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Computational study of the activity,dynamics, energetics and conformations of insulin analogues using molecular dynamics simulations: Application to hyperinsulinemia and the critical residue B26
Authors:Anastasios Papaioannou  Serdar Kuyucak  Zdenka Kuncic
Institution:1. Charles Perkins Centre, University of Sydney, Sydney, NSW, Australia;2. School of Physics, University of Sydney, NSW, Australia
Abstract:Due to the increasing prevalence of diabetes, finding therapeutic analogues for insulin has become an urgent issue. While many experimental studies have been performed towards this end, they have limited scope to examine all aspects of the effect of a mutation. Computational studies can help to overcome these limitations, however, relatively few studies that focus on insulin analogues have been performed to date. Here, we present a comprehensive computational study of insulin analogues—three mutant insulins that have been identified with hyperinsulinemia and three mutations on the critical B26 residue that exhibit similar binding affinity to the insulin receptor—using molecular dynamics simulations with the aim of predicting how mutations of insulin affect its activity, dynamics, energetics and conformations. The time evolution of the conformers is studied in long simulations. The probability density function and potential of mean force calculations are performed on each insulin analogue to unravel the effect of mutations on the dynamics and energetics of insulin activation. Our conformational study can decrypt the key features and molecular mechanisms that are responsible for an enhanced or reduced activity of an insulin analogue. We find two key results: 1) hyperinsulinemia may be due to the drastically reduced activity (and binding affinity) of the mutant insulins. 2) Y26BS and Y26BE are promising therapeutic candidates for insulin as they are more active than WT-insulin. The analysis in this work can be readily applied to any set of mutations on insulin to guide development of more effective therapeutic analogues.
Keywords:Molecular dynamics  Insulin  Mutations  Diabetes
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