title: How do thermophilic proteins resist aggregation?
abstract: Aggregation is an ancient threat that must be overcome by proteins from all organisms to maintain their native functional states. This is essential for the maintenance of metabolic flux and viability of their cellular machineries. Here, we compare the aggregation-resistance strategies adapted by the thermophilic proteins and their mesophilic homologs using a dataset of 373 protein families. Like their mesophilic homologs, the thermophilic protein sequences also contain potential aggregation prone regions (APRs), capable of forming cross-β motif and amyloid-like fibrils. Tetrapeptide and hexapeptide amyloid-like fibril forming sequence patterns and experimentally proven amyloid-like fibril forming peptide sequences were also detected in the thermophilic proteins. Both the thermophilic and the mesophilic proteins use similar strategies to resist aggregation. However, the thermophilic proteins show superior utilization of these strategies. The thermophilic protein monomers show greater ability to "stow away" the APRs in the hydrophobic cores to protect them from solvent exposure. The thermophilic proteins are also better at gatekeeping the APRs by surrounding them with charged residues (Asp, Glu, Lys, and Arg) and Pro to a greater extent. While thermophilic and mesophilic proteins in our dataset are highly homologous and show strong overall sequence conservation, the APRs are not conserved between the homologs. These findings indicate that evolution is working to avoid amyloidogenic regions in proteins. Our results are also consistent with the observation that thermophilic cells often accumulate small molecule osmolytes capable of stabilizing their proteins and other macromolecules. This study has important implications for rational design and formulation of therapeutic proteins and antibodies.
authors.affiliation: Department of Crystallography and Biophysics, University of Madras, Chennai, Tamil Nadu 600025, India.
authors.forename: Anthony Mary
authors.initials: AM
authors.lastname: Thangakani
authors.forename: Sandeep
authors.initials: S
authors.lastname: Kumar
authors.forename: Devadasan
authors.initials: D
authors.lastname: Velmurugan
authors.forename: Maria Siluvay Michael
authors.initials: MS
authors.lastname: Gromiha
mesh_terms: D000465:Algorithms; D000595:Amino Acid Sequence; D000682:Amyloid / Q000737:chemistry*; D001407:Bacillus / Q000737:chemistry; D001426:Bacterial Proteins / Q000737:chemistry; D019295:Computational Biology / Q000379:methods*; D017124:Conserved Sequence; D006360:Heat-Shock Proteins / Q000737:chemistry; D006863:Hydrogen-Ion Concentration; D057927:Hydrophobic and Hydrophilic Interactions; D008969:Molecular Sequence Data; D009842:Oligopeptides / Q000737:chemistry*; D011487:Protein Conformation; D017510:Protein Folding; D025941:Protein Interaction Mapping / Q000379:methods; D055550:Protein Stability; D016415:Sequence Alignment; D020539:Sequence Analysis, Protein; D012997:Solvents / Q000737:chemistry; D013816:Thermodynamics
chemical_list: D000682:Amyloid; D001426:Bacterial Proteins; D006360:Heat-Shock Proteins; D009842:Oligopeptides; D012997:Solvents; C407094:cold shock protein, Bacillus