  A grand canonical Monte Carlo (MC) algorithm is presented for studying the
lattice gas model (LGM) of multiple protein sequence alignment, which
coherently combines long-range interactions and variable-length insertions. MC
simulations are used for both parameter optimization of the model and
production runs to explore the sequence subspace around a given protein family.
In this Note, I describe the details of the MC algorithm as well as some
preliminary results of MC simulations with various temperatures and chemical
potentials, and compare them with the mean-field approximation. The existence
of a two-state transition in the sequence space is suggested for the SH3 domain
family, and inappropriateness of the mean-field approximation for the LGM is
demonstrated.
