Methyl-TROSY spectroscopy has extended the reach of solution-state NMR to supra-molecular machineries over 100 kDa in size. Methyl groups are ideal probes for studying structure, dynamics, and protein-protein interactions in quasi-physiological conditions with atomic resolution. Successful implementation of the methodology requires accurate methyl chemical shift assignment, and the task still poses a significant challenge in the field. In this work, we outline the current state of technology for methyl labeling, data collection, data analysis, and nuclear Overhauser effect (NOE)-based automated methyl assignment approaches. We present MAGIC-Act and MAGIC-View, two Python extensions developed as part of the popular NMRFAM-Sparky package, and MAGIC-Net a standalone structure-based network analysis program. MAGIC-Act conducts statistically driven amino acid typing, Leu/Val pairing guided by 3D HMBC-HMQC, and NOESY cross-peak symmetry checking. MAGIC-Net provides model-based NOE statistics to aid in selection of a methyl labeling scheme. The programs provide a versatile, semi-automated framework for rapid methyl assignment.
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http://dx.doi.org/10.1016/j.str.2021.11.009 | DOI Listing |
Cell Genom
December 2024
Department of Molecular & Medical Genetics, Oregon Health & Science University, Portland, OR, USA; Cancer Early Detection Advanced Research Institute, Oregon Health & Science University, Portland, OR, USA; Knight Cardiovascular Institute, Oregon Health & Science University, Portland, OR, USA; Knight Cancer Institute, Oregon Health & Science University, Portland, OR, USA. Electronic address:
Single-cell methods to assess DNA methylation have not achieved the same level of cell throughput per experiment compared to other modalities, with large-scale datasets requiring extensive automation, time, and other resources. Here, we describe sciMETv3, a combinatorial indexing-based technique that enables atlas-scale libraries to be produced in a single experiment. To reduce the sequencing burden, we demonstrate the compatibility of sciMETv3 with capture techniques to enrich regulatory regions, as well as the ability to leverage enzymatic conversion, which can yield higher library diversity.
View Article and Find Full Text PDFOphthalmology
December 2024
John P. Hussman Institute for Human Genomics, University of Miami, FL; Dr. John T. Macdonald Foundation Department of Human Genetics, University of Miami, FL.
Purpose: To investigate the association between epigenetic age acceleration and glaucoma progression.
Design: Retrospective cohort study.
Participants: 100 primary open-angle glaucoma (POAG) patients with fast progression and 100 POAG patients with slow progression.
J Chem Phys
December 2024
Department of Chemistry, University of Chicago, Chicago, Illinois 60637, USA.
Peptoids (N-substituted glycines) are a class of sequence-defined synthetic peptidomimetic polymers with applications including drug delivery, catalysis, and biomimicry. Classical molecular simulations have been used to predict and understand the conformational dynamics of single chains and their self-assembly into morphologies including sheets, tubes, spheres, and fibrils. The CGenFF-NTOID model based on the CHARMM General Force Field has demonstrated success in accurate all-atom molecular modeling of peptoid structure and thermodynamics.
View Article and Find Full Text PDFArXiv
December 2024
Medical Artificial Intelligence and Automation (MAIA) Lab, Department of Radiation Oncology, University of Texas Southwestern Medical Center, Dallas, TX, 75235, USA.
Purpose: A reliable and comprehensive cancer prognosis model for clear cell renal cell carcinoma (ccRCC) could better assist in personalizing treatment. In this work, we developed a multi-modal ensemble model (MMEM) which integrates pretreatment clinical information, multi-omics data, and histopathology whole slide image (WSI) data to learn complementary information to predict overall survival (OS) and disease-free survival (DFS) for patients with ccRCC.
Methods And Materials: We collected 226 patients from The Cancer Genome Atlas Kidney Renal Clear Cell Carcinoma dataset (TCGA-KIRC).
J Pathol
December 2024
Department of Pathology and Molecular Pathology, University Hospital and University of Zurich, Zurich, Switzerland.
Tumour content plays a pivotal role in directing the bioinformatic analysis of molecular profiles such as copy number variation (CNV). In clinical application, tumour purity estimation (TPE) is achieved either through visual pathological review [conventional pathology (CP)] or the deconvolution of molecular data. While CP provides a direct measurement, it demonstrates modest reproducibility and lacks standardisation.
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