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1447 Publications visible to you, out of a total of 1447
Host–guest interactions in framework materials: Insight from modeling
Computational Carbon Chemistry

Abstract (Expand)

The performance of metal–organic and covalent organic framework materials in sought-after applications—capture, storage, and delivery of gases and molecules, and separation of their mixtures—heavily …xtures—heavily depends on the host–guest interactions established inside the pores of these materials. Computational modeling provides information about the structures of these host–guest complexes and the strength and nature of the interactions present at a level of detail and precision that is often unobtainable from experiment. In this Review, we summarize the key simulation techniques spanning from molecular dynamics and Monte Carlo methods to correlate ab initio approaches and energy, density, and wavefunction partitioning schemes. We provide illustrative literature examples of their uses in analyzing and designing organic framework hosts. We also describe modern approaches to the high-throughput screening of thousands of existing and hypothetical metal–organic frameworks (MOFs) and covalent organic frameworks (COFs) and emerging machine learning techniques for predicting their properties and performances. Finally, we discuss the key methodological challenges on the path toward computation-driven design and reliable prediction of high-performing MOF and COF adsorbents and catalysts and suggest possible solutions and future directions in this exciting field of computational materials science.

Authors: Michelle Ernst, Jack D. Evans, Ganna Gryn'ova

Date Published: 1st Dec 2023

Publication Type: Journal

Wird KI neue Medikamente gegen Herzkrankheiten hervorbringen?
Molecular and Cellular Modeling

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 Entdeckung …enzial 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

Evaluating probabilistic classifiers: The triptych
Computational Statistics

Abstract

Not specified

Authors: Timo Dimitriadis, Tilmann Gneiting, Alexander I. Jordan, Peter Vogel

Date Published: 4th Nov 2023

Publication Type: Journal

High-Throughput Phenotypic Screening and Machine Learning Methods Enabled the Selection of Broad-Spectrum Low-Toxicity Antitrypanosomatidic Agents.
Scientific Databases and Visualisation

Abstract (Expand)

Broad-spectrum anti-infective chemotherapy agents with activity against Trypanosomes, Leishmania, and Mycobacterium tuberculosis species were identified from a high-throughput phenotypic screening … program of the 456 compounds belonging to the Ty-Box, an in-house industry database. Compound characterization using machine learning approaches enabled the identification and synthesis of 44 compounds with broad-spectrum antiparasitic activity and minimal toxicity against Trypanosoma brucei, Leishmania Infantum, and Trypanosoma cruzi. In vitro studies confirmed the predictive models identified in compound 40 which emerged as a new lead, featured by an innovative N-(5-pyrimidinyl)benzenesulfonamide scaffold and promising low micromolar activity against two parasites and low toxicity. Given the volume and complexity of data generated by the diverse high-throughput screening assays performed on the compounds of the Ty-Box library, the chemoinformatic and machine learning tools enabled the selection of compounds eligible for further evaluation of their biological and toxicological activities and aided in the decision-making process toward the design and optimization of the identified lead.

Authors: P. Linciano, A. Quotadamo, R. Luciani, M. Santucci, K. M. Zorn, D. H. Foil, T. R. Lane, A. Cordeiro da Silva, N. Santarem, C. B Moraes, L. Freitas-Junior, U. Wittig, W. Mueller, M. Tonelli, S. Ferrari, A. Venturelli, S. Gul, M. Kuzikov, B. Ellinger, J. Reinshagen, S. Ekins, M. P. Costi

Date Published: 3rd Nov 2023

Publication Type: Journal

Myristoyl's dual role in allosterically regulating and localizing Abl kinase
Molecular Biomechanics

Abstract (Expand)

c-Abl kinase, a key signalling hub in many biological processes ranging from cell development to proliferation, is tightly regulated by two inhibitory Src homology domains. An N-terminal myristoyl-modification … can bind to a hydrophobic pocket in the kinase C-lobe, which stabilizes the auto-inhibitory assembly. Activation is triggered by myristoyl release. We used molecular dynamics simulations to show how both myristoyl and the Src homology domains are required to impose the full inhibitory effect on the kinase domain, and reveal the allosteric transmission pathway at residue-level resolution. Importantly, we find myristoyl insertion into a membrane to thermodynamically compete with binding to c-Abl. Myristoyl thus not only localizes the protein to the cellular membrane, but membrane attachment at the same time enhances activation of c-Abl by stabilizing its pre-activated state. Our data put forward a model in which lipidation tightly couples kinase localization and regulation, a scheme that currently appears to be unique for this non-receptor tyrosine kinase.

Authors: Svenja de Buhr, Frauke Gräter

Date Published: 16th Oct 2023

Publication Type: Journal

Sources of predictability of synoptic‐scale rainfall during the West African summer monsoon
Computational Statistics

Abstract

Not specified

Authors: Athul Rasheeda Satheesh, Peter Knippertz, Andreas H. Fink, Eva-Maria Walz, Tilmann Gneiting

Date Published: 16th Oct 2023

Publication Type: Journal

A community effort in SARS‐CoV‐2 drug discovery
Molecular and Cellular Modeling

Abstract (Expand)

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‐molecule drugs …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: 13th Oct 2023

Publication Type: Journal

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