MOTIVATION: The cost of molecular quasi-statics or dynamics simulations increases with the size of the simulated systems, which is a problem when studying biological phenomena that involve large molecules over long time scales. To address this problem, one has often to either increase the processing power (which might be expensive), or make arbitrary simplifications to the system (which might bias the study). RESULTS: We introduce adaptive torsion-angle quasi-statics, a general simulation method able to rigorously and automatically predict the most mobile regions in a simulated system, under user-defined precision or time constraints. By predicting and simulating only these most important regions, the adaptive method provides the user with complete control on the balance between precision and computational cost, without requiring him or her to perform a priori, arbitrary simplifications. We build on our previous research on adaptive articulated-body simulation and show how, by taking advantage of the partial rigidification of a molecule, we are able to propose novel data structures and algorithms for adaptive update of molecular forces and energies. This results in a globally adaptive molecular quasi-statics simulation method. We demonstrate our approach on several examples and show how adaptive quasi-statics allows a user to interactively design, modify and study potentially complex protein structures.