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442 Publications visible to you, out of a total of 442

Abstract (Expand)

Abstract The COVID‐19 pandemic continues to pose a substantial threat to human lives and is likely to do so for years to come. Despite the availability of vaccines, searching for efficient small‐moleculer efficient small‐molecule drugs that are widely available, including in low‐ and middle‐income countries, is an ongoing challenge. In this work, we report the results of an open science community effort, the “Billion molecules against COVID‐19 challenge”, to identify small‐molecule inhibitors against SARS‐CoV‐2 or relevant human receptors. Participating teams used a wide variety of computational methods to screen a minimum of 1 billion virtual molecules against 6 protein targets. Overall, 31 teams participated, and they suggested a total of 639,024 molecules, which were subsequently ranked to find ‘consensus compounds’. The organizing team coordinated with various contract research organizations (CROs) and collaborating institutions to synthesize and test 878 compounds for biological activity against proteases (Nsp5, Nsp3, TMPRSS2), nucleocapsid N, RdRP (only the Nsp12 domain), and (alpha) spike protein S. Overall, 27 compounds with weak inhibition/binding were experimentally identified by binding‐, cleavage‐, and/or viral suppression assays and are presented here. Open science approaches such as the one presented here contribute to the knowledge base of future drug discovery efforts in finding better SARS‐CoV‐2 treatments.

Authors: Johannes Schimunek, Philipp Seidl, Katarina Elez, Tim Hempel, Tuan Le, Frank Noé, Simon Olsson, Lluís Raich, Robin Winter, Hatice Gokcan, Filipp Gusev, Evgeny M. Gutkin, Olexandr Isayev, Maria G. Kurnikova, Chamali H. Narangoda, Roman Zubatyuk, Ivan P. Bosko, Konstantin V. Furs, Anna D. Karpenko, Yury V. Kornoushenko, Mikita Shuldau, Artsemi Yushkevich, Mohammed Benabderrahmane, Patrick Bousquet-Melou, Ronan Bureau, Beatrice Charton, Bertrand Cirou, Gérard Gil, William J. Allen, Suman Sirimulla, Stanley Watowich, Nick Antonopoulos, Nikolaos Epitropakis, Agamemnon Krasoulis, Vassilis Pitsikalis, Stavros Theodorakis, Igor Kozlovskii, Anton Maliutin, Alexander Medvedev, Petr Popov, Mark Zaretckii, Hamid Eghbal-zadeh, Christina Halmich, Sepp Hochreiter, Andreas Mayr, Peter Ruch, Michael Widrich, Francois Berenger, Ashutosh Kumar, Yoshihiro Yamanishi, Kam Zhang, Emmanuel Bengio, Yoshua Bengio, Moksh Jain, Maksym Korablyov, Cheng-Hao Liu, Marcous Gilles, Enrico Glaab, Kelly Barnsley, Suhasini M. Iyengar, Mary Jo Ondrechen, V. Joachim Haupt, Florian Kaiser, Michael Schroeder, Luisa Pugliese, Simone Albani, Christina Athanasiou, Andrea Beccari, Paolo Carloni, Giulia D'Arrigo, Eleonora Gianquinto, Jonas Goßen, Anton Hanke, Benjamin P. Joseph, Daria B. Kokh, Sandra Kovachka, Candida Manelfi, Goutam Mukherjee, Abraham Muñiz-Chicharro, Francesco Musiani, Ariane Nunes-Alves, Giulia Paiardi, Giulia Rossetti, S. Kashif Sadiq, Francesca Spyrakis, Carmine Talarico, Alexandros Tsengenes, Rebecca Wade, Conner Copeland, Jeremiah Gaiser, Daniel R. Olson, Amitava Roy, Vishwesh Venkatraman, Travis J. Wheeler, Haribabu Arthanari, Klara Blaschitz, Marco Cespugli, Vedat Durmaz, Konstantin Fackeldey, Patrick D. Fischer, Christoph Gorgulla, Christian Gruber, Karl Gruber, Michael Hetmann, Jamie E. Kinney, Krishna M. Padmanabha Das, Shreya Pandita, Amit Singh, Georg Steinkellner, Guilhem Tesseyre, Gerhard Wagner, Zi-Fu Wang, Ryan J. Yust, Dmitry S. Druzhilovskiy, Dmitry Filimonov, Pavel V. Pogodin, Vladimir Poroikov, Anastassia V. Rudik, Leonid A. Stolbov, Alexander V. Veselovsky, Maria De Rosa, Giada De Simone, Maria R. Gulotta, Jessica Lombino, Nedra Mekni, Ugo Perricone, Arturo Casini, Amanda Embree, D. Benjamin Gordon, David Lei, Katelin Pratt, Christopher A. Voigt, Kuang-Yu Chen, Yves Jacob, Tim Krischuns, Pierre Lafaye, Agnès Zettor, M. Luis Rodríguez, Kris M. White, Daren Fearon, Frank von Delft, Martin A. Walsh, Dragos Horvath, Charles L. Brooks, Babak Falsafi, Bryan Ford, Adolfo García-Sastre, Sang Yup Lee, Nadia Naffakh, Alexandre Varnek, Guenter Klambauer, Thomas M. Hermans

Date Published: 2024

Publication Type: Journal

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Abstract Mitochondrial fatty acid synthesis (mtFAS) is essential for respiratory function. MtFAS generates the octanoic acid precursor for lipoic acid synthesis, but the role of longer fatty acidthesis, but the role of longer fatty acid products has remained unclear. The structurally well-characterized component of mtFAS, human 2E -enoyl-ACP reductase (MECR) rescues respiratory growth and lipoylation defects of a Saccharomyces cerevisiae Δ etr1 strain lacking native mtFAS enoyl reductase. To address the role of longer products of mtFAS, we employed in silico molecular simulations to design a MECR variant with a shortened substrate binding cavity. Our in vitro and in vivo analyses indicate that the MECR G165Q variant allows synthesis of octanoyl groups but not long chain fatty acids, confirming the validity of our computational approach to engineer substrate length specificity. Furthermore, our data imply that restoring lipoylation in mtFAS deficient yeast strains is not sufficient to support respiration and that long chain acyl-ACPs generated by mtFAS are required for mitochondrial function.

Authors: M. Tanvir Rahman, M. Kristian Koski, Joanna Panecka-Hofman, Werner Schmitz, Alexander J. Kastaniotis, Rebecca C. Wade, Rik K. Wierenga, J. Kalervo Hiltunen, Kaija J. Autio

Date Published: 1st Dec 2023

Publication Type: Journal

Abstract (Expand)

Abstract The propensity of poorly water-soluble drugs to aggregate at supersaturation impedes their bioavailability. Supersaturated amorphous drug-salt-polymer systems provide an emergent approach tor systems provide an emergent approach to this problem. However, the effects of polymers on drug-drug interactions in aqueous phase are largely unexplored and it is unclear how to choose an optimal salt-polymer combination for a particular drug. Here, we describe a comparative experimental and computational characterization of amorphous solid dispersions containing the drug celecoxib, and a polymer, polyvinylpyrrolidone vinyl acetate (PVP-VA) or hydroxypropyl methylcellulose acetate succinate, with or without Na + /K + salts. Classical models for drug-polymer interactions fail to identify the best drug-salt-polymer combination. In contrast, more stable drug-polymer interaction energies computed from molecular dynamics simulations correlate with prolonged stability of supersaturated amorphous drug-salt-polymer systems, along with better dissolution and pharmacokinetic profiles. The celecoxib-salt-PVP-VA formulations exhibit excellent biopharmaceutical performance, offering the prospect of a low-dosage regimen for this widely used anti-inflammatory, thereby increasing cost-effectiveness, and reducing side-effects.

Authors: Sumit Mukesh, Goutam Mukherjee, Ridhima Singh, Nathan Steenbuck, Carolina Demidova, Prachi Joshi, Abhay T. Sangamwar, Rebecca C. Wade

Date Published: 1st Dec 2023

Publication Type: Journal

Abstract (Expand)

Zusammenfassung Angesichts der umwälzenden Auswirkungen, die künstliche Intelligenz (KI) auf Wissenschaft, Medizin und darüber hinaus hat, betrachten wir hier das Potenzial von KI für die Entdeckungenzial von KI für die Entdeckung neuer Medikamente gegen Herzkrankheiten. Wir definieren KI im weitesten Sinne als den Einsatz von maschinellem Lernen, einschließlich Statistik und Deep Learning, um Muster in Datensätzen zu erkennen, die für Vorhersagen genutzt werden können. Jüngste Durchbrüche in der Fähigkeit, sehr große Datenmengen zu berücksichtigen, haben einen Boom in der KI-gestützten Arzneimittelentdeckung sowohl in der Wissenschaft als auch in der Industrie ausgelöst. Viele neue Unternehmen verfügen bereits über Arzneimittel-Pipelines, die bis in die klinische Erprobung reichen, aber noch keine Medikamente gegen Herzkrankheiten enthalten. Wir beschreiben hier den Einsatz von KI für die Entdeckung von niedermolekularen Medikamenten und Biologika, einschließlich therapeutischer Peptide, sowie für die Vorhersage von Wirkungen wie Kardiotoxizität. Der konzertierte Einsatz von KI zusammen mit physikbasierten Simulationen und experimentellen Rückkopplungsschleifen wird notwendig sein, um das Potenzial der KI für die Arzneimittelentdeckung und die Entwicklung von Präzisionsarzneimitteln für Herzkrankheiten voll auszuschöpfen.

Authors: Manuel Glaser, Julia Ritterhof, Patrick Most, Rebecca C. Wade

Date Published: 20th Nov 2023

Publication Type: Journal

Abstract (Expand)

Protein-surface adsorption phenomena play a crucial role in a variety of fields, including medicine, molecular and cell biology, biotechnology, phar- maceutical sciences, and biophysics. It is therefore desirable to develop accu- rate models to describe them. Hen-Egg-White-Lysozyme (HEWL) adsorption to silica- and mica-like surfaces entails minimal conformational changes, rendering it an ideal system for rigid-body Brownian dynamics simulations. Experimen- tal studies revealed that the fluorescence attached to HEWL exhibits a sharp overshoot followed by a trough as a function of time. This work identifies two inconsistencies in the explanation previously used by the authors to interpret the experiment. A reorientation does not seem to be the main driving factor for the overshoot. Furthermore, I examine previously used electrostatic potential models based on the Poisson-Boltzmann equation (PBE) used by Romanowska et al. and Reinhardt et al.. It is found that even though different orientations of HEWL- FITC on the surface are possible, the required amount of adsorbed proteins and corresponding reorientation is attained only with the linearized PBE-potential. The study provides a possible explanation why reaching the critical overshoot value with non-linearized PBE-based models poses difficulties. Overcoming this problem is an indispensable step in developing Brownian-dynamics-based atomic- detail multi-molecule models for protein-surface adsorption.

Author: Jakob Nießner

Date Published: 14th Nov 2023

Publication Type: Master's Thesis

Abstract (Expand)

Neurotrophins (NTs) are growth factors that are expressed in the central and peripheral nervous systems. They are implicated in different phases of the development and maintenance of the nervous system and they can regulate neuronal survival, development, function, plasticity, as well as neuronal apoptosis. NTs can be used as therapeutics for the treatment of neurodegenerative disorders. However, their poor pharmacokinetic properties and their invasive administration to patients renders them inefficient for use as pharmaceuticals. A solution to this can be offered by small molecule NT mimetics, which can elicit NT mechanisms through binding to NT receptors, which are transmembrane (TM) glycoproteins. The mechanism of activation of NT receptors remains elusive and thus, in this thesis, I have investigated the mechanism of action of NT receptors and mimetics through molecular modeling and molecular dynamics (MD) simulations. I modeled and simulated the glycosylated state of the full extracellular (EC) domains of Tropomyosin receptor kinases A and B (TrkA, TrkB) NT receptors, which revealed that the glycans can shield the accessible surface area of the receptors and participate in the contact area between receptor and NT. Most importantly, glycosylation promoted the extended conformations of the EC domains, which might facilitate NT binding. Then, I performed coarse-grained MD simulations to study the possible arrangements of the TM helical homodimers of TrkA and TrkB receptors in micelles. The results revealed arrangements that could correspond to the active state of the receptors, while metadynamics simulations indicated a stronger binding for the TrkA helices by 10 kJ/mol compared to TrkB. Next, I modeled the full-length structures of the TrkA and TrkB receptors in their homodimeric, glycosylated state bound to their NTs. I embedded the receptors in a realistic model of a neuronal asymmetric membrane. I verified the proper behavior of the membrane and proteins with smaller systems comprising of the TM and intracellular monomers of the receptors. These test simulations revealed interactions between positively charged residues of the kinase domain of TrkA with negatively charged lipids of the inner leaflet of the membrane. These interactions were also formed in the full-length system, and they might stabilize the two kinase domains of the receptor dimer in an orientation that promotes activation, even though the kinase domains were not activated during the simulations. Also, in the full-length systems, the EC domains approached and lay down on the neuronal membrane, while interacting with membrane lipids, such as gangliosides, which are able to activate the NT receptors. Finally, I investigated the binding of small-molecule NT mimetics to the EC and TM domains of TrkA and TrkB receptors, with molecular docking and MD simulations. While plausible poses were 8 obtained, they were not able to explain the selectivity of the compounds for the receptors and the simulations showed that binding was weak. Due to the cholesterol core of the NT mimetics, I tested the ability of the compounds to enter the cell membrane with MD simulations. The compounds were able to spontaneously penetrate the membranes, indicating that their binding site could also lie in the TM region of the receptors. However, simulations with the compounds bound or close to the TM helices in the membrane environment, showed no specific binding. Further experimental exploration of the binding mechanism of these compounds is required. Overall, this thesis sheds light on the dynamic behavior of TrkA and TrkB NT receptors in membranes and the mechanistic insights provide a basis for future studies to develop NT mimetics.

Author: Christina Athanasiou

Date Published: 30th Oct 2023

Publication Type: Doctoral Thesis

Abstract

Not specified

Authors: Marina Roussaki, George E. Magoulas, Theano Fotopoulou, Nuno Santarem, Emile Barrias, Ina Pöhner, Sara Luelmo, Pantelis Afroudakis, Kalliopi Georgikopoulou, Paloma Tejera Nevado, Julia Eick, Eugenia Bifeld, María J. Corral, María Dolores Jiménez-Antón, Bernhard Ellinger, Maria Kuzikov, Irini Fragiadaki, Effie Scoulica, Sheraz Gul, Joachim Clos, Kyriakos C. Prousis, Juan J. Torrado, José María Alunda, Rebecca C. Wade, Wanderley de Souza, Anabela Cordeiro da Silva, Theodora Calogeropoulou

Date Published: 1st Sep 2023

Publication Type: Journal

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