Session: Self-assembly in Polymer Systems:

Aggregation of amyloid-beta (Aβ) protein leading to formation of insoluble fibrils is strongly associated with Alzheimer’s disease (AD). Understanding the molecular mechanism of aggregation will enable in developing efficient treatment strategies for AD. The sequence KLVFFAE, the 16-22 fragment of Aβ, plays a critical role in the aggregation of Aβ. Aggregation is, however, an intrinsic property of all polypeptides. KFFE and KVVE have been experimentally determined to be the shortest peptides to form amyloid like fibrils. Comparatively, the peptides KLLE or KAAE did not form fibrils but potentially have a tendency to aggregate at higher peptide concentration. Interestingly, the aggregation propensity of the tetra peptides is strongly correlated to the β-sheet propensity of the peptides. Assessing the dynamics of the molecular level conformational changes during aggregation needs sophisticated experimental techniques; molecular simulations have evolved as a complementary tool in this regard. Since peptide aggregation occurs in the timescales of microseconds to even days, it is computationally prohibitive to probe the aggregation dynamics through atomistic simulation. We will use coarse-grained simulations using Martini 2.2P force field to investigate the aggregation dynamics of short amyloidogenic peptides. We will first ascertain the accuracy of the force field, if required optimize the parameters, to capture the difference in the aggregation propensity of the peptides in agreement with the experiments. The evolving peptide aggregates will be identified through appropriate clustering algorithms and the morphology of each cluster will be analyzed. The molecular structure and orientation of the peptides within the clusters will also be investigated systematically. Through mutation of the peptides the influence of electrostatic and hydrophobic interactions on the aggregation propensity and cluster morphology will be examined. Our results will also provide insights in designing peptides for various biomedical applications.

Dr Hamsa Priya Mohana Sundaram Assistant Professor

Indian Institute of Technology Madras

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