Protein - protein interactions govern every aspect of the cellular life cycle. Despite the pivotal role of interprotein association, many of its aspects remain poorly understood. This pertains particularly to the specificity determinants in interactions between large families of proteins and in intrafamily interactions. To elucidate the origins of affinity and specificity in paralogous inter- and intrafamily interactions, a series of in silico techniques of increasing theoretical sophistication and computational cost were employed on several datasets from key physiological pathways, under the initial assumption that interactions are mediated through a common interface on a conserved steric scaffold. A large-scale bioinformatics study on all combinations of potential interactors within the examined systems was carried out first, performing side chain replacement on X-ray- and NMR-derived templates to produce up to thousands of models of the various binary interactions within the examined systems. Simultaneously, polar and nonpolar areas, buried upon complexation, and the energy of electrostatic interaction between the binding partners were computed. Comparison of surfaces and energies between interacting and non-interacting pairs, identified from literature, reveals that all three parameters are significantly different between interactors and non-interactors, with electrostatics being most discriminatory of the three interfacial descriptors. Despite the statistical significance of the separation between binders and non-binders, considerable overlap remains, making any predictions solely based on buried surface and charge interactions unreliable. To probe deeper into the binding process, extensive molecular mechanics - Poisson-Boltzmann surface area calculations were then performed on a medium-sized set of 60 protein - peptide complexes from the Bcl-2-family of proteins - key regulators of the intrinsic apoptotic pathway. Per-residue decomposition of the enthalpy of interaction between the different protein - peptide pairs provides much finer detail on the binding process than the large-scale surface and charge calculations previously performed. This allowed pinpointing where affinity and specificity within the system originate, identification of key interactions, determination of how affinity is dependent on peptide properties, and provided a quantitative estimate of the energetics of binding. Crucially, this work demonstrates that the proteins' per-residue energies can be viewed as an energy fingerprint. Finally, this point was further developed by performing free energy calculations at a higher level of theory - thermodynamic integration - on eight large, drug and drug-like compounds bound to the Bcl-xL and Bcl-2 proteins. Comparison of the information content provided by energetic fingerprinting with a traditional two-dimensional quantitative structure-activity relationship study demonstrates the added value of free energy calculations. Crucially, this method affords a more comprehensive description of the binding process and every individual protein - ligand/peptide/protein complex, and extends the framework of four-dimensional molecular dynamics - quantitative structure-activity relationships (4D-MD/QSAR). Finally, directions for future work aiming to derive and validate hyperpredictive 4D-MD/QSAR models incorporating ligand- and receptor-based descriptors are set out.