WebHere we provide a deep learning approach (DLKcat) for high-throughput kcat prediction for metabolic enzymes from any organism merely from substrate structures and protein sequences. DLKcat... WebYear. Deep learning based kcat prediction enables improved enzyme constrained model reconstruction. F Li, L Yuan, H Lu, G Li, Y Chen, MKM Engqvist, EJ Kerkhoven, J Nielsen. Nature Catalysis 5, 662–672. , 2024. 39. 2024. AdditiveChem: a comprehensive bioinformatics knowledge-base for food additive chemicals.

Deep learning based kcat prediction enables improved enzyme …

WebNov 23, 2024 · More representative, Feiran proposed deep learning-based k cat prediction solely from substrate structures and protein sequences, which realized high-throughput prediction [10]. However, the model performance needs to ... we propose a pretrained language model-based Kcat prediction approach (PreKcat), which precisely … WebSep 25, 2024 · Deep learning-based kcat prediction enables improved enzyme-constrained model reconstruction. 16 June 2024. Feiran Li, Le Yuan, … Jens Nielsen. datachannel protocol

Deep learning allows genome-scale prediction of Michaelis ... - PLOS

WebSep 5, 2024 · The study Deep learning based kcat prediction enables improved enzyme constrained model reconstruction has been published in Nature Catalysis. The authors are Feiran Li, Le Yuan, Hongzhong Lu, Gang Li, Yu Chen, Martin Engqvist, Eduard Kerkhoven and Jens Nielsen. The researchers are active at Chalmers University of Technology. WebOn the other hand, deep learning method has been applied in chemical space modeling and has shown excellent performance. DLKcat (Deep Learning-based Kcat prediction) using substrate structure and protein sequence as input, has the ability to predict various biological enzyme activities (Kcat) on a large scale. WebDLKcat To compensate for missing Kcat values in the Actinomyces database and to predict the effect of protein mutations on enzyme activity, we introduced a deep learning algorithm to predict the unique Kcat value corresponding to the substrate and protein, combined in ecGEM. GNN Structure of GNN model: marshalls enterprise india private limited