title: CAMELOT: A machine learning approach for coarse-grained simulations of aggregation of block-copolymeric protein sequences.
abstract: We report the development and deployment of a coarse-graining method that is well suited for computer simulations of aggregation and phase separation of protein sequences with block-copolymeric architectures. Our algorithm, named CAMELOT for Coarse-grained simulations Aided by MachinE Learning Optimization and Training, leverages information from converged all atom simulations that is used to determine a suitable resolution and parameterize the coarse-grained model. To parameterize a system-specific coarse-grained model, we use a combination of Boltzmann inversion, non-linear regression, and a Gaussian process Bayesian optimization approach. The accuracy of the coarse-grained model is demonstrated through direct comparisons to results from all atom simulations. We demonstrate the utility of our coarse-graining approach using the block-copolymeric sequence from the exon 1 encoded sequence of the huntingtin protein. This sequence comprises of 17 residues from the N-terminal end of huntingtin (N17) followed by a polyglutamine (polyQ) tract. Simulations based on the CAMELOT approach are used to show that the adsorption and unfolding of the wild type N17 and its sequence variants on the surface of polyQ tracts engender a patchy colloid like architecture that promotes the formation of linear aggregates. These results provide a plausible explanation for experimental observations, which show that N17 accelerates the formation of linear aggregates in block-copolymeric N17-polyQ sequences. The CAMELOT approach is versatile and is generalizable for simulating the aggregation and phase behavior of a range of block-copolymeric protein sequences.
authors.affiliation: Computational and Systems Biology Program and Center for Biological Systems Engineering, Washington University in St. Louis, St. Louis, Missouri 63130-4899, USA.
authors.forename: Kiersten M
authors.initials: KM
authors.lastname: Ruff
authors.affiliation: Department of Physics and Center for Biological Systems Engineering, Washington University in St. Louis, St. Louis, Missouri 63130-4899, USA.
authors.forename: Tyler S
authors.initials: TS
authors.lastname: Harmon
authors.affiliation: Department of Biomedical Engineering and Center for Biological Systems Engineering, Washington University in St. Louis, CB 1097, St. Louis, Missouri 63130-4899, USA.
authors.forename: Rohit V
authors.initials: RV
authors.lastname: Pappu
mesh_terms: D000595:Amino Acid Sequence; D003198:Computer Simulation; D006801:Humans; D000071058:Huntingtin Protein; D000069550:Machine Learning; D008969:Molecular Sequence Data; D009419:Nerve Tissue Proteins / Q000737:chemistry*
chemical_list: C086055:HTT protein, human; D000071058:Huntingtin Protein; D009419:Nerve Tissue Proteins