วีดีโอ

Yes, please first unzip the file. It will contain mmCIF files. Open it in any visualizer of your choice.

@Bioinformaticsinsights thank you so much

Kamal, the notebook is working fine. I guess you had missed running a cell some where. Please re run a fresh notebook.. if the issue persist... Please send me the last lines of the error here .. with the step name.

Good Research Proposal, Publication, and Skills mentioned in Publications.

@Bioinformaticsinsights thank you Sir

Why are you looking for another tool. Why not try AlphaFold3? th-cam.com/video/bfEtvtWJEGg/w-d-xo.html

How will you write an email to more than 1 professor, if one of them is working on Fisheries and the other on cattle's? What will you mention as your interest?

thanks

Dear Isaac, I have covered performing MDS on SAMSON. I will cover MSD on Google Colab Soon. You can explore the SAMSON play list on the channel. Regarding second part of the question, please read the next message 🙂

Message 2: MDS, normal simulation as I explained in the video. In CG, simulations we simplify systems by grouping multiple atoms into larger "beads" or pseudo-particles, reducing the number of degrees of freedom. It is faster than MD because here we are not analyzing individual atoms, therefore, CG can easily go to Microseconds. As I said, we check group of atoms as one atom, therefore, it is hard to study individual atoms in CG

Message 3: MC simulations use random sampling to explore the configuration space of a system, often based on statistical mechanics principles. As MC are performed on random sampling therefore time factor is not important here, in fact a user has to search for equilibrium. MC can be coupled on MDS data and pick random population of conformers, produced by MDS. Limitations are they are not providing time evolution in nano or pico seconds etc

list of unwanted substructures. I already mentioned the citation from where to get it. TH-cam description do not support file upload, therefore, now either please get it from the research paper i mentioned or send me an email. i will provide you there. You can have my email from the channel pages.

You are welcome. I have covered all the three competitive suits, AlphaFold3, Boltz-1, and Chai-1. There are others but not at the level of these three, therefore, I didn't waste people time, so far 😔.

Thanks mate for your encouragement.

No.

You are most welcome.

Dear Dr. Nisar, so far there are three released programs that are able to perform comparable against each other. Let me drop you here, tutorial link for the other two also, in case you want to try them also. You have asked for the citation, so far there is no citation for protenix (probably will emerge soon). for the other i have dropped link for you. 1. Boltz-1 tutorial: th-cam.com/video/9ZV2rA5gy0Q/w-d-xo.html citation: www.biorxiv.org/content/10.1101/2024.11.19.624167v2 2. Chai-1 tutorial: th-cam.com/video/ba9ER-TeTYY/w-d-xo.html citation: www.biorxiv.org/content/10.1101/2024.10.10.615955v1

Here are the three tutorials I covered. All of them are capable of entertaining ligands. Among them, I would suggest Chai-1. 1. AlphaFold3 : th-cam.com/video/bfEtvtWJEGg/w-d-xo.html 2. Boltz-1: th-cam.com/video/9ZV2rA5gy0Q/w-d-xo.html 3. Chai-1: th-cam.com/video/ba9ER-TeTYY/w-d-xo.html Cheers, and thanks for watching

th-cam.com/users/liveGPQ98E62PBI?feature=share

Happy to hear that. Good Luck

The saved files contains all the information about RMSD, Achieved Energies, and PDBQT files. Therefore, here I am confused what exactly you are asking?

Yes Jaspreet, you can, majority of the antioxidants retain the same principles.

Dear Dr. Nisar, in that case you have to probe the active site residues first. Nowadays, too many trained models are present, like AlphaFold, Chai, and Boltz. It is better to test them. Also, you can pick these information from the literature.

@@Bioinformaticsinsights Thank you

Please copy the last line of the error in the comment, also the section where it produce error.

Dear Manna, yes one can perform docking using the predicted structure of AF3, but I would suggest also include the pLDDT score in your manuscript before docking. So the reviewer must have a clear idea, how good this structure is. I have covered almost 4 different tutorials of Autodock Vina, I would suggest to consider Docking playlist. Here, I am going to drop you only one link, in case you are struggling. th-cam.com/video/iGGby6zavAY/w-d-xo.html

@@Bioinformaticsinsights Thank you Sir.

Thanks for good words

I am happy it helps you.

I have covered few tutorials. Let me drops those links here for you. You choose the one suits you. 1. th-cam.com/video/_xSpl2-lJD4/w-d-xo.html 2. th-cam.com/video/AYll_iebwHE/w-d-xo.html 3. th-cam.com/video/oJpi2OsQBBI/w-d-xo.html 4. th-cam.com/video/5_WQaLXcc18/w-d-xo.html

@@Bioinformaticsinsights Thank you very much. I tried docking following your tutorial. but they failed! my proteins were quite big more than 3000 AA chain. one of the proteins were PDB ID: 5K5M, this is a dengue virus protein. Can you help me sort out this problem?

Welcome

Chai-1: th-cam.com/video/ba9ER-TeTYY/w-d-xo.html I have covered Autodock vina extensively, by different offline and online methods. But i will suggest you perform your job with Chai-1, even it is better or comparable to AlphaFold3

please turn on your notification, at least you will have a notification in future.

Thanks Waleed, in recent time, I am not considering DFT as priority, as I don't grip it fully personally.

I didn't number in title, but the next video is part 7. Open the playlist, the next video is about KLIFS. Some of these videos are like different chapters of the book, therefore, I removed the number from the title. That made things confusing,

Okay sure Sir. Thank you Sir.

Good to know that someone is learning somewhere

Welcome. I have already covered. Let me drop links here. The Google Colab video is longer one, and to avoid any mistake, please watch it carefully. 1. Perform Docking with Google Colab. th-cam.com/video/c0ydWFlb2xM/w-d-xo.html 2. Perform Docking in offline mode. th-cam.com/video/tX4GWXmlwxw/w-d-xo.html 3. Perform docking through SAMSON. th-cam.com/video/zUVsscJ_zvk/w-d-xo.html I hope it is what you are looking for.

So nice of you

thanks

thanks

Appreciated

Thanks for watching

You are welcome

I checked, there is a dedicated colab notebook available. Follow it, if you encounter some error or problems, just drop the step name here. I will try to look into it.

@ ok. Thank you. I have followed that collab but end up in an error. I will work on it again and get back to you. Many thanks.

ok- it seems a straight-forward but I will check it first

@ thank you.

@ seems like some libraries are not compatible

Let me check

@@Bioinformaticsinsights thank you. I will be early waiting for it.

Thanks dear

Hello

Thank you for appreciation.

Dear I have covered almost a complete series on CADD. Have you watched? All is python based run in colab

@Bioinformaticsinsights sir I have been watching.

Dear, I have rechecked and found it fine. Can you paste the step here, where it sticks?

My pleasure

Abid you have asked your question under irrelevant video. Well, I am confused here. As you mentioned that you are not finding data. Please tell me, you are finding data to train the model, or your model is trained already?

Yes Sir, I am finding data to train the model.

@@abidaliyousafzai3123 then you can predict pIC50 either for 1 compound or thousands. I do not see any issue further, however if you interested to add similar compounds to the library of unknown compounds, sure you can.

Most welcome! Dear Abid.

You are welcome. Yes certainly, you can use Chai-1 in offline mode. Here are the source files, with proper installation details. github.com/chaidiscovery/chai-lab Cheers

@@Bioinformaticsinsights shall we use it as an open source? Thanks

@@jaypalsingh6376 as far as usage is concerned, yes but if you are interested in modification, then i will suggest to go for Boltz-1 released by MIT. th-cam.com/video/9ZV2rA5gy0Q/w-d-xo.html