(197r) Exploring the Free Energy Landscape of Insulin Multimer Using Metadynamics

Protein-protein interactions play a crucial role in the stability and function of proteins. In therapeutic applications, protein associations like the dimerization and hexamerization of insulin play an essential role during transport and storage. To provide insights into insulin's physiological role and to develop more effective strategies for optimizing its stability and efficacy, it is vital to delve deeper into the formation of higher-order structures and the associated dissociation processes. While experimental and computational approaches such as molecular dynamics simulations have been used to understand the aggregation process, atomistic-level details of insulin hexamerization remain elusive. However, it is challenging to study higher-order protein aggregation using classical MD simulations alone, due to the timescales involved. Enhanced sampling methods such as metadynamics are powerful techniques to overcome slow fluctuations in the system and effectively explore the underlying free energy landscape.

In this study, we investigate the process of insulin hexamerization by studying dimerization, followed by the association of three dimer pairs to form a hexamer. To effectively probe this process, we construct a new rotational collective variable (CV), which considers protein orientation and rotation relative to one another, offering detailed insights into the underlying association mechanisms. By employing well-tempered metadynamics (WT-MetaD) and parallel bias metadynamics (PB-MetaD), we probe the thermodynamics of insulin dimer and hexamer formation to understand association and dissociation processes. The established methodology and CV can be used as a tool for examining the thermodynamics of other protein systems, including their association free energy, augmenting our comprehension of intricate biological interactions.