<blockquote>
<p>This is a comment to redirect to other answers, but go too long.</p>
</blockquote>
<p>Docking is the <em>in silico</em> prediction of where a ligand binds in a protein.</p>
<p>There are several Q&amp;As about docking here that are relevant, so please check out:</p>
<ul>
<li>machine learning, docking and the factors that affect it: <a href="https://bioinformatics.stackexchange.com/questions/12971/generate-ligands-candidates-based-on-protein-shape/12975#12975">Generate ligands candidates based on protein shape</a> —also worth a read the <a href="https://academic.oup.com/bioinformatics/article-abstract/36/3/758/5554651" rel="nofollow noreferrer">&quot;learning from the ligand&quot; paper</a> paper, which discusses why some ligand only parameters tell a lot about binding.</li>
<li>correlation between docking scores and enzyme kinetics: <a href="https://bioinformatics.stackexchange.com/questions/7504/purpose-of-correlating-docking-score-with-catalytic-efficiencykcat-km/10593#10593">Purpose of correlating docking score with catalytic efficiency(Kcat/km)</a> —discusses a paper <a href="https://www.nature.com/articles/ncomms12965" rel="nofollow noreferrer">https://www.nature.com/articles/ncomms12965</a> wherein a linear regression is done between docking scores and kcat/KM</li>
</ul>

CC BY-SA 4.0
2020-06-29T08:10:29.220Z
2020-06-29T08:10:29.220Z
Matteo Ferla
<p>I would like to work on a project that involves the prediction of protein-ligand binding kinetics. What might be the feature that is relevant for the prediction?</p>

CC BY-SA 4.0
2020-06-28T17:11:14.670Z
Does this answer your question? [What is the current state-of-the-art in protein-ligand binding affinity prediction using machine learning?](https://bioinformatics.stackexchange.com/questions/13636/what-is-the-current-state-of-the-art-in-protein-ligand-binding-affinity-predicti)
M__
CC BY-SA 4.0
2020-06-28T18:06:30.460Z
Anyway, yes but you need access to a large database of experimental daa for protein-ligand affinity binding for training and validation. In addition, you'll need to vectorise the ligands ... which may not be at all easy. Personally, I would update your original question.
M__
<proteins><machine-learning><interactions>
Is it possible to predict protein-ligand binding kinetics using machine learning?
# Is it possible to predict protein-ligand binding kinetics using machine learning?

(Asked by: username_0 on 2020-06-28)

I would like to work on a project that involves the prediction of protein-ligand binding kinetics. What might be the feature that is relevant for the prediction?

**Tags:** proteins, machine-learning, interactions
> **Comments:**
> **username_1**: Does this answer your question? [What is the current state-of-the-art in protein-ligand binding affinity prediction using machine learning?](https://bioinformatics.stackexchange.com/questions/13636/what-is-the-current-state-of-the-art-in-protein-ligand-binding-affinity-predicti)  
> **username_1**: Anyway, yes but you need access to a large database of experimental daa for protein-ligand affinity binding for training and validation. In addition, you'll need to vectorise the ligands ... which may not be at all easy. Personally, I would update your original question.  

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## 1 answers

### Answer by username_2 on 2020-06-29. Score: 1 | Accepted answer

> This is a comment to redirect to other answers, but go too long.

Docking is the *in silico* prediction of where a ligand binds in a protein.

There are several Q&As about docking here that are relevant, so please check out:

* machine learning, docking and the factors that affect it: [Generate ligands candidates based on protein shape](https://bioinformatics.stackexchange.com/questions/12971/generate-ligands-candidates-based-on-protein-shape/12975#12975) —also worth a read the ["learning from the ligand" paper](https://academic.oup.com/bioinformatics/article-abstract/36/3/758/5554651) paper, which discusses why some ligand only parameters tell a lot about binding.
* correlation between docking scores and enzyme kinetics: [Purpose of correlating docking score with catalytic efficiency(Kcat/km)](https://bioinformatics.stackexchange.com/questions/7504/purpose-of-correlating-docking-score-with-catalytic-efficiencykcat-km/10593#10593) —discusses a paper <https://www.nature.com/articles/ncomms12965> wherein a linear regression is done between docking scores and kcat/KM


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