During the last few decades, the energy landscape framework has emerged as a conceptual, as well as a computational tool to understand the intimate connections between biomolecular structure, dynamics, and function. Nonetheless, determining the global topography of the energy landscape using standard computational techniques has proved challenging. In this context, a coarse-graining of the landscape in terms of stationary points, which can be located using geometry optimization techniques, can prove effective. In the first part of my talk, I will highlight how this approach can be exploited to obtain key atomistic insights into RNA folding, as well as conformational transitions between the different helical morphologies of DNA duplexes. In the second part, I will illustrate how coarse graining the degrees of freedom can also be a viable route towards understanding key biophysical phenomena. In this context, a problem related to the aggregation propensities of Aβ40 and Aβ42 peptides, will be discussed.