  We previously introduced a conformational sampling method, a
multi-dimensional virtual-system coupled molecular dynamics (mD-VcMD), to
enhance conformational sampling of a biomolecular system by computer
simulations. Here, we present a new sampling method, subzone-based mD-VcMD, as
an extension of mD-VcMD. Then, we further extend the subzone-based method using
genetic algorithm (GA), and named it the GA-based mD-VcMD. Because the
conformational space of the biomolecular system is vast, a single simulation
cannot sample the conformational space throughout. Then, iterative simulations
are performed to increase the sampled region gradually. The new methods have
the following advantages: (1) The methods are free from a production run: I.e.,
all snapshots from all iterations can be used for analyses. (2) The methods are
free from fine tuning of a weight function (probability distribution function
or potential of mean force). (3) A simple procedure is available to assign a
thermodynamic weight to snapshots sampled in spite that the weight function is
not used to proceed the iterative simulations. Thus, a canonical ensemble
(i.e., a thermally equilibrated ensemble) is generated from the resultant
snapshots. (4) If a poorly-sampled region emerges in sampling, selective
sampling can be performed focusing on the poorly-sampled region without
breaking the proportion of the canonical ensemble. A free-energy landscape of
the biomolecular system is obtainable from the canonical ensemble.
