Methods in molecular biology (Clifton, N.J.)
38987469
Protein-protein interactions are involved in almost all processes in a living cell and determine the biological functions of proteins. To obtain mechanistic understandings of protein-protein interactions, the tertiary structures of protein complexes ...
The use of artificial intelligence to process diffraction images is challenged by the need to assemble large and precisely designed training data sets. To address this, a codebase called Resonet was developed for synthesizing diffraction data and tra...
Here, a machine-learning method based on a kinetically informed neural network (NN) is introduced. The proposed method is designed to analyze a time series of difference electron-density maps from a time-resolved X-ray crystallographic experiment. Th...
When solving a structure of a protein from single-wavelength anomalous diffraction X-ray data, the initial phases obtained by phasing from an anomalously scattering substructure usually need to be improved by an iterated electron-density modification...
The NLRP3 inflammasome plays a central role in the pathogenesis of various intractable human diseases, making it an urgent target for therapeutic intervention. Here, we report the development of SN3-1, a novel orally potent NLRP3 inhibitor, designed ...
Structure-based virtual screening is a key tool in early drug discovery, with growing interest in the screening of multi-billion chemical compound libraries. However, the success of virtual screening crucially depends on the accuracy of the binding p...
Nucleic acid electron density interpretation after phasing by molecular replacement or other methods remains a difficult problem for computer programs to deal with. Programs tend to rely on time-consuming and computationally exhaustive searches to re...
MOTIVATION: Accurately identifying ligands plays a crucial role in the process of structure-guided drug design. Based on density maps from X-ray diffraction or cryogenic-sample electron microscopy (cryoEM), scientists verify whether small-molecule li...
Protein sequence design in the context of small molecules, nucleotides and metals is critical to enzyme and small-molecule binder and sensor design, but current state-of-the-art deep-learning-based sequence design methods are unable to model nonprote...
Journal of chemical information and modeling
40228012
The development of new materials is a time-consuming and resource-intensive process. Deep learning has emerged as a promising approach to accelerate this process. However, accurately predicting crystal structures using deep learning remains a signifi...