01 Crystallization | Lecture Series "Basics of Macromolecular Crystallography"

Questions are down in the description
In the first lecture in the lecture Series "Basics of Macromolecular Crystallography", Andrea Thorn gives an overview of protein crystallization, some of its theoretical foundation and lots of practical advice on how (and how not) to crystallize your protein.
The lecture was held on the 9th of June 2020 via Zoom and attended by 40 participants from different institutions/countries.
Questions:
Q: "How can I make my cat surrender whiskers?"
A: "They loose them from time to time. (About one per week). Cut the whiskers in pieces before mounting them with glue in a pipet tip to make the most of them. Wash with Acetone before mounting to remove fat and dirt."
Q: "I would be interested to know, how do you ‘check the unit cell’ (when you are checking if the protein structure is correct)?"
A: "After you've measured the dataset. you can already determine the unit cell by the distance of the spots on the detector image. The unit cell edge length is reciprocal to the distance between spots in reciprocal space (hence the name). You also may have an idea fwhat the symmetry is, and as the point symmetry of the crystal is the symmetry of the reflections in reciprocal space, plus an additional centrosymmetry. Then, the average amino-acid takes up 120 cubic Angstroem, so if you know the sequence, you can calculate the volume of the protein expected, and compare it to the asymmetric unit's volume."
Q: "From the discussion of nucleation, would you expect that you can predictably form microcrystals by increasing precipitant concentration slightly from one that produces large crystals?"
A: "While this would be nice, getting small crystals on purpose can be as tedious as getting larger ones."
Q: "About crystallization conditions: Are there any softwares that have tried to predict the conditions that work? Or is there any database from all the screens that have been done with the respective conditions?"
A: "Yes, there is actually quite a lot of work on this. As I said crystallization is a bottleneck, many people have worked on this and there is software that can help you predict, even with machine learning."

[@Sarah-hc6kj]

This is a remarkable lecture! I’m just stating in a crystallography lab and appreciate this series greatly!

[@AlohaMoloha]

What a great help for a new crystallographer. Thank you all!

[@surajitgandhi10]

Excellent !

[@cicisdaily7311]

Really helpful!!

[@nidhinfrancis3140]

Excellent introduction to 'Protein Crystallography'

[@muhammadafsal9928]

Gud