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442 Publications visible to you, out of a total of 442
Anti-trypanosomatid structure-based drug design – lessons learned from targeting the folate pathway

Abstract

Not specified

Authors: Joanna Panecka-Hofman, Ina Poehner, Rebecca C. Wade

Date Published: 2nd Sep 2022

Publication Type: Journal

Graphene BioFET sensors for SARS-CoV-2 detection: a multiscale simulation approach

Abstract (Expand)

Two-dimensional (2D) materials BioFETs have already demonstrated their potential for detecting low amounts of molecules. Here, we present a multiscale simulation platform in the context of Graphene …xt of Graphene BioFET for the detection of SARS-CoV-2.

Authors: A. Toral-Lopez, D. B. Kokh, E. G. Marin, R. C. Wade, A. Godoy

Date Published: 15th Jul 2022

Publication Type: Journal

Multitarget, Selective Compound Design Yields Potent Inhibitors of a Kinetoplastid Pteridine Reductase 1

Abstract

Not specified

Authors: Ina Pöhner, Antonio Quotadamo, Joanna Panecka-Hofman, Rosaria Luciani, Matteo Santucci, Pasquale Linciano, Giacomo Landi, Flavio Di Pisa, Lucia Dello Iacono, Cecilia Pozzi, Stefano Mangani, Sheraz Gul, Gesa Witt, Bernhard Ellinger, Maria Kuzikov, Nuno Santarem, Anabela Cordeiro-da-Silva, Maria P. Costi, Alberto Venturelli, Rebecca C. Wade

Date Published: 14th Jul 2022

Publication Type: Journal

Combining hypothesis- and data-driven neuroscience modeling in FAIR workflows

Abstract (Expand)

Modeling in neuroscience occurs at the intersection of different points of view and approaches. Typically, hypothesis-driven modeling brings a question into focus so that a model is constructed to …constructed to investigate a specific hypothesis about how the system works or why certain phenomena are observed. Data-driven modeling, on the other hand, follows a more unbiased approach, with model construction informed by the computationally intensive use of data. At the same time, researchers employ models at different biological scales and at different levels of abstraction. Combining these models while validating them against experimental data increases understanding of the multiscale brain. However, a lack of interoperability, transparency, and reusability of both models and the workflows used to construct them creates barriers for the integration of models representing different biological scales and built using different modeling philosophies. We argue that the same imperatives that drive resources and policy for data – such as the FAIR (Findable, Accessible, Interoperable, Reusable) principles – also support the integration of different modeling approaches. The FAIR principles require that data be shared in formats that are Findable, Accessible, Interoperable, and Reusable. Applying these principles to models and modeling workflows, as well as the data used to constrain and validate them, would allow researchers to find, reuse, question, validate, and extend published models, regardless of whether they are implemented phenomenologically or mechanistically, as a few equations or as a multiscale, hierarchical system. To illustrate these ideas, we use a classical synaptic plasticity model, the Bienenstock–Cooper–Munro rule, as an example due to its long history, different levels of abstraction, and implementation at many scales.

Authors: Olivia Eriksson, Upinder Singh Bhalla, Kim T Blackwell, Sharon M Crook, Daniel Keller, Andrei Kramer, Marja-Leena Linne, Ausra Saudargienė, Rebecca C Wade, Jeanette Hellgren Kotaleski

Date Published: 6th Jul 2022

Publication Type: Journal

Cholenic acid derivative UniPR1331 impairs tumor angiogenesis via blockade of VEGF/VEGFR2 in addition to Eph/ephrin

Abstract (Expand)

Abstract Angiogenesis, the formation of new blood vessels from preexisting ones, is crucial for tumor growth and metastatization, and is considered a promising therapeutic target. Unfortunately, drugs … therapeutic target. Unfortunately, drugs directed against a specific proangiogenic growth factor or receptor turned out to be of limited benefit for oncology patients, likely due to the high biochemical redundancy of the neovascularization process. In this scenario, multitarget compounds that are able to simultaneously tackle different proangiogenic pathways are eagerly awaited. UniPR1331 is a 3β-hydroxy-Δ 5 -cholenic acid derivative, which is already known to inhibit Eph–ephrin interaction. Here, we employed an analysis pipeline consisting of molecular modeling and simulation, surface plasmon resonance spectrometry, biochemical assays, and endothelial cell models to demonstrate that UniPR1331 directly interacts with the vascular endothelial growth factor receptor 2 (VEGFR2) too. The binding of UniPR1331 to VEGFR2 prevents its interaction with the natural ligand vascular endothelial growth factor and subsequent autophosphorylation, signal transduction, and in vitro proangiogenic activation of endothelial cells. In vivo, UniPR1331 inhibits tumor cell-driven angiogenesis in zebrafish. Taken together, these data shed light on the pleiotropic pharmacological effect of UniPR1331, and point to Δ 5 -cholenic acid as a promising molecular scaffold for the development of multitarget antiangiogenic compounds.

Authors: Marco Rusnati, Giulia Paiardi, Chiara Tobia, Chiara Urbinati, Alessio Lodola, Pasqualina D’Ursi, Miriam Corrado, Riccardo Castelli, Rebecca C. Wade, Massimiliano Tognolini, Paola Chiodelli

Date Published: 1st Jul 2022

Publication Type: Journal

Development and Biological Characterization of a Novel Selective TrkA Agonist with Neuroprotective Properties against Amyloid Toxicity

Abstract (Expand)

Neurotrophins are growth factors that exert important neuroprotective effects by preventing neuronal death and synaptic loss. Nerve Growth Factor (NGF) acts through the activation of its high-affinity, …high-affinity, pro-survival TrkA and low-affinity, pro-apoptotic p75NTR receptors. NGF has been shown to slow or prevent neurodegenerative signals in Alzheimer’s Disease (AD) progression. However, its low bioavailability and its blood–brain-barrier impermeability limit the use of NGF as a potential therapeutic agent against AD. Based on our previous findings on synthetic dehydroepiandrosterone derivatives, we identified a novel NGF mimetic, named ENT-A013, which selectively activates TrkA and exerts neuroprotective, anti-amyloid-β actions. We now report the chemical synthesis, in silico modelling, metabolic stability, CYP-mediated reaction phenotyping and biological characterization of ENT-A013 under physiological and neurodegenerative conditions. We show that ENT-A013 selectively activates the TrkA receptor and its downstream kinases Akt and Erk1/2 in PC12 cells, protecting these cells from serum deprivation-induced cell death. Moreover, ENT-A013 promotes survival of primary Dorsal Root Ganglion (DRG) neurons upon NGF withdrawal and protects hippocampal neurons against Amyloid β-induced apoptosis and synaptic loss. Furthermore, this neurotrophin mimetic partially restores LTP impairment. In conclusion, ENT-A013 represents a promising new lead molecule for developing therapeutics against neurodegenerative disorders, such as Alzheimer’s Disease, selectively targeting TrkA-mediated pro-survival signals.

Authors: Thanasis Rogdakis, Despoina Charou, Alessia Latorrata, Eleni Papadimitriou, Alexandros Tsengenes, Christina Athanasiou, Marianna Papadopoulou, Constantina Chalikiopoulou, Theodora Katsila, Isbaal Ramos, Kyriakos C. Prousis, Rebecca C. Wade, Kyriaki Sidiropoulou, Theodora Calogeropoulou, Achille Gravanis, Ioannis Charalampopoulos

Date Published: 1st Mar 2022

Publication Type: Journal

The Non-phosphorylating Glyceraldehyde-3-Phosphate Dehydrogenase GapN Is a Potential New Drug Target in Streptococcus pyogenes

Abstract (Expand)

The strict human pathogen Streptococcus pyogenes causes infections of varying severity, ranging from self-limiting suppurative infections to life-threatening diseases like necrotizing fasciitis or …to life-threatening diseases like necrotizing fasciitis or streptococcal toxic shock syndrome. Here, we show that the non-phosphorylating glyceraldehyde-3-phosphate dehydrogenase GapN is an essential enzyme for S. pyogenes . GapN converts glyceraldehyde 3-phosphate into 3-phosphoglycerate coupled to the reduction of NADP to NADPH. The knock-down of gapN by antisense peptide nucleic acids (asPNA) significantly reduces viable bacterial counts of S. pyogenes laboratory and macrolide-resistant clinical strains in vitro . As S. pyogenes lacks the oxidative part of the pentose phosphate pathway, GapN appears to be the major NADPH source for the bacterium. Accordingly, other streptococci that carry a complete pentose phosphate pathway are not prone to asPNA-based gapN knock-down. Determination of the crystal structure of the S. pyogenes GapN apo-enzyme revealed an unusual cis-peptide in proximity to the catalytic binding site. Furthermore, using a structural modeling approach, we correctly predicted competitive inhibition of S. pyogenes GapN by erythrose 4-phosphate, indicating that our structural model can be used for in silico screening of specific GapN inhibitors. In conclusion, the data provided here reveal that GapN is a potential target for antimicrobial substances that selectively kill S. pyogenes and other streptococci that lack the oxidative part of the pentose phosphate pathway.

Authors: Philip Eisenberg, Leon Albert, Jonathan Teuffel, Eric Zitzow, Claudia Michaelis, Jane Jarick, Clemens Sehlke, Lisa Große, Nicole Bader, Ariane Nunes-Alves, Bernd Kreikemeyer, Hermann Schindelin, Rebecca C. Wade, Tomas Fiedler

Date Published: 15th Feb 2022

Publication Type: Journal

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