The Infona portal uses cookies, i.e. strings of text saved by a browser on the user's device. The portal can access those files and use them to remember the user's data, such as their chosen settings (screen view, interface language, etc.), or their login data. By using the Infona portal the user accepts automatic saving and using this information for portal operation purposes. More information on the subject can be found in the Privacy Policy and Terms of Service. By closing this window the user confirms that they have read the information on cookie usage, and they accept the privacy policy and the way cookies are used by the portal. You can change the cookie settings in your browser.
In‐cell NMR spectroscopy is an effective tool for observing proteins at atomic resolution in their native cellular environment. However, its utility is limited by its low sensitivity and the extensive line broadening caused by nonspecific interactions in the cells, which is even more pronounced in human cells due to the difficulty of overexpressing or delivering high concentrations of isotopically...
In‐cell NMR spectroscopy is an effective tool for observing proteins at atomic resolution in their native cellular environment. However, its utility is limited by its low sensitivity and the extensive line broadening caused by nonspecific interactions in the cells, which is even more pronounced in human cells due to the difficulty of overexpressing or delivering high concentrations of isotopically...
As rapidly increasing number of sequenced genomes, the methods for predicting protein-protein interactions (PPIs) from one organism to another is becoming important. Best-match and generalized interolog mapping methods have been proposed for predicting (PPIs). However, best-match mapping method suffers from low coverage of the total interactome, because of using only best matches. Generalized interolog...
Prediction of protein-ligand binding affinities is an important issue in molecular recognition and virtual screening. We have developed a scoring function, namely GemAffinity, to predict binding affinities by analyzing 88 descriptors derived from 891 protein-ligand structures selected from the protein data bank (PDB). Based on these 88 descriptors, we derived GemAffinity using a stepwise regression...
The prediction of the binding affinity of protein- ligand complexes is important for the molecular docking and rational drug discovery. In this study, we have analyzed the descriptors, which affect the binding affinities of protein-ligand complexes, from five dimensions, including protein-ligand interactions, protein properties, structural and physicochemical descriptors of ligands, metal-ligand bonding,...
Set the date range to filter the displayed results. You can set a starting date, ending date or both. You can enter the dates manually or choose them from the calendar.