Design of sequences with good folding properties in coarse-grained proteinmodels

Background: Designing amino acid sequences that are stable in a given targe t structure amounts to maximizing a conditional probability. A straightforw ard approach to accomplishing this is a nested Monte Carte where the confor mation space is explored over and over again for different fixed sequences; this requires excessive computational demand. Several approximate attempts to remedy this situation, based on energy minimization for fixed structure or high-T expansions, have been proposed. These methods are fast but often not accurate, as folding occurs at low T. Results: We have developed a multisequence Monte Carte procedure where both sequence and conformational space are simultaneously probed with efficient prescriptions for pruning sequence space. The method is explored on hydrop hobic/polar models. First we discuss short lattice chains in order to compa re with exact data and with other methods. The method is then successfully applied to lattice chains with up to 50 monomers and to off-lattice 20mers. Conclusions: The multisequence Monte Carlo method offers a new approach to sequence design in coarse-grained models. It is much more efficient than pr evious Monte Carto methods, and is, as it stands, applicable to a fairly wi de range of two-letter models.