AI-Driven prediction of binding trends of SARS-CoV-2 variants from atomistic simulations
Sign Up to like & getrecommendations! Published in 2022 at "Biophysical Journal"
DOI: 10.1016/j.bpj.2021.11.1211
Abstract: Protein-protein interactions are fundamental for cellular processes underlying functions such as signal transduction, cell regulation, or immune response activation among others. However, in silico characterization at atomistic level of the binding process between two proteins… read more here.
Keywords: driven prediction; two molecules; prediction binding; prediction ... See more keywords
Accurate and Reliable Prediction of the Binding Affinities of Macrocycles to Their Protein Targets.
Sign Up to like & getrecommendations! Published in 2017 at "Journal of chemical theory and computation"
DOI: 10.1021/acs.jctc.7b00885
Abstract: Macrocycles have been emerging as a very important drug class in the past few decades largely due to their expanded chemical diversity benefiting from advances in synthetic methods. Macrocyclization has been recognized as an effective… read more here.
Keywords: binding affinities; drug; accurate reliable; prediction binding ... See more keywords
Prediction of Binding Stability of Pu(IV) and PuO2(VI) by Nitrogen Tridentate Ligands in Aqueous Solution
Sign Up to like & getrecommendations! Published in 2020 at "International Journal of Molecular Sciences"
DOI: 10.3390/ijms21082791
Abstract: Plutonium has potential applications in energy production in well-controlled nuclear reactors. Since nuclear power plants have great merit as environmentally friendly energy sources with a recyclable system, a recycling system for extracting Pu from spent… read more here.
Keywords: tridentate ligands; nitrogen tridentate; tridentate; stability ... See more keywords