IEEE/ACM transactions on computational biology and bioinformatics
Dec 8, 2022
Drug discovery is one of the major goals of computational biology and bioinformatics. A novel framework has recently been proposed for the design of chemical graphs using both artificial neural networks (ANNs) and mixed integer linear programming (MI...
Journal of chemical information and modeling
Dec 6, 2022
Hematotoxicity has been becoming a serious but overlooked toxicity in drug discovery. However, only a few models have been reported for the prediction of hematotoxicity. In this study, we constructed a high-quality dataset comprising 759 hematotoxic...
Journal of chemical information and modeling
Dec 1, 2022
Machine learning has become a crucial tool in drug discovery and chemistry at large, , to predict molecular properties, such as bioactivity, with high accuracy. However, activity cliffs─pairs of molecules that are highly similar in their structure bu...
Journal of chemical information and modeling
Dec 1, 2022
We report a novel framework for achieving fragment-based molecular design using pixel convolutional neural network (PixelCNN) combined with the simplified molecular input line entry system (SMILES) as molecular representation. While a widely used rec...
Annals of the New York Academy of Sciences
Nov 29, 2022
As the global burden of antibiotic resistance continues to grow, creative approaches to antibiotic discovery are needed to accelerate the development of novel medicines. A rapidly progressing computational revolution-artificial intelligence-offers an...
Journal of chemical information and modeling
Nov 21, 2022
The discovery of new hits through ligand-based virtual screening in drug discovery is essentially a low-data problem, as data acquisition is both difficult and expensive. The requirement for large amounts of training data hinders the application of c...
Scientific reports
Nov 18, 2022
Graph level anomaly detection (GLAD) aims to spot anomalous graphs that structure pattern and feature information are different from most normal graphs in a graph set, which is rarely studied by other researchers but has significant application value...
Computers in biology and medicine
Nov 17, 2022
Effectively predicting protein toxicity plays an essential step in the early stage of protein-based drug discovery, which is of great help to speed up novel drug screening and reduce costs. Recently, several relevant datasets have been designed, and ...
Nature communications
Nov 12, 2022
The retrieval of hit/lead compounds with novel scaffolds during early drug development is an important but challenging task. Various generative models have been proposed to create drug-like molecules. However, the capacity of these generative models ...
Molecular diversity
Nov 11, 2022
Kinase plays a significant role in various disease signaling pathways. Due to the highly conserved sequence of kinase family members, understanding the selectivity profile of kinase inhibitors remains a priority for drug discovery. Previous methods f...