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Mutual information analysis of mutation, nonlinearity and triple interactions in proteins
  • Burak Erman
Burak Erman
Koc Universitesi

Corresponding Author:berman@ku.edu.tr

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Mutations are the cause of several diseases as well as the underlying force of evolution. A thorough understanding of its biophysical consequences is essential. We present a computational framework for evaluating different levels of mutual information (MI) and its dependence on mutation. We used molecular dynamics trajectories of the third PDZ domain and its different mutations. MI calculated from these trajectories shows that: (i) the multivariate Gaussian distribution of joint probabilities characterizes the MI between residue pairs with sufficient accuracy. Nonlinearities in joint probabilities calculated by tensor Hermite polynomials up to the fifth order contribute insignificantly. (ii) Changes in MI between residue pairs show the characteristic patterns resulting from specific mutations. (iii) Triple correlations are characterized by evaluating MI between triplets of residues, certain triplets are strongly affected by mutation. (iv) Susceptibility of residues to perturbation are obtained by MI and discussed in terms of linear response theory.
14 May 2022Submitted to PROTEINS: Structure, Function, and Bioinformatics
14 May 2022Submission Checks Completed
14 May 2022Assigned to Editor
01 Jun 2022Reviewer(s) Assigned
21 Jun 2022Review(s) Completed, Editorial Evaluation Pending
28 Jun 2022Editorial Decision: Revise Major
18 Jul 20221st Revision Received
18 Jul 2022Submission Checks Completed
18 Jul 2022Assigned to Editor
18 Jul 2022Reviewer(s) Assigned
18 Jul 2022Review(s) Completed, Editorial Evaluation Pending
18 Jul 2022Editorial Decision: Accept
05 Sep 2022Published in Proteins: Structure, Function, and Bioinformatics. 10.1002/prot.26415