Analogies Between Digital Radio and Chemical Orthogonality as a Method for Enhanced Analysis of Molecular Recognition Events

Acoustic wave biosensors are a real-time, label-free biosensor technology, which have been exploited for the detection of proteins and cells. One of the conventional biosensor approaches involves the immobilization of a monolayer of antibodies onto the surface of the acoustic wave device for the detection of a specific analyte. The method described within includes at least two immobilizations of two different antibodies onto the surfaces of two separate acoustic wave devices for the detection of several analogous analytes. The chemical specificity of the molecular recognition event is achieved by virtue of the extremely high (nM to pM) binding affinity between the antibody and its antigen. In a standard ELISA (Enzyme-Linked ImmunoSorbent Assay) test, there are multiple steps and the end result is a measure of what is bound so tightly that it does not wash away easily. The fact that this “gold standard” is very much not real time, masks the dance that is the molecular recognition event. X-Ray Crystallographer, Ian Wilson, demonstrated more than a decade ago that antibodies undergo conformational change during a binding event[1, 2]. Further, it is known in the arena of immunochemistry that some antibodies exhibit significant cross-reactivity and this is widely termed antibody promiscuity. A third piece of the puzzle that we will exploit in our system of acoustic wave biosensors is the notion of chemical orthogonality. These three biochemical constructs, the dance, antibody promiscuity and chemical orthogonality will be combined in this paper with the notions of in-phase (I) and quadrature (Q) signals from digital radio to manifest an approach to molecular recognition that allows a level of discrimination and analysis unobtainable without the aggregate. As an example we present experimental data on the detection of TNT, RDX, C4, ammonium nitrate and musk oil from a system of antibody-coated acoustic wave sensors

Cell Signaling by Receptor Tyrosine Kinases

Recent structural studies of receptor tyrosine kinases (RTKs) have revealed unexpected diversity in the mechanisms of their activation by growth factor ligands. Strategies for inducing dimerization by ligand binding are surprisingly diverse, as are mechanisms that couple this event to activation of the intracellular tyrosine kinase domains. As our understanding of these details becomes increasingly sophisticated, it provides an important context for therapeutically countering the effects of pathogenic RTK mutations in cancer and other diseases. Much remains to be learned, however, about the complex signaling networks downstream from RTKs and how alterations in these networks are translated into cellular responses

Dissecting the Extracellular Complexity of Neuromuscular Junction Organizers

Synapse formation is a very elaborate process dependent upon accurate coordination of pre and post-synaptic specialization, requiring multiple steps and a variety of receptors and signaling molecules. Due to its relative structural simplicity and the ease in manipulation and observation, the neuromuscular synapse or neuromuscular junction (NMJ)—the connection between motor neurons and skeletal muscle—represents the archetype junction system for studying synapse formation and conservation. This junction is essential for survival, as it controls our ability to move and breath. NMJ formation requires coordinated interactions between motor neurons and muscle fibers, which ultimately result in the formation of a highly specialized post-synaptic architecture and a highly differentiated nerve terminal. Furthermore, to ensure a fast and reliable synaptic transmission following neurotransmitter release, ligand-gated channels (acetylcholine receptors, AChRs) are clustered on the post-synaptic muscle cell at high concentrations in sites opposite the presynaptic active zone, supporting a direct role for nerves in the organization of the post-synaptic membrane architecture. This organized clustering process, essential for NMJ formation and for life, relies on key signaling molecules and receptors and is regulated by soluble extracellular molecules localized within the synaptic cleft. Notably, several mutations as well as auto-antibodies against components of these signaling complexes have been related to neuromuscular disorders. The recent years have witnessed strong progress in the understanding of molecular identities, architectures, and functions of NMJ macromolecules. Among these, prominent roles have been proposed for neural variants of the proteoglycan agrin, its receptor at NMJs composed of the lipoprotein receptor-related protein 4 (LRP4) and the muscle-specific kinase (MuSK), as well as the regulatory soluble synapse-specific protease Neurotrypsin. In this review we summarize the current state of the art regarding molecular structures and (agrin-dependent) canonical, as well as (agrin-independent) non-canonical, MuSK signaling mechanisms that underscore the formation of neuromuscular junctions, with the aim of providing a broad perspective to further stimulate molecular, cellular and tissue biology investigations on this fundamental intercellular contact

BCR-ABL residues interacting with ponatinib are critical to preserve the tumorigenic potential of the oncoprotein

Patients with chronic myeloid leukemia in whom tyrosine kinase inhibitors (TKIs) fail often present mutations in the BCR-ABL catalytic domain. We noticed a lack of substitutions involving 4 amino acids (E286, M318, I360, and D381) that form hydrogen bonds with ponatinib. We therefore introduced mutations in each of these residues, either preserving or altering their physicochemical properties. We found that E286, M318, I360, and D381 are dispensable for ABL and BCR-ABL protein stability but are critical for preserving catalytic activity. Indeed, only a "conservative" I360T substitution retained kinase proficiency and transforming potential. Molecular dynamics simulations of BCR-ABLI360T revealed differences in both helix αC dynamics and protein-correlated motions, consistent with a modified ATP-binding pocket. Nevertheless, this mutant remained sensitive to ponatinib, imatinib, and dasatinib. These results suggest that changes in the 4 BCR-ABL residues described here would be selected against by a lack of kinase activity or by maintained responsiveness to TKIs. Notably, amino acids equivalent to those identified in BCR-ABL are conserved in 51% of human tyrosine kinases. Hence, these residues may represent an appealing target for the design of pharmacological compounds that would inhibit additional oncogenic tyrosine kinases while avoiding the emergence of resistance due to point mutations.This work was supported by an investigator grant to P.V. from Associazione Italiana per la Ricerca sul Cancro (AIRC) and by funding from the Biotechnology and Biological Sciences Research Council (BB/I023291/1 and BB/H018409/1 to AP and FF). P.B. is the recipient of an AIRC - Marie Curie fellowship

Characterizing human odorant signals: insights from insect semiochemistry and in silico modelling

Interactions relating to human chemical signalling, although widely acknowledged, are relatively poorly characterized chemically, except for human axillary odour. However, the extensive chemical ecology of insects, involving countless pheromone and other semiochemical identifications, may offer insights into overcoming problems of characterizing human-derived semiochemicals more widely. Current techniques for acquiring insect semiochemicals are discussed, particularly in relation to the need for samples to relate, as closely as possible, to the ecological situation in which they are naturally deployed. Analysis is facilitated by chromatography coupled to electrophysiological preparations from the olfactory organs of insects in vivo. This is not feasible with human olfaction, but there are now potential approaches using molecular genetically reconstructed olfactory preparations already in use with insect systems. There are specific insights of value for characterizing human semiochemicals from advanced studies on semiochemicals of haematophagous insects, which include those involving human hosts, in addition to wider studies on farm and companion animals. The characterization of the precise molecular properties recognized in olfaction could lead to new advances in analogue design and a range of novel semiochemicals for human benefit. There are insights from successful synthetic biology studies on insect semiochemicals using novel biosynthetic precursors. Already, wider opportunities in olfaction emerging from in silico studies, involving a range of theoretical and computational approaches to molecular design and understanding olfactory systems at the molecular level, are showing promise for studying human semiochemistry

ELUCIDATION OF THE CELLULAR AND MOLECULAR MECHANISMS OF MISSENSE MUTATIONS ASSOCIATED WITH FAMILIAL EXUDATIVE VITREORETINOPATHY AND CONGENITAL MYASTHENIC SYNDROME

The endoplasmic reticulum (ER), within eukaryotic cells, is a hub for protein folding and assembly. Misfolded proteins and unassembled subunits of protein complexes are retained in the ER and degraded by a process termed endoplasmic reticulum associated degradation (ERAD). Frizzled class receptor 4 (FZD4) and muscle, skeletal, receptor tyrosine kinase (MuSK) are Wnt receptors. These proteins contain the frizzled cysteine-rich domain (Fz-CRD) required for dimerization in the ER. Mutations in FZD4 and MuSK genes are known to cause familial exudative vitreoretinopathy (FEVR, an autosomal dominant disease) and congenital myasthenic syndrome (CMS, an autosomal recessive disease), respectively. It was hypothesized that missense mutations within Fz-CRD lead to misfolding of FZD4 and MuSK proteins and consequent ER-retention. Investigating the molecular mechanism of these mutations is important since misfolded protein and ER-targeted therapies are in development being developed. Wild-type and mutants of FZD4 and MuSK were expressed at 37 °C in HeLa, COS-7, and HEK293 cells and their subcellular localizations were investigated using confocal microscopy imaging and glycosidase treatments. Abnormal trafficking was demonstrated in 10 of 21 mutants studied; nine mutants were within Fz-CRD and one was distant from Fz-CRD. These ER-retained mutants were improperly N-glycosylated confirming ER-localization. They were tagged with polyubiquitin chains confirming targeting for proteasomal degradation. The half-lives of wild-type MuSK and P344R-MuSK were 45 and 37 minutes, respectively; the latter half-life improved on incubation with proteasomal inhibitor MG132. The P344R-MuSK kinase mutant showed around 50% of its in vivo autophosphorylation activity. Trafficking defects in three of the 10 mutants (M105T-FZD4, C204Y-FZD4, and P344R-MuSK) were rescued by expression at 27 °C and by chemical chaperones (2.5-7.5% glycerol, 0.1-1% dimethyl sulfoxide, 10 μM thapsigargin, or 1 μM curcumin). Trafficking of wild-type FZD4 was not affected by co-expression with any of the nine ER-retained mutants, suggesting haploinsufficiency as the mechanism of disease. Thus, all nine Fz-CRD mutants of FEVR and CMS studied resulted in misfolded proteins. In contrast, only one of the 12 mutants outside Fz-CRD resulted in ER-retention. These findings demonstrate a common mechanism for diseases associated with Fz-CRD missense mutations. Disorders of Fz-CRD may be receptive to novel therapies that alleviate protein misfolding

Implementation of Multiple-Instance Learning in Drug Activity Prediction

In the context of drug discovery and development, much effort has been exerted to determine which conformers of a given molecule are responsible for the observed biological activity. In this work we aimed to predict bioactive conformers using a variant of supervised learning, named multiple-instance learning. A single molecule, treated as a bag of conformers, is biologically active if and only if at least one of its conformers, treated as an instance, is responsible for the observed bioactivity; and a molecule is inactive if none of its conformers is responsible for the observed bioactivity. The implementation requires instance-based embedding, and joint feature selection and classification. The goal of the present project is to implement multiple-instance learning in drug activity prediction, and subsequently to identify the bioactive conformers for each molecule. We encoded the 3-dimensional structures using pharmacophore fingerprints which are binary strings, and accomplished instance-based embedding using calculated dissimilarity distances. Four dissimilarity measures were employed and their performances were compared. 1-norm SVM was used for joint feature selection and classification. The approach was applied to four data sets, and the best proposed model for each data set was determined by using the dissimilarity measure yielding the smallest number of selected features. The predictive abilities of the proposed approach were compared with three classical predictive models without instance-based embedding. The proposed approach produced the best predictive models for one data set and second best predictive models for the rest of the data sets, based on the external validations. To validate the ability of the proposed approach to find bioactive conformers, 12 small molecules with co-crystallized structures were seeded in one data set. 10 out of 12 co-crystallized structures were indeed identified as significant conformers using the proposed approach. The proposed approach was demonstrated to be highly competitive with classical predictive models, hence it is very powerful for drug activity prediction. The approach was also validated as a useful method for pursuit of bioactive conformers

Structural Insights into Pseudokinase Domains of Receptor Tyrosine Kinases

Despite their apparent lack of catalytic activity, pseudokinases are essential signaling molecules. Here, we describe the structural and dynamic properties of pseudokinase domains from the Wnt-binding receptor tyrosine kinases (PTK7, ROR1, ROR2, and RYK), which play important roles in development. We determined structures of all pseudokinase domains in this family and found that they share a conserved inactive conformation in their activation loop that resembles the autoinhibited insulin receptor kinase (IRK). They also have inaccessible ATP-binding pockets, occluded by aromatic residues that mimic a cofactor-bound state. Structural comparisons revealed significant domain plasticity and alternative interactions that substitute for absent conserved motifs. The pseudokinases also showed dynamic properties that were strikingly similar to those of IRK. Despite the inaccessible ATP site, screening identified ATP-competitive type-II inhibitors for ROR1. Our results set the stage for an emerging therapeutic modality of "conformational disruptors" to inhibit or modulate non-catalytic functions of pseudokinases deregulated in disease.Peer reviewe

Multiscale Modeling of the ErbB Receptor Tyrosine Kinase Signaling Network Through Theory and Experiment

The biochemical processes occurring within a living cell span a spectrum of scales in space and time, ranging from the nano- to the macro-scale. We note that a single cellular process often operates on multiple spatial and temporal scales, and thus it becomes necessary to combine modeling techniques in multiscale approaches, in which different levels of theory are synergized to describe a system at a number of scales or resolutions. In this work we apply a multiscale modeling framework to investigate the molecular regulatory mechanisms governing the activation of the ErbB receptor tyrosine kinases, a family of kinases which are commonly over-expressed or mutated in human cancers, with a focus on the HER3 and HER4 kinases. Our multiscale model of HER3, a kinase which, until recently, has been considered kinase-dead, presents evidence of HER3 catalytic activity and demonstrates that even a weak HER3 signal can be amplified by other cellular signaling mechanisms to induce drug resistance to tyrosine kinase inhibitors in silico. Thus HER3, rather than the commonly-targeted EGFR and HER2 kinases, may represent a superior therapeutic target in specific ErbB-driven cancers. In the second major study, we construct a multiscale model of activity in the HER4 kinase, which has been shown to perform an anti-cancer role in certain tumor cells, by steering the cell toward a program of cellular differentiation and away from a program of uncontrolled proliferation. Our HER4 model, which applies a combined computational and experimental approach, elucidates the molecular mechanisms underlying this HER4-mediated ‘switch’ to the cellular differentiation program, with the ultimate aim of exploiting or modulating the HER4 pathway as a potential therapy in specific ErbB-driven cancers. Furthermore, the model provides structural insights into the effects of several HER4 somatic mutations which have recently been discovered in a subset of cancer patients, and which abrogate the anti-cancer effects of HER4 activity. We have illustrated that multiscale modeling provides a powerful and quantitative platform for investigating the complexity inherent in intracellular signaling pathways and rationalizing the effects of molecular perturbations on downstream signaling events and ultimately, on the cell phenotype

Unveiling the Molecular Mechanisms Regulating the Activation of the ErbB Family Receptors at Atomic Resolution through Molecular Modeling and Simulations

The EGFR/ErbB/HER family of kinases contains four homologous receptor tyrosine kinases that are important regulatory elements in key signaling pathways. To elucidate the atomistic mechanisms of dimerization-dependent activation in the ErbB family, we have performed molecular dynamics simulations of the intracellular kinase domains of the four members of the ErbB family (those with known kinase activity), namely EGFR, ErbB2 (HER2) and ErbB4 (HER4) as well as ErbB3 (HER3), an assumed pseudokinase, in different molecular contexts: monomer vs. dimer, wildtype vs. mutant. Using bioinformatics and fluctuation analyses of the molecular dynamics trajectories, we relate sequence similarities to correspondence of specific bond-interaction networks and collective dynamical modes. We find that in the active conformation of the ErbB kinases (except ErbB3), key subdomain motions are coordinated through conserved hydrophilic interactions: activating bond-networks consisting of hydrogen bonds and salt bridges. The inactive conformations also demonstrate conserved bonding patterns (albeit less extensive) that sequester key residues and disrupt the activating bond network. Both conformational states have distinct hydrophobic advantages through context-specific hydrophobic interactions. The inactive ErbB3 kinase domain also shows coordinated motions similar to the active conformations, in line with recent evidence that ErbB3 is a weakly active kinase, though the coordination seems to arise from hydrophobic interactions rather than hydrophilic ones. We show that the functional (activating) asymmetric kinase dimer interface forces a corresponding change in the hydrophobic and hydrophilic interactions that characterize the inactivating interaction network, resulting in motion of the αC-helix through allostery. Several of the clinically identified activating kinase mutations of EGFR act in a similar fashion to disrupt the inactivating interaction network. Our molecular dynamics study reveals the asymmetric dimer interface helps progress the ErbB family through the activation pathway using both hydrophilic and hydrophobic interaction. There is a fundamental difference in the sequence of events in EGFR activation compared with that described for the Src kinase Hck