Macrostate Identification
from Biomolecular Simulations
through Time Series Analysis
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Abstract
This paper builds upon the need for a more descriptive
and accurate
understanding of the landscape of intermolecular interactions, particularly
those involving macromolecules such as proteins. For this, we need
methods that move away from the single conformation description of
binding events, toward a descriptive free energy landscape where different
macrostates can coexist. Molecular dynamics simulations and molecular
mechanics Poisson–Boltzmann surface area (MM-PBSA) methods
provide an excellent approach for such a dynamic description of the
binding events. An alternative to the standard method of the statistical
reporting of such results is proposed