Sequence design in coarse-grained protein models

Designing amino acid sequences that are stable in a given target structure amounts to maximizing a conditional probability A straightforward approach to accomplish this is a nested Monte Carlo where the conformation space is explored over and over again for different fixed sequences. In this paper w e discuss an alternative Monte Carlo approach, multisequence design, where conformation and sequence degrees of freedom are simultaneously probed. The method is explored on hydrophobic/polar models. A statistical analysis of sequence correlations is also discussed. It is found that hydrophobic/polar model sequences and enzymes display hydrophobicity correlations that are q ualitatively similar.