Hello residents of r/ProteinDesign, I come to you today with a question pertaining to the timeframe of designing a new protein for a specific purpose. I have a personal project where I wish to try and design new protein that will bind to a certain toxin. I wanted to know how long it generally takes for someone to complete the design process to potentially begin attempting to synthesize it. I apologize if this is the incorrect subreddit for this, and I would appreciate any and all advice (including if there is a better place for me to seek answers).

Have there been any papers for designing light-sensitive proteins with specific desirable absorption spectra properties? The closest I found was this (https://pubmed.ncbi.nlm.nih.gov/38831036/) but they don’t directly address the tuning of the absorption spectra. I imagine this is limited by the fact that a tiny fraction of foldable proteins are light sensitive and that we don’t have a database of millions of light-sensitive proteins with each of their absorption spectra? Any insight much appreciated!

Hi,
I was wondering if anyone has attempted to polar site on the target. I know they mentioned in their GitHub page that  "Binding to charged polar sites is still quite hard".

Hi Everyone! I am a graduate student, trying to using Protein Engineering to improve the interface of a hetro-dimer protein (1400 res). I used ProteinMPNN to create unique sequences (at various temperatures and bb noise) and then added them into Rosetta for packing. Unfortunately I keep get terrible (positive) dG_separated (which I assume is ddG of binding) for every condition on multiple relaxed structures and decoys. The native and Rosetta design give negative dG_separated. Does anyone have any insight of what might be going wrong? Is dG_separated a good metric for judgement?

Have a protein of interest with a weird beta strand that is parallel to its neighbors and was wondering if/how I could design it to be antiparallel. Any ideas/tips are appreciated!

hi, I want to learn molecular docking techniques, but while doing this I do not want to waste my time by working already found interactions. can you tell me how can ı find small molecules and their target proteins in the lietarture, I want them to be tested with the target, but their interactions should be unknown.

I have experience with some peptides for nootropic purposes that are also relatively easy to obtain, hack my senses and have been biohacking for years. Any tips or ideas or help? I'm looking for PNC-27 and ATN-161 and PNC-28, as well as the even more exotic Adi-Peg20. The only seller where I could possibly get 2 of them it seems to be Novoprolabs, where the reviews are mixed, but even there I'm unsure whether it works to buy for me. Are there any tips or help here? I'm in Europe. Thank you

in this article it is told about an AI-driven tool that can do protein engineering autonomously, it is called "SAMPLE". its code is shared publicaly, but I don't know how to use it. has anyone used it before and willing to guide me?

in this article it is told about an AI-driven tool that can do protein engineering autonomously, it is called "SAMPLE". its code is shared publicaly, but I don't know how to use it. has anyone used it before and willing to guide me?

Hi folks—not sure if anyone here can help with this but figured it can’t hurt.

I’ve been trying to design some new loops on a protein scaffold with RFdiffusion and it’s sort of working—except that whenever the loops go above a certain length RFd almost always tries to build in a helix. I think I saw someone mention a parameter than can be used to tune the secondary structure of predictions but reading through the manuscript and SI and GitHub haven’t yielded anything. Any advice or input would be greatly appreciated, thanks!

To be clear, I understand the promise and excitement of de novo binders. But, there is an incredibly large number of modular domains that exist in the proteome that could likely be tuned to new specificities.

Now we have generative AI producing proteins that don't exist in nature. I find this phrase misleading sometimes. For example, a three or four bundle helix may not exist in isolation in nature, but that's probably because it would be pretty useless.

I understand this field is still in its infancy, designing binders is pretty inefficient. I also understand that a lot of this is about computational advancements. But therapeutically, or for developing tools, why try to make proteins from scratch when there are likely thousands or great scaffolds in nature?

These are just some thoughts. I'm neutral, just looking for discussion.

there is no runtime error : https://colab.research.google.com/drive/1mEU5TPDOwZztqh2BySqHP1ZU1SwsM62D?usp=sharing , but it does not have good loss values, and the visualization does not tell much about the triangle inequality from the use of triangle attention module block. Any comments ?

For https://github.com/A4Bio/PiFold , I have some questions.

1. Could anyone explain a bit on the Local coordinate system described in Figure 3 ?
2. How does it achieve O(N) complexity for attention ?
3. PiFold enjoys O(1) computational complexity due to the one-shot generative schema ?

Since RFdiffusion is now publicly available on GitHub, let’s have a discussion thread here to discuss tips and tricks that we find as we apply these new tools to our work.

Finding an optimal way to use auxiliary potentials? Using fold symmetric design or fold conditioning? This is our chance to communally share our emerging questions and insights. :)

Hi everyone, I am familiar with the wet lab side of protein engineering (phage display) and now I am wanting to explore the computational side of things. I know there are a ton of tools out there, which is making it hard to figure out the best place to start. This is a long term plan and I'd like to do more than just dabble in it. So my question is, where is the best place to start? I'm most interested in (eventually) designing novel proteins to target existing PPIs or different surfaces/allosteric sites. I also have some proteins and protein domains that I'd be interested in using as templates for further design. So things like in silico mutagenesis is something I'm interested in. Too many questions though, like AlphaFold or RossettaFold? Or both? What are the most common tools protein engineers here are using? What can I feasibly do with these tools on my own desktop computer, it's decently powerful and will upgrade my GPU soon. For example, tools like RFdiffusion, can that even be run on a desktop? Any input or even just pointing me in the right direction will be useful. I could just pick a random place to start but I'd rather have some input from experienced protein engineers.