mCSM-NA: How To Use


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Main page

About mCSM-NA

mCSM-NA is a novel, updated, scalable method capable of quantitatevely predicting the effects of mutations in protein coding regions on nucleic acid binding affinities. It is a machine learning approach that uses graph-based structural signatures to train and test predictive models.

We have significantly enhanced the original method by including a pharmacophore modelling and information of nucleic acid properties into our graph-based signatures, considering the reverse mutation and by using a refined, more reliable dataset, based on a new release of the ProNIT.

Submission page

How to run a prediction

To run a single prediction:

  • Click on "Predict" (1) to open the submission page.
  • Provide the structure of the wild-type antibody-antigen complex (2), which must comply with the PDB format.
  • Select the nucleic acid type (RNA, dsDNA or ssDNA) (3).
  • A single mutation to be analysed should be provided (4). A mutation code consists of wild-type code, residue position and mutant code (using the one letter amino acid code). Residue position must be consistent with the PDB file. The chain for the mutation code must also be provided.
  • You are then ready to submit your query for analysis (5).

To run the prediction on a mutation list:

  • Click on "Predict" (1) to open the submission page.
  • Provide the structure of the wild-type antibody-antigen complex (6), which must comply with the PDB format.
  • A file with a list of mutations to be analysed should be provided (7). One mutation should be provided per line, with the chain identifier in one column, followed by an empty space and the mutation code, as previously described.
  • Select the nucleic acid type (RNA, dsDNA or ssDNA) (8).
  • You are then ready to submit your query for analysis (9).

Results page

Results - Single mutation

Your results (1) for a single mutation will be displayed once computations are completed. The results will display the predicted change in affinity upon mutation (ΔΔG in kcal/mol). A negative value (and red writing) corresponds to a mutation predicted as reducing affinity; while a positive sign (and blue writing) corresponds to a mutation predicted as increasing affinity. Complementary information also displayed include:

  • A summary of the mutation is presented (2) highlighting the wild-type residue, position number and chain.

  • Complementary information, regarding nucleic acid type, residue solvent accessibility and predicted effect on protein stability is also presented (3).

  • The protein complex and mutation can be visualised directly from the server (4). Several options are provided for customization of the molecule. Mouse controls are also enabled.

  • (5) allows users to download a pymol session of the residue and its interactions.

Results page

Results - List of Mutations

Your results for a list of mutations will be displayed in a table format with the following information:

  • Mutant residue code (1).

  • Residue relative solvent accessibility (RSA) (2).

  • The predicted ΔΔG (3) and the predicted outcome (4).

An option to download the predictions as a tab-separated file is also available (5).

Contact page

Getting in touch

In case you experience any trouble using mCSM-NA or have any suggestions or comments, please do not hesitate in contacting us either via e-mail (1) or through the online form (2) .