Journal of the American Chemical Society
Oct 22, 2025
Fragment-Based Drug Discovery (FBDD) is a powerful strategy used in the development of new therapeutics. Molecular fragments are screened against a target protein, where interactions are typically characterized by a low affinity. Nuclear Magnetic Res...
High-dimensional nuclear magnetic resonance (NMR) spectroscopy can assist in determining protein structure, but it requires time-consuming acquisition. Deep learning enables ultrafast reconstruction but is limited to spectra of up to three dimensions...
Accurate dynamic protein structures are essential for drug design. NMR experiments can detect protein structures and potential dynamics, but the spectrum assignment and structure determination requires expertise and is time-consuming, while deep-lear...
Chemphyschem : a European journal of chemical physics and physical chemistry
May 7, 2025
DNA G-quadruplexes are known to play myriad functional roles in the cellular context and their structural diversity has diverse applications in various fields of science. Solution-state NMR spectroscopy has been instrumental in characterization of DN...
Journal of chemical theory and computation
Apr 10, 2025
This work introduces LEGOLAS, a fully open source TorchANI-based neural network model designed to predict NMR chemical shifts for protein backbone atoms (N, Cα, Cβ, C', HN, Hα). LEGOLAS has been designed to be fast without loss of accuracy, as our mo...
Nuclear magnetic resonance (NMR) spectroscopy is an important technique for deriving the dynamics and interactions of macromolecules; however, characterizations of aromatic residues in proteins still pose a challenge. Here, we present a deep neural n...
Solid-state NMR (ssNMR) methods have continued to be developed in recent years for the efficient assignment of signals and 3D structure modeling of biomacromolecules. Consequently, we are approaching an era in which vigorous applications of these met...
Biomolecular dynamics simulation is a fundamental technology for life sciences research, and its usefulness depends on its accuracy and efficiency. Classical molecular dynamics simulation is fast but lacks chemical accuracy. Quantum chemistry methods...
Artificial intelligence (AI) models are revolutionising scientific data analysis but are reliant on large training data sets. While artificial training data can be used in the context of NMR processing and data analysis methods, relating NMR paramete...
International journal of molecular sciences
Sep 8, 2024
Protein dynamics play a crucial role in biological function, encompassing motions ranging from atomic vibrations to large-scale conformational changes. Recent advancements in experimental techniques, computational methods, and artificial intelligence...
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