Many peptide hormones form an α-helix on binding their receptors, and sensitive methods for their detection could contribute to better clinical management of disease. De novo protein design can now generate binders with high affinity and specificity ...
Current opinion in structural biology
Dec 14, 2023
Characterizing structural and dynamic properties of proteins and large macromolecular assemblies is crucial to understand the molecular mechanisms underlying biological functions. In the field of structural biology, no single method comprehensively r...
Proteins can spontaneously tie a variety of intricate topological knots through twisting and threading of the polypeptide chains. Recently developed artificial intelligence algorithms have predicted several new classes of topological knotted proteins...
Three-dimensional structure modeling from maps is an indispensable step for studying proteins and their complexes with cryogenic electron microscopy. Although the resolution of determined cryogenic electron microscopy maps has generally improved, the...
BACKGROUND: Recently, significant progress has been made in the field of protein structure prediction by the application of artificial intelligence techniques, as shown by the results of the CASP13 and CASP14 (Critical Assessment of Structure Predict...
Acta crystallographica. Section D, Structural biology
Nov 3, 2023
Model building and refinement, and the validation of their correctness, are very effective and reliable at local resolutions better than about 2.5 Å for both crystallography and cryo-EM. However, at local resolutions worse than 2.5 Å both the procedu...
Journal of chemical information and modeling
Oct 26, 2023
Small-molecule conformer generation (SMCG) is an extremely important task in both ligand- and structure-based computer-aided drug design, especially during the hit discovery phase. Recently, a multitude of artificial intelligence (AI) models tailored...
Proteins are molecular machinery that participate in virtually all essential biological functions within the cell, which are tightly related to their 3D structure. The importance of understanding protein structure-function relationship is highlighted...
Molecular representation learning plays an important role in molecular property prediction. Existing molecular property prediction models rely on the de facto standard of covalent-bond-based molecular graphs for representing molecular topology at the...
DNA and RNA play fundamental roles in various cellular processes, where their three-dimensional structures provide information critical to understanding the molecular mechanisms of their functions. Although an increasing number of nucleic acid struct...