A Multi-Scale Model for Insulin Self-Association Rates and Oligomerization Kinetics

Abstract

Insulin, a therapeutic protein, can aggregate during manufacture and is considered detrimental to its quality. Early identification of aggregation inducing factors would be an essential aspect concerning the design of mitigation strategies during manufacturing processes. The time-scales and length-scales relevant for aggregation makes the use of all-atom (AA) explicit solvent simulations for prediction of aggregation thermodynamics and/or kinetics very difficult. Since aggregation is mainly driven by non-native interactions, we have used the physics based MARTINI coarse grained model to model protein-protein interactions. In an earlier work we had identified aggregation-prone, partially folded intermediates (PFIs) of insulin. Here we have employed a transient-complex model to determine self-association rate of native insulin (N) and the PFIs of insulin. To this end, a set of most probable conformations of the N-PFI complex were first obtained using docking and scoring on basis of MMPBSA energies. These docked complexes were then refined by separating the N and PFI monomers translationally followed by long molecular dynamics simulations. In two sets of test cases we show that the binding interface of the final N-PFI complex is similar in both the AA simulations and CG-MARTINI simulations with elastic network constraints. We hypothesize that this N-PFI complex can be taken as the diffusion limited transient state for the insulin homodimer on aggregation pathway. We use the TransComp server to calculate association rates for formation of this diffusion limited complex. The dimer association rates and monomer conformational transition rates are used to determine all the rates for formation of various small oligomeric species on insulin aggregation pathway. These rates are then input to a kinetic monte carlo (KMC) scheme to determine oligomerization kinetics of insulin.