Answers.Body: <p>Assuming this is human data, this seems like a job for the <a href="https://ensembl.org/info/docs/tools/vep/index.html" rel="nofollow noreferrer">Ensembl Variant Effect Predictor (VEP)</a>:</p>
  <blockquote>
  <p>VEP determines the effect of your variants (SNPs, insertions, deletions, CNVs or structural variants) on genes, transcripts, and protein sequence, as well as regulatory regions.</p>
  <p>Simply input the coordinates of your variants and the nucleotide changes to find out the:</p>
  <ul>
  <li>Genes and Transcripts affected by the variants</li>
  <li>Location of the variants (e.g. upstream of a transcript, in coding sequence, in non-coding RNA, in regulatory regions)</li>
  <li>Consequence of your variants on the protein sequence (e.g. stop gained, missense, stop lost, frameshift), see variant consequences</li>
  <li>Known variants that match yours, and associated minor allele frequencies from the 1000 Genomes Project</li>
  <li>SIFT and PolyPhen-2 scores for changes to protein sequence</li>
  <li>... And more! See data types, versions.</li>
  </ul>
  </blockquote>
  <p>If you can get your data into VCF format, you should be able to run VEP on it, which will tell you if there is a protein change, and whether that change is predicted to have a biological consequence.</p>
  <p>Aside on terminology: in bioinformatics, when the term <em>structural change</em> is used, it usually refers to large-scale genetic changes (e.g. large deletions, translocations, insertions, or inversions). As SNPs are single point variations, they don't pass the threshold for structural change.</p>
  
Answers.ContentLicense: CC BY-SA 4.0
Answers.CreationDate: 2024-07-24T20:48:35.213Z
Answers.Text: Thank you so much !
Answers.UserDisplayName: Sneha
Answers.ContentLicense: CC BY-SA 4.0
Answers.CreationDate: 2024-07-22T19:54:34.333Z
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Answers.UserDisplayName: gringer
Body: <p>I'm a beginner bioinformatics student. I am currently working on my first project. We have gathered data about SNPs that are associated with a particular disease. We aim to understand the functional and structural implications of these SNPs. I have run mutagenesis on Pymol and gathered data on the variation in Hydrogen bonds.
  We are now unsure how to analyze this data or interpret the mutagenesis result to get to a point where we can say that:</p>
  <ol>
  <li>A particular structural change is occurring and</li>
  <li>This change is now leading to functional changes thereby making it pathogenic.</li>
  </ol>
  <p>Is it just basic understanding? Or are there any other software tools to help with this interpretation?</p>
  <p>Thanks in advance!</p>
  
Comments.ContentLicense: CC BY-SA 4.0
Comments.CreationDate: 2024-07-22T11:40:32.453Z
Comments.Text: Please clarify your specific problem or provide additional details to highlight exactly what you need. As it's currently written, it's hard to tell exactly what you're asking.
Comments.UserDisplayName: Community
Comments.ContentLicense: CC BY-SA 4.0
Comments.CreationDate: 2024-07-22T19:43:32.500Z
Comments.Text: Is this human data?
Comments.UserDisplayName: gringer
Tags: <protein-structure><snp><mutations><pymol><structural-variation>
Title: How to interpret mutagenesis results from pymol to make conclusions about structural/functional changes and predict resulting pathogenesis?
ThreadText: # How to interpret mutagenesis results from pymol to make conclusions about structural/functional changes and predict resulting pathogenesis?
  
  (Asked by: username_0 on 2024-07-22)
  
  I'm a beginner bioinformatics student. I am currently working on my first project. We have gathered data about SNPs that are associated with a particular disease. We aim to understand the functional and structural implications of these SNPs. I have run mutagenesis on Pymol and gathered data on the variation in Hydrogen bonds.
  We are now unsure how to analyze this data or interpret the mutagenesis result to get to a point where we can say that:
  
  1. A particular structural change is occurring and
  2. This change is now leading to functional changes thereby making it pathogenic.
  
  Is it just basic understanding? Or are there any other software tools to help with this interpretation?
  
  Thanks in advance!
  
  **Tags:** protein-structure, snp, mutations, pymol, structural-variation
  
  > **Comments:**
  > **username_1**: Please clarify your specific problem or provide additional details to highlight exactly what you need. As it's currently written, it's hard to tell exactly what you're asking.  
  > **username_2**: Is this human data?  
  
  ---
  
  ## 1 answers
  
  ### Answer by username_2 on 2024-07-22. Score: 1
  
  Assuming this is human data, this seems like a job for the [Ensembl Variant Effect Predictor (VEP)](https://ensembl.org/info/docs/tools/vep/index.html):
  
  > VEP determines the effect of your variants (SNPs, insertions, deletions, CNVs or structural variants) on genes, transcripts, and protein sequence, as well as regulatory regions.
  >
  > Simply input the coordinates of your variants and the nucleotide changes to find out the:
  >
  > * Genes and Transcripts affected by the variants
  > * Location of the variants (e.g. upstream of a transcript, in coding sequence, in non-coding RNA, in regulatory regions)
  > * Consequence of your variants on the protein sequence (e.g. stop gained, missense, stop lost, frameshift), see variant consequences
  > * Known variants that match yours, and associated minor allele frequencies from the 1000 Genomes Project
  > * SIFT and PolyPhen-2 scores for changes to protein sequence
  > * ... And more! See data types, versions.
  
  If you can get your data into VCF format, you should be able to run VEP on it, which will tell you if there is a protein change, and whether that change is predicted to have a biological consequence.
  
  Aside on terminology: in bioinformatics, when the term *structural change* is used, it usually refers to large-scale genetic changes (e.g. large deletions, translocations, insertions, or inversions). As SNPs are single point variations, they don't pass the threshold for structural change.
  
  > **Comments:**
  > **username_0**: Thank you so much !  
  
  ---
  
  