Article
Chemistry, Physical
Joerg Schaarschmidt, Jie Yuan, Timo Strunk, Ivan Kondov, Sebastiaan P. Huber, Giovanni Pizzi, Leonid Kahle, Felix T. Bolle, Ivano E. Castelli, Tejs Vegge, Felix Hanke, Tilmann Hickel, Jorg Neugebauer, Celso R. C. Rego, Wolfgang Wenzel
Summary: Modeling and simulation of materials have become essential in materials design to select promising materials and provide insights. Multiple simulation tools are often needed to achieve modeling goals, requiring methods and tools for high-throughput simulations and rapid prototyping of new protocols.
ADVANCED ENERGY MATERIALS
(2022)
Article
Biology
Diego del Alamo, Davide Sala, Hassane S. Mchaourab, Jens Meiler
Summary: This article presents an approach to drive AlphaFold2 to sample multiple conformations of membrane proteins and demonstrates that this approach can generate accurate models. The results suggest the need for the next generation of deep learning algorithms to be designed to predict ensembles of biophysically relevant states.
Article
Multidisciplinary Sciences
Jason C. Porta, Bing Han, Alican Gulsevin, Jeong Min Chung, Yelena Peskova, Sarah Connolly, Hassane S. Mchaourab, Jens Meiler, Erkan Karakas, Anne K. Kenworthy, Melanie D. Ohi
Summary: This study reveals the structural characteristics of the human caveolin-1 complex using cryo-electron microscopy, providing new insights into its membrane remodeling activity and uncovering the roles of key regions of caveolin-1 in its function.
Article
Materials Science, Multidisciplinary
Celso R. C. Rego, Jorg Schaarschmidt, Tobias Schloeder, Montserrat Penaloza-Amion, Saientan Bag, Tobias Neumann, Timo Strunk, Wolfgang Wenzel
Summary: Establishing a fundamental understanding of materials through computational simulation approaches requires knowledge from diverse fields. However, traditional patch-work solutions often lack scalability, reproducibility, and flexibility. Therefore, this study presents the SimStack workflow framework, which simplifies workflow setup and allows users to combine cutting-edge models into custom-tailored, scalable simulation solutions.
FRONTIERS IN MATERIALS
(2022)
Article
Biochemistry & Molecular Biology
Francis J. Roushar, Andrew G. McKee, Charles P. Kuntz, Joseph T. Ortega, Wesley D. Penn, Hope Woods, Laura M. Chamness, Victoria Most, Jens Meiler, Beata Jastrzebska, Jonathan P. Schlebach
Summary: The study conducted deep mutational scanning to compare the plasma membrane expression of 123 known pathogenic rhodopsin variants, identifying 69 retinopathy variants with diminished expression and an increase in expression in the presence of 9-cis-retinal. The response to retinal varied considerably across the mutations spectrum, suggesting underlying differences in stability. Evaluation also showed that some variants compromised binding, but two of the previously uncharacterized variants retained residual function in vitro.
JOURNAL OF BIOLOGICAL CHEMISTRY
(2022)
Article
Biochemistry & Molecular Biology
Davide Sala, Diego del Alamo, Hassane S. Mchaourab, Jens Meiler
Summary: Conformational changes are crucial for the functional cycles of proteins, and their study often requires an integrative approach. In this study, a new method called ConfChangeMover (CCM) was introduced and tested for modeling protein conformational changes using sparse experimental data. CCM outperformed state-of-the-art methods in two benchmarks, demonstrating its ability to model diverse conformational changes. Moreover, the integration of CCM with other experimental data using the Rosetta framework further expands its capability.
Article
Biochemistry & Molecular Biology
Marcus Nagel, Rocco Moretti, Ralf Paschke, Martin von Bergen, Jens Meiler, Stefan Kalkhof
Summary: This study reveals the role of the hinge region in hormone binding and signal transduction of the follicle-stimulating hormone receptor through experimentally driven full-length models. Important information such as the interface, side-chain interactions, and activation mechanism is obtained by molecular modeling and chemical crosslinking.
Editorial Material
Radiology, Nuclear Medicine & Medical Imaging
Anke Werner, Martin Freesmeyer, Claudia Bensch, Markus Eszlinger, Philipp Seifert
Summary: A 66-year-old woman had an incidental finding of a bilateral papillary thyroid microcarcinoma after thyroidectomy. A Warthin-like variant was observed on the right side. Further imaging tests revealed iodine and glucose uptake within a hypoechoic lesion in the right parotid gland. Surgical excision confirmed a Warthin tumor ipsilateral to the Warthin-like variant of the papillary thyroid microcarcinoma. Targeted minimal-invasive surgery was possible due to extensive imaging.
CLINICAL NUCLEAR MEDICINE
(2023)
Article
Multidisciplinary Sciences
Nathaniel Bloodworth, Natalia Ruggeri Barbaro, Rocco Moretti, David G. Harrison, Jens Meiler
Summary: Computation methods for predicting peptide-MHC-I binding are important for accelerating vaccine and drug development. However, most available tools are optimized for peptides containing standard amino acids and lack the ability to predict binding of peptides with non-canonical amino acids or post-translational modifications. The Rosetta FlexPepDock ab-initio protocol is a structure-based computational method that can accurately model MHC-I bound epitopes containing non-canonical amino acids, providing valuable insights into immunologic responses.
Article
Biochemical Research Methods
Marion F. S. Fischer, James E. Crowe, Jens Meiler
Summary: Antibody epitope mapping is crucial for understanding the immune system's protection mechanisms. A novel method called AxIEM improves the accuracy of predicting antibody epitopes and provides structural insights for vaccine development.
PLOS COMPUTATIONAL BIOLOGY
(2022)
Article
Biochemistry & Molecular Biology
Hope Woods, Dominic L. Schiano, Jonathan I. Aguirre, Kaitlyn V. Ledwitch, Eli F. McDonald, Markus Voehler, Jens Meiler, Clara T. Schoeder
Summary: This study investigates the impact of in-frame deletion mutations on protein structure and function, and proposes a computational method using AlphaFold2 and RosettaRelax for prediction and classification of deletion mutants. The results demonstrate the effectiveness of this method, especially when using a metric combining pLDDT values and Rosetta DDG for classifying tolerated deletion mutations.
Article
Biochemical Research Methods
Brennica Marlow, Georg Kuenze, Jens Meiler, Julia Koehler Leman
Summary: Lipid molecules, such as cholesterol, interact with integral membrane proteins (IMP) in a different way compared to drug-like molecules. The RosettaCholesterol protocol, developed in this study, improves the sampling and scoring of native poses of protein-cholesterol complexes. It also quantifies the specificity of cholesterol binding sites, providing a basis for further experimental validation and modeling.
PLOS COMPUTATIONAL BIOLOGY
(2023)
Article
Oncology
Arnaldo Marin, Abdullah Al Mamun, Hima Patel, Hiroaki Akamatsu, Dan Ye, Dhivya R. Sudhan, Lisa Eli, Katherine Marcelain, Benjamin P. Brown, Jens Meiler, Carlos L. Arteaga, Ariella B. Hanker
Summary: This study reveals the driver function of acquired HER2 mutations in resistance to HER2 tyrosine kinase inhibitors, and provides a potential treatment strategy to overcome this resistance.
Article
Biochemistry & Molecular Biology
Hannes Junker, Jens Meiler, Clara T. Schoeder
Summary: Recent studies have shown that G protein-coupled receptors (GPCRs) can adopt various conformations that coexist in equilibrium, with the apo state possessing high entropy. The formation of a ligand-GPCR-transducer complex comes at the cost of reduced conformational space and increased entropy. This study suggests that the conservation of binding partners, their affinity, and the rigidity of binding sites are important factors in balancing the energetic cost of intra- and extracellular binding events in GPCR signal transduction.
CURRENT OPINION IN STRUCTURAL BIOLOGY
(2023)
Article
Biochemistry & Molecular Biology
D. Sala, F. Engelberger, H. S. Mchaourab, J. Meiler
Summary: Many proteins switch among different structures to exert their function, and understanding these conformational ensembles is crucial for unraveling key mechanistic aspects of protein function. Experimental determination of these structures is limited by cost, time, and technical challenges, but the machine-learning technology AlphaFold has shown promising accuracy in predicting the three-dimensional structure of monomeric proteins. However, AlphaFold typically represents a single conformational state with minimal structural heterogeneity, leading to the development of pipelines to expand the diversity or bias the prediction towards desired conformational states. In this study, we analyze the functionality, limitations, and future directions of these pipelines.
CURRENT OPINION IN STRUCTURAL BIOLOGY
(2023)