As we embarked on creating a new Gō-like model concept for coarse-grained simulations of proteins, we also established further goals for the model's properties that we think will be advantageous for the Martini 3 community and for supporting future developments. To facilitate the advancement of the Martini 3 protein model, we differentiate between the secondary-and tertiary networks, such that they could potentially be optimized independently and any imbalances could expose problems in the underlying protein model. Specifically, we wanted to develop a model that stabilizes protein secondary structure without the need for the secondary structure restraints currently used, such as harmonic bonds in β-sheets and high force constant dihedrals in α-helices. Importantly, this could unlock the ability to do more realistic (un)folding simulations of proteins, a goal also addressed in the original work behind GoMARTINI. Having a foldable secondary structure will also be a first step towards enabling protein conformational changes in Martini 3, which often require alternating secondary structures. Additionally, we searched for a model with minimal external bias. Since a Gō-like model can essentially be regarded as a force field correction, the Martini 3 protein model should be built with a minimal set of external bias potentials which will in turn increase the transferability and consistency of Martini 3 force field parameters between proteins and other molecule classes not using a Gō-like model. Naturally, reducing the number of restraints would also have the benefit of making simulations faster. Finally, we wanted to have an easy-to-use model that can be applied by a single script using the command line.