MOTIVATION Identifying protein enzymatic or pharmacological activities are important areas of research in biology and chemistry. Biological and chemical databases are increasingly being populated with linkages between protein sequences and chemical structures. There is now sufficient information to apply machine-learning techniques to predict interactions between chemicals and proteins at a gen...

in this study, chemical composition and functional properties of red bean, chickpea, lentil and canellini bean were evaluated. our results revealed that chickpea had the highest protein (43.4%) and fat (5.17%) content and lentil, red bean and canellini bean were the following ones. the isoelectric point of all the samples were determined as about ph=4 but other than lentil, the remaining sample...

The sensitivity of (129)Xe chemical shifts to weak nonspecific xenon-protein interactions has suggested the use of xenon to probe biomolecular structure and interactions. The realization of this potential necessitates a further understanding of how different macromolecular properties influence the (129)Xe chemical shift in aqueous solution. Toward this goal, we have acquired (129)Xe NMR spectra...

Biomimetic nanoparticles are known to serve as nanoscale adjuvants, enzyme mimics and amyloid fibrillation inhibitors. Their further development requires better understanding of their interactions with proteins. The abundant knowledge about protein–protein can a guide for designing protein–nanoparticle assemblies, but the chemical biological inputs used in computational packages not applicable ...

Analysis of protein-ligand complexes and recognition of spatially conserved physico-chemical properties is important for the prediction of binding and function. Here, we present two webservers for multiple alignment and recognition of binding patterns shared by a set of protein structures. The first webserver, MultiBind (http://bioinfo3d.cs.tau.ac.il/MultiBind), performs multiple alignment of p...

STITCH is a database of protein-chemical interactions that integrates many sources of experimental and manually curated evidence with text-mining information and interaction predictions. Available at http://stitch.embl.de, the resulting interaction network includes 390 000 chemicals and 3.6 million proteins from 1133 organisms. Compared with the previous version, the number of high-confidence p...