A general strategy for discovery of inhibitors and activators of RING and U-box E3 ligases with ubiquitin variants

RING and U-box E3 ubiquitin ligases regulate diverse eukaryotic processes and have been implicated in numerous diseases, but targeting these enzymes remains a major challenge. We report the development of three ubiquitin variants (UbVs), each binding selectively to the RING or U-box domain of a distinct E3 ligase: monomeric UBE4B, phosphorylated active CBL, or dimeric XIAP. Structural and biochemical analyses revealed that UbVs specifically inhibited the activity of UBE4B or phosphorylated CBL by blocking the E2∼Ub binding site. Surprisingly, the UbV selective for dimeric XIAP formed a dimer to stimulate E3 activity by stabilizing the closed E2∼Ub conformation. We further verified the inhibitory and stimulatory functions of UbVs in cells. Our work provides a general strategy to inhibit or activate RING/U-box E3 ligases and provides a resource for the research community to modulate these enzymes

Identification and characterization of mutations in ubiquitin required for non-covalent dimer formation

Ubiquitin (Ub) is a small protein that post-translationally modifies a variety of substrates in eukaryotic cells to modulate substrate function. The ability of Ub to interact with numerous protein domains makes Ub an attractive scaffold for engineering ubiquitin variants (UbVs) with high target specificity. Previously, we identified a UbV that formed a non-covalent stable dimer via a β-strand exchange, and in the current work we identified and characterized the minimal substitutions in the primary sequence of Ub required to form a higher ordered complex. Using solution angle scattering and X-ray crystallography, we show that a single substitution of residue Gly10 to either Ala or Val is sufficient to convert Ub from a monomer to a dimer. We also investigate contributions to dimer formation by the residues in the surrounding sequence. These results can be used to develop next-generation phage-display libraries of UbVs to engineer new interfaces for protein recognition

Neural stem cell therapy for neuropsychiatric disorders

Introduction. To conduct a comprehensive literature review of the area of neural stem cells and neuropsychiatry. Methods. Neural stem cells’ (NSCs) and ‘neurogenesis’ were used as key words in Medline (1966 - November 2006) to identify relevant papers in the areas of Alzheimer’s disease (AD), depression, schizophrenia and Parkinson’s disease (PD). This list was supplemented with papers from reference lists of seminal reviews. Results. The concept of a ‘stem cell’ continues to evolve and is currently defined by operational criteria related to symmetrical renewal, multipotency and functional viability. In vivo adult mammalian neurogenesis occurs in discrete niches in the subventricular and subgranular zones - however, functional precursor cells can be generated in vitro from a wide variety of biological sources. Both artificial and physiological microenvironment is therefore critical to the characteristics and behaviour of neural precursors, and it is not straightforward how results from the laboratory can be extrapolated to the living organism. Transplant strategies in PD have shown that it is possible for primitive neural tissue to engraft into neuropathic brain areas, become biologically functional and lead to amelioration of clinical signs and symptoms. However, with long-term follow-up, significant problems related to intractable side-effects and potential neoplastic growth have been reported. These are therefore the potentials and pitfalls for NSC technology in neuropsychiatry. In AD, the physiology of amyloid precursor protein may directly interact with NSCs, and a role in memory function has been speculated. The role of endogenous neurogenesis has also been implicated in the etiology of depression. The significance of NSCs and neurogenesis for schizophrenia is still emerging. Conclusions. There are a number of technical and conceptual challenges ahead before the promise of NSCs can be harnessed for the understanding and treatment of neuropsychiatric disorders. Further research into fundamental NSC biology and how this interacts with the neuropsychiatric disease processes is required.Wstęp. W niniejszej pracy przeprowadzono wszechstronny przegląd piśmiennictwa na temat nerwowych komórek macierzystych oraz zaburzeń neurologicznych i psychicznych. Metody. W celu odnalezienia odpowiednich prac dotyczących choroby Alzheimera, depresji, schizofrenii i choroby Parkinsona jako słowa klucze w bazie Medline (1966 - listopad 2006) zastosowano wyrażania "nerwowe komórki macierzyste" (NSC, neural stem cells) i "neurogeneza" (neurogenesis). Uzyskaną listę uzupełniono pracami z wykazu piśmiennictwa prac przeglądowych. Wyniki. Koncepcja "komórek macierzystych" stale ewoluuje i obecnie opiera się na kryteriach operacyjnych związanych z symetrycznym powielaniem się komórek, ich multipotencjalnością i funkcjonalną żywotnością. W warunkach in vivo neurogeneza u dorosłych ssaków zachodzi w niewielkich niszach w strefie okołokomorowej i podziarnistej. Funkcjonalne komórki prekursorowe można jednak uzyskiwać in vitro z różnych źródeł biologicznych. Z tego powodu, zarówno mikrośrodowisko fizjologiczne, jak i sztuczne, ma podstawowe znaczenie dla rozwoju określonych cech i czynności prekursorów komórek nerwowych, a przeniesienie wyników uzyskanych w laboratorium na żywe organizmy nie jest łatwe. Na podstawie strategii z wykorzystaniem przeszczepów w chorobie Parkinsona wykazano, że prymitywna tkanka nerwowa może się zaszczepić w patologicznych obszarach mózgu i uzyskać biologiczną funkcjonalność, co może prowadzić do poprawy w zakresie objawów klinicznych. W trakcie dłuższego okresu obserwacji pojawiły się jednak istotne problemy związane z niepodatnymi na leczenie działaniami niepożądanymi; zgłaszano także niebezpieczeństwo rozwoju nowotworów. Stanowi to o możliwościach i pułapkach stosowania technologii opartych na NSC w neurologii i psychiatrii. W przypadku choroby Alzheimera białko prekursorowe amyloidu może wchodzić w bezpośrednie interakcje z NSC, spekulowano też nad ich znaczeniem w funkcjach pamięci. Rolę endogennej neurogenezy postuluje się także w etiologii depresji. Znaczenie NSC i neurogenezy w schizofrenii jest wciąż odkrywane. Wnioski. Przed wykorzystaniem NSC do zrozumienia i leczenia zaburzeń neurologicznych i psychicznych należy sprostać wielu technicznym i koncepcyjnym wyzwaniom. Konieczne są dalsze badania nad podstawami biologii NSC i interakcjami tych komórek z procesami zachodzącymi w przebiegu zaburzeń neurologicznych i psychicznych

Biosynthetic Oligoclonal Antivenom (BOA) for Snakebite and Next-Generation Treatments for Snakebite Victims

Snakebite envenoming is a neglected tropical disease that each year claims the lives of 80,000⁻140,000 victims worldwide. The only effective treatment against envenoming involves intravenous administration of antivenoms that comprise antibodies that have been isolated from the plasma of immunized animals, typically horses. The drawbacks of such conventional horse-derived antivenoms include their propensity for causing allergenic adverse reactions due to their heterologous and foreign nature, an inability to effectively neutralize toxins in distal tissue, a low content of toxin-neutralizing antibodies, and a complex manufacturing process that is dependent on husbandry and procurement of snake venoms. In recent years, an opportunity to develop a fundamentally novel type of antivenom has presented itself. By using modern antibody discovery strategies, such as phage display selection, and repurposing small molecule enzyme inhibitors, next-generation antivenoms that obviate the drawbacks of existing plasma-derived antivenoms could be developed. This article describes the conceptualization of a novel therapeutic development strategy for biosynthetic oligoclonal antivenom (BOA) for snakebites based on recombinantly expressed oligoclonal mixtures of human monoclonal antibodies, possibly combined with repurposed small molecule enzyme inhibitors

Highly multiplexed and quantitative cell-surface protein profiling using genetically barcoded antibodies.

Human cells express thousands of different surface proteins that can be used for cell classification, or to distinguish healthy and disease conditions. A method capable of profiling a substantial fraction of the surface proteome simultaneously and inexpensively would enable more accurate and complete classification of cell states. We present a highly multiplexed and quantitative surface proteomic method using genetically barcoded antibodies called phage-antibody next-generation sequencing (PhaNGS). Using 144 preselected antibodies displayed on filamentous phage (Fab-phage) against 44 receptor targets, we assess changes in B cell surface proteins after the development of drug resistance in a patient with acute lymphoblastic leukemia (ALL) and in adaptation to oncogene expression in a Myc-inducible Burkitt lymphoma model. We further show PhaNGS can be applied at the single-cell level. Our results reveal that a common set of proteins including FLT3, NCR3LG1, and ROR1 dominate the response to similar oncogenic perturbations in B cells. Linking high-affinity, selective, genetically encoded binders to NGS enables direct and highly multiplexed protein detection, comparable to RNA-sequencing for mRNA. PhaNGS has the potential to profile a substantial fraction of the surface proteome simultaneously and inexpensively to enable more accurate and complete classification of cell states

Identification of specificity determining residues in peptide recognition domains using an information theoretic approach applied to large-scale binding maps

<p>Abstract</p> <p>Background</p> <p>Peptide Recognition Domains (PRDs) are commonly found in signaling proteins. They mediate protein-protein interactions by recognizing and binding short motifs in their ligands. Although a great deal is known about PRDs and their interactions, prediction of PRD specificities remains largely an unsolved problem.</p> <p>Results</p> <p>We present a novel approach to identifying these Specificity Determining Residues (SDRs). Our algorithm generalizes earlier information theoretic approaches to coevolution analysis, to become applicable to this problem. It leverages the growing wealth of binding data between PRDs and large numbers of random peptides, and searches for PRD residues that exhibit strong evolutionary covariation with some positions of the statistical profiles of bound peptides. The calculations involve only information from sequences, and thus can be applied to PRDs without crystal structures. We applied the approach to PDZ, SH3 and kinase domains, and evaluated the results using both residue proximity in co-crystal structures and verified binding specificity maps from mutagenesis studies.</p> <p>Discussion</p> <p>Our predictions were found to be strongly correlated with the physical proximity of residues, demonstrating the ability of our approach to detect physical interactions of the binding partners. Some high-scoring pairs were further confirmed to affect binding specificity using previous experimental results. Combining the covariation results also allowed us to predict binding profiles with higher reliability than two other methods that do not explicitly take residue covariation into account.</p> <p>Conclusions</p> <p>The general applicability of our approach to the three different domain families demonstrated in this paper suggests its potential in predicting binding targets and assisting the exploration of binding mechanisms.</p

MOTIPS: Automated Motif Analysis for Predicting Targets of Modular Protein Domains

<p>Abstract</p> <p>Background</p> <p>Many protein interactions, especially those involved in signaling, involve short linear motifs consisting of 5-10 amino acid residues that interact with modular protein domains such as the SH3 binding domains and the kinase catalytic domains. One straightforward way of identifying these interactions is by scanning for matches to the motif against all the sequences in a target proteome. However, predicting domain targets by motif sequence alone without considering other genomic and structural information has been shown to be lacking in accuracy.</p> <p>Results</p> <p>We developed an efficient search algorithm to scan the target proteome for potential domain targets and to increase the accuracy of each hit by integrating a variety of pre-computed features, such as conservation, surface propensity, and disorder. The integration is performed using naïve Bayes and a training set of validated experiments.</p> <p>Conclusions</p> <p>By integrating a variety of biologically relevant features to predict domain targets, we demonstrated a notably improved prediction of modular protein domain targets. Combined with emerging high-resolution data of domain specificities, we believe that our approach can assist in the reconstruction of many signaling pathways.</p