Accurately describing the electronic structure of molecules on metal surfaces is key to correctlymodeling their surface-enhanced properties. These properties are the basis for a variety of topicsin chemistry, such as single molecule spectroscopy and organic photovoltaic systems. In fact,the most recent Nobel Prize in Chemistry was awarded for work in the eld of single moleculeuorescence. While single-molecule uorescence is now widely used within both the chemical andbiochemical communities, its spectroscopic signal gives very little information about the structureand identity of the uorophore. Surface enhanced Raman spectroscopy (SERS), on the otherhand, can be used to uniquely identify a molecule as well detect the presence of a known scatterer.Raman diers from uorescence, as its the result of the inelastic scattering of photons by amolecule rather than an absorption process. These scattered photons contain information aboutthe vibrational and rotational states within the molecule, similar to IR spectroscopic techniques.However, the Raman signal from a single molecule is very weak. The mechanisms behind SERSprovide sucient enhancement to enable single molecule detection and identication. ModelingSERS and other surface-enhanced properties is dicult due to the complex interactions betweenthe molecule and the metal surface. In order to accurately describe how these interactions impactthe electronic structure, we require rst-principles based methods. Density functional theory(DFT) remains the go-to method for simulations of large systems thanks to its balance betweenaccuracy and computational complexity. However, one encounters certain failures within DFTthat limit its application to accurately describing the interactions between molecules and metalsurfaces. In principle, DFT is an exact method if one knows the correct exchange-correlation(XC) potential. In practice, this potential is only an approximation determined by an XCfunctional. Many XC functionals exist and the accuracy of a DFT calculation is highly dependenton the choice of XC. Recently, a new class of XC functionals called long-range corrected (LC)functionals have been developed that show signicant improvement to the traditional failures ofDFT. Of particular interest is their ability to be `tuned' in order to enforce properties that theexact XC functional would have. In this dissertation, we present the importance of using LCfunctionals when describing the electronic structure of molecules on metal surfaces using DFT.We rst demonstrate how LC functionals improve the description of the energy gap betweenthe frontier orbitals for a set of substituted pyridines on a small silver cluster. This allowsfor a better prediction to the magnitude of the SERS enhancement. While DFT is capable ofdescribing `large' systems on the order of hundreds of atoms, realistically sized nanoparticles withdimensions on the order of 1 to 100 nm can contain between 300 and 10,000,000 atoms, makingthem computationally intractable even for DFT. In order to go beyond small metal clusters, we have developed a hybrid model that combines a quantum mechanical description of a moleculesusing density functional theory (DFT) with a classical atomistic electrodynamics model of themetal system. We present here a new implementation of the discrete interaction model/quantummechanical (DIM/QM) method within the NWChem computational package. We demonstratethat by combining DIM/QM with the tuning of LC functionals, we can accurately describe thechanges in electronic structure seen when molecules approach a metal surface at a signicantlyreduced computational cost compared to other methods. These changes are important to capturein a metal-molecule system, as they signicantly alter the molecule's optical properties. Inaddition, we have made several improvements to the underlying DIM/QM algorithm whichdecrease the computational cost of DIM/QM by 30%. Furthermore, we extend DIM toaccount for experimentally observed changes in the optical properties of metal nanoparticles withdimensions less than