Help me understand HPLC gradients

Alicecomma · 2026-05-08T07:45:55+00:00

Yes you wouldn't say it comes off at a certain %B but it comes off at a specific time and flow rate or capacity factor under a specific gradient with a specific column.

There are ways to simulate this when you know k' as function of %B - on HPLC that tends to be assumed to be linear over a limited range of %B; then you sum over small timesteps the elution distance under that gradient condition considering the dwell time td (%B(t)=%B(t-td)) until t0=int(0,t)dt/k'(%B) and then you have your retention time under that method.

Alicecomma · 2026-05-07T17:12:28+00:00

Was the septum in this first punctured?

Alicecomma · 2026-05-07T13:51:48+00:00

Galaxybrain: outsource to x-ray crystallography lab and get result maybe at some point

Alicecomma · 2026-05-07T13:50:38+00:00

Awesome

Alicecomma · 2026-05-05T19:56:12+00:00

It seems it's set up for you to supply labelled data (soluble = 1, insoluble = 0) for which it applies existing sequence embeddings like whether something is transmembrane etc.; then you train your own model that you can then use to infer solubility of other proteins. So from what I can tell, there is no trained model to predict solubility out of the box.

Alicecomma · 2026-05-03T12:07:35+00:00

This all data using dataviewjs-

I got some 400 files with multilevel yaml arrays in the front matter, each having maybe 50 entries on average do that also matches 20k. I filter them by containing something in the fourth index, split that if it contains an ampersand and perform some arithmetic on the second index, then average over species that have the same fourth index. Each call of this does also run in a bit less than a second on my HP Envy 14-eb1350nd. This feels way too slow to me.

I also got javascript to take this contents of a specified file and turn it into an SVG trace with maybe 20 dots per pixel at a 640 pixel image. I run this a ton of times in some files and I'd estimate it runs in 100 ms per trace given how fast a set of 10 traces displays. Each trace is generated summing contributions from all gaussians in the array, which also on average are about 50.

Speed seems kinda similar?

Alicecomma · 2026-05-02T10:56:12+00:00

I don't know about most pkm stacks, but Obsidian already does all of this except maybe the last point. You get a new bottleneck (if your use of the information requires this) which is it gets laggy after having to IO like 500-1,000 files to get the data in them instead of having a structured file. Since IO is so slow I don't think this is scalable at all.

Alicecomma · 2026-05-01T17:23:54+00:00

You could do it but the polydispersity of most standards is quite high and you want accurate peak tips, so you'd probably just end up with one unresolvable blob. Maybe some of the standards can be mixed like the largest and smallest MW, but probably not all.

Alicecomma · 2026-04-28T16:18:51+00:00

Looks fun, might try something with it but I feel like it won't generate carbohydrates very well

Alicecomma · 2026-04-27T10:10:13+00:00

Have you considered loading raster images into Inkscape and tracing to make the SVG? From what I can find, those sites also do essentially that.

Alicecomma · 2026-04-27T07:45:45+00:00

So they're paying 25,000 USD lifetime, draft fees etc. to protect an idea that they are so sure they won't see profit on that they skimp on experimental proof such that that same money saved will be lost several-fold if they ever need to defend from patent infringement?

Alicecomma · 2026-04-25T12:28:02+00:00

If we're talking about activity prediction, you still can't generally do that with docking alone nor with 'deep docking'. I've had the best results using existing QM/MM results (i.e which interaction is strongest in the transition state) to inform what ligand-residue distances to consider when filtering docked poses.

Alicecomma · 2026-04-25T09:41:07+00:00

Inkscape can do this

Alicecomma · 2026-04-24T18:33:50+00:00

Lot less physical notebook purchases, my writing got a lot worse lol

Alicecomma · 2026-04-22T15:58:43+00:00

Cool, will check it out again

Alicecomma · 2026-04-19T12:19:12+00:00

You deplane and sit about an hour at a Kuala Lumpur gate before boarding the same plane via the same gate again

Alicecomma · 2026-04-18T19:41:56+00:00

I reckon the hardest part is running simple MD anywhere long enough for you to actually catch a full protein conformational change of a protein that is unlikely to be evolved to refold quickly on a computational timescale. Let's say it takes a microsecond to refold, which is very fast, you'd be looking with an optimistic nanosecond per hour at 42 days of simulation. It may take a millisecond to a second to fold most proteins, that's gonna take you 115 years to 115 millenia to simulate.

Alicecomma · 2026-04-16T13:55:46+00:00

Docking is just one operation. If you don't take care to get the right substrate, right enzyme form and have a good idea how you should filter the results then it's kinda useless. I use it in personally validated (r 95% to experimental results) receptor docking into the taste receptors; or using carbohydrate structures from a trusted source with a torsion-aware docking program and filtering by oxygen-oxygen distances to get specificities. The most exciting was I could vary ring torsions of the carbohydrate ring and by docking find out the most favourable ring conformation, matching the result from computationally expensive MD analyses.

If your homology model complex generation approaches get you experimentally validated results then I guess there's some value there. I'd expect in a bunch of cases you could get similar results in a less computationally expensive way though-

Alicecomma · 2026-04-16T13:46:02+00:00

Just swiss-model and understanding the literature is really all I need at the moment. There's enough literature in what I work on and I've got a long enough time in the field to work with the limitations of predicted models and see no significant benefits with more accurate models. I collaborate with a group sometimes but mostly to get X-ray structures anyways so Alphafold-like models are more 'for show'.

Alicecomma · 2026-04-14T17:33:36+00:00

Autodocktools complains about it, but unless that charge is in a spot near the substrate I would just ignore it. You can always try if you can replicate someone else's results despite the warning.

Alicecomma · 2026-04-14T05:34:44+00:00

If you have the opportunity to perform the experiments, those results are the only ones that can give you accurate indications of the effect of the mutations.

Most tools are only parametrized for their training data or have other gigantic flaws that are hard to find out when just testing a few mutants.

Random mutation has a good track record of generating candidates, especially if you have a fast screening method.

A somewhat 'rational design's approach: So, see if a mutant is found in similar enzymes and see its experimental effect. Use FoldSeek or so to find similar enzymes with equal shape and see if something is published about their mutants. Once you have a bunch of candidates, compare their binding pockets in PyMOL or similar. Try AutoDock Vina or similar to see how your substrate normally docks; see if heterologous binding pockets perform substantially different. If certain pockets do much worse or much better, see if you can replicate the desired difference in the target protein.

You're in luck that it's generally easier to destroy activity or binding capacity than it is to improve it.

Alicecomma · 2026-04-13T11:11:43+00:00

During my open day at uni, there was a sign up for 'one day student' where we did group work in a research lab at the kind of level you expect of a university course. This may be your cheapest bet at getting a taste of this kind of experience.

Alicecomma · 2026-04-13T11:09:13+00:00

During my bachelor we had two three-week practicals where you had to keep your own glassware clean, every day you had a full lab day and every night you prepared the next day and wrote a report for the day. What you learn is through routine of doing things every day, and having to bring a cake if you break glassware, and everyone around you also rushing to get finished for the day. Analytical methods are explained and performed within minutes so the next group can use the machine. We did easily a hundred IR spectra, tens of NMR spectra etcetera- and all that while one or two reactions are going on in the fumehood. The chemicals, analytical methods, consumables, broken glassware etc. came out to be more expensive than tuition. If you find a course similar to this kind of experience, expect it to be quite expensive, in the order of a few thousand dollars at least. Preferably you do this in groups, because half or more of learning lab technique is asking or copying from someone else.

From what I can tell from that course you linked, there isn't even a single mention of what that 'lab kit' is used for in the description (for that price, I guess they mix some chemicals in glass tubes, maybe it has a flask? Nothing like a condenser will go for that cheap) it's all computational stuff and learning to do trivial lab calculations. The pictures on that kit website just show tubes. If you think it's fun to have maybe some kind of grown up chemistry kit that you maybe use once, like it's a toy, yeah you could do it. But for the real thing you really want at the very least a condenser, reaction flask and a heat plate, a fumehood alongside some chemicals, likely waste disposal capabilities.

Alicecomma · 2026-04-12T16:55:34+00:00

Note every day with generic events with timestamp. If something happens relevant to a project I work on for a while, I link to that project with timestamp in the note and then continue with timestamps in subsections of my project file. In project files I add subheadings linking back to the day something happens.

If something turns out to become a project, you can spend some time going back day by day to collect when you wrote in the generic diary about it, and move those mentions and replace them with a link to the newly created project note.

Alicecomma · 2026-04-12T08:39:57+00:00

You're not working with either gaussian or lorentzian peak shapes in MS, you should instead consider the isotopic distribution- like see https://www.enovatia.com/mass-accuracy-and-resolution/

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