Review
Cell Biology
Elisa Uliassi, Lea Nikolic, Maria Laura Bolognesi, Giuseppe Legname
Summary: This article reviews the major advances in prion drug discovery, including the identification of anti-prion small molecules through screening methods, as well as the discovery of novel compounds with expanded anti-prion profiles through multi-target-directed ligand (MTDLs) strategies and theranostics.
CELL AND TISSUE RESEARCH
(2023)
Review
Chemistry, Multidisciplinary
Antonio Shegani, Steven Kealey, Federico Luzi, Filippo Basagni, Joana do Mar Machado, Sevban Dogan Ekici, Alessandra Ferocino, Antony D. Gee, Salvatore Bongarzone
Summary: The presence of PET centers at major hospitals and the improvement of PET scanner sensitivity have increased interest in PET tracer development using carbon-11. Methodological improvements and automated modules have allowed the development of carbon-11 tracers for clinical use. Radiolabeling natural compounds with carbon-11 has provided important information on their biochemistry and in vivo behavior.
Article
Chemistry, Medicinal
Matteo Staderini, Silvia Vanni, Arianna Colini Baldeschi, Gabriele Giachin, Marco Zattoni, Luigi Celauro, Chiara Ferracin, Edoardo Bistaffa, Fabio Moda, Daniel Perez, Ana Martinez, M. Antonia Martin, Olmo Martin-Camara, Angel Cores, Giulia Bianchini, Robert Kammerer, J. Carlos Menendez, Giuseppe Legname, Maria Laura Bolognesi
Summary: This study designed novel carbazole derivatives as pharmacological chaperones for prion diseases. These derivatives showed anti-prion activity and could detect prion protein aggregates through fluorescent staining. The compounds exhibited activity against RML-infected cell lines and have potential applications in the treatment of prion diseases.
EUROPEAN JOURNAL OF MEDICINAL CHEMISTRY
(2023)
Article
Chemistry, Medicinal
Bharath Raghavan, Mirko Paulikat, Katya Ahmad, Lara Callea, Andrea Rizzi, Emiliano Ippoliti, Davide Mandelli, Laura Bonati, Marco De Vivo, Paolo Carloni
Summary: Currently, in silico drug design in the initial stages of drug discovery can benefit from first-principle Quantum Mechanics/Molecular Mechanics (QM/MM) molecular dynamics (MD) simulations in explicit solvent, but many applications are limited by the short time scales that this approach can cover. The development of scalable first principle QM/MM MD interfaces that fully exploit current exascale machines is crucial in overcoming this problem and allowing for the study of ligand binding to protein with first principle accuracy. This study showcases the use of the Multiscale Modeling in Computational Chemistry (MiMiC) QM/MM framework, which demonstrates strong scaling and parallel efficiency of >70% up to >80,000 cores, making it a promising candidate for exascale applications.
JOURNAL OF CHEMICAL INFORMATION AND MODELING
(2023)
Article
Chemistry, Medicinal
Bharath Raghavan, Florian K. Schackert, Andrea Levy, Sophia K. Johnson, Emiliano Ippoliti, Davide Mandelli, Jogvan Magnus Haugaard Olsen, Ursula Rothlisberger, Paolo Carloni
Summary: MiMiC is a flexible and scalable multiscale modeling framework that combines quantum mechanics (QM) and molecular mechanics (MM) codes. The paragraph introduces MiMiCPy, a user-friendly tool written in Python 3 that automates the preparation of MiMiC input files. It also highlights the modular structure of MiMiCPy, allowing for easy extensions to new program formats.
JOURNAL OF CHEMICAL INFORMATION AND MODELING
(2023)
Article
Chemistry, Medicinal
Florian Karl Schackert, Johann Biedermann, Saeid Abdolvand, Sonja Minniberger, Chen Song, Andrew J. R. Plested, Paolo Carloni, Han Sun
Summary: This study investigates calcium conduction in calcium-permeable AMPAR using Molecular Dynamics (MD) simulations and multiscale Quantum Mechanics/Molecular Mechanics (QM/MM) simulations. The results explain the distinct calcium permeability in different RNA-edited forms of GluA2 and provide unprecedented insights into Ca(2+) permeation mechanisms in AMPARs.
JOURNAL OF CHEMICAL INFORMATION AND MODELING
(2023)
Article
Chemistry, Physical
S. Decherchi, G. Ciccotti, A. Cavalli
Summary: We address the problem of estimating free energy from the perspectives of regularization and Bayes estimation theory. By utilizing prior knowledge of the free energy, we reformulate the Bennett acceptance ratio method and present a numerical algorithm to solve it. Additionally, we provide a closed formula to estimate confidence in the prior. Finally, the derived estimators are tested on a toy model.
JOURNAL OF CHEMICAL PHYSICS
(2023)
Article
Chemistry, Physical
Riccardo Aguti, Mattia Bernetti, Stefano Bosio, Sergio Decherchi, Andrea Cavalli
Summary: Allostery is a crucial feature of biomolecular systems, impacting their functioning through intricate interplays between residues and protein structures. Computational approaches for correlation estimation provide insights into these complexes but can lead to different conclusions and outcomes. This article compares three computational methods on pharmaceutical targets, revealing consensus in some aspects but also highlighting the importance of different notions in identifying specific pockets and communications.
JOURNAL OF CHEMICAL PHYSICS
(2023)
Article
Chemistry, Physical
S. Decherchi, A. Cavalli
Summary: Optimal transport theory is a growing field of mathematics with numerous applications. In this work, we utilize optimal transport for computational free energy estimation and demonstrate its effectiveness in optimizing barriers of alchemical transformations through analytical and simulation-based approaches.
JOURNAL OF PHYSICAL CHEMISTRY LETTERS
(2023)
Article
Chemistry, Medicinal
Lais Flavia Nunes Lemes, George E. Magoulas, Andressa Souza de Oliveira, Emile Barrias, Luciana de Camargo Nascente, Renato Granado, Sara Teixeira de Macedo Silva, Nikos Assimomytis, Wanderley de Souza, Maria Laura Bolognesi, Luiz Antonio Soares Romeiro, Theodora Calogeropoulou
Summary: Synthetic ether phospholipid analogues derived from cashew nut shell liquid exhibited potent antiparasitic activity against Trypanosoma cruzi, the causative agent of Chagas disease. Two compounds (16 and 17) showed higher selectivity indices against different developmental stages of T. cruzi compared to the current drug benznidazole. This study suggests that these analogues derived from inexpensive agro-waste materials have the potential to be developed as new treatments for Chagas disease.
ACS INFECTIOUS DISEASES
(2023)
Article
Biochemistry & Molecular Biology
Benjamin Philipp Joseph, Verena Weber, Lisa Knuepfer, Alejandro Giorgetti, Mercedes Alfonso-Prieto, Sybille Krauss, Paolo Carloni, Giulia Rossetti
Summary: In this study, novel HuR inhibitors were identified using a combination of chemoinformatic methods, high-throughput virtual screening, and RNA-protein pulldown assays. The 4-(2-(2,4,6-trioxotetrahydropyrimidin-5(2H)-ylidene)hydrazineyl)benzoate ligand showed dose-dependent inhibition of HuR binding. This novel chemical scaffold provides a new avenue for the design of pharmaceutical agents targeting HuR.
INTERNATIONAL JOURNAL OF MOLECULAR SCIENCES
(2023)
Article
Chemistry, Medicinal
Sarmistha Majumdar, Francesco Di Palma, Francesca Spyrakis, Sergio Decherchi, Andrea Cavalli
Summary: Tyrosine kinases play critical roles in cellular machinery, and dysregulation of their active or inactive forms is associated with diseases like cancer. This study aimed to comprehensively understand the flexibility-activity relationships of tyrosine kinases, focusing on pockets and fluctuations. By conducting molecular dynamics simulations, pocket and residue fluctuation analysis, and using a complementary machine learning approach, we studied 43 different tyrosine kinases. We found that the inactive forms often exhibit increased flexibility, particularly at the DFG motif level. Notably, using long simulations and a decision tree, we identified a semi-quantitative fluctuation threshold of the DGF+3 residue, beyond which the kinase is more likely to be in the inactive form.
JOURNAL OF CHEMICAL INFORMATION AND MODELING
(2023)
Article
Chemistry, Multidisciplinary
Jonas Gossen, Rui Pedro Ribeiro, Dirk Bier, Bernd Neumaier, Paolo Carloni, Alejandro Giorgetti, Giulia Rossetti
Summary: This study presents an approach that combines structural data with a random forest agonist/antagonist classifier and a signal-transduction kinetic model to identify novel chemotype ligands. As a test case, the approach is applied to identify novel antagonists of the human adenosine transmembrane receptor type 2A, a target against Parkinson's disease and cancer.
Article
Chemistry, Physical
Ke Zuo, Agata Kranjc, Riccardo Capelli, Giulia Rossetti, Rachel Nechushtai, Paolo Carloni
Summary: This study introduces a new drug design approach that combines metadynamics free energy methods and experimental structural information to identify ligand poses on protein surfaces.
PHYSICAL CHEMISTRY CHEMICAL PHYSICS
(2023)
Article
Biochemistry & Molecular Biology
Luigi Celauro, Marco Zattoni, Giuseppe Legname
Summary: Cellular prion protein plays a significant role in neurodegenerative diseases and can be taken up by neighboring cells. The intercellular routing of prion proteins involves the release through vesicles and nanotubes.
RECEPTOR ENDOCYTOSIS AND SIGNALLING IN HEALTH AND DISEASE, PT B
(2023)
