Answers.Body: <p>Clustering mutations could reveal lots about the protein providing one has the functional impact of each mutation (this cluster are benign, this cluster causes misfolding etc). Many tools are emerging to explore this and there are plenty of established tools that can handle this.</p>
  <p><a href="https://academic.oup.com/bioinformatics/article/35/22/4854/5514476?login=true" rel="nofollow noreferrer">VarMap</a> is a tool that is able to map genomic variant coordinates to the best available structure.</p>
  <p><a href="https://pymol.org/" rel="nofollow noreferrer">PyMol</a> can open PDB files and you can programmatically or manually mutate each position using the <a href="https://pymolwiki.org/index.php/Mutagenesis" rel="nofollow noreferrer">mutagenesis tool</a>.</p>
  
Answers.ContentLicense: CC BY-SA 4.0
Answers.CreationDate: 2021-09-14T14:51:32.870Z
Answers.LastActivityDate: 2021-09-14T14:51:32.870Z
Answers.UserDisplayName: James
Body: <p>I have a pdb file for a protein (3D structure predicted by a tool) and around hundreds of known point mutations in the protein. I want to visualize the protein with all the mutations to see the hub of or core where the mutations are mostly. Is there are tool that does this? I would give the structure in a pdb file and a list of point mutations myself.</p>
  
Comments.ContentLicense: CC BY-SA 4.0
Comments.CreationDate: 2021-09-14T09:35:46.153Z
Comments.Text: Mutations can have different effects and severity. "Visualising" them is very powerful for discussion purposes, but quantifying them may be better, see [this past Q](https://bioinformatics.stackexchange.com/questions/17650/how-to-see-effect-of-point-mutation-in-pymol). You can open your protein in [PyMOL](https://pymol.org/2/) and select the residues in the command line part (`select interested, resi 1+2+3+5`) and then show them (`show sticks, interested`)... but the problem then the format you have the mutations in influences how you make the concatenated indices...
Comments.UserDisplayName: Matteo Ferla
Comments.ContentLicense: CC BY-SA 4.0
Comments.CreationDate: 2021-09-14T09:36:46.953Z
Comments.Text: Also this would be showing the wild type residue, but showing all mutations in a single structure makes no sense in most cases.
Comments.UserDisplayName: Matteo Ferla
Comments.ContentLicense: CC BY-SA 4.0
Comments.CreationDate: 2021-09-14T14:48:20.240Z
Comments.Text: @MatteoFerla Clustering mutations could reveal lots about the protein providing one has the functional impact of each mutation (this cluster are benign, this cluster causes misfolding etc). Indeed a region of no mutations could indicate constraint.
Comments.UserDisplayName: James
Tags: <protein-structure><3d-structure><point-mutation>
Title: Site Mutations in a 3D protein structure to locate the core of mutations
ThreadText: # Site Mutations in a 3D protein structure to locate the core of mutations
  
  (Asked by: username_0 on 2021-09-14)
  
  I have a pdb file for a protein (3D structure predicted by a tool) and around hundreds of known point mutations in the protein. I want to visualize the protein with all the mutations to see the hub of or core where the mutations are mostly. Is there are tool that does this? I would give the structure in a pdb file and a list of point mutations myself.
  
  **Tags:** protein-structure, 3d-structure, point-mutation
  
  > **Comments:**
  > **username_1**: Mutations can have different effects and severity. "Visualising" them is very powerful for discussion purposes, but quantifying them may be better, see [this past Q](https://bioinformatics.stackexchange.com/questions/17650/how-to-see-effect-of-point-mutation-in-pymol). You can open your protein in [PyMOL](https://pymol.org/2/) and select the residues in the command line part (`select interested, resi 1+2+3+5`) and then show them (`show sticks, interested`)... but the problem then the format you have the mutations in influences how you make the concatenated indices...  
  > **username_1**: Also this would be showing the wild type residue, but showing all mutations in a single structure makes no sense in most cases.  
  > **username_2**: @username_1 Clustering mutations could reveal lots about the protein providing one has the functional impact of each mutation (this cluster are benign, this cluster causes misfolding etc). Indeed a region of no mutations could indicate constraint.  
  
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  ## 1 answers
  
  ### Answer by username_2 on 2021-09-14. Score: 0 | Accepted answer
  
  Clustering mutations could reveal lots about the protein providing one has the functional impact of each mutation (this cluster are benign, this cluster causes misfolding etc). Many tools are emerging to explore this and there are plenty of established tools that can handle this.
  
  [VarMap](https://academic.oup.com/bioinformatics/article/35/22/4854/5514476?login=true) is a tool that is able to map genomic variant coordinates to the best available structure.
  
  [PyMol](https://pymol.org/) can open PDB files and you can programmatically or manually mutate each position using the [mutagenesis tool](https://pymolwiki.org/index.php/Mutagenesis).
  
  
  ---
  
  