (LiP-MS). [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2023; Part 1 (Regular and Invited Abstracts); 2023 Apr 14-19; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2023;83(7_Suppl):Abstract nr 3847.

Activation of G protein-coupled receptors by agonists may result in the activation of one or more G proteins and recruitment of arrestins. The extent of the activation of each of these pathways depends on the intrinsic efficacy of the ligand. Quantification of intrinsic efficacy relative to a reference compound is essential for the development of novel compounds. In the operational model, changes in efficacy can be compensated by changes in the "functional" affinity, resulting in poorly defined values. To separate the effects of ligand affinity from the intrinsic activity of the receptor, we developed a Michaelis-Menten based quantification of G protein activation bias that uses experimentally measured ligand affinities and provides a single measure of ligand efficacy. We used it to evaluate the signaling of a promiscuous model receptor, the Vasopressin V2 receptor (V2R). Using BRET-based biosensors, we show that the V2R engages many different G proteins across all G protein subfamilies in response to its primary endogenous agonist, arginine vasopressin, including Gs and members of the Gi/o and G12/13 families. These signaling pathways are also activated by the synthetic peptide desmopressin, oxytocin, and the nonmammalian hormone vasotocin. We compared bias quantification using the operational model with Michaelis-Menten based quantification; the latter accurately quantified ligand efficacies despite large difference in ligand affinities. Together, these results showed that the V2R is promiscuous in its ability to engage several G proteins and that its' signaling profile is biased by small structural changes in the ligand. SIGNIFICANCE STATEMENT: By modelling the G protein activation as Michaelis-Menten reaction, we developed a novel way of quantifying signalling bias. V2R activates, or at least engages, G proteins from all G protein subfamilies, including Gi2, Gz, Gq, G12, and G13. Their relative activation may explain its Gs-independent signalling.

Activation of the G protein-coupled receptors by agonists may result in the activation of one or more G proteins, and in the recruitment of arrestins. The balance of activation of different pathways can be influenced by the ligand. Using BRET-based biosensors, we showed that the vasopressin V2 receptor activates or at least engages many different G proteins across all G protein subfamilies in response to its native agonist arginine vasopressin (AVP). This includes members of the Gi/o and G12/13 families that have not been previously reported. These signalling pathways are also activated by the synthetic peptide desmopressin and natural homologs of AVP, namely oxytocin and the non-mammalian hormone vasotocin. They demonstrated varying degrees of functional selectivity relative to AVP, as quantified using the operational model for quantifying ligand bias. Additionally, we modelled G protein activation as a Michaelis-Menten reaction. This approach provided a complementary way to quantify signalling bias, with an added benefit of clear separation of the effects of ligand affinity from the intrinsic activity of the receptor. These results showed that V2 receptor is not only promiscuous in its ability to engage several G proteins, but also that its signalling profile could be easily biased by small structural changes in the ligand.

G protein-coupled receptors (GPCRs) are intensively studied due to their therapeutic potential as drug targets. Members of this large family of transmembrane receptor proteins mediate signal transduction in diverse cell types and play key roles in human physiology and health. In 2013 the research consortium GLISTEN (COST Action CM1207) was founded with the goal of harnessing the substantial growth in knowledge of GPCR structure and dynamics to push forward the development of molecular modulators of GPCR function. The success of GLISTEN, coupled with new findings and paradigm shifts in the field, led in 2019 to the creation of a related consortium called ERNEST (COST Action CA18133). ERNEST broadens focus to entire signaling cascades, based on emerging ideas of how complexity and specificity in signal transduction are not determined by receptor-ligand interactions alone. A holistic approach that unites the diverse data and perspectives of the research community into a single multidimensional map holds great promise for improved drug design and therapeutic targeting.

Arrestin-1 desensitizes the activated and phosphorylated photoreceptor rhodopsin by forming transient rhodopsin−arrestin-1 complexes that eventually decay to opsin, retinal and arrestin-1. Via a multi-dimensional screening setup, we identified and combined arrestin-1 mutants that form lasting complexes with light-activated and phosphorylated rhodopsin in harsh conditions, such as high ionic salt concentration. Two quadruple mutants, D303A + T304A + E341A + F375A and R171A + T304A + E341A + F375A share similar heterologous expression and thermo-stability levels with wild type (WT) arrestin-1, but are able to stabilize complexes with rhodopsin with more than seven times higher half-maximal inhibitory concentration (IC 50 ) values for NaCl compared to the WT arrestin-1 protein. These quadruple mutants are also characterized by higher binding affinities to phosphorylated rhodopsin, light-activated rhodopsin and phosphorylated opsin, as compared with WT arrestin-1. Furthermore, the assessed arrestin-1 mutants are still specifically associating with phosphorylated or light-activated receptor states only, while binding to the inactive ground state of the receptor is not significantly altered. Additionally, we propose a novel functionality for R171 in stabilizing the inactive arrestin-1 conformation as well as the rhodopsin–arrestin-1 complex. The achieved stabilization of the active rhodopsin–arrestin-1 complex might be of great interest for future structure determination, antibody development studies as well as drug-screening efforts targeting G protein-coupled receptors (GPCRs).

Vascular endothelial growth factor receptor-2 (VEGFR2) and its ligands (VEGFs) are crucial players in vasculogenesis and angiogenesis. General blocking of this signaling system with antibodies or small molecule inhibitors is an established strategy to treat cancer and age-related macular degeneration. Nevertheless, the activated receptor can signal to discrete downstream signaling pathways and the equilibrium between these pathways is modulated by coreceptors and distinct isoforms of VEGF. Here we investigated the influence of Rab GTPase activating proteins (RabGAPs) on VEGFR2 signaling, tube formation, and migration of endothelial cells. We demonstrate that members of the TBC1D10 subfamily of RabGAPs have opposite effects. Whereas TBC1D10A leads to increased Erk1/2 signaling, TBC1D10B lowered Erk1/2 and p38 signaling and reduced tube formation in vitro. TBC1D10A is a RabGAP acting on RAB13 that was shown before to play a role in angiogenesis and we could indeed show colocalization of these two proteins with VEGFR2 in activated cells. In addition, we observed that cells expressing TBC1D10B show lower expression of VEGFR2 and NRP1 on filopodia of activated cells. Taken together, our systematic analysis of influence of RabGAPs on VEGFR2 signaling identifies the TBC1D10 subfamily members as modulators of angiogenesis.

Multigene delivery and subsequent cellular expression is emerging as a key technology required in diverse research fields including, synthetic and structural biology, cellular reprogramming and functional pharmaceutical screening. Current viral delivery systems such as retro- and adenoviruses suffer from limited DNA cargo capacity, thus impeding unrestricted multigene expression. We developed MultiPrime, a modular, non-cytotoxic, non-integrating, baculovirus-based vector system expediting highly efficient transient multigene expression from a variety of promoters. MultiPrime viruses efficiently transduce a wide range of cell types, including non-dividing primary neurons and induced-pluripotent stem cells (iPS). We show that MultiPrime can be used for reprogramming, and for genome editing and engineering by CRISPR/Cas9. Moreover, we implemented dual-host-specific cassettes enabling multiprotein expression in insect and mammalian cells using a single reagent. Our experiments establish MultiPrime as a powerful and highly efficient tool, to deliver multiple genes for a wide range of applications in primary and established mammalian cells.

Quantitative image analysis plays an important role in contemporary biomedical research. Squassh is a method for automatic detection, segmentation, and quantification of subcellular structures and analysis of their colocalization. Here we present the applications Squassh3C and SquasshAnalyst. Squassh3C extends the functionality of Squassh to three fluorescence channels and live-cell movie analysis. SquasshAnalyst is an interactive web interface for the analysis of Squassh3C object data. It provides segmentation image overview and data exploration, figure generation, object and image filtering, and a statistical significance test in an easy-to-use interface. The overall procedure combines the Squassh3C plug-in for the free biological image processing program ImageJ and a web application working in conjunction with the free statistical environment R, and it is compatible with Linux, MacOS X, or Microsoft Windows. Squassh3C and SquasshAnalyst are available for download at www.psi.ch/lbr/SquasshAnalystEN/SquasshAnalyst.zip.

Detection and quantification of fluorescently labeled molecules in subcellular compartments is a key step in the analysis of many cell biological processes. Pixel-wise colocalization analyses, however, are not always suitable, because they do not provide object-specific information, and they are vulnerable to noise and background fluorescence. Here we present a versatile protocol for a method named 'Squassh' (segmentation and quantification of subcellular shapes), which is used for detecting, delineating and quantifying subcellular structures in fluorescence microscopy images. The workflow is implemented in freely available, user-friendly software. It works on both 2D and 3D images, accounts for the microscope optics and for uneven image background, computes cell masks and provides subpixel accuracy. The Squassh software enables both colocalization and shape analyses. The protocol can be applied in batch, on desktop computers or computer clusters, and it usually requires <1 min and <5 min for 2D and 3D images, respectively. Basic computer-user skills and some experience with fluorescence microscopy are recommended to successfully use the protocol.

Seven‐transmembrane receptors (7TMRs) are involved in nearly all aspects of chemical communications and represent major drug targets. 7TMRs transmit their signals not only via heterotrimeric G proteins but also through β‐arrestins, whose recruitment to the activated receptor is regulated by G protein‐coupled receptor kinases (GRKs). In this paper, we combined experimental approaches with computational modeling to decipher the molecular mechanisms as well as the hidden dynamics governing extracellular signal‐regulated kinase (ERK) activation by the angiotensin II type 1A receptor (AT1AR) in human embryonic kidney (HEK)293 cells. We built an abstracted ordinary differential equations (ODE)‐based model that captured the available knowledge and experimental data. We inferred the unknown parameters by simultaneously fitting experimental data generated in both control and perturbed conditions. We demonstrate that, in addition to its well‐established function in the desensitization of G‐protein activation, GRK2 exerts a strong negative effect on β‐arrestin‐dependent signaling through its competition with GRK5 and 6 for receptor phosphorylation. Importantly, we experimentally confirmed the validity of this novel GRK2‐dependent mechanism in both primary vascular smooth muscle cells naturally expressing the AT1AR, and HEK293 cells expressing other 7TMRs. The molecular mechanisms and hidden dynamics governing ERK activation by the angiotensin II type 1A receptor are studied and deciphered, revealing a signal balancing mechanism that is found to be relevant to a range of other seven transmembrane receptors. The molecular mechanisms and hidden dynamics governing ERK activation by the angiotensin II type 1A receptor are studied and deciphered, revealing a signal balancing mechanism that is found to be relevant to a range of other seven transmembrane receptors.

In systems biology, the number of available models of cellular processes has increased rapidly, but re-using models in different contexts or for different questions remains a challenging issue. In this paper, we study the coupling of different models playing a role in the mammalian cell cycle and in cancer therapies. We show how the formalization of experimental observations in temporal logic with numerical constraints can be used to compute the unknown coupling kinetics parameter values agreeing with experimental data. This constraint-based approach to computing with partial information is illustrated through the design of a complex model of the mammalian cell cycle, the circadian clock, the p53/Mdm2 DNA-damage repair system, the metabolism of irinotecan and the control of cell exposure to it. We discuss the use of this model for cancer chronotherapies and evaluate its predictive power with respect to circadian core gene knock-outs.

The paper addresses the problem of synthesizing programs using a restricted set of input–output data. The program to be synthesized consists of assigning, to individual Boolean variables x ′ , the result of evaluating functions involving other Boolean variables x . The program can be initially viewed as a black box having n inputs corresponding to the variables x and n outputs corresponding to the x ′ . The goal is to determine the Boolean functions that produce x ′ given x . It is shown that by suitably selecting a limited number of input sets to the black box and examining their output, the assignments can be fully reconstructed. The paper describes an effective representation of the Boolean functions, identifies related work, and provides an upper bound on the number of I - O pairs needed to rebuild the program. The work is based on discrete Jacobians that are computed from the selected I - O pairs. Finally, it is shown that the synthesis can be extended to programs whose variables are bounded integers. The results indicate that, if each Boolean function involves a small number of variables, a limited set of selectively chosen I - O pairs suffices for synthesizing the program (instead of a potentially exponential number of pairs that would be needed in a worst case scenario). These results are of interest in the reverse engineering of genetic networks from biological experiments.

Finding mathematical models satisfying a specification built from the formalization of biological experiments, is a common task of the modeler that techniques like model-checking help solving, in the qualitative but also in the quantitative case. In this article we define a continuous degree of satisfaction of temporal logic formulae with constraints. We show how such a satisfaction measure can be used as a fitness function with state-of-the-art evolutionary optimization methods in order to find biochemical kinetic parameter values satisfying a set of biological properties formalized in temporal logic. We also show how it can be used to define a measure of robustness of a biological model with respect to some temporal specification. These methods are evaluated on models of the cell cycle and of the MAPK signaling cascade.