The cell is a crowded place! For example, the concentration of proteins and nucleic acids in the cytoplasm of E. Coli is >     300 g/L, and eye lens fiber cells contain crystallin proteins at a concentration of ~400 g/L. The nature of the interactions and organization
of the macromolecules in such crowded environments is obviously quite different than in typical in vitro experiments and atomistic simulati    ons, which are carried out at orders of magnitude lower concentrations. There are a number of challenges to atomically detailed
simulations of biological macromolecules in realistic (i.e., crowded) cellular environments. First and foremost is the necessity of including a large numb    er of macromolecules, which means that the minimal system size is prohibitive to atomistic simulations with
explicit solvent. The usual approach to meet this challenge is to employ Brownian dynamics (BD) simulations of atomically detailed, rigid macromolecules in implicit solvent.     This approach enables the simulation of ~1,000 macromolecules for ~10-100 microseconds. In
this talk, I will describe our efforts to use the energy function employed in BD simulations in Monte Carlo (MC) simulations, which, through clever choices of trial moves, enable much more ef    ficient configurational sampling than BD simulations. I will also describe
how we incorporate conformational flexibility into our MC simulations. Finally, I will present preliminary results from our MC simulations of crowded solutions of wild-type and cataract-related variants of e    ye lens crystallin proteins, which provide molecular-scale
insights into the role of altered inter-protein interactions in the formation of large-scale aggregates implicated in cataract formation.