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NMR is a powerful structural tool for studying proteins. Learn how to use multidimensional NMR to identify ligand binding sites and more!
NMR can generate tons of useful data for protein samples. Learn all about NMR and Protein Dimerization in this easy intro.
NMR is a structural tool that plays second fiddle to crystallography. But there’s a cheap, label-free method of investigating protein folding by NMR.
Getting to know your protein’s structure can help uncover deeper insights and inspire new hypotheses. Discover how protein data bank files can help.
Circular dichroism is a type of spectroscopy that can tell you the type and percentage of secondary structure units in a protein sample. Here are 5 handy pointers on best circular dichroism practice to set up your experiment properly.
Circular dichroism is a type of spectroscopy that can tell you the type and percentage of secondary structure units in a protein sample. This article will take you through circular dichroism theory and some of its applications.
Protein crystals are crucial for structure solution via X-ray crystallography but are notoriously hard to grow. We’ve got you covered with 5 clever protein crystallization seeding methods to grow impressive protein crystals.
How do you explain to your friends and family what you have you’ve been working on all this time? Conveying the true wonder and intricacy of your work to the layperson can be tricky. They won’t be familiar with the lingo, and they might not immediately know how to interpret scientific graphs and figures. You…
Negative staining of proteins is a versatile tool for structural biology. The sample preparation protocol is simple: the sample is embedded in a heavy metal stain that gives rise to increased specimen contrast. Thus, negative staining is a very convenient method to assess sample homogeneity, formation of macromolecular complexes, or quality of protein preparation. Conventional…
Predicting how proteins will fold in vivo is a Holy Grail of proteomics and theoretical chemistry. Current hopes are that this can be achieved by designing an in silico platform that can predict protein folding, either de novo (a.k.a. from scratch) or using known proteins as a guide. What would we need to do, why…
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