Open kbea282 opened 3 years ago
Hi Kaitlin,
So great to hear from you! We have a meeting tomorrow (Tuesday 27th April) at 9 PM (Sydney, Australia time) that will be extremely late for you (1am!) so no pressure to join us but I'll add this to the agenda for us to discuss. It is recorded so you can always watch later but we will sum up the discussion here afterwards and get the ball rolling on this.
Also when would the students be starting this work?
Just noting @wwjvdsande suggestion from the Zoom meeting so we don't forget
When the fenarimol library is very large, we have the smaller azole library. It is targeting CYP51 as well (like the fenarimols) may be you can train them using the azoles and repeat with the larger data set of the fenarimols?
As discussed earlier this year, the students in a second year honours-track chemistry course at the University of Auckland spent some time exploring the series 1/2 data in DataWarrior from a modelling perspective (they have exactly no medicinal chemistry training at this point in there degrees).
As an educator, I learned a great deal about how to set this project up for next year so that it connects better with all the other work going on in this project. The students learned a lot about how messy raw data can be (among other things). However, I wanted to share their final posters with anyone who is interested. Keen to chat again next year about how to structure better this so that the outputs are a bit more directly relevant.
CHEM254 Poster - Group A.pdf CHEM254 Poster - Group B.pdf CHEM254 Poster - Group C.pdf CHEM254 Poster - Group D.pdf CHEM254 Poster - Group E.pdf CHEM254 Poster - J.V.pdf
Kia ora e hoa mā,
My name is Kaitlin Beare, and I am an education-focused academic at the University of Auckland and former(reformed?) synthetic organic chemist. I know Alice and Matt from USyd and met Kym recently on a Zoom call. I'd really like to get my second year advanced students involved in some data analysis for this project and have a couple of quick questions about what would be most useful.
Context: I teach a course to 20 advanced second year undergrads on modelling in chemical sciences that's a mixture of practical applications and philosophy of chemistry. For their final project last year, they used DataWarrior to analyse a series of compounds from an in-house research project with the goal of suggesting a handful of structures for future work. They don't have any med-chem training (the very idea of SARs was brand new) but they were more than able to use DW for problem solving and pattern recognition. We were particularly focused on SALI plots and how to use these for data analysis.
This year, we'd love to swap out the data set for the fenarimol analogues so that we can get this year's cohort involved in something bigger. I can see that @fantasy121 is doing some SAR work too (#48) and I don't want to step on any toes - so is there anything particular you recommend we focus on, or should I just let them loose on the data and see what they do with it?
ngā mihi / kind regards Kaitlin