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Protein WISDOM: A Workbench for In silico De novo Design of BioMolecules
10:58

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Published on: July 25, 2013

Statistical theory of protein sequence design by random mutation.

Arnab Bhattacherjee1, Parbati Biswas

  • 1Department of Chemistry, University of Delhi, Delhi-110007.

The Journal of Physical Chemistry. B
|March 28, 2009
PubMed
Summary

A new theory evaluates amino acid pair probabilities in protein sequences, accounting for correlated mutations. This computational approach aids in protein design and engineering by predicting sequence patterns.

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Area of Science:

  • Computational Biology
  • Protein Engineering
  • Biophysics

Background:

  • Understanding protein sequence-structure relationships is crucial for protein engineering.
  • Correlated mutations influence protein stability and function.
  • Predicting residue-residue interactions is key to de novo protein design.

Purpose of the Study:

  • To develop a self-consistent mean-field theory for evaluating site-specific amino acid pair probabilities.
  • To incorporate the effects of correlated mutations in protein sequence analysis.
  • To provide a framework for protein design and engineering strategies.

Main Methods:

  • Developed a self-consistent mean-field theory to compute residue-residue substitution patterns.
  • Characterized all possible residue-residue combinations for a given protein structure.
  • Screened sequence libraries based on a generalized foldability criterion.
  • Applied the theory to a lattice protein model and compared with real protein sequences.

Main Results:

  • The theory successfully evaluates site-specific amino acid pair probabilities, considering correlated mutations.
  • The computed pairwise sequence probability profiles show good agreement with real protein sequences (lysozyme and 1789 globular proteins).
  • A simple coarse-grained potential was sufficient for accurate predictions in the lattice model.

Conclusions:

  • The developed mean-field theory provides a robust framework for analyzing protein sequence patterns.
  • This approach can guide site-directed mutagenesis for engineering existing proteins.
  • The theory offers potential for de novo design of novel proteins.