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corrected AF2 section
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@amjjbonvin
amjjbonvin committed May 21, 2024
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Expand Up @@ -515,7 +515,52 @@ Are the active residues at the interface in the different clusters? How is the r
<br>
<br>
<hr>
## BONUS 1: Modelling the antibody-antigen complex with AlphaFold2 - does it work?
## BONUS 2: Does the antibody bind to a known interface of interleukin? ARCTIC-3D analysis

Gevokizumab is a highly specific antibody that targets an allosteric site of Interleukin-1β (IL-1β) in PDB file *4G6M*, thus reducing its binding affinity for its substrate, interleukin-1 receptor type I (IL-1RI). Canakinumab, another antibody binding to IL-1β, has a different mode of action, as it competes directly with IL-1RI's binding site (in PDB file *4G6J*). For more details please check [this article](https://www.sciencedirect.com/science/article/abs/pii/S0022283612007863?via%3Dihub){:target="\_blank"}.

We will now use our new software, [ARCTIC-3D](https://www.biorxiv.org/content/10.1101/2023.07.10.548477v1){:target="\_blank"}, to visualize the binding interfaces formed by IL-1β. First, the program retrieves all the existing binding surfaces formed by IL-1β from the [PDBe website](https://www.ebi.ac.uk/pdbe/){:target="\_blank"}. Then, these binding surfaces are compared and clustered together if they span a similar region of the selected protein (IL-1β in our case).

We now use the ARCTIC-3D web-server available [here](https://wenmr.science.uu.nl/arctic3d/){:target="\_blank"} to run an ARCTIC-3D job targeting the uniprot ID of human Interleukin-1 beta, namely [P01584](https://www.uniprot.org/uniprotkb/P01584/entry){:target="\_blank"}.

<a class="prompt prompt-info">
Insert the selected uniprot ID in the **UniprotID** field.
</a>

<a class="prompt prompt-info">
Leave the other parameters as they are and click on **Submit**.
</a>

Wait a few seconds for the job to complete or access a precalculated run [here](https://wenmr.science.uu.nl/arctic3d/example-P01584){:target="\_blank"}.

<a class="prompt prompt-question">
How many interface clusters were found for this protein?
</a>

Once you download the output archive, you can find the clustering information presented in the dendrogram:

<figure style="text-align: center;">
<img width="75%" src="/education/HADDOCK3/HADDOCK3-antibody-antigen-bioexcel2023/dendrogram_average_P01584.png">
</figure>

We can see how the two *4G6M* antibody chains are recognized as a unique cluster, clearly separated from the other binding surfaces and, in particular, from those proper to IL-1RI (uniprot ID P14778).

<a class="prompt prompt-info">
Rerun ARCTIC-3D with a clustering threshold equal to 0.95
</a>

This means that the clustering will be looser, therefore lumping more dissimilar surfaces into the same object.

You can inspect a precalculated run [here](https://wenmr.science.uu.nl/arctic3d/example-P01584-095){:target="\_blank"}.

<a class="prompt prompt-question">
How do the results change? Are gevokizumab or canakinumab PDB files being clustered with any IL-1RI-related interface?
</a>

<br>
<br>
<hr>
## BONUS 2: Modelling the antibody-antigen complex with AlphaFold2 - does it work?

With the advent of Artificial Intelligence (AI) and AlphaFold we can also try to predict with AlphaFold this antibody-antigen complex.
For a short introduction to AI and AlphaFold refer to this other tutorial [introduction](/education/molmod_online/alphafold/#introduction){:target="_blank"}.
Expand All @@ -536,34 +581,33 @@ These are respectively

* Antibody heavy chain:
<pre style="background-color:#DAE4E7">
QVQLQESGPGLVKPSQTLSLTCSFSGFSLSTSGMGVGWIRQPSGKGLEWLAHIWWDGDES
YNPSLKSRLTISKDTSKNQVSLKITSVTAADTAVYFCARNRYDPPWFVDWGQGTLVTVSS
ASTKGPSVFPLAPSSKSTSGGTAALGCLVKDYFPEPVTVSWNSGALTSGVHTFPAVLQSS
GLYSLSSVVTVPSSSLGTQTYICNVNHKPSNTKVDKRVEP
QVQLQESGPGLVKPSQTLSLTCSFSGFSLSTSGMGVGWIRQPSGKGLEWLAHIWWDGDESYNPSLKSRLTISKDTSKNQVSLKITSVTAADTAVYFCARNRYDPPWFVDWGQGTLVTVSSASTKGPSVFPLAPSSKSTSGGTAALGCLVKDYFPEPVTVSWNSGALTSGVHTFPAVLQSSGLYSLSSVVTVPSSSLGTQTYICNVNHKPSNTKVDKRVEP
</pre>

* Antibody light chain:
<pre style="background-color:#DAE4E7">
DIQMTQSTSSLSASVGDRVTITCRASQDISNYLSWYQQKPGKAVKLLIYYTSKLHSGVPS
RFSGSGSGTDYTLTISSLQQEDFATYFCLQGKMLPWTFGQGTKLEIKRTVAAPSVFIFPP
SDEQLKSGTASVVCLLNNFYPREAKVQWKVDNALQSGNSQESVTEQDSKDSTYSLSSTLT
LSKADYEKHKVYACEVTHQGLSSPVTKSFNRG
DIQMTQSTSSLSASVGDRVTITCRASQDISNYLSWYQQKPGKAVKLLIYYTSKLHSGVPSRFSGSGSGTDYTLTISSLQQEDFATYFCLQGKMLPWTFGQGTKLEIKRTVAAPSVFIFPPSDEQLKSGTASVVCLLNNFYPREAKVQWKVDNALQSGNSQESVTEQDSKDSTYSLSSTLTLSKADYEKHKVYACEVTHQGLSSPVTKSFNRG
</pre>

* Antigen:
<pre style="background-color:#DAE4E7">
APVRSLNCTLRDSQQKSLVMSGPYELKALHLQGQDMEQQVVFSMSFVQGEESNDKIPVAL
GLKEKNLYLSCVLKDDKPTLQLESVDPKNYPKKKMEKRFVFNKIEINNKLEFESAQFPNW
YISTSQAENMPVFLGGTKGGQDITDFTMQFVSS
APVRSLNCTLRDSQQKSLVMSGPYELKALHLQGQDMEQQVVFSMSFVQGEESNDKIPVALGLKEKNLYLSCVLKDDKPTLQLESVDPKNYPKKKMEKRFVFNKIEINNKLEFESAQFPNWYISTSQAENMPVFLGGTKGGQDITDFTMQFVSS
</pre>
<br>

To use AlphaFold2 to predict e.g. the pentamer follow the following steps:

To use AlphaFold2 to predict this antibody-antigen complex follow the following steps:

<a class="prompt prompt-info">
Copy and paste each of the above sequence in the _query_sequence_ field, adding a colon `:` in between the sequences.
Copy and paste each of the above sequence in the _query_sequence_ field, adding a colon *:* in between the sequences.
</a>

For your convenience the full sequence with colons is:

<pre style="background-color:#DAE4E7">
QVQLQESGPGLVKPSQTLSLTCSFSGFSLSTSGMGVGWIRQPSGKGLEWLAHIWWDGDESYNPSLKSRLTISKDTSKNQVSLKITSVTAADTAVYFCARNRYDPPWFVDWGQGTLVTVSS:DIQMTQSTSSLSASVGDRVTITCRASQDISNYLSWYQQKPGKAVKLLIYYTSKLHSGVPSRFSGSGSGTDYTLTISSLQQEDFATYFCLQGKMLPWTFGQGTKLEIK:VRSLNCTLRDSQQKSLVMSGPYELKALHLQGQDMEQQVVFSMSFVQGEESNDKIPVALGLKEKNLYLSCVLKDDKPTLQLESVDPKNYPKKKMEKRFVFNKIEINNKLEFESAQFPNWYISTSQAENMPVFLGGTKGGQDITDFTMQFVSS
</pre>

<a class="prompt prompt-info">
Define the _jobname_, e.g. Ab_Ag
</a>
Expand Down Expand Up @@ -768,52 +812,6 @@ alignto sele
<br>
<hr>

## BONUS 2: Does the antibody bind to a known interface of interleukin? ARCTIC-3D analysis

Gevokizumab is a highly specific antibody that targets an allosteric site of Interleukin-1β (IL-1β) in PDB file *4G6M*, thus reducing its binding affinity for its substrate, interleukin-1 receptor type I (IL-1RI). Canakinumab, another antibody binding to IL-1β, has a different mode of action, as it competes directly with IL-1RI's binding site (in PDB file *4G6J*). For more details please check [this article](https://www.sciencedirect.com/science/article/abs/pii/S0022283612007863?via%3Dihub){:target="\_blank"}.

We will now use our new software, [ARCTIC-3D](https://www.biorxiv.org/content/10.1101/2023.07.10.548477v1){:target="\_blank"}, to visualize the binding interfaces formed by IL-1β. First, the program retrieves all the existing binding surfaces formed by IL-1β from the [PDBe website](https://www.ebi.ac.uk/pdbe/){:target="\_blank"}. Then, these binding surfaces are compared and clustered together if they span a similar region of the selected protein (IL-1β in our case).

We now use the ARCTIC-3D web-server available [here](https://wenmr.science.uu.nl/arctic3d/){:target="\_blank"} to run an ARCTIC-3D job targeting the uniprot ID of human Interleukin-1 beta, namely [P01584](https://www.uniprot.org/uniprotkb/P01584/entry){:target="\_blank"}.

<a class="prompt prompt-info">
Insert the selected uniprot ID in the **UniprotID** field.
</a>

<a class="prompt prompt-info">
Leave the other parameters as they are and click on **Submit**.
</a>

Wait a few seconds for the job to complete or access a precalculated run [here](https://wenmr.science.uu.nl/arctic3d/example-P01584){:target="\_blank"}.

<a class="prompt prompt-question">
How many interface clusters were found for this protein?
</a>

Once you download the output archive, you can find the clustering information presented in the dendrogram:

<figure style="text-align: center;">
<img width="75%" src="/education/HADDOCK3/HADDOCK3-antibody-antigen-bioexcel2023/dendrogram_average_P01584.png">
</figure>

We can see how the two *4G6M* antibody chains are recognized as a unique cluster, clearly separated from the other binding surfaces and, in particular, from those proper to IL-1RI (uniprot ID P14778).

<a class="prompt prompt-info">
Rerun ARCTIC-3D with a clustering threshold equal to 0.95
</a>

This means that the clustering will be looser, therefore lumping more dissimilar surfaces into the same object.

You can inspect a precalculated run [here](https://wenmr.science.uu.nl/arctic3d/example-P01584-095){:target="\_blank"}.

<a class="prompt prompt-question">
How do the results change? Are gevokizumab or canakinumab PDB files being clustered with any IL-1RI-related interface?
</a>

<br>
<br>
<hr>

## BONUS 3: Dissecting the interface energetics: PROT-ON analysis

PROT-ON (Structure-based detection of designer mutations in PROTein-protein interface mutatiONs) is a tool and [online server](http://proton.tools.ibg.edu.tr:8001){:target="\_blank"} that allows to identify critical amino acids for redesigning a structurally characterized protein-protein interfaces, which paves the way for developing protein-based therapeutics to deal with diverse range of diseases. To find such amino acids positions, the residues across the protein interaction surfaces are either randomly or strategically mutated. Scanning mutations in this manner is experimentally costly. Therefore, computational methods have been developed to estimate the impact of an interfacial mutation on protein-protein interactions. PROT-ON scans all possible interfacial mutations by using EvoEF1 (active in both on the web server and stand-alone versions) or FoldX (active only in the stand-alone version) with the aim of finding the most mutable positions. The original publication describing PROT-ON can be found [here](https://www.frontiersin.org/articles/10.3389/fmolb.2023.1063971/full){:target="\_blank"}.
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