Statistical information about interparticle spatial correlations can be inferred from measured X-ray scattering patterns. While such information is essential, it is impossible to uniquely reconstruct the real-space correlation functions from the scattering patterns without invoking approximate models, in part because scattering measurements only cover a finite wavevector range. Even when accurate structural information for disordered ensembles can be obtained, a working knowledge of which aspects control optical properties in the near-and far-field is lacking, and design rules learned from dimers or superlattices cannot be readily extended to such materials. Electromagnetic simulations can help fill the gaps in understanding of disordered plasmonic assemblies. However, many conventionally used approaches, including finite element, finite difference time domain, and discrete dipole methods, while sufficiently flexible and robust to handle small numbers of nanoparticles with complex shapes, are too computationally expensive to address the large number of nanoparticles required to model the hierarchical structures of disordered assemblies like colloidal gels. Efficient boundary element methods, multiparticle Mie theory and transition-matrix (T-matrix) approaches, and coupled dipole methods can treat larger systems sizes and multiscale structures within various levels of approximation. Motivated by these latter approaches, we recently introduced a mutual polarization method (MPM), which leverages the coupled dipole approximation to compute the optical response of large configurations of spherical particles that result from dynamic simulations of plasmonic assemblies. The algorithm is formulated to efficiently treat up to triply periodic boundary conditions and "overlaps" of nanoparticles, which commonly occur in simulations where colloids (e.g., ligand-capped nanocrystals) interact via coarse-grained potentials. MPM has been used as part of integrated computational and experimental studies to understand the optical response of doped metal oxide nanocrystals assembled into single- and multicomponent colloidal gels, and multicomponent meta-surfaces. It has also furnished predictions about the defect-tolerance of single-component plasmonic superlattices with experimentally relevant levels of structural disorder and the mechano-optical response of linked plasmonic nanoparticle gels under mechanical deformation. In this work, we aim to quantitatively characterize the relationship between the optical properties and structures for disordered states of plasmonic nanoparticles. To this end, we adopt a minimalist model of spherical colloids that interact via hard-sphere repulsions and isotropic, short-range attractive interactions. We use a combination of MPM and Brownian dynamics simulations, varying colloidal volume fraction and strength of interparticle attractions to study equilibrium colloidal dispersion and nonequilibrium, structurally arrested gel states. To understand the role of nanoparticle material composition, we consider particles with different Drude model dielectric parameters that influence their dipole polarizability.